Search results for: automatic recognition of speech

Authors: Ibrahim Ozkan

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In this study, a cross-layer design which combines adaptive modulation and coding (AMC) and hybrid automatic repeat request (HARQ) techniques for a cooperative wireless network is investigated analytically. Previous analyses of such systems in the literature are confined to the case where the fading channel is independent at each retransmission, which can be unrealistic unless the channel is varying very fast. On the other hand, temporal channel correlation can have a significant impact on the performance of HARQ systems. In this study, utilizing a Markov channel model which accounts for the temporal correlation, the performance of non-cooperative and cooperative networks are investigated in terms of packet loss rate and throughput metrics for Chase combining HARQ strategy.

Keywords: cooperative network, adaptive modulation and coding, hybrid ARQ, correlated fading

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Authors: Ogbu Harry Omilonye

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This paper examines feminism as a literary ideology which attempts to win for women a status of recognition and parity in a male-dominated society like Nigeria. This article deals essentially with the emergence of the ideology and literary personalities behind it. It focuses sharply on Zaynab Alkali’s brand of feminism as demonstrated in the delineation of her female characters vis-à-vis her male characters. The woman’s destiny, this paper believes, lies in her hand, and that true emancipation of women can only be realized through education and hard work.

Keywords: feminism, stillborn, literary ideology, literature

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Authors: Jurijs Salijevs, Katrina Bolocko

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The integration of artificial intelligence and neural networks has significantly changed full-body imaging and high-resolution 3D mapping systems, and this paper reviews research in these areas. With an emphasis on their use in the early identification of melanoma and other disorders, the goal is to give a wide perspective on the current status and potential future of these medical imaging technologies. Authors also examine methodologies such as machine learning and deep learning, seeking to identify efficient procedures that enhance diagnostic capabilities through the analysis of 3D body scans. This work aims to encourage further research and technological development to harness the full potential of AI in disease diagnosis.

Keywords: artificial intelligence, neural networks, 3D scan, body scan, 3D mapping system, healthcare

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Authors: Zhongfei Cai, Hui He, Changsheng Li

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This paper studied in the automatic repeat request (ARQ) transmission technique in Mars detection telecommunications system. An ARQ method applied to proximity-1 space link protocol was proposed by this paper. In order to ensure the efficiency of data reliable transmission, this ARQ method combined these different ARQ maneuvers characteristics. Considering the Mars detection communication environments, this paper analyzed the characteristics of the saturation throughput rate, packet dropping probability, average delay and energy efficiency with different ARQ algorithms. Combined thus results with the theories of ARQ transmission technique, an ARQ transmission project in Mars detection telecommunications system was established. The simulation results showed that this algorithm had excellent saturation throughput rate and energy efficiency with low complexity.

Keywords: ARQ, mars, CCSDS, proximity-1, deepspace

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Authors: Ward Makhoul

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Code-switching (CS) is known as a ubiquitous phenomenon in multilingual societies and countries. Vernacular Palestinian Arabic (PA) variety spoken in Israel is among these languages, informally used for day-to-day conversations only. Such conversations appear to contain code-switched instances from Hebrew, the formal and dominant language of the country, even in settings where the need for CS seems to be unnecessary. This study examines the CS practices in PA and investigates the reason behind these CS instances in controlled settings and the correlation between bilingual dominance and CS. In the production-task interviews and Bilingual Language Profile test (BLP), there was a correlation between language dominance and CS; 13 participants were interviewed to elicit and analyze natural speech-containing CS instances, along with undergoing a BLP test. The acceptability judgment task observed the limits and boundaries of different code-switched linguistic structures.

Keywords: code-switching, Hebrew, Palestinian-Arabic, vernacular

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Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng

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Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.

Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation

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Authors: Mario Kubek, Herwig Unger

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Due to the large amount of information in the World Wide Web (WWW, web) and the lengthy and usually linearly ordered result lists of web search engines that do not indicate semantic relationships between their entries, the search for topically similar and related documents can become a tedious task. Especially, the process of formulating queries with proper terms representing specific information needs requires much effort from the user. This problem gets even bigger when the user's knowledge on a subject and its technical terms is not sufficient enough to do so. This article presents the new and interactive search application DocAnalyser that addresses this problem by enabling users to find similar and related web documents based on automatic query formulation and state-of-the-art search word extraction. Additionally, this tool can be used to track topics across semantically connected web documents

Keywords: DocAnalyser, interactive web search, search word extraction, query formulation, source topic detection, topic tracking

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Authors: Yan Lu, Song Hong, Janakiraman Udaiyappan, Aarti Nagayach, Quoc-Viet A. Duong, Masao Morita, Shun Saito, Yuichi Kobayashi, Yuhai, Zhao, Hongying Peng, Nicholas B. Pham, Walter J Lukiw, Christopher A. Vuong, Nicolas G. Bazan

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Aims: Neurodegeneration and behavior dysfunction occurs in patients with Alzheimer's Disease (AD), and as the disease progresses many patients develop cognitive impairment. 5XFAD mouse model of AD is widely used to study AD pathogenesis and treatment. This study aimed to investigate the effect of maresin like 1 (MaR-L1) treatment in AD pathology using 5XFAD mice. Methods: We tested 12-month-old male 5XFAD mice and wild type control mice treated with MaR-L1 in a battery of behavioral tasks. We performed open field test, beam walking test, clasping test, inverted grid test, acetone test, marble burring test, elevated plus maze test, cross maze test and novel object recognition test. We also studied neuronal loss, amyloid β burden, and inflammation in the brains of 5XFAD mice using immunohistology and Western blotting. Results: MaR-L1 treatment to the 5XFAD mice showed improved cognitive function of 5XFAD mice. MaR-L1 showed decreased anxiety behavior in open field test and marble burring test, increased muscular strength in the beam walking test, clasping test and inverted grid test. Cognitive function was improved in MaR-L1 treated 5XFAD mice in the novel object recognition test. MaR-L1 prevented neuronal loss and aberrant inflammation. Conclusion: Our finding suggests that behavioral abnormalities were normalized by the administration of MaR-L1 and the neuroprotective role of MaR-L1 in the AD. It also indicates that MaR-L1 treatment is able to prevent and or ameliorate neuronal loss and aberrant inflammation. Further experiments to validate the results are warranted using other AD models in the future.

Keywords: Alzheimer's disease, motor and cognitive behavior, 5XFAD mice, Maresin Like 1, microglial cell, astrocyte, neurodegeneration, inflammation, resolution of inflammation

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Authors: Moein Izadi, Ali Mohammadzadeh

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Detection of damaged parts of roads after earthquake is essential for coordinating rescuers. In this study, an approach is presented for the semi-automatic detection of damaged roads in a city using pre-event vector maps and both pre- and post-earthquake QuickBird satellite images. Damage is defined in this study as the debris of damaged buildings adjacent to the roads. Some spectral and texture features are considered for SVM classification step to detect damages. Finally, the proposed method is tested on QuickBird pan-sharpened images from the Bam City earthquake and the results show that an overall accuracy of 81% and a kappa coefficient of 0.71 are achieved for the damage detection. The obtained results indicate the efficiency and accuracy of the proposed approach.

Keywords: SVM classifier, disaster management, road damage detection, quickBird images

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

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Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: Yaojun Wang, Yaoqing Wang

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Stock selection is an important decision-making problem. Many machine learning and data mining technologies are employed to build automatic stock-selection system. A profitable stock-selection system should consider the stock’s investment value and the market timing. In this paper, we present a hybrid system including both engage for stock selection. This system uses a case-based reasoning (CBR) model to execute the stock classification, uses a decision-tree model to help with market timing and stock selection. The experiments show that the performance of this hybrid system is better than that of other techniques regarding to the classification accuracy, the average return and the Sharpe ratio.

Keywords: case-based reasoning, decision tree, stock selection, machine learning

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Authors: Aileen Editha

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The legal recognition of property rights over human genes is a divisive topic to which there is no resolution. As a frequently discussed topic, scholars and practitioners often highlight the inadequacies of a proprietary regime. However, little has been said in regard to the nature of human genetic materials (HGMs). This paper proposes approaching the issue of property over HGMs from an alternative perspective that looks at the personal and social value and valuation of HGMs. This paper will highlight how the unique and unresolved status of HGMs is incompatible with the main tenets of property and, consequently, contributes to legal ambiguity and uncertainty in the regulation of property rights over human genes. HGMs are perceived as part of nature and a free-for-all while also being within an individual’s private sphere. Additionally, it is also considered to occupy a unique “not-private-nor-public” status. This limbo-like position clashes with property’s fundamental characteristic that relies heavily on a clear public/private dichotomy. Moreover, as property is intrinsically linked to the legal recognition of one’s personhood, this irresolution benefits some while disadvantages others. In particular, it demands the publicization of once-private genes for the “common good” but subsequently encourages privatization (through labor) of these now-public genes. This results in the gain of some (already privileged) individuals while enabling the disenfranchisement of members of minority groups, such as Indigenous communities. This paper will discuss real and intellectual property rights over human genes, such as the right to income or patent rights, in Canada and the US. This paper advocates for a sui generis approach to governing rights and interests over human genes that would not rely on having a strict public/private dichotomy. Not only would this improve legal certainty and clarity, but it would also alleviate—or, at the very least, minimize—the role that the current law plays in further entrenching existing systemic inequalities. Despite the specificity of this topic, this paper argues that there are broader lessons to be learned. This issue is an insightful case study on the interconnection of various principles in law, society, and property, and what must be done when discordance between one or more of those principles has detrimental societal outcomes. Ultimately, it must be remembered that property is an adaptable and malleable instrument that can be developed to ensure it contributes to equity and flourishing.

Keywords: property rights, human genetic materials, critical legal scholarship, systemic inequalities

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Authors: Amandeep Kaur

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Digital Image processing is a fundamental tool to perform various operations on the digital images for pattern recognition, noise removal and feature extraction. In this paper noise removal technique has been described for various types of noises. This paper comprises discussion about various noises available in the image due to different environmental, accidental factors. In this paper, various de-noising approaches have been discussed that utilize different wavelets and filters for de-noising. By analyzing various papers on image de-noising we extract that wavelet based de-noise approaches are much effective as compared to others.

Keywords: de-noising techniques, edges, image, image processing

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Authors: Sekou Kangoye, Alexis Todoskoff, Mihaela Barreau

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Modified Condition/Decision Coverage (MC/DC) is a structural coverage criterion that aims to prove that all conditions involved in a Boolean expression can influence the result of that expression. In the context of automotive, MC/DC is highly recommended and even required for most security and safety applications testing. However, due to complex Boolean expressions that often embedded in those applications, generating a set of MC/DC compliant test cases for any of these expressions is a nontrivial task and can be time consuming for testers. In this paper we present an approach to automatically generate MC/DC test cases for any Boolean expression. We introduce novel techniques, essentially based on binary trees to quickly and optimally generate MC/DC test cases for the expressions. Thus, the approach can be used to reduce the manual testing effort of testers.

Keywords: binary trees, MC/DC, test case generation, nontrivial task

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Authors: Yu Qin

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In order to tackle the ever-growing problem of the lack of parking space, this paper presents the design and implementation of a smart unmanned parking system that is based on RFID (radio frequency identification) technology and Wireless communication technology. This system uses RFID technology to achieve the identification function (transmitted by 2.4 G wireless module) and is equipped with an STM32L053 micro controller as the main control chip of the smart vehicle. This chip can accomplish automatic parking (in/out), charging and other functions. On this basis, it can also help users easily query the information that is stored in the database through the Internet. Experimental tests have shown that the system has the features of low power consumption and stable operation, among others. It can effectively improve the level of automation control of the parking lot management system and has enormous application prospects.

Keywords: RFID, embedded system, unmanned, parking management

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Authors: Naima Mohammadi

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The present paper critically reports on the emergency of Iranian international students in a large public university in Italy. Although the most sizeable diaspora of Iranians dates back to the 1979 revolution, a huge wave of Iranian female students travelled abroad after the Iranian Green Movement (2009) due to the intensification of gender discrimination and Islamization. To explore the experience of Iranian female students at an Italian public university, two complementary methods were adopted: a focus group and individual interviews. Focus groups yield detailed collective conversations and provide researchers with an opportunity to observe the interaction between participants, rather than between participant and researcher, which generates data. Semi-structured interviews allow participants to share their stories in their own words and speak about personal experiences and opinions. Research participants were invited to participate through a public call in a Telegram group of Iranian students. Theoretical and purposive sampling was applied to select participants. All participants were assured that full anonymity would be ensured and they consented to take part in the research. A two-hour focus group was held in English with participants in the presence and some online. They were asked to share their motivations for studying in Italy and talk about their experiences both within and outside the university context. Each of these interviews lasted from 45 to 60 minutes and was mostly carried out online and in Farsi. The focus group consisted of 8 Iranian female post-graduate students. In analyzing the data a blended approach was adopted, with a combination of deductive and inductive coding. According to research findings, although 9/11 was the beginning of the West’s challenges against Muslims, the nuclear threats of Islamic regimes promoted the toughest international sanctions against Iranians as a nation across the world. Accordingly, carrying an Iranian identity contributes to social, political, and economic exclusion. Research findings show that geopolitical factors such as international sanctions and Islamophobia, and a lack of reciprocity in terms of recognition, have created a sense of stigmatization for veiled and unveiled Iranian female students who are the largest groups of ‘non-European Muslim international students’ enrolled in Italian universities. Participants addressed how their nationality has devalued their public image and negatively impacted their self-confidence and self-realization in academia. They highlighted the experience of an unwelcoming atmosphere by different groups of people and institutes, such as receiving marked students’ badges, rejected bank account requests, failed visa processes, secondary security screening selection, and hyper-visibility of veiled students. This study corroborates the need for institutions to pay attention to geopolitical factors and religious diversity in student recruitment and provide support mechanisms and access to basic rights. Accordingly, it is suggested that Higher Education Institutions (HEIs) have a social and moral responsibility towards the discrimination and both social and academic exclusion of Iranian students.

Keywords: Iranian diaspora, female students, recognition theory, inclusive university

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Authors: B. S. Premalatha, Kausalya Sahani

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Background: Voice is multidimensional which convey emotion, feelings, and communication. Voice disorders have an adverse effect on the physical, emotional and functional domains of an individual. Self-rating by clients about their voice problem helps the clinicians to plan intervention strategies. Voice handicap index is one such self-rating scale contains 30 questions that quantify the functional, physical and emotional impacts of a voice disorder on a patient’s quality of life. Each subsection has 10 questions. Though adapted and validated versions of VHI are available in other Indian languages but not in Telugu, which is a Dravidian language native to India. It is mainly spoken in Andhra Pradesh and neighbouring states in southern India. Objectives: To adapt and validate the English version of Voice Handicap Index (VHI) into Telugu language and evaluate its internal consistency and clinical validate in Telugu speaking population. Materials: The study carried out in three stages. First stage was a forward translation of English version of VHI, was given to ten experts, who were well proficient in writing and reading Telugu and five speech-language pathologists to translate into Telugu. Second Stage was backward translation where translated version of Telugu was given to a different group of ten experts (who were well proficient in writing and reading Telugu) and five speech-language pathologists who were native Telugu speakers and had good proficiency in Telugu and English. The third stage was an administration of translated version on Telugu to the targeted population. Totally 40 clinical subjects and 40 normal controls served as participants, and each group had 26 males and 14 females’ age range of 20 to 60 years. Clinical group comprised of individuals with laryngectomee with the Tracheoesophageal puncture (n=18), laryngitis (n=11), vocal nodules (n=7) and vocal fold palsy (n=4). Participants were asked to mark of their each experience on a 5 point equal appearing scale (0=never, 1=almost never, 2=sometimes, 3=almost always, 4=always) with a maximum total score of 120. Results: Statistical analysis was made by using SPSS software (22.0.0 Version). Mean, standard deviation and percentage (%) were calculated all the participants for both the groups. Internal consistency of VHI in Telugu was found to be excellent with the consistency scores for all the domains such as physical, emotional and functional are 0.742, 0.934and 0.938. The validity of scores showed a significant difference between clinical population and control group for domains like physical, emotional and functional and total scores. P value found to be less than 0.001( < 0.001). Negative correlation found in age and gender among self-domains such as physical, emotional and functional total scores in dysphonic and control group. Conclusion: The present study indicated that VHI in Telugu is able to discriminate participants having voice pathology from normal populations, which make this as a valid tool to collect information about their voice from the participants.

Keywords: adaptation, Telugu Version, translation, Voice Handicap Index (VHI)

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Authors: Reham Banwair, Lana Alshehri, Sara Hadrawi

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The purpose of this project is to identify user satisfaction with the AI functions on Snapchat, in order to generate improvement proposals that allow its development within the app. To achieve this, a qualitative analysis was carried out through interviews to people who usually use the application, revealing their satisfaction or dissatisfaction with the usefulness of the AI. In addition, the background of the company and its introduction in these algorithms were analyzed. Furthermore, the characteristics of the three main functions of AI were explained: identify songs, solve mathematical problems, and recognize plants. As a result, it was obtained that 50% still do not know the characteristics of AI, 50% still believe song recognition is not always correct, 41.7% believe that math problems are usually accurate and 91.7% believes the plant detection tool is working properly.

Keywords: artificial intelligence, scanning, Snapchat, machine learning

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Authors: Yasser Y. Lenis, Amy Jo Montgomery, Diego F. Carrillo-Gonzalez

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Introduction: The use of didactic instruments in different learning environments plays a pivotal role in enhancing the level of knowledge in veterinary science students. The direct instruction of basic animal reproduction concepts in students enrolled in veterinary medicine programs allows them to elucidate the biological and molecular mechanisms that perpetuate the animal species in an ecosystem. Therefore, universities must implement didactic strategies that facilitate the teaching and learning processes for students and, in turn, enrich learning environments. Objective: to evaluate the effect of the use of a didactic textbook on the level of theoretical knowledge in embryo-maternal recognition for veterinary medicine students. Methods: the participants (n=24) were divided into two experimental groups: control (Ctrl) and treatment (Treat). Both groups received 4 hours of theoretical training regarding the basic concepts in bovine embryo-maternal recognition. However, the Treat group was also exposed to a guided lecture and the activity play-to-learn from a cow reproduction didactic textbook. A pre-test and a post-test were applied to assess the prior and subsequent knowledge in the participants. Descriptive statistics were applied to identify the success rates for each of the tests. Afterwards, a repeated measures model was applied where the effect of the intervention was considered. Results: no significant difference (p>0,05) was observed in the number of right answers for groups Ctrl (54,2%±12,7) and Treat (40,8%±16,8) in the pre-test. There was no difference (p>0,05) compering the number of right answers in Ctrl pre-test (54,2%±12,7) and post-test (60,8±18,8). However, the Treat group showed a significant (p>0,05) difference in the number of right answers when comparing pre-test (40,8%±16,8) and post-test (71,7%±14,7). Finally, after the theoretical training and the didactic activity in the Treat group, an increase of 10.9% (p<0,05) in the number of right answers was found when compared with the Ctrl group. Conclusion: the use of didactic tools that include guided lectures and activities like play-to-learn from a didactic textbook enhances the level of knowledge in an animal reproduction course for veterinary medicine students.

Keywords: animal reproduction, pedagogic, level of knowledge, learning environment

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Authors: Panagiota Katsikouli, William Hamilton Byrne, Thomas Gammeltoft-Hansen, Tijs Slaats

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An individual who demonstrates a well-founded fear of persecution or faces real risk of being subjected to torture is eligible for asylum. In Danish law, the exact legal thresholds reflect those established by international conventions, notably the 1951 Refugee Convention and the 1950 European Convention for Human Rights. These international treaties, however, remain largely silent when it comes to how states should assess asylum claims. As a result, national authorities are typically left to determine an individual’s legal eligibility on a narrow basis consisting of an oral testimony, which may itself be hampered by several factors, including imprecise language interpretation, insecurity or lacking trust towards the authorities among applicants. The leaky ground, on which authorities must assess their subjective perceptions of asylum applicants' credibility, questions whether, in all cases, adjudicators make the correct decision. Moreover, the subjective element in these assessments raises questions on whether individual asylum cases could be afflicted by implicit biases or stereotyping amongst adjudicators. In fact, recent studies have uncovered significant correlations between decision outcomes and the experience and gender of the assigned judge, as well as correlations between asylum outcomes and entirely external events such as weather and political elections. In this study, we analyze a publicly available dataset containing approximately 8,000 summaries of asylum cases, initially rejected, and re-tried by the Refugee Appeals Board (RAB) in Denmark. First, we look for variations in the recognition rates, with regards to a number of applicants’ features: their country of origin/nationality, their identified gender, their identified religion, their ethnicity, whether torture was mentioned in their case and if so, whether it was supported or not, and the year the applicant entered Denmark. In order to extract those features from the text summaries, as well as the final decision of the RAB, we applied natural language processing and regular expressions, adjusting for the Danish language. We observed interesting variations in recognition rates related to the applicants’ country of origin, ethnicity, year of entry and the support or not of torture claims, whenever those were made in the case. The appearance (or not) of significant variations in the recognition rates, does not necessarily imply (or not) bias in the decision-making progress. None of the considered features, with the exception maybe of the torture claims, should be decisive factors for an asylum seeker’s fate. We therefore investigate whether the decision can be predicted on the basis of these features, and consequently, whether biases are likely to exist in the decisionmaking progress. We employed a number of machine learning classifiers, and found that when using the applicant’s country of origin, religion, ethnicity and year of entry with a random forest classifier, or a decision tree, the prediction accuracy is as high as 82% and 85% respectively. tentially predictive properties with regards to the outcome of an asylum case. Our analysis and findings call for further investigation on the predictability of the outcome, on a larger dataset of 17,000 cases, which is undergoing.

Keywords: asylum adjudications, automated decision-making, machine learning, text mining

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Authors: Benchalak Muangmeesri

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Glazes ceramics are ceramic materials produced through controlled crystallization of a parent glass. The great variety of compositions and the possibility of developing special micro structures with specific technological properties have allowed glass ceramic materials to be used in a wide range of applications. At the same time, glazes ceramics need to improvement in the mechanical and chemical properties of glazed. The pick and place station is equipped with a three-axis module. test piece housings placed on the vacuum are detected module picks up a test piece insert from the slide and places it on the test piece housing. Overall, glazes ceramics are compared with automatically and manually of speed and position control. The handling modules of automatic transfer are a new generation of high speed and precision then these color results from absorption and thickness than manual is also included.

Keywords: glaze, PID control, pick and place, ceramic

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Authors: Y. Saylan, F. Yılmaz, A. Denizli

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Rheumatoid arthritis (RA) which is the most common autoimmune disorder of the body's own immune system attacking healthy cells. RA has both articular and systemic effects.Until now romatiod factor (RF) assay is used the most commonly diagnosed RA but it is not specific. Anti-cyclic citrullinated peptide (anti-CCP) antibodies are IgG autoantibodies which recognize citrullinated peptides and offer improved specificity in early diagnosis of RA compared to RF. Anti-CCP antibodies have specificity for the diagnosis of RA from 91 to 98% and the sensitivity rate of 41-68%. Molecularly imprinted polymers (MIP) are materials that are easy to prepare, less expensive, stable have a talent for molecular recognition and also can be manufactured in large quantities with good reproducibility. Molecular recognition-based adsorption techniques have received much attention in several fields because of their high selectivity for target molecules. Quartz crystal microbalance (QCM) is an effective, simple, inexpensive approach mass changes that can be converted into an electrical signal. The applications for specific determination of chemical substances or biomolecules, crystal electrodes, cover by the thin films for bind or adsorption of molecules. In this study, we have focused our attention on combining of molecular imprinting into nanofilms and QCM nanosensor approaches and producing QCM nanosensor for anti-CCP, chosen as a model protein, using anti-CCP imprinted nanofilms. For this aim, anti-CCP imprinted QCM nanosensor was characterized by Fourier transform infrared spectroscopy, atomic force microscopy, contact angle measurements and ellipsometry. The non-imprinted nanosensor was also prepared to evaluate the selectivity of the imprinted nanosensor. Anti-CCP imprinted QCM nanosensor was tested for real-time detection of anti-CCP from aqueous solution. The kinetic and affinity studies were determined by using anti-CCP solutions with different concentrations. The responses related with mass shifts (Δm) and frequency shifts (Δf) were used to evaluate adsorption properties and to calculate binding (Ka) and dissociation (Kd) constants. To show the selectivity of the anti-CCP imprinted QCM nanosensor, competitive adsorption of anti-CCP and IgM was investigated.The results indicate that anti-CCP imprinted QCM nanosensor has a higher adsorption capabilities for anti-CCP than for IgM, due to selective cavities in the polymer structure.

Keywords: anti-CCP, molecular imprinting, nanosensor, rheumatoid arthritis, QCM

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Authors: Javiera Espinosa, Patricia López, Noelia Santos, Nadia Loro, Esther Moraleda

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In recent years, there has been a notable increase in the number of investigations that establish that Down Syndrome and Autism Spectrum Disorder are diagnoses that can coexist together. However, there are also many studies that consider that both diagnoses present neuropsychological, linguistic and adaptive characteristics with a totally different profile. The objective of this research is to question whether there really can be a profile that encompasses both disorders or if they can be incompatible with each other. To this end, a review of the scientific literature of recent years has been carried out. The results indicate that the two lines collect opposite approaches. On the one hand, there is research that supports the increase in comorbidity between Down Syndrome and Autism Spectrum Disorder, and on the other hand, many investigations show a totally different general development profile between the two. The discussion focuses on discussing both lines of work and on proposing future lines of research in this regard.

Keywords: disability, language, speech, down syndrome

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Authors: Sarra Roubi, Mohammed Erramdani, Samir Mbarki

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This paper presents an approach for the model-driven generating of Rich Internet Application (RIA) focusing on the graphical aspect. We used well known Model-Driven Engineering (MDE) frameworks and technologies, such as Eclipse Modeling Framework (EMF), Graphical Modeling Framework (GMF), Query View Transformation (QVTo) and Acceleo to enable the design and the code automatic generation of the RIA. During the development of the approach, we focused on the graphical aspect of the application in terms of interfaces while opting for the Model View Presenter pattern that is designed for graphics interfaces. The paper describes the process followed to define the approach, the supporting tool and presents the results from a case study.

Keywords: metamodel, model-driven engineering, MVP, rich internet application, transformation, user interface

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Authors: Jun-Yong Lee, Hyoung-Gook Kim

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In this paper, we propose a smart music player that combines the musical genre classification and the spatial audio processing. The musical genre is classified based on content analysis of the musical segment detected from the audio stream. In parallel with the classification, the spatial audio quality is achieved by adding an artificial reverberation in a virtual acoustic space to the input mono sound. Thereafter, the spatial sound is boosted with the given frequency gains based on the musical genre when played back. Experiments measured the accuracy of detecting the musical segment from the audio stream and its musical genre classification. A listening test was performed based on the virtual acoustic space based spatial audio processing.

Keywords: automatic equalization, genre classification, music segment detection, spatial audio processing

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Authors: B. H. Aitchanov, Sh. K. Aitchanova, O. A. Baimuratov

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This paper is focused on dynamic pulse-frequency modulation (DPFM) control systems. Currently, the control law based on DPFM control signals is widely used in direct digital control subsystems introduced in the automated control systems of technological processes. Statistical analysis of automatic control systems is reduced to its construction of functional relationships between the statistical characteristics of the errors processes and input processes. Structural and dynamic Volterra models of digital pulse-frequency control systems can be used to develop methods for generating the dependencies, differing accuracy, requiring the amount of information about the statistical characteristics of input processes and computing labor intensity of their use.

Keywords: digital dynamic pulse-frequency control systems, dynamic pulse-frequency modulation, control object, discrete filter, impulse device, microcontroller

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Authors: Khaldon Lweesy, Feryal Alskafi, Rabaa Hammad, Shaker Khanfar, Yara Alsukhni

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Electronic noses are devices designed to emulate the humane sense of smell by characterizing and differentiating odor profiles. In this study, we build a low-cost e-nose using an array module containing four different types of metal oxide semiconductor gas sensors. We used this system to create a profile for a meat specimen over three days. Then using a pattern recognition software, we correlated the odor of the specimen to its age. It is a simple, fast detection method that is both non-expensive and non-destructive. The results support the usage of this technology in food control management.

Keywords: e-nose, low cost, odor detection, food safety

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Authors: Daoudi Abdelaziz, Mahmoudi Saïd, Chikh Mohamed Amine

Abstract:

This paper presents a fully automatic segmentation method of the left ventricle at End Systolic (ES) and End Diastolic (ED) in the ultrasound images by means of an implicit deformable model (level set) based on Geodesic Active Contour model. A pre-processing Gaussian smoothing stage is applied to the image, which is essential for a good segmentation. Before the segmentation phase, we locate automatically the area of the left ventricle by using a detection approach based on the Hough Transform method. Consequently, the result obtained is used to automate the initialization of the level set model. This initial curve (zero level set) deforms to search the Endocardial border in the image. On the other hand, quantitative evaluation was performed on a data set composed of 15 subjects with a comparison to ground truth (manual segmentation).

Keywords: level set method, transform Hough, Gaussian smoothing, left ventricle, ultrasound images.

Procedia PDF Downloads 447

Authors: Hemendra Singh Rathod

Abstract:

Frequency is, among other factors, one of the governing parameters for maintaining electrical grid stability. The quality of an electrical transmission and supply system is mainly described by the stability of the grid frequency. Over the past few decades, energy generation by intermittent sustainable sources like wind and solar has seen a significant increase globally. Consequently, controlling the associated deviations in grid frequency within safe limits has been gaining momentum so that the balance between demand and supply can be maintained. Lithium-ion battery energy storage system (Li-Ion BESS) has been a promising technology to tackle the challenges associated with grid instability. BESS is, therefore, an effective response to the ongoing debate whether it is feasible to have an electrical grid constantly functioning on a hundred percent renewable power in the near future. In recent years, large-scale manufacturing and capital investment into battery production processes have made the Li-ion battery systems cost-effective and increasingly efficient. The Li-ion systems require very low maintenance and are also independent of geographical constraints while being easily scalable. The paper highlights the use of stationary and moving BESS for balancing electrical energy, thereby maintaining grid frequency at a rapid rate. Moving BESS technology, as implemented in the selected railway network in Germany, is here considered as an exemplary concept for demonstrating the same functionality in the electrical grid system. Further, using certain applications of Li-ion batteries, such as self-consumption of wind and solar parks or their ancillary services, wind and solar energy storage during low demand, black start, island operation, residential home storage, etc. offers a solution to effectively integrate the renewables and support Europe’s future smart grid. EMT software tool DIgSILENT PowerFactory has been utilised to model an electrical transmission system with 100% renewable energy penetration. The stability of such a transmission system has been evaluated together with BESS within a defined frequency band. The transmission system operators (TSO) have the superordinate responsibility for system stability and must also coordinate with the other European transmission system operators. Frequency control is implemented by TSO by maintaining a balance between electricity generation and consumption. Li-ion battery systems are here seen as flexible, controllable loads and flexible, controllable generation for balancing energy pools. Thus using Li-ion battery storage solution, frequency-dependent load shedding, i.e., automatic gradual disconnection of loads from the grid, and frequency-dependent electricity generation, i.e., automatic gradual connection of BESS to the grid, is used as a perfect security measure to maintain grid stability in any case scenario. The paper emphasizes the use of stationary and moving Li-ion battery storage for meeting the demands of maintaining grid frequency and stability for near future operations.

Keywords: frequency control, grid stability, li-ion battery storage, smart grid

Procedia PDF Downloads 134

Authors: Seynabou Toure, Oumar Diop, Kidiyo Kpalma, Amadou S. Maiga

Abstract:

Color and texture are the two most determinant elements for perception and recognition of the objects in an image. For this reason, color and texture analysis find a large field of application, for example in image classification and segmentation. But, the pioneering work in texture analysis was conducted on grayscale images, thus discarding color information. Many grey-level texture descriptors have been proposed and successfully used in numerous domains for image classification: face recognition, industrial inspections, food science medical imaging among others. Taking into account color in the definition of these descriptors makes it possible to better characterize images. Color texture is thus the subject of recent work, and the analysis of color texture images is increasingly attracting interest in the scientific community. In optical remote sensing systems, sensors measure separately different parts of the electromagnetic spectrum; the visible ones and even those that are invisible to the human eye. The amounts of light reflected by the earth in spectral bands are then transformed into grayscale images. The primary natural colors Red (R) Green (G) and Blue (B) are then used in mixtures of different spectral bands in order to produce RGB images. Thus, good color texture discrimination can be achieved using RGB under controlled illumination conditions. Some previous works investigate the effect of using different color space for color texture classification. However, the selection of the best performing color space in land-sea segmentation is an open question. Its resolution may bring considerable improvements in certain applications like coastline detection, where the detection result is strongly dependent on the performance of the land-sea segmentation. The aim of this paper is to present the results of a study conducted on different color spaces in order to show the best-performing color space for land-sea segmentation. In this sense, an experimental analysis is carried out using five different color spaces (RGB, XYZ, Lab, HSV, YCbCr). For each color space, the Haar wavelet decomposition is used to extract different color texture features. These color texture features are then used for Fusion of Over Segmentation (FOOS) based classification; this allows segmentation of the land part from the sea one. By analyzing the different results of this study, the HSV color space is found as the best classification performance while using color and texture features; which is perfectly coherent with the results presented in the literature.

Keywords: classification, coastline, color, sea-land segmentation

Procedia PDF Downloads 230