Search results for: text recognition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2799

Search results for: text recognition

1869 Category-Base Theory of the Optimum Signal Approximation Clarifying the Importance of Parallel Worlds in the Recognition of Human and Application to Secure Signal Communication with Feedback

Authors: Takuro Kida, Yuichi Kida

Abstract:

We show a base of the new trend of algorithm mathematically that treats a historical reason of continuous discrimination in the world as well as its solution by introducing new concepts of parallel world that includes an invisible set of errors as its companion. With respect to a matrix operator-filter bank that the matrix operator-analysis-filter bank H and the matrix operator-sampling-filter bank S are given, firstly, we introduce the detailed algorithm to derive the optimum matrix operator-synthesis-filter bank Z that minimizes all the worst-case measures of the matrix operator-error-signals E(ω) = F(ω) − Y(ω) between the matrix operator-input-signals F(ω) and the matrix operator-output signals Y(ω) of the matrix operator-filter bank at the same time. Further, feedback is introduced to the above approximation theory and it is indicated that introducing conversations with feedback does not superior automatically to the accumulation of existing knowledge of signal prediction. Secondly, the concept of category in the field of mathematics is applied to the above optimum signal approximation and is indicated that the category-based approximation theory is applied to the set-theoretic consideration of the recognition of humans. Based on this discussion, it is shown naturally why the narrow perception that tends to create isolation shows an apparent advantage in the short term and, often, why such narrow thinking becomes intimate with discriminatory action in a human group. Throughout these considerations, it is presented that, in order to abolish easy and intimate discriminatory behavior, it is important to create a parallel world of conception where we share the set of invisible error signals, including the words and the consciousness of both worlds.

Keywords: signal prediction, pseudo inverse matrix, artificial intelligence, conditional optimization

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1868 Structure and Dimensions Of Teacher Professional Identity

Authors: Vilma Zydziunaite, Gitana Balezentiene, Vilma Zydziunaite

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Teaching is one of most responsible profession, and it is not only a job of an artisan. This profes-sion needs a developed ability to identify oneself with the chosen teaching profession. Research questions: How teachers characterize their authentic individual professional identity? What factors teachers exclude, which support and limit the professional identity? Aim was to develop the grounded theory (GT) about teacher’s professional identity (TPI). Research methodology is based on Charmaz GT version. Data were collected via semi-structured interviews with the he sample of 12 teachers. Findings. 15 extracted categories revealed that the core of TPI is teacher’s professional calling. Premises of TPI are family support, motives for choos-ing teacher’s profession, teacher’s didactic competence. Context of TPI consists of teacher compli-ance with the profession, purposeful preparation for pedagogical studies, professional growth. The strategy of TPI is based on teacher relationship with school community strengthening. The profes-sional frustration limits the TPI. TPI outcome includes teacher recognition, authority; professional mastership, professionalism, professional satisfaction. Dimensions of TPI GT the past (reaching teacher’s profession), present (teacher’s commitment to professional activity) and future (teacher’s profession reconsideration). Conclusions. The substantive GT describes professional identity as complex, changing and life-long process, which develops together with teacher’s personal identity and is connected to professional activity. The professional decision "to be a teacher" is determined by the interaction of internal (professional vocation, personal characteristics, values, self-image, talents, abilities) and external (family, friends, school community, labor market, working condi-tions) factors. The dimensions of the TPI development includes: the past (the pursuit of the teaching profession), the present (the teacher's commitment to professional activity) and the future (the revi-sion of the teaching profession). A significant connection emerged - as the teacher's professional commitment strengthens (creating a self-image, growing the teacher's professional experience, recognition, professionalism, mastery, satisfaction with pedagogical activity), the dimension of re-thinking the teacher's profession weakens. This proves that professional identity occupies an im-portant place in a teacher's life and it affects his professional success and job satisfaction. Teachers singled out the main factors supporting a teacher's professional identity: their own self-image per-ception, professional vocation, positive personal qualities, internal motivation, teacher recognition, confidence in choosing a teaching profession, job satisfaction, professional knowledge, professional growth, good relations with the school community, pleasant experiences, quality education process, excellent student achievements.

Keywords: grounded theory, teacher professional identity, semi-structured interview, school, students, school community, family

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1867 Prevalence and Risk Factors of Low Back Disorder among Waste Collection Workers: A Systematic Review

Authors: Benedicta Asante, Catherine Trask, Brenna Bath

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Background: Waste Collection Workers’ (WCWs) activities contribute greatly to the recycling sector and are an important component of the waste management industry. As the recycling sector evolves, there is the increase in reports of injuries, particularly for common and debilitating musculoskeletal disorders such as low back disorder (LBD). WCWs are likely exposed to diverse work-related hazards that could contribute to LBD. However, there is currently no summary of the state of knowledge on the prevalence and risk factors of LBD within this workforce. Method: A comprehensive search was conducted in Ovid Medline, EMBASE, and Global Health e-publications with search term categories ‘low back disorder’ and ‘waste collection workers’. Two reviewers screened articles at title, abstract, and full-text stages. Data were extracted on study design, sampling strategy, socio-demographics, geographical region, and exposure definition, the definition of LBD, response rate, statistical techniques, LBD prevalence and risk factors. The risk of bias was assessed with a standardized tool. Results: The search of three databases generated 79 studies. Thirty-two studies met the study inclusion criteria for both title and abstract; only thirteen full-text articles met the study criteria and underwent data extraction. The majority of articles reported a 12-month prevalence of LBD between 16-74%. Although none of the included studies quantified relationships between risk factors and LBD, the suggested risk factors for LBD among WCWs included: awkward posture; lifting; pulling; pushing; repetitive motions; work duration; and physical loads. Conclusion: LBD is a major occupational health issue among WCWs. In light of these risks and future growth in this industry, further research should focus on the investigation of risk factors, with more focus on ergonomic exposure assessment, and LBD prevention efforts.

Keywords: low back pain, scavenger, waste pickers, waste collection workers

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1866 The Solid-Phase Sensor Systems for Fluorescent and SERS-Recognition of Neurotransmitters for Their Visualization and Determination in Biomaterials

Authors: Irina Veselova, Maria Makedonskaya, Olga Eremina, Alexandr Sidorov, Eugene Goodilin, Tatyana Shekhovtsova

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Such catecholamines as dopamine, norepinephrine, and epinephrine are the principal neurotransmitters in the sympathetic nervous system. Catecholamines and their metabolites are considered to be important markers of socially significant diseases such as atherosclerosis, diabetes, coronary heart disease, carcinogenesis, Alzheimer's and Parkinson's diseases. Currently, neurotransmitters can be studied via electrochemical and chromatographic techniques that allow their characterizing and quantification, although these techniques can only provide crude spatial information. Besides, the difficulty of catecholamine determination in biological materials is associated with their low normal concentrations (~ 1 nM) in biomaterials, which may become even one more order lower because of some disorders. In addition, in blood they are rapidly oxidized by monoaminooxidases from thrombocytes and, for this reason, the determination of neurotransmitter metabolism indicators in an organism should be very rapid (15—30 min), especially in critical states. Unfortunately, modern instrumental analysis does not offer a complex solution of this problem: despite its high sensitivity and selectivity, HPLC-MS cannot provide sufficiently rapid analysis, while enzymatic biosensors and immunoassays for the determination of the considered analytes lack sufficient sensitivity and reproducibility. Fluorescent and SERS-sensors remain a compelling technology for approaching the general problem of selective neurotransmitter detection. In recent years, a number of catecholamine sensors have been reported including RNA aptamers, fluorescent ribonucleopeptide (RNP) complexes, and boronic acid based synthetic receptors and the sensor operated in a turn-off mode. In this work we present the fluorescent and SERS turn-on sensor systems based on the bio- or chemorecognizing nanostructured films {chitosan/collagen-Tb/Eu/Cu-nanoparticles-indicator reagents} that provide the selective recognition, visualization, and sensing of the above mentioned catecholamines on the level of nanomolar concentrations in biomaterials (cell cultures, tissue etc.). We have (1) developed optically transparent porous films and gels of chitosan/collagen; (2) ensured functionalization of the surface by molecules-'recognizers' (by impregnation and immobilization of components of the indicator systems: biorecognizing and auxiliary reagents); (3) performed computer simulation for theoretical prediction and interpretation of some properties of the developed materials and obtained analytical signals in biomaterials. We are grateful for the financial support of this research from Russian Foundation for Basic Research (grants no. 15-03-05064 a, and 15-29-01330 ofi_m).

Keywords: biomaterials, fluorescent and SERS-recognition, neurotransmitters, solid-phase turn-on sensor system

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1865 Corporate Governance in Higher Education: A South African Perspective

Authors: Corlia van der Walt, Michele K. Havenga

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The study considers corporate governance regulation and practice in South African higher education institutions and makes recommendations for the improvement of current governance practices in this sector. The development of corporate governance principles and practices in South Africa, culminating in the King IV Report on Corporate Governance which was launched in November 2016, is discussed. King IV enjoys international recognition as a progressive corporate governance instrument. It was necessitated by the fundamental changes in business and society nationally and globally, as well as by the significant changes to South African company law introduced by new legislation. Corporate governance and the corporate form are narrowly associated, but there is general recognition that the principles of ethical and effective leadership are not restricted to corporations. Thus King IV was drafted with the express aim that it should apply to all organisations, regardless of their form of incorporation, and the report includes specific sector supplements in support of this aspiration. The South African higher education sector has of late been under intense scrutiny, and a few universities have been placed under administration because of poor governance practices. Universities have also been severely impacted by the consequences of what is generally known as ‘#FeesmustFall’, a student led protest movement initially aimed against the increase of fees at public universities, but which rapidly expanded to also include other concerns. It was clearly necessary to revisit corporate governance policy and practice in the sector. The review of the current higher education governance regime in light of the King IV recommendations, lessons from company law regarding the entrenchment and enforcement of corporate governance principles, and a comparison of higher education governance practices in selected other jurisdictions led to recommendations for the improvement of governance practices in South African higher education. It is further suggested that a sector supplement for higher education institutions may provide additional clarity. Some of the recommendations may be of comparative value for international higher education governance.

Keywords: committees, corporate governance, ethical leadership, higher education institutions, integrated reporting, King IV, sector supplements, sustainability

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1864 The Impact of an Educational Program on Knowledge, Attitude and Practices of Healthcare Professionals towards Family Presence during Resuscitation in an Emergency Department at a Tertiary Care Setting, in Karachi, Pakistan

Authors: Shaista Meghani, Rozina Karmaliani, Khairulnissa Ajani, Shireen Shahzad, Nadeem Ullah Khan

Abstract:

Background: The concept of Family Presence During Resuscitation (FPDR) is gradually gaining recognition in western countries, however, it is rarely considered in South Asian countries including Pakistan. Over time, patients’ and families’ rights have gained recognition and healthcare has progressed to become more patient-family centered. Objectives: The objective of this study was to evaluate the impact of an educational program on the Knowledge, Attitude, and Practices (KAP) of healthcare professionals (HCPs) towards FPDR in Emergency Department (ED), at a tertiary care setting, in Karachi, Pakistan. Methods: This was a Pre-test and Post-test study design. A convenient universal sampling was done, and all ED nurses and physicians with more than one year of experience were eligible. The intervention included one-hour training sessions for physicians (three sessions) and nurses (eight sessions), The KAP of nurses and physicians were assessed immediately after (post-test I), and two weeks(post-test II) after the intervention using a pretested questionnaire. Results: The findings of the study revealed that the mean scores of knowledge and attitude of HCPs at both time points were statistically significant (p-value=<0.001), however, an insignificant difference was found on practice of FPDR (p-value=>0.05). Conclusion: The study findings recommend that the educational program on FPDR for HCPs needs to be offered on an ongoing basis. Moreover, training modules need to be developed for the staff, and formal guidelines need to be proposed for FPDR, through a multidisciplinary team approach.

Keywords: family presence, cardiopulmonary resuscitation, attitude, education, practices, health care professionals

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1863 The Making of a Yijing (Classic of Changes) Cultural Sphere in Asia

Authors: Ng Wai Ming

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The Yijing (Classic of Changes) is one of the most influential Chinese classics, and its text, images and divination have been widely studied and used by different people in the world from past to present. Its impact in Asia has been particularly strong due to cultural and geographical proximity. Based on many years of textual study of the history of the Yijing in the Sinosphere, the author attempts to identify various levels of acceptance and localization of the Yijing in different Asian regions, including Japan, Korea, the Ryukyu Kingdom, Vietnam, Mongolia and Tibet. It will create a new concept of “Yijing cultural sphere” to explain the popularization and indigenization of the Yijing in Asia.

Keywords: classic of changes, asia, sinosphere, localization

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1862 Computational Linguistic Implications of Gender Bias: Machines Reflect Misogyny in Society

Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Computational linguistics is a growing field dealing with such issues of data collection for technological development. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Computational analysis on such linguistic data is used to find patterns of misogyny. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: computational analysis, gendered grammar, misogynistic language, neural networks

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1861 Optimizing the Use of Google Translate in Translation Teaching: A Case Study at Prince Sultan University

Authors: Saadia Elamin

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The quasi-universal use of smart phones with internet connection available all the time makes it a reflex action for translation undergraduates, once they encounter the least translation problem, to turn to the freely available web resource: Google Translate. Like for other translator resources and aids, the use of Google Translate needs to be moderated in such a way that it contributes to developing translation competence. Here, instead of interfering with students’ learning by providing ready-made solutions which might not always fit into the contexts of use, it can help to consolidate the skills of analysis and transfer which students have already acquired. One way to do so is by training students to adhere to the basic principles of translation work. The most important of these is that analyzing the source text for comprehension comes first and foremost before jumping into the search for target language equivalents. Another basic principle is that certain translator aids and tools can be used for comprehension, while others are to be confined to the phase of re-expressing the meaning into the target language. The present paper reports on the experience of making a measured and reasonable use of Google Translate in translation teaching at Prince Sultan University (PSU), Riyadh. First, it traces the development that has taken place in the field of translation in this age of information technology, be it in translation teaching and translator training, or in the real-world practice of the profession. Second, it describes how, with the aim of reflecting this development onto the way translation is taught, senior students, after being trained on post-editing machine translation output, are authorized to use Google Translate in classwork and assignments. Third, the paper elaborates on the findings of this case study which has demonstrated that Google Translate, if used at the appropriate levels of training, can help to enhance students’ ability to perform different translation tasks. This help extends from the search for terms and expressions, to the tasks of drafting the target text, revising its content and finally editing it. In addition, using Google Translate in this way fosters a reflexive and critical attitude towards web resources in general, maximizing thus the benefit gained from them in preparing students to meet the requirements of the modern translation job market.

Keywords: Google Translate, post-editing machine translation output, principles of translation work, translation competence, translation teaching, translator aids and tools

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1860 Using Textual Pre-Processing and Text Mining to Create Semantic Links

Authors: Ricardo Avila, Gabriel Lopes, Vania Vidal, Jose Macedo

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This article offers a approach to the automatic discovery of semantic concepts and links in the domain of Oil Exploration and Production (E&P). Machine learning methods combined with textual pre-processing techniques were used to detect local patterns in texts and, thus, generate new concepts and new semantic links. Even using more specific vocabularies within the oil domain, our approach has achieved satisfactory results, suggesting that the proposal can be applied in other domains and languages, requiring only minor adjustments.

Keywords: semantic links, data mining, linked data, SKOS

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1859 A Novel Machine Learning Approach to Aid Agrammatism in Non-fluent Aphasia

Authors: Rohan Bhasin

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Agrammatism in non-fluent Aphasia Cases can be defined as a language disorder wherein a patient can only use content words ( nouns, verbs and adjectives ) for communication and their speech is devoid of functional word types like conjunctions and articles, generating speech of with extremely rudimentary grammar . Past approaches involve Speech Therapy of some order with conversation analysis used to analyse pre-therapy speech patterns and qualitative changes in conversational behaviour after therapy. We describe this approach as a novel method to generate functional words (prepositions, articles, ) around content words ( nouns, verbs and adjectives ) using a combination of Natural Language Processing and Deep Learning algorithms. The applications of this approach can be used to assist communication. The approach the paper investigates is : LSTMs or Seq2Seq: A sequence2sequence approach (seq2seq) or LSTM would take in a sequence of inputs and output sequence. This approach needs a significant amount of training data, with each training data containing pairs such as (content words, complete sentence). We generate such data by starting with complete sentences from a text source, removing functional words to get just the content words. However, this approach would require a lot of training data to get a coherent input. The assumptions of this approach is that the content words received in the inputs of both text models are to be preserved, i.e, won't alter after the functional grammar is slotted in. This is a potential limit to cases of severe Agrammatism where such order might not be inherently correct. The applications of this approach can be used to assist communication mild Agrammatism in non-fluent Aphasia Cases. Thus by generating these function words around the content words, we can provide meaningful sentence options to the patient for articulate conversations. Thus our project translates the use case of generating sentences from content-specific words into an assistive technology for non-Fluent Aphasia Patients.

Keywords: aphasia, expressive aphasia, assistive algorithms, neurology, machine learning, natural language processing, language disorder, behaviour disorder, sequence to sequence, LSTM

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1858 Behavioral and EEG Reactions in Native Turkic-Speaking Inhabitants of Siberia and Siberian Russians during Recognition of Syntactic Errors in Sentences in Native and Foreign Languages

Authors: Tatiana N. Astakhova, Alexander E. Saprygin, Tatyana A. Golovko, Alexander N. Savostyanov, Mikhail S. Vlasov, Natalia V. Borisova, Alexandera G. Karpova, Urana N. Kavai-ool, Elena D. Mokur-ool, Nikolay A. Kolchanov, Lubomir I. Aftanas

Abstract:

The aim of the study is to compare behaviorally and EEG reactions in Turkic-speaking inhabitants of Siberia (Tuvinians and Yakuts) and Russians during the recognition of syntax errors in native and foreign languages. 63 healthy aboriginals of the Tyva Republic, 29 inhabitants of the Sakha (Yakutia) Republic, and 55 Russians from Novosibirsk participated in the study. All participants completed a linguistic task, in which they had to find a syntax error in the written sentences. Russian participants completed the task in Russian and in English. Tuvinian and Yakut participants completed the task in Russian, English, and Tuvinian or Yakut, respectively. EEG’s were recorded during the solving of tasks. For Russian participants, EEG's were recorded using 128-channels. The electrodes were placed according to the extended International 10-10 system, and the signals were amplified using ‘Neuroscan (USA)’ amplifiers. For Tuvinians and Yakuts EEG's were recorded using 64-channels and amplifiers Brain Products, Germany. In all groups 0.3-100 Hz analog filtering, sampling rate 1000 Hz were used. Response speed and the accuracy of recognition error were used as parameters of behavioral reactions. Event-related potentials (ERP) responses P300 and P600 were used as indicators of brain activity. The accuracy of solving tasks and response speed in Russians were higher for Russian than for English. The P300 amplitudes in Russians were higher for English; the P600 amplitudes in the left temporal cortex were higher for the Russian language. Both Tuvinians and Yakuts have no difference in accuracy of solving tasks in Russian and in their respective national languages (Tuvinian and Yakut). However, the response speed was faster for tasks in Russian than for tasks in their national language. Tuvinians and Yakuts showed bad accuracy in English, but the response speed was higher for English than for Russian and the national languages. With Tuvinians, there were no differences in the P300 and P600 amplitudes and in cortical topology for Russian and Tuvinian, but there was a difference for English. In Yakuts, the P300 and P600 amplitudes and topology of ERP for Russian were the same as Russians had for Russian. In Yakuts, brain reactions during Yakut and English comprehension had no difference and were reflected foreign language comprehension -while the Russian language comprehension was reflected native language comprehension. We found out that the Tuvinians recognized both Russian and Tuvinian as native languages, and English as a foreign language. The Yakuts recognized both English and Yakut as a foreign language, only Russian as a native language. According to the inquirer, both Tuvinians and Yakuts use the national language as a spoken language, whereas they don’t use it for writing. It can well be a reason that Yakuts perceive the Yakut writing language as a foreign language while writing Russian as their native.

Keywords: EEG, language comprehension, native and foreign languages, Siberian inhabitants

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1857 Combining Corpus Linguistics and Critical Discourse Analysis to Study Power Relations in Hindi Newspapers

Authors: Vandana Mishra, Niladri Sekhar Dash, Jayshree Charkraborty

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This present paper focuses on the application of corpus linguistics techniques for critical discourse analysis (CDA) of Hindi newspapers. While Corpus linguistics is the study of language as expressed in corpora (samples) of 'real world' text, CDA is an interdisciplinary approach to the study of discourse that views language as a form of social practice. CDA has mainly been studied from a qualitative perspective. However, we can say that recent studies have begun combining corpus linguistics with CDA in analyzing large volumes of text for the study of existing power relations in society. The corpus under our study is also of a sizable amount (1 million words of Hindi newspaper texts) and its analysis requires an alternative analytical procedure. So, we have combined both the quantitative approach i.e. the use of corpus techniques with CDA’s traditional qualitative analysis. In this context, we have focused on the Keyword Analysis Sorting Concordance Lines of the selected Keywords and calculating collocates of the keywords. We have made use of the Wordsmith Tool for all these analysis. The analysis starts with identifying the keywords in the political news corpus when compared with the main news corpus. The keywords are extracted from the corpus based on their keyness calculated through statistical tests like chi-squared test and log-likelihood test on the frequent words of the corpus. Some of the top occurring keywords are मोदी (Modi), भाजपा (BJP), कांग्रेस (Congress), सरकार (Government) and पार्टी (Political party). This is followed by the concordance analysis of these keywords which generates thousands of lines but we have to select few lines and examine them based on our objective. We have also calculated the collocates of the keywords based on their Mutual Information (MI) score. Both concordance and collocation help to identify lexical patterns in the political texts. Finally, all these quantitative results derived from the corpus techniques will be subjectively interpreted in accordance to the CDA’s theory to examine the ways in which political news discourse produces social and political inequality, power abuse or domination.

Keywords: critical discourse analysis, corpus linguistics, Hindi newspapers, power relations

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1856 ARABEX: Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder and Custom Convolutional Recurrent Neural Network

Authors: Hozaifa Zaki, Ghada Soliman

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In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

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1855 IT-Based Global Healthcare Delivery System: An Alternative Global Healthcare Delivery System

Authors: Arvind Aggarwal

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We have developed a comprehensive global healthcare delivery System based on information technology. It has medical consultation system where a virtual consultant can give medical consultation to the patients and Doctors at the digital medical centre after reviewing the patient’s EMR file consisting of patient’s history, investigations in the voice, images and data format. The system has the surgical operation system too, where a remote robotic consultant can conduct surgery at the robotic surgical centre. The instant speech and text translation is incorporated in the software where the patient’s speech and text (language) can be translated into the consultant’s language and vice versa. A consultant of any specialty (surgeon or Physician) based in any country can provide instant health care consultation, to any patient in any country without loss of time. Robotic surgeons based in any country in a tertiary care hospital can perform remote robotic surgery, through patient friendly telemedicine and tele-surgical centres. The patient EMR, financial data and data of all the consultants and robotic surgeons shall be stored in cloud. It is a complete comprehensive business model with healthcare medical and surgical delivery system. The whole system is self-financing and can be implemented in any country. The entire system uses paperless, filmless techniques. This eliminates the use of all consumables thereby reduces substantial cost which is incurred by consumables. The consultants receive virtual patients, in the form of EMR, thus the consultant saves time and expense to travel to the hospital to see the patients. The consultant gets electronic file ready for reporting & diagnosis. Hence time spent on the physical examination of the patient is saved, the consultant can, therefore, spend quality time in studying the EMR/virtual patient and give his instant advice. The time consumed per patient is reduced and therefore can see more number of patients, the cost of the consultation per patients is therefore reduced. The additional productivity of the consultants can be channelized to serve rural patients devoid of doctors.

Keywords: e-health, telemedicine, telecare, IT-based healthcare

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1854 A Study of Topical and Similarity of Sebum Layer Using Interactive Technology in Image Narratives

Authors: Chao Wang

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Under rapid innovation of information technology, the media plays a very important role in the dissemination of information, and it has a totally different analogy generations face. However, the involvement of narrative images provides more possibilities of narrative text. "Images" through the process of aperture, a camera shutter and developable photosensitive processes are manufactured, recorded and stamped on paper, displayed on a computer screen-concretely saved. They exist in different forms of files, data, or evidence as the ultimate looks of events. By the interface of media and network platforms and special visual field of the viewer, class body space exists and extends out as thin as sebum layer, extremely soft and delicate with real full tension. The physical space of sebum layer of confuses the fact that physical objects exist, needs to be established under a perceived consensus. As at the scene, the existing concepts and boundaries of physical perceptions are blurred. Sebum layer physical simulation shapes the “Topical-Similarity" immersing, leading the contemporary social practice communities, groups, network users with a kind of illusion without the presence, i.e. a non-real illusion. From the investigation and discussion of literatures, digital movies editing manufacture and produce the variability characteristics of time (for example, slices, rupture, set, and reset) are analyzed. Interactive eBook has an unique interaction in "Waiting-Greeting" and "Expectation-Response" that makes the operation of image narrative structure more interpretations functionally. The works of digital editing and interactive technology are combined and further analyze concept and results. After digitization of Interventional Imaging and interactive technology, real events exist linked and the media handing cannot be cut relationship through movies, interactive art, practical case discussion and analysis. Audience needs more rational thinking about images carried by the authenticity of the text.

Keywords: sebum layer, topical and similarity, interactive technology, image narrative

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1853 Deep Learning Based Text to Image Synthesis for Accurate Facial Composites in Criminal Investigations

Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

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1852 Dwindling the Stability of DNA Sequence by Base Substitution at Intersection of COMT and MIR4761 Gene

Authors: Srishty Gulati, Anju Singh, Shrikant Kukreti

Abstract:

The manifestation of structural polymorphism in DNA depends on the sequence and surrounding environment. Ample of folded DNA structures have been found in the cellular system out of which DNA hairpins are very common, however, are indispensable due to their role in the replication initiation sites, recombination, transcription regulation, and protein recognition. We enumerate this approach in our study, where the two base substitutions and change in temperature embark destabilization of DNA structure and misbalance the equilibrium between two structures of a sequence present at the overlapping region of the human COMT gene and MIR4761 gene. COMT and MIR4761 gene encodes for catechol-O-methyltransferase (COMT) enzyme and microRNAs (miRNAs), respectively. Environmental changes and errors during cell division lead to genetic abnormalities. The COMT gene entailed in dopamine regulation fosters neurological diseases like Parkinson's disease, schizophrenia, velocardiofacial syndrome, etc. A 19-mer deoxyoligonucleotide sequence 5'-AGGACAAGGTGTGCATGCC-3' (COMT19) is located at exon-4 on chromosome 22 and band q11.2 at the intersection of COMT and MIR4761 gene. Bioinformatics studies suggest that this sequence is conserved in humans and few other organisms and is involved in recognition of transcription factors in the vicinity of 3'-end. Non-denaturating gel electrophoresis and CD spectroscopy of COMT sequences indicate the formation of hairpin type DNA structures. Temperature-dependent CD studies revealed an unusual shift in the slipped DNA-Hairpin DNA equilibrium with the change in temperature. Also, UV-thermal melting techniques suggest that the two base substitutions on the complementary strand of COMT19 did not affect the structure but reduces the stability of duplex. This study gives insight about the possibility of existing structurally polymorphic transient states within DNA segments present at the intersection of COMT and MIR4761 gene.

Keywords: base-substitution, catechol-o-methyltransferase (COMT), hairpin-DNA, structural polymorphism

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1851 Exploration of the Protection Theory of Chinese Scenic Heritage Based on Local Chronicles

Authors: Mao Huasong, Tang Siqi, Cheng Yu

Abstract:

The cognition and practice of Chinese landscapes have distinct uniqueness. The intergenerational inheritance of urban and rural landscapes is a common objective fact which has created a unique type of heritage in China - scenic heritage. The current generalization of the concept of scenic heritage has affected the lack of innovation in corresponding protection practices. Therefore, clarifying the concepts and connotations of scenery and scenic heritage, clarifying the protection objects of scenic heritage and the methods and approaches in intergenerational inheritance can provide theoretical support for the practice of Chinese scenic heritage and contribute Chinese wisdom to the transformation of world heritage sites. Taking ancient Shaoxing, which has a long time span and rich descriptions of scenic types and quantities, as the research object and using local chronicles as the basic research material, based on text analysis, word frequency analysis, case statistics, and historical, geographical spatial annotation methods, this study traces back to ancient scenic practices and conducts in-depth descriptions in both text and space. it have constructed a scenic heritage identification method based on the basic connotation characteristics and morphological representation characteristics of natural and cultural correlations, combined with the intergenerational and representative characteristics of scenic heritage; Summarized the bidirectional integration of "scenic spots" and "form scenic spots", "outstanding people" and "local spirits" in the formation process of scenic heritage; In inheritance, guided by Confucian values of education; In communication, the cultural interpretation constructed by scenery and the way of landscape life are used to strengthen the intergenerational inheritance of natural, artificial material elements, and intangible spirits. As a unique type of heritage in China, scenic heritage should improve its standards, values, and connotations in current protection practices and actively absorb historical experience.

Keywords: scenic heritage, heritage protection, cultural landscape, shaoxing, chinese landscape

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1850 Facial Recognition and Landmark Detection in Fitness Assessment and Performance Improvement

Authors: Brittany Richardson, Ying Wang

Abstract:

For physical therapy, exercise prescription, athlete training, and regular fitness training, it is crucial to perform health assessments or fitness assessments periodically. An accurate assessment is propitious for tracking recovery progress, preventing potential injury and making long-range training plans. Assessments include necessary measurements, height, weight, blood pressure, heart rate, body fat, etc. and advanced evaluation, muscle group strength, stability-mobility, and movement evaluation, etc. In the current standard assessment procedures, the accuracy of assessments, especially advanced evaluations, largely depends on the experience of physicians, coaches, and personal trainers. And it is challenging to track clients’ progress in the current assessment. Unlike the tradition assessment, in this paper, we present a deep learning based face recognition algorithm for accurate, comprehensive and trackable assessment. Based on the result from our assessment, physicians, coaches, and personal trainers are able to adjust the training targets and methods. The system categorizes the difficulty levels of the current activity for the client or user, furthermore make more comprehensive assessments based on tracking muscle group over time using a designed landmark detection method. The system also includes the function of grading and correcting the form of the clients during exercise. Experienced coaches and personal trainer can tell the clients' limit based on their facial expression and muscle group movements, even during the first several sessions. Similar to this, using a convolution neural network, the system is trained with people’s facial expression to differentiate challenge levels for clients. It uses landmark detection for subtle changes in muscle groups movements. It measures the proximal mobility of the hips and thoracic spine, the proximal stability of the scapulothoracic region and distal mobility of the glenohumeral joint, as well as distal mobility, and its effect on the kinetic chain. This system integrates data from other fitness assistant devices, including but not limited to Apple Watch, Fitbit, etc. for a improved training and testing performance. The system itself doesn’t require history data for an individual client, but the history data of a client can be used to create a more effective exercise plan. In order to validate the performance of the proposed work, an experimental design is presented. The results show that the proposed work contributes towards improving the quality of exercise plan, execution, progress tracking, and performance.

Keywords: exercise prescription, facial recognition, landmark detection, fitness assessments

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1849 Migration Law in Republic of Panama

Authors: Ronel Solis, Leonardo Collado

Abstract:

Migration law in the Republic of Panama has been regulated mainly by the executive branch. This has created a crisis not only institutional but also social because the evolution of these norms has rested greatly from the discretion of the government in office. This has created instability in immigration regulation and more now, with the migration crisis of which Panama is also part. Different migration policies have been established. The most recent is that of the controlled migration flow, in which, for humanitarian reasons, migrants move from the border with Colombia to the border with Costa Rica. Unfortunately, such control is not enough, and in some cases, unprotected migrants have been confined for months, their passports have been withheld, and no recognition of their rights is offered. The Inter-American Court of Human Rights has condemned Panama for the unfair detention of an irregular migrant, who was detained for two years in Panamanian prisons, without having committed a crime and without accessing a just defense. This is the case Vélez Loor vs. the Republic of Panama. Uncontrollable migration has been putting pressure on Panamanian public health services. The recent denunciation of HIV-related NGOs that warns that there are hundreds of foreigners who receive expensive antiretroviral therapy in Panama is serious, and several of them are irregular migrants. On the other hand, there are no border control posts with the Republic of Colombia, because it is a jungle area and migrants are exposed to arms and drug trafficking, and unfortunately, also to prostitution. Government entities such as the border police service have provided humanitarian support to migrants on the border with Colombia, although it is not their administrative function, and various entities discuss who should address this crisis. However, few economic resources are allocated by the government to solve this problem, especially with the recent mass migration of Venezuelans who have fled their country. The establishment of a migratory normative code is necessary to establish uniformity in the recognition and application of migratory rights. In this way, dependence on the changing migration policies of the different Panamanian governments would be eliminated, and the rights of migrants and nationals would be guaranteed.

Keywords: executive branch, irregular migration, migration code, Republic of Panama

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1848 Honneth, Feenberg, and the Redemption of Critical Theory of Technology

Authors: David Schafer

Abstract:

Critical Theory is in sore need of a workable account of technology. It had one in the writings of Herbert Marcuse, or so it seemed until Jürgen Habermas mounted a critique in 'Technology and Science as Ideology' (Habermas, 1970) that decisively put it away. Ever since Marcuse’s work has been regarded outdated – a 'philosophy of consciousness' no longer seriously tenable. But with Marcuse’s view has gone the important insight that technology is no norm-free system (as Habermas portrays it) but can be laden with social bias. Andrew Feenberg is among a few serious scholars who have perceived this problem in post-Habermasian critical theory and has sought to revive a basically Marcusean account of technology. On his view, while so-called ‘technical elements’ that physically make up technologies are neutral with regard to social interests, there is a sense in which we may speak of a normative grammar or ‘technical code’ built-in to technology that can be socially biased in favor of certain groups over others (Feenberg, 2002). According to Feenberg, those perspectives on technology are reified which consider technology only by their technical elements to the neglect of their technical codes. Nevertheless, Feenberg’s account fails to explain what is normatively problematic with such reified views of technology. His plausible claim that they represent false perspectives on technology by itself does not explain how such views may be oppressive, even though Feenberg surely wants to be doing that stronger level of normative theorizing. Perceiving this deficit in his own account of reification, he tries to adopt Habermas’s version of systems-theory to ground his own critical theory of technology (Feenberg, 1999). But this is a curious move in light of Feenberg’s own legitimate critiques of Habermas’s portrayals of technology as reified or ‘norm-free.’ This paper argues that a better foundation may be found in Axel Honneth’s recent text, Freedom’s Right (Honneth, 2014). Though Honneth there says little explicitly about technology, he offers an implicit account of reification formulated in opposition to Habermas’s systems-theoretic approach. On this ‘normative functionalist’ account of reification, social spheres are reified when participants prioritize individualist ideals of freedom (moral and legal freedom) to the neglect of an intersubjective form of freedom-through-recognition that Honneth calls ‘social freedom.’ Such misprioritization is ultimately problematic because it is unsustainable: individual freedom is philosophically and institutionally dependent upon social freedom. The main difficulty in adopting Honneth’s social theory for the purposes of a theory of technology, however, is that the notion of social freedom is predicable only of social institutions, whereas it appears difficult to conceive of technology as an institution. Nevertheless, in light of Feenberg’s work, the idea that technology includes within itself a normative grammar (technical code) takes on much plausibility. To the extent that this normative grammar may be understood by the category of social freedom, Honneth’s dialectical account of the relationship between individual and social forms of freedom provides a more solid basis from which to ground the normative claims of Feenberg’s sociological account of technology than Habermas’s systems theory.

Keywords: Habermas, Honneth, technology, Feenberg

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1847 Revolutionizing Healthcare Communication: The Transformative Role of Natural Language Processing and Artificial Intelligence

Authors: Halimat M. Ajose-Adeogun, Zaynab A. Bello

Abstract:

Artificial Intelligence (AI) and Natural Language Processing (NLP) have transformed computer language comprehension, allowing computers to comprehend spoken and written language with human-like cognition. NLP, a multidisciplinary area that combines rule-based linguistics, machine learning, and deep learning, enables computers to analyze and comprehend human language. NLP applications in medicine range from tackling issues in electronic health records (EHR) and psychiatry to improving diagnostic precision in orthopedic surgery and optimizing clinical procedures with novel technologies like chatbots. The technology shows promise in a variety of medical sectors, including quicker access to medical records, faster decision-making for healthcare personnel, diagnosing dysplasia in Barrett's esophagus, boosting radiology report quality, and so on. However, successful adoption requires training for healthcare workers, fostering a deep understanding of NLP components, and highlighting the significance of validation before actual application. Despite prevailing challenges, continuous multidisciplinary research and collaboration are critical for overcoming restrictions and paving the way for the revolutionary integration of NLP into medical practice. This integration has the potential to improve patient care, research outcomes, and administrative efficiency. The research methodology includes using NLP techniques for Sentiment Analysis and Emotion Recognition, such as evaluating text or audio data to determine the sentiment and emotional nuances communicated by users, which is essential for designing a responsive and sympathetic chatbot. Furthermore, the project includes the adoption of a Personalized Intervention strategy, in which chatbots are designed to personalize responses by merging NLP algorithms with specific user profiles, treatment history, and emotional states. The synergy between NLP and personalized medicine principles is critical for tailoring chatbot interactions to each user's demands and conditions, hence increasing the efficacy of mental health care. A detailed survey corroborated this synergy, revealing a remarkable 20% increase in patient satisfaction levels and a 30% reduction in workloads for healthcare practitioners. The poll, which focused on health outcomes and was administered to both patients and healthcare professionals, highlights the improved efficiency and favorable influence on the broader healthcare ecosystem.

Keywords: natural language processing, artificial intelligence, healthcare communication, electronic health records, patient care

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1846 Caregiver Training Results in Accurate Reporting of Stool Frequency

Authors: Matthew Heidman, Susan Dallabrida, Analice Costa

Abstract:

Background:Accuracy of caregiver reported outcomes is essential for infant growth and tolerability study success. Crying/fussiness, stool consistencies, and other gastrointestinal characteristics are important parameters regarding tolerability, and inter-caregiver reporting can see a significant amount of subjectivity and vary greatly within a study, compromising data. This study sought to elucidate how caregiver reported questions related to stool frequency are answered before and after a short amount of training and how training impacts caregivers’ understanding, and how they would answer the question. Methods:A digital survey was issued for 90 daysin the US (n=121) and 30 days in Mexico (n=88), targeting respondents with children ≤4 years of age. Respondents were asked a question in two formats, first without a line of training text and second with a line of training text. The question set was as follows, “If your baby had stool in his/her diaper and you changed the diaper and 10 min later there was more stool in the diaper, how many stools would you report this as?” followed by the same question beginning with “If you were given the instruction that IF there are at least 5 minutes in between stools, then it counts as two (2) stools…”.Four response items were provided for both questions, 1) 2 stools, 2) 1stool, 3) it depends on how much stool was in the first versus the second diaper, 4) There is not enough information to be able to answer the question. Response frequencies between questions were compared. Results: Responses to the question without training saw some variability in the US, with 69% selecting “2 stools”,11% selecting “1 stool”, 14% selecting “it depends on how much stool was in the first versus the second diaper”, and 7% selecting “There is not enough information to be able to answer the question” and in Mexico respondents selected 9%, 78%, 13%, and 0% respectively. However, responses to the question after training saw more consolidation in the US, with 85% of respondents selecting“2 stools,” representing an increase in those selecting the correct answer. Additionally in Mexico, with 84% of respondents selecting “1 episode” representing an increase in the those selecting the correct response. Conclusions: Caregiver reported outcomes are critical for infant growth and tolerability studies, however, they can be highly subjective and see a high variability of responses without guidance. Training is critical to standardize all caregivers’ perspective regarding how to answer questions accurately in order to provide an accurate dataset.

Keywords: infant nutrition, clinical trial optimization, stool reporting, decentralized clinical trials

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1845 A Randomized, Controlled Trial to Test Habit Formation Theory for Low Intensity Physical Exercise Promotion in Older Adults

Authors: Patrick Louie Robles, Jerry Suls, Ciaran Friel, Mark Butler, Samantha Gordon, Frank Vicari, Joan Duer-Hefele, Karina W. Davidson

Abstract:

Physical activity guidelines focus on increasing moderate-intensity activity for older adults, but adherence to recommendations remains low. This is despite the fact that scientific evidence finds increasing physical activity is positively associated with health benefits. Behavior change techniques (BCTs) have demonstrated some effectiveness in reducing sedentary behavior and promoting physical activity. This pilot study uses a personalized trials (N-of-1) design, delivered virtually, to evaluate the efficacy of using five BCTs in increasing low-intensity physical activity (by 2,000 steps of walking per day) in adults aged 45-75 years old. The 5 BCTs described in habit formation theory are goal setting, action planning, rehearsal, rehearsal in a consistent context, and self-monitoring. The study recruited health system employees in the target age range who had no mobility restrictions and expressed interest in increasing their daily activity by a minimum of 2,000 steps per day at least five days per week. Participants were sent a Fitbit Charge 4 fitness tracker with an established study account and password. Participants were recommended to wear the Fitbit device 24/7 but were required to wear it for a minimum of ten hours per day. Baseline physical activity was measured by Fitbit for two weeks. Participants then engaged remotely with a clinical research coordinator to establish a “walking plan” that included a time and day interval (e.g., between 7am -8am on Monday-Friday), a location for the walk (e.g., park), and how much time the plan would need to achieve a minimum of 2,000 steps over their baseline average step count (20 minutes). All elements of the walking plan were required to remain consistent throughout the study. In the 10-week intervention phase of the study, participants received all five BCTs in a single, time-sensitive text message. The text message was delivered 30 minutes prior to the established walk time and signaled participants to begin walking when the context (i.e., day of the week, time of day) they pre-selected is encountered. Participants were asked to log both the start and conclusion of their activity session by pressing a button on the Fitbit tracker. Within 30 minutes of the planned conclusion of the activity session, participants received a text message with a link to a secure survey. Here, they noted whether they engaged in the BCTs when prompted and completed an automaticity survey to identify how “automatic” their walking behavior had become. At the end of their trial, participants received a personalized summary of their step data over time, helping them learn more about their responses to the five BCTs. Whether the use of these 5 ‘habit formation’ BCTs in combination elicits a change in physical activity behavior among older adults will be reported. This study will inform the feasibility of a virtually-delivered N-of-1 study design to effectively promote physical activity as a component of healthy aging.

Keywords: aging, exercise, habit, walking

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1844 Towards Learning Query Expansion

Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

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1843 Embedded Semantic Segmentation Network Optimized for Matrix Multiplication Accelerator

Authors: Jaeyoung Lee

Abstract:

Autonomous driving systems require high reliability to provide people with a safe and comfortable driving experience. However, despite the development of a number of vehicle sensors, it is difficult to always provide high perceived performance in driving environments that vary from time to season. The image segmentation method using deep learning, which has recently evolved rapidly, provides high recognition performance in various road environments stably. However, since the system controls a vehicle in real time, a highly complex deep learning network cannot be used due to time and memory constraints. Moreover, efficient networks are optimized for GPU environments, which degrade performance in embedded processor environments equipped simple hardware accelerators. In this paper, a semantic segmentation network, matrix multiplication accelerator network (MMANet), optimized for matrix multiplication accelerator (MMA) on Texas instrument digital signal processors (TI DSP) is proposed to improve the recognition performance of autonomous driving system. The proposed method is designed to maximize the number of layers that can be performed in a limited time to provide reliable driving environment information in real time. First, the number of channels in the activation map is fixed to fit the structure of MMA. By increasing the number of parallel branches, the lack of information caused by fixing the number of channels is resolved. Second, an efficient convolution is selected depending on the size of the activation. Since MMA is a fixed, it may be more efficient for normal convolution than depthwise separable convolution depending on memory access overhead. Thus, a convolution type is decided according to output stride to increase network depth. In addition, memory access time is minimized by processing operations only in L3 cache. Lastly, reliable contexts are extracted using the extended atrous spatial pyramid pooling (ASPP). The suggested method gets stable features from an extended path by increasing the kernel size and accessing consecutive data. In addition, it consists of two ASPPs to obtain high quality contexts using the restored shape without global average pooling paths since the layer uses MMA as a simple adder. To verify the proposed method, an experiment is conducted using perfsim, a timing simulator, and the Cityscapes validation sets. The proposed network can process an image with 640 x 480 resolution for 6.67 ms, so six cameras can be used to identify the surroundings of the vehicle as 20 frame per second (FPS). In addition, it achieves 73.1% mean intersection over union (mIoU) which is the highest recognition rate among embedded networks on the Cityscapes validation set.

Keywords: edge network, embedded network, MMA, matrix multiplication accelerator, semantic segmentation network

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1842 Using the Dokeos Platform for Industrial E-Learning Solution

Authors: Kherafa Abdennasser

Abstract:

The application of Information and Communication Technologies (ICT) to the training area led to the creation of this new reality called E-learning. That last one is described like the marriage of multi- media (sound, image and text) and of the internet (diffusion on line, interactivity). Distance learning became an important totality for training and that last pass in particular by the setup of a distance learning platform. In our memory, we will use an open source platform named Dokeos for the management of a distance training of GPS called e-GPS. The learner is followed in all his training. In this system, trainers and learners communicate individually or in group, the administrator setup and make sure of this system maintenance.

Keywords: ICT, E-learning, learning plate-forme, Dokeos, GPS

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1841 Rendering Religious References in English: Naguib Mahfouz in the Arabic as a Foreign Language Classroom

Authors: Shereen Yehia El Ezabi

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The transition from the advanced to the superior level of Arabic proficiency is widely known to pose considerable challenges for English speaking students of Arabic as a Foreign Language (AFL). Apart from the increasing complexity of the grammar at this juncture, together with the sprawling vocabulary, to name but two of those challenges, there is also the somewhat less studied hurdle along the way to superior level proficiency, namely, the seeming opacity of many aspects of Arab/ic culture to such learners. This presentation tackles one specific dimension of such issues: religious references in literary texts. It illustrates how carefully constructed translation activities may be used to expand and deepen students’ understanding and use of them. This is shown to be vital for making the leap to the desired competency, given that such elements, as reflected in customs, traditions, institutions, worldviews, and formulaic expressions lie at the very core of Arabic culture and, as such, pervade all modes and levels of Arabic discourse. A short story from the collection “Stories from Our Alley”, by preeminent novelist Naguib Mahfouz is selected for use in this context, being particularly replete with such religious references, of which religious expressions will form the focus of the presentation. As a miniature literary work, it provides an organic whole, so to speak, within which to explore with the class the most precise denotation, as well as the subtlest connotation of each expression in an effort to reach the ‘best’ English rendering. The term ‘best’ refers to approximating the meaning in its full complexity from the source text, in this case Arabic, to the target text, English, according to the concept of equivalence in translation theory. The presentation will show how such a process generates the sort of thorough discussion and close text analysis which allows students to gain valuable insight into this central idiom of Arabic. A variety of translation methods will be highlighted, gleaned from the presenter’s extensive work with advanced/superior students in the Center for Arabic Study Abroad (CASA) program at the American University in Cairo. These begin with the literal rendering of expressions, with the purpose of reinforcing vocabulary learning and practicing the rules of derivational morphology as they form each word, since the larger context remains that of an AFL class, as opposed to a translation skills program. However, departures from the literal approach are subsequently explored by degrees, moving along the spectrum of functional and pragmatic freer translations in order to transmit the ‘real’ meaning in readable English to the target audience- no matter how culture/religion specific the expression- while remaining faithful to the original. Samples from students’ work pre and post discussion will be shared, demonstrating how class consensus is formed as to the final English rendering, proposed as the closest match to the Arabic, and shown to be the result of the above activities. Finally, a few examples of translation work which students have gone on to publish will be shared to corroborate the effectiveness of this teaching practice.

Keywords: superior level proficiency in Arabic as a foreign language, teaching Arabic as a foreign language, teaching idiomatic expressions, translation in foreign language teaching

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1840 The Responsible Lending Principle in the Spanish Proposal of the Mortgage Credit Act

Authors: Noelia Collado-Rodriguez

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The Mortgage Credit Directive 2014/17/UE should have been transposed the 21st of March of 2016. However, in Spain not only we did not meet the deadline, but currently we just have a preliminary draft of the so-called Mortgage Credit Act. Before we analyze the preliminary draft from the standpoint of the responsible lending principle, we should point out that this preliminary draft is not a consumer law statute. Through the text of the preliminary draft we cannot see any reference to the consumer, but we see references to the borrower. Furthermore, and more important, the application of this statute would not be, according to its text, circumscribed to borrowers who address the credit to a personal purpose. Instead, it seems that the preliminary draft aims to be one more of the rules of banking transparency that already exists in the Spanish legislation. In this sense, we can also mention that the sanctions contained in the preliminary draft are referred to these laws of banking ordination and oversight – where the rules of banking transparency belong –. This might be against the spirit of the Mortgage Credit Directive, which allows the extension of its scope to credits aimed to acquire other immovable property beyond the residential one. However, the borrower has to be a consumer accordingly with the Directive. It is quite relevant that the prospective Spanish Mortgage Credit Act might not be a consumer protection statute; specially, from the perspective of the responsible lending principle. The responsible lending principle is a consumer law principle, which is based on the structural weakness of the consumer’s position in the relationship with the creditor. Therefore, it cannot surprise that the Spanish preliminary draft does not state any of the pre contractual conducts that express the responsible lending principle. We are referring to the lender’s duty to provide adequate explanations; the consumer’s suitability test; the lender’s duty to assess consumer’s creditworthiness; the consultation of databases to perform the creditworthiness assessment; and the most important, the lender’s prohibition to grant credit in case of a negative creditworthiness assessment. The preliminary draft just entitles the Economy Ministry to enact provisions related to those topics. Thus, the duties and rules derived from the responsible lending principle included in the EU Directive will not have legal character in Spain, being mere administrative regulations. To conclude, the two main questions that come up after reading the Spanish Mortgage Credit Act preliminary draft are, in the first place, what kind of consequences might arise from the Mortgage Credit Act if finally it is not a consumer law statute. And in the second place, what might be the consequences for the responsible lending principle of being developed by administrative regulations instead of by legislation.

Keywords: consumer credit, consumer protection, creditworthiness assessment, responsible lending

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