Search results for: English as an additional language

Authors: Lung-Lung Hu

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Ronald Dworkin offered a legal theory of ‘chain enterprise’ that all the judges in legal history altogether create a ‘law’ aiming a specific purpose. Those judges are like co-writers of a chain-story who not only create freely but also are constrained by the story made by the judges before them. The law created by Chinese traditional judges is another case, they, compared with the judges mentioned by Ronald Dworkin, have relatively narrower space of making a legal sentence according to their own discretions because the statutes in Chinese traditional law at the very beginning have been designed as panel code that leaves small room to judge’s discretion. Furthermore, because law is a representative of the authority of the government, i.e. the emperor, any misjudges and misuses deviated from the law will be considered as a challenge to the supreme power. However, different from judges as the defenders of law, Chinese litigation masters who want to win legal cases have to be offenders challenging the verdict that does not favor his or his client’s interest. Besides, litigation master as an illegal or non-authorized profession does not belong to any legal system, therefore, they are relatively freer to ‘create’ the law. According to Stanley Fish’s articles that question Ronald Dworkin and Owen Fiss’ ideas about law, he construes that, since law is made of language, law is open to interpretations that cannot be constrained by any rules or any particular legal purposes. Stanley Fish’s idea can also be applied on the analysis about the stories of Chinese litigation masters in traditional Chinese literature. These Chinese litigation masters’ legal opinions in the so-called chain enterprise are like an unexpected episode that tries to revise the fixed story told by law. Although they are not welcome to the officials and also to the society, their existence is still a phenomenon representing another version of justice different from the official’s and can be seen as a de-structural power to the government. Hence, in this present paper the language and strategy applied by Chinese litigation masters in Chinese legal stories will be analysed to see how they refute made legal judgments and challenge the official standard of justice.

Keywords: Chinese legal stories, interdisciplinary, litigation master, post-structuralism

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Authors: N. Schneider, M. Bruchhage, M. Hartweg, G. Mutungi, J. O Regan, S. Deoni

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Observational neuroimaging studies suggest differences between breast-fed and formula-fed infants in developmental myelination, a key brain process for learning and cognitive development. However, the possible effects of a nutrient formulation on myelin development in healthy term infants in an intervention study have not been investigated. Objective was, therefore, to investigate the efficacy of a nutrient formulation with higher levels of myelin-relevant nutrients as compared to a control formulation with lower levels of the same nutrients on brain myelination and cognitive development in the first 6 months of life. The study is an ongoing randomized, controlled, double-blind, two-center, parallel-group clinical trial with a nonrandomized, non-blinded arm of exclusively breastfed infants. The current findings result from a staged statistical analysis at 6 months; the recruitment and intervention period has been completed for all participants. Follow-up visits at 12, 18 and 24 months are still ongoing. N= 81 enrolled full term, neurotypical infants of both sexes were randomized into either the investigational (N= 42) or the control group (N= 39), and N= 108 children in the breast-fed arm served as a natural reference group. The effect of a blend of docosahexaenoic acid, arachidonic acid, iron, vitamin B12, folic acid as well as sphingomyelin from a uniquely proceed whey protein concentrate enriched in alpha-lactalbumin and phospholipids in an infant nutrition product matrix was investigated. The main outcomes for the staged statistical analyses at 6 months included brain myelination measures derived from MRI. Additional outcomes were brain volume, cognitive development and safety. The full analyses set at 6 months comprised N= 66 infants. Higher levels of myelin-relevant nutrients compared to lower levels resulted in significant differences in myelin structure, volume, and rate of myelination as early as 3 and 6 months of life. The cross-sectional change of means between groups for whole-brain myelin volume was 8.4% for investigational versus control formulation (3.5% versus the breastfeeding reference) group at 3 months and increased to 36.4% for investigational versus control formulation (14.1% versus breastfeeding reference) at 6 months. No statistically significant differences were detected for early cognition scores. Safety findings were largely similar across groups. This is the first pediatric nutritional neuroimaging study demonstrating the efficacy of a myelin nutrient blend on developmental myelination in well-nourished term infants. Myelination is a critical process in learning and development. The effects were demonstrated across the brain, particularly in temporal and parietal regions, known to be functionally involved in sensory, motor and language skills. These first results add to the field of nutritional neuroscience by demonstrating early life nutrition benefits for brain architecture which may be foundational for later cognitive and behavioral outcomes. ClinicalTrials.gov Identifier: NCT03111927 (Infant Nutrition and Brain Development - Full-Text View - ClinicalTrials.gov).

Keywords: brain development, infant nutrition, MRI, myelination

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Authors: N. Paparisteidi, D. Rodamitou

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This article focuses on the skills development and path planning of students studying computer science in EPITECH: french private institute of Higher Education. The researchers examine students’ points of view and experience in a blended learning model based on a skills development curriculum. The study is based on the collection of four main categories of data: semi-participant observation, distribution of questionnaires, interviews, and analysis of internal school databases. The findings seem to indicate that a skills-based program on active learning enables students to develop their learning strategies as well as their personal skills and to actively engage in the creation of their career path and contribute to providing additional information to curricula planners and decision-makers about learning design in higher education.

Keywords: active learning, blended learning, higher education, skills development

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Authors: Haytham Yassine

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This article mainly aims to detect and understand how money laundering activities are executed by transport of cash, identifying the underlying factors and separating legitimate from illegitimate usage of cash and how it is being used. This research provides academics with additional literature and provides bank supervisors and practitioners with a better understanding of sources and uses of cash in criminal activities and how cash is used in the laundering mechanism. Data are gathered through survey in the Middle East and North Africa region and review of the available research. The results of the analysis will help distinguish the factors affecting preference for cash rather other payment instruments in the region, identify what causes the tendency to launder illegal proceeds through cash transportation and how illegal cash is being laundered and moved. On the other hand, this paper sheds the light on major cash generating criminal activities, its sources and main destinations.

Keywords: illegitimate activities, cash, money laundering, terrorism financing

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Authors: Charline David, Alexandre Blondin Massé, Arnaud Zinflou

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In 2016, Clements, Hurn, and Li proposed a multiple equation time series approach for the short-term load forecasting, reporting an average mean absolute percentage error (MAPE) of 1.36% on an 11-years dataset for the Queensland region in Australia. We present an adaptation of their model to the electrical power load consumption for the whole Quebec province in Canada. More precisely, we take into account two additional meteorological variables — cloudiness and wind speed — on top of temperature, as well as the use of multiple meteorological measurements taken at different locations on the territory. We also consider other minor improvements. Our final model shows an average MAPE score of 1:79% over an 8-years dataset.

Keywords: short-term load forecasting, special days, time series, multiple equations, parallelization, clustering

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Authors: Nelya Babynets

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Shakespeare and Mexican theatregoers have enjoyed quite a complex relationship. Shakespearean plays have appeared on the Mexican stage with remarkable perseverance, yet with mixed success. Although Shakespeare has long been a part of the global cultural marketplace and his works are celebrated all around the world, the adaptation of his plays on the contemporary Mexican stage is always an adventure, since the works of this early modern author are frequently seen as the legacy of a ‘high’, but obsolete, culture, one that is quite distant from the present-day viewers’ daily experiences and concerns. Moreover, Mexican productions of Shakespeare are presented mostly in Peninsular Spanish, a language similar yet alien to the language spoken in Mexico, one that does not wholly fit into the viewers’ cultural praxis. This is the reason why Mexican dramatic adaptations of Shakespearean plays tend to replace the cultural references of the original piece with ones that are more significant and innate to Latin American spectators. This paper analyses the new Mexican production of Richard III adapted and directed by Mauricio Garcia Lozano, which employs onstage violence - a cultural force that is inherent to all human beings regardless of their beliefs, ethnic background or nationality - as the means to make this play more relevant to a present-day audience. Thus, this paper addresses how the bloody bombast of staged murders helps to avoid the tyranny of a rigid framework of fixed meanings that denies the possibility of an intercultural appropriation of this European play written over four hundred years ago. The impact of violence displayed in Garcia Lozano’s adaptation of Richard III on Mexican audiences will also be examined. This study is particularly relevant in Mexico where the term ‘tragedy’ has become a commonplace and where drug wars and state-sanctioned violence have already taken the lives of many people.

Keywords: audience, dramatic adaptation, Shakespeare, viewer

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Authors: Andrey Yatsun, Andrei Malchikov

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Exoskeletons are used to support and compensate for the load on the human musculoskeletal system. Elastomers are an important component of exoskeletons, providing additional support and compensating for the load. The algorithm of the active elastomer tension system provides the required auxiliary force depending on the angle of rotation and the tilt speed of the operator's torso. Feedback for the drive is provided by a force sensor integrated into the attachment of the exoskeleton vest. The use of direct force measurement ensures the required accuracy in all settings of the man-machine system. Non-adjustable elastic elements make it difficult to move without load, tilt forward and walk. A strategy for the organization of the auxiliary forces management system is proposed based on the allocation of 4 operating modes of the human-machine system.

Keywords: soft exoskeleton, mathematical modeling, pre-tension elastomer, human-machine interaction

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Authors: Thomas Schalow

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This paper posits the need to take a cross-cultural approach to communication with non-human cultures and intelligences in order to meet the following three imminent contingencies: communicating with sentient biological intelligences, communicating with extraterrestrial intelligences, and communicating with artificial super-intelligences. The paper begins with a discussion of how intelligence emerges. It disputes some common assumptions we maintain about consciousness, intention, and language. The paper next explores cross-cultural communication among humans, including non-sapiens species. The next argument made is that we need to become much more serious about communicating with the non-human, intelligent life forms that already exist around us here on Earth. There is an urgent need to broaden our definition of communication and reach out to the other sentient life forms that inhabit our world. The paper next examines the science and philosophy behind CETI (communication with extraterrestrial intelligences) and how it has proven useful, even in the absence of contact with alien life. However, CETI’s assumptions and methodology need to be revised and based on the cross-cultural approach to communication proposed in this paper if we are truly serious about finding and communicating with life beyond Earth. The final theme explored in this paper is communication with non-biological super-intelligences using a cross-cultural communication approach. This will present a serious challenge for humanity, as we have never been truly compelled to converse with other species, and our failure to seriously consider such intercourse has left us largely unprepared to deal with communication in a future that will be mediated and controlled by computer algorithms. Fortunately, our experience dealing with other human cultures can provide us with a framework for this communication. The basic assumptions behind intercultural communication can be applied to the many types of communication envisioned in this paper if we are willing to recognize that we are in fact dealing with other cultures when we interact with other species, alien life, and artificial super-intelligence. The ideas considered in this paper will require a new mindset for humanity, but a new disposition will prepare us to face the challenges posed by a future dominated by artificial intelligence.

Keywords: artificial intelligence, CETI, communication, culture, language

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Authors: CarlyWill Sloan

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Racial disparities in criminal justice outcomes are well-documented. However, there is little evidence on the extent to which racial bias by prosecutors is responsible for these disparities. This paper tests for racial bias in conviction by prosecutors. To identify effects, this paper leverages as good as random variation in prosecutor race using detailed administrative data on the case assignment process and case outcomes in New York County, New York. This paper shows that the assignment of an opposite-race prosecutor leads to a 5 percentage point (~ 8 percent) increase in the likelihood of conviction for property crimes. There is no evidence of effects for other types of crimes. Additional results indicate decreased dismissals by opposite-race prosecutors likely drive my property crime estimates.

Keywords: criminal justice, discrimination, prosecutors, racial disparities

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Authors: Momoka Sunohara, Ashley J. Lemieux, Esther Yakobov, Andrew G. Ryder, Tomas Jurcik

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Immigration brings changes in many aspects of an individual's life, from social support dynamics, to housing and language, as well as difficulties with regards to discrimination, trauma, and loss. Past research has mostly emphasized individual differences in mental health and has neglected the impact of social-ecological context, such as acculturation and ethnic density. Purpose: The present study aimed to assess the relationship between variables associated with social integration such as perceived ethnic density and ways of coping, as well as psychological adjustment in a rapidly growing non-visible minority group of immigrants in Canada. Data: A small subset of an archival data from our previously published study was reanalyzed with additional variables. Data included information from 269 Russian-Speaking immigrants in Montreal, Canada. Method: Canonical correlation analysis (CCA) investigated the relationship between two sets of variables. SAS PROC CANCORR was used to conduct CCA on a set of social integration variables, including ethnic density, discrimination, social support, family functioning, and acculturation, and a set of psychological well-being variables, including distress, depression, self-esteem, and life satisfaction. In addition, canonical redundancy analysis was performed to calculate the proportion of variances of original variables explained by their own canonical variates. Results: Significance tests using Rao’s F statistics indicated that the first two canonical correlations (i.e., r1 = 0.64, r2 = 0.40) were statistically significant (p-value < 0.0001). Additionally, canonical redundancy analysis showed that the first two well-being canonical variates explained separately 62.9% and 12.8% variances of the standardized well-being variables, whereas the first two social integration canonical variates explained separately 14.7% and 16.7% variances of the standardized social integration variables. These results support the selection of the first two canonical correlations. Then, we interpreted the derived canonical variates based on their canonical structure (i.e., correlations with original variables). Two observations can be concluded. First, individuals who have adequate social support, and who, as a family, cope by acquiring social support, mobilizing others and reframing are more likely to have better self-esteem, greater life satisfaction and experience less feelings of depression or distress. Second, individuals who feel discriminated yet rate higher on a mainstream acculturation scale, and who, as a family, cope by acquiring social support, mobilizing others and using spirituality, while using less passive strategies are more likely to have better life satisfaction but also higher degree of depression. Implications: This model may serve to explain the complex interactions that exist between social and emotional adjustment and aid in facilitating the integration of individuals immigrating into new communities. The same group may experience greater depression but paradoxically improved life satisfaction associated with their coping process. Such findings need to be placed in the context of Russian cultural values. For instance, some Russian-speakers may value the expression of negative emotions with significant others during the integration process; this in turn may make negative emotions more salient, but also facilitate a greater sense of family and community connection, as well as life satisfaction.

Keywords: acculturation, ethnic density, mental health, Russian-speaking

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Authors: Fleura Shkëmbi, Valbona Treska

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In elementary school, we discover that a metaphor is a decorative linguistic device just for poets. But now that we know, it's also a crucial tactic that individuals employ to understand the universe, from fundamental ideas like time and causation to the most pressing societal challenges today. Metaphor is the use of language to refer to something other than what it was originally intended for or what it "literally" means in order to suggest a similarity or establish a connection between the two. People do not identify metaphors as relevant in their decisions, according to a study on metaphor and its effect on decision-making; instead, they refer to more "substantive" (typically numerical) facts as the basis for their problem-solving decision. Every day, metaphors saturate our lives via language, cognition, and action. They argue that our conceptions shape our views and interactions with others and that concepts define our reality. Metaphor is thus a highly helpful tool for both describing our experiences to others and forming notions for ourselves. In therapeutic contexts, their shared goal appears to be twofold. The cognitivist approach to metaphor regards it as one of the fundamental foundations of human communication. The benefits and disadvantages of utilizing the metaphor differ depending on the target domain that the metaphor portrays. The challenge of creating messages and surroundings that affect customers' notions of abstract ideas in a variety of industries, including health, hospitality, romance, and money, has been studied for decades in marketing and consumer psychology. The aim of this study is to examine, through a systematic literature review, the role of the metaphor in communication and in advertising. This study offers a selected analysis of this literature, concentrating on research on customer attitudes and product appraisal. The analysis of the data identifies potential research questions. With theoretical and applied implications for marketing, design, and persuasion, this study sheds light on how, when, and for whom metaphoric communications are powerful.

Keywords: metaphor, communication, advertising, cognition, action

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Authors: Sujith Rajashekar Swamy, Meghana Rajashekara Swamy

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Although T1-weighted gadolinium-enhanced imaging (T1-Gd) has its established clinical role in diagnosing brain lesions of infectious and metastatic origins, the use of post-contrast susceptibility-weighted imaging (SWI) has been understudied. This observational study aims to explore and compare the prominence of brain parenchymal lesions between T1-Gd and SWI-Gd images. A cross-sectional study design was utilized to analyze 58 patients with brain parenchymal lesions using T1-Gd and SWI-Gd scanning techniques. Our results indicated that SWI-Gd enhanced the conspicuity of metastatic as well as infectious brain lesions when compared to T1-Gd. Consequently, it can be used as an adjunct to T1-Gd for post-contrast imaging, thereby avoiding additional contrast administration. Improved conspicuity of brain lesions translates directly to enhanced patient outcomes, and hence SWI-Gd imaging proves useful to meet that endpoint.

Keywords: susceptibility weighted, T1 weighted, brain lesions, gadolinium contrast

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: Judith Sue Hwa Joo

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Guanyin (Avalokiteśvara in Sanskrit), the Bodhisattva of Mercy and Compassion, is the most widely worshipped Buddhist Divinity in Chinese societies and is also believed by more than half of Asian populations across various countries. The most overwhelming reason for the popularity of Guanyin in Chinese societies is, according to the Lotus Sutra, that Guanyin would apperceive voices of those suffering from immense afflictions and troubles, and liberate them upon crying for his/her holy name with wholeheartedness. Its pervasive social influence has spanned more than two thousand years and is still deeply affecting the lives of most Chinese people. This study aimed to investigate whether Guanyin Worship has evolved and changed in modern Chinese societies across the Taiwan Strait. Taiwan and China, albeit having the same language and culture, have been territorially divided and governed by two different political regimes for over 70 years. It would be scientifically intriguing to unveil any substantial changes in religious behaviors in the context of Guanyin Worship. A comprehensive anonymous questionnaire survey in Chinese communities was conducted from October 2017 to May 2019 across various countries, mostly in China, Taiwan, and Hong Kong areas. Since the religious survey is officially prohibited in China, the study was difficult and could only be exercised by means of snowball sampling. Demographic data (age, sex, education, religious belief) were registered and Guanyin’s salvation functions under various confronting situations were investigated. Psychological dimensions of religious belief in Guanyin were probed in terms of the worship experience, the willingness of veneration, and egoistic or altruistic ideations. A literature review on documented functional attributes was carried out in parallel for comparison analyses with traditional roles. Effective 1123 out of 1139 samples were obtained. Statistical analysis revealed that Guanyin Worship is still commonly practiced and deeply rooted in the hearts of all Chinese people regardless of gender, age, education, and residential area, even though they may not enshrine Guanyin at home nowadays. The conventional roles of Guanyin Bodhisattva are still valid and best satisfy the real interests of lifestyles in modern times. When comparing the traditional Buddhist Sutra and the documented literature, the divine power of modern Guanyin has notably empowered to recover, protect and transform fetal and infant spirits due to the sexual liberation, increased abortion rate, gender awakening and enhanced female autonomy in the reproductive decision. However, the One-Child policy may have critically impacted the trajectory of Guanyin Worship so that people in China prevail over those in Taiwan praying for aborted lives or premature deaths. Furthermore, particularly in Hong Kong and Macao, Guanyin not only serves as the sea guardian for the fishermen but also additional services a new function as the God of Wealth. The divine powers and salvation functions of Guanyin are indeed evolving and expanding to comply with the modern psychosocial, cultural and societal needs. This study sheds light on the modernization process of the two-thousand-year-old Guanyin Worship of contemporary Chinese societies.

Keywords: Buddhism, Guanyin, religious behavior, salvation function

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Authors: Aminu Hamza

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This study examines the factors that play vital role in the adoption of mobile payment system among consumers in Nigeria. Technology Acceptance Model (TAM) was used with two additional variables to form the conceptual model. The study was conducted in three Universities in Kano state, Nigeria. Convenience sampling method was used with a total valid 202 respondents which involved the students of Bayero University Kano (BUK), Northwest University, and Kano University of Science and Technology (KUST) Wudil, Kano, Nigeria. Results of the regression analysis revealed that Perceived ease of use (PEOU) and Perceived usefulness (PU) have significant and positive correlation with the behavioral intention to adopt mobile payment system. The findings of this study would be useful to the policy makers Central Bank of Nigeria (CBN), mobile network operators and providers of the services.

Keywords: mobile payment system, Nigeria, technology adoption, technology acceptance model

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Authors: Tayyaba Azim, Bibi Amina

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The increase in the popularity of opinion mining with the rapid growth in the availability of social networks has attracted a lot of opportunities for research in the various domains of Sentiment Analysis and Natural Language Processing (NLP) using Artificial Intelligence approaches. The latest trend allows the public to actively use the internet for analyzing an individual’s opinion and explore the effectiveness of published facts. The main theme of this research is to account the public opinion on the most crucial and extensively discussed development projects, China Pakistan Economic Corridor (CPEC), considered as a game changer due to its promise of bringing economic prosperity to the region. So far, to the best of our knowledge, the theme of CPEC has not been analyzed for sentiment determination through the ML approach. This research aims to demonstrate the use of ML approaches to spontaneously analyze the public sentiment on Twitter tweets particularly about CPEC. Support Vector Machine SVM is used for classification task classifying tweets into positive, negative and neutral classes. Word2vec and TF-IDF features are used with the SVM model, a comparison of the trained model on manually labelled tweets and automatically generated lexicon is performed. The contributions of this work are: Development of a sentiment analysis system for public tweets on CPEC subject, construction of an automatic generation of the lexicon of public tweets on CPEC, different themes are identified among tweets and sentiments are assigned to each theme. It is worth noting that the applications of web mining that empower e-democracy by improving political transparency and public participation in decision making via social media have not been explored and practised in Pakistan region on CPEC yet.

Keywords: machine learning, natural language processing, sentiment analysis, support vector machine, Word2vec

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Authors: Alex Ellery

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Solar power satellites (SPS), despite their promise as a clean energy source, have been relegated out of consideration due to their enormous cost and technological challenge. It has been suggested that for solar power satellites to become economically feasible, launch costs must decrease from their current $20,000/kg to < $200/kg. Even with the advent of single-stage-to-orbit launchers which propose launch costs dropping to $2,000/kg, this will not be realized. Yet, the advantages of solar power satellites are many. Here, I present a novel approach to reduce the specific cost of solar power satellites to ~$1/kg by leveraging two enabling technologies – in-situ resource utilization and 3D printing. The power of such technologies will open up enormous possibilities for providing additional options for combating climate change whilst meeting demands for global energy. From the constraints imposed by in-situ resource utilization, a novel approach to solar energy conversion in SPS may be realized.

Keywords: clean energy sources, in-situ resource utilisation, solar power satellites, thermionic emission

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Authors: Reggie Chandra

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Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

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Authors: Aleksey Fedorov

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Building a scalable platform for quantum computing remains one of the most challenging tasks in quantum science and technologies. However, the implementation of most important quantum operations with qubits (quantum analogues of classical bits), such as multiqubit Toffoli gate, requires either a polynomial number of operation or a linear number of operations with the use of ancilla qubits. Therefore, the reduction of the number of operations in the presence of scalability is a crucial goal in quantum information processing. One of the most elegant ideas in this direction is to use qudits (multilevel systems) instead of qubits and rely on additional levels of qudits instead of ancillas. Although some of the already obtained results demonstrate a reduction of the number of operation, they suffer from high complexity and/or of the absence of scalability. We show a strong reduction of the number of operations for the realization of the Toffoli gate by using qudits for a scalable multi-qudit processor. This is done on the basis of a general relation between the dimensionality of qudits and their topology of connections, that we derived.

Keywords: quantum computing, qudits, Toffoli gates, gate decomposition

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Authors: Lutendo Nendauni

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Colonialism breaks things, colonisers exploded native cultural solidarity, producing the spiritual confusion, psychic wounding, and economic exploitation of a new and dominated ‘other’. Colonialism as the cultural and economic exploitation began when the West defended in their seizure of foreign territories for the exploitation of its natural resources; this resulted in brutal socio-economic imbalances. The Western profited at the detriment of the weak Africa. However, colonialism has since passed, but the effects are still evident culturally, socially, and economically. This paper explored how postcolonial writers and critics attempt to reverse the socio-economic imbalances resulting from the fragmentation of colonialism, with a focus on the play 'I will Marry When I Want' by Ngugi wa Thiong’o and Ngugi wa Mirii, as a primary text. Using qualitative discourse-textual analysis as the research methodology, the researcher purposively extracts discourse segments from the text for analysis and interpretation. The findings reveal that Postcolonial critics and writers attempt to reverse the socio-economic effects of colonialism through various counter discourses; their literature is concerned with the destruction of colonised identity, the search for this identity, and its assertion. It is manifest in the text that writers offer corrective views about Africans; they stress that they write their literary texts to conscientise their fellow Africans. Postcolonial writers and critics argue that language is a carrier of culture and that the only way to break free from colonial influence is by not adopting a foreign language. They further through their poems, novels, plays, and music strategically shine the spotlight on the previously nameless and destitute people so that they can develop the human spirit’s desire to overcome defeat, socio-political deprivation, and isolation.

Keywords: colonialism, postcoloniality, critics, socio-economic imbalances

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Authors: Qiao Fan, Xiaobo Guo, Junxian Zhu, Xiaohu Ding, Ching-Yu Cheng, Tien-Yin Wong, Mingguang He, Heping Zhang, Xueqin Wang

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A systematic, simultaneous analysis of multiple phenotypes in genome-wide association studies (GWASs) draws a great attention to integrate the signals from single phenotypes with increased power. However, lacking an interpretable and efficient multivariate GWAS analysis impede the application of such approach. In this study, we propose to decompose the multivariate model into a series of simple univariate models. This transformation illuminates what exactly the individual trait contributes to the significant signals from the multivariate analyses. By employing our approach in the analysis of three myopia-related endophenotypes from the Singapore Malay Eye Study (SIMES), we identify novel candidate loci which were successfully validated in an independent Guangzhou Twin Eye Study (GTES).

Keywords: GWAS multivariate, multiple traits, myopia, association

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Authors: T. A. Khan, A. B. Khan, M. Babar, T. A. Taj, Imran Ijaz Imran

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Smart Meter is a key element in the evolving concept of Smart Grid, which plays an important role in interaction between the consumer and the supplier. In general, the smart meter is an intelligent digital energy meter that measures the consumption of electrical energy and provides other additional services as compared to the conventional energy meters. One of the important element that makes a meter smart and different is its communication module. Smart meters usually have two way and real-time communication between the consumer and the supplier through which its transfer data and information. In this paper, Ultra Wide Band (UWB) is recommended as communication platform because of its high data-rate and presents the physical layer, which could be easily incorporated in existing Smart Meters. The physical layer is simulated in MATLAB Simulink and the results are provided.

Keywords: Ultra Wide Band (UWB), Smart Meter, MATLAB, transfer data

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Authors: Shirin Sadat Ahmadi

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The number of people, particularly university students, migrating from Iran and applying for American and European universities has been rising during recent years. Different people may have various reasons and goals for migration, but one of the common issues among all these people is the cultural challenges they experience when living in the adopted society. Immigrants usually confront obstacles during the Intercultural transition and adaption process. Different variables such as age, religion, gender, education, knowing the spoken language in destination country, financial condition, interactions with natives, and using social media can affect the cultural challenges people face after migration and how they conquer issues appearing due to intercultural differences and conflicts. In this research we have interviewed a sample consisted of 15 Iranian students living and studying abroad found by using snowball sampling technique via video call to realize what cultural challenges they have experienced in the new society, how the mentioned variables above eased these challenges or made them harder and what approaches and solutions they adopted to adjust themselves to the new society and its cultural dimensions. Based on John Berry's acculturation theory of migrant-host relationship, we have classified these 15 people in five different categories: Assimilation, Separation, Marginalization, and Integration. In addition we have considered Y.Y. Kim's communication-based theory of cross-cultural adaption to explain how communications helped migrant populations in adaption process. Based on the findings of this study, 12 of 15 interviewed members of the study used the integration strategy to adapt to the new cultural environment, 3 of them used the assimilation strategy, and none of them used marginalization or separation strategies. Communicating with natives, knowing the language, and education were the factors that helped all the interviewed members of the sample to overcome the difficulties of intercultural transition.

Keywords: acculturation, culture, intercultural transition, migration

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Authors: Sook Ching Yee, Angela Siew Hoong Lee

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Big data technologies have become a trend to exploit business opportunities and provide valuable business insights through the analysis of big data. However, there are still many organizations that have yet to adopt big data technologies especially small and medium organizations (SME). This study uses the technology acceptance model (TAM) to look into several constructs in the TAM and other additional constructs which are positive affect, negative affect, organizational factor and motivational factor. The conceptual model proposed in the study will be tested on the relationship and influence of positive affect, negative affect, organizational factor and motivational factor towards the intention to use big data technologies to produce an outcome. Empirical research is used in this study by conducting a survey to collect data.

Keywords: big data technologies, motivational factor, negative affect, organizational factor, positive affect, technology acceptance model (TAM)

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Authors: Anuta Mukherjee, Saswati Mukherjee

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Data is growing everyday. Social networking sites such as Twitter are becoming an integral part of our daily lives, contributing a large increase in the growth of data. It is a rich source especially for sentiment detection or mining since people often express honest opinion through tweets. However, although sentiment analysis is a well-researched topic in text, this analysis using Twitter data poses additional challenges since these are unstructured data with abbreviations and without a strict grammatical correctness. We have employed collision theory to achieve sentiment analysis in Twitter data. We have also incorporated discourse analysis in the collision theory based model to detect accurate sentiment from tweets. We have also used the retweet field to assign weights to certain tweets and obtained the overall weightage of a topic provided in the form of a query. Hadoop has been exploited for speed. Our experiments show effective results.

Keywords: sentiment analysis, twitter, collision theory, discourse analysis

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Authors: Nada Bezić, Valerija Dunkić, Rušćić Mirko

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Astragalus monspessulanus L. ssp. illyricus (Bernhardt) Chater is endemic species of Fabaceae family and belongs to hemicryptophyte. This plant grows wild in the sub-Mediterranean area. We analyzed the composition of the essential oil of stems and leaves of A. monspessulanus L. ssp. Illyricus, collected in Tijarica, near Split, Croatia. Water distilled essential oils from aerial parts of investigation plant have been analysed by GC and GC/MS using VF-5ms capillary column. The total yield of oil was 0.08%, based on dry weight of samples. Thirty-eight compounds were representing 88.5% of the total oil. This essential oil was characterized by a high concentration of cis-myrtanol (20.5%), geranyl acetate (9.6%) and phytone (6.6%). Previous research in the species A. monspessulanus have included flavoalkaloids and flavonoids composition. The present study gives additional knowledge about secondary metabolites contents on the genus Astragalus.

Keywords: essential oil, isovaleric acid, Valeriana tuberosa, geranyl acetate, phytone

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Authors: Ilona Krone

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Maternal smoking during pregnancy increases the risk of perinatal/postnatal negative health outcomes; however, only 1 in 5 pregnant smokers quit smoking. That is a clinical and public health problem. Pregnant smokers have negative paternal support, and higher levels of perceived stress than non-smokers and quitters return to smoking in a stressful situation. A crisis like the COVID-19 outbreak causes significant uncertainty and stress. For pregnant women, additional stress may increase due to concerns for their fetus. Strategies targeting maternal stress and isolation may be particularly useful to prevent negative outcomes for women and their fetuses. Within the post-doctoral study, cooperating with leading specialists, an innovative program for pregnant smokers will be developed. Feasibility for reducing craving, distress intolerance, Covid 19 related stress, and fear in pregnant women in Latvia will be assessed.

Keywords: COVID 19, mindfulness, motivation, pregnancy, smoking cessation

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Authors: Shaik Jilani Basha, Inavolu Avinash, Alla Venu Sai Reddy, Bitragunta Taraka Ramu

Abstract:

We can use the neural style transfer technique to build a picture with the same "content" as the beginning image but the "style" of the picture we've chosen. Neural style transfer is a technique for merging the style of one image into another while retaining its original information. The only change is how the image is formatted to give it an additional artistic sense. The content image depicts the plan or drawing, as well as the colors of the drawing or paintings used to portray the style. It is a computer vision programme that learns and processes images through deep convolutional neural networks. To implement software, we used to train deep learning models with the train data, and whenever a user takes an image and a styled image, the output will be as the style gets transferred to the original image, and it will be shown as the output.

Keywords: neural networks, computer vision, deep learning, convolutional neural networks

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Authors: Jeff A. Tysinger, Dawn P. Tysinger

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There has been considerable growth in online learning. Researchers continue to explore the impact various methods of delivery. Podcasting is a popular method for sharing information. The purpose of this study was to examine the impact of student motivation and the perception of the acquisition of knowledge in an online environment of a skill-based class. 25 students in a school psychology graduate class completed a pretest and posttest examining podcast use and familiarity. In addition, at the completion of the course they were administered a modified version of the Instructional Materials Motivation Survey. The four subscales were examined (attention, relevance, confidence, and satisfaction). Results indicated that students are motivated, they perceive podcasts as positive instructional tools, and students are successful in acquiring the needed information. Additional benefits of using podcasts and recommendations in school psychology training are discussed.

Keywords: motivation, online learning, pedagogy, podcast

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Authors: Sidi Yang, Haiyi Zhang

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Twitter is a microblogging platform, where millions of users daily share their attitudes, views, and opinions. Using a probabilistic Latent Dirichlet Allocation (LDA) topic model to discern the most popular topics in the Twitter data is an effective way to analyze a large set of tweets to find a set of topics in a computationally efficient manner. Sentiment analysis provides an effective method to show the emotions and sentiments found in each tweet and an efficient way to summarize the results in a manner that is clearly understood. The primary goal of this paper is to explore text mining, extract and analyze useful information from unstructured text using two approaches: LDA topic modelling and sentiment analysis by examining Twitter plain text data in English. These two methods allow people to dig data more effectively and efficiently. LDA topic model and sentiment analysis can also be applied to provide insight views in business and scientific fields.

Keywords: text mining, Twitter, topic model, sentiment analysis

Procedia PDF Downloads 173