Search results for: foreign language learning

Authors: Azizeh Chalak, Niloufar Nasri

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Students' academic achievement, along with the effects of different variables, has been a serious concern of educators since long ago. This study was an attempt to investigate the interplay of Locus of Control (LOC), academic achievement and biological variables among Iranian online EFL Learners. The participants of the study included 100 students of different age groups and genders studying English online at Iran Language Institute (ILI), Isfahan, Iran. The instrument used was Trice Academic LOC questionnaire which identifies orientations of internality or externality. The participants' Grade Point Averages (GPAs) were used as the measure of their academic achievement. A series of independent samples t-tests were performed on the data. The results of the study showed that (a) there were no significant differences between male and female participants in LOC orientation, (b) there was no relationship between LOC and academic achievement among internal males and females, (c) external females were better achievers than external males, (d) and the age had no significant relationship with LOC and academic achievement. It can be concluded that the social, cultural patterns of genders have changed. This study might help sociologists and psychologists as well as applied linguists in that they reflect the recent social changes and their effects on the LOC and their consequent implications in teaching languages.

Keywords: academic achievement, biological variables, Iranian online EFL learners, locus of control

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Authors: Zareen Khan

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Islamic Banking has experienced high growth in Pakistan in recent years and has successfully survived the economic downturn of 2009-2011. Despite the increase in branch network and expansion of services, it is unclear if Islamic banks are truly following the theory and practical application of Shariah Law. This paper explores the theological basis of Islamic finance and examines the discrepancies between the theory and practice of Islamic banking using Pakistan as a case study. It discusses areas where Islamic banks lack proper Shariah compliance and analyzes the financial weaknesses of Islamic banks in terms of the services offered. Furthermore, the paper offers plausible explanations for the clientele of Islamic banks. The case study has three major findings. Firstly, most of the employees of Islamic banks come from conventional banking backgrounds and the banks have to invest in additional trainings to specialize employees in Islamic Banking. Secondly despite the efforts of State Bank of Pakistan, there is a lack of accounting and auditing standards tailored for Islamic Banking. Thirdly, majority of the clients of Islamic banks in Pakistan are accustomed to conventional banking causing the bankers to “speak the conventional banking language.” Combined, these three factors can create gaps in the practical application of Islamic finance in Islamic banks in Pakistan.

Keywords: islamic finance, comparing theory with practice, islamic banking, Pakistan

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Authors: Chinaza Uleanya, Martin Duma, Bongani Gamede

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The research investigated pedagogic malpractices by lecturers in sub-Sahara African universities. The population of the study consisted of undergraduates and lecturers in selected universities in Nigeria and South Africa. Mixed method approach was adopted for data collection. The sample population of the study was 480 undergraduate students and 16 lecturers. Questionnaires with 4 point Likert-scale were administered to 480 respondents while interviews were conducted with 6 lecturers. In addition, the teaching strategies of 10 lecturers were observed. Data analyses indicated that poor work environment demotivates lecturers and makes them involved in pedagogic malpractice which is one of the causes of learning challenges faced by undergraduates. The finding of the study also shows that pedagogic malpractice contributes to the high rate of dropout in sub-Sahara African universities. Based on the results, it was recommended that qualified lecturers be employed and given conducive environments to work.

Keywords: malpractice, pedagogy, pedagogic malpractice, correlates

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Authors: Érick Aragão Ribeiro, George André Pereira Thé, José Marques Soares

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Graphical Human Interface, also known as supervision software, are increasingly present in industrial processes supported by Supervisory Control and Data Acquisition (SCADA) systems and so it is evident the need for qualified developers. In order to make engineering students able to produce high quality supervision software, method for the development must be created. In this paper we propose model, based on the international standards ISO/IEC 25010 and ISO/IEC 25040, for the development of graphical human interface. When compared with to other methods through experiments, the model here presented leads to improved quality indexes, therefore help guiding the decisions of programmers. Results show the efficiency of the models and the contribution to student learning. Students assessed the training they have received and considered it satisfactory.

Keywords: software development models, software quality, supervision software, fuzzy logic

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Authors: Defne Akinci Midas

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The aim of this study was to determine the minimum, and maximum number of words that would be sufficient to fulfill the writing task in the local English Proficiency Exam (EPE) produced and administered at the Middle East Technical University, Ankara, Turkey. The relationship between the number of words and the scores of the written products that had been awarded by two raters in three online EPEs administered in 2020 was examined. The means, standard deviations, percentages, range, minimum and maximum scores as well as correlations of the scores awarded to written products with the words that amount to 0-50, 51-100, 101-150, 151-200, 201-250, 251-300, and so on were computed. The results showed that the raters did not award a full score to texts that had fewer than 100 words. Moreover, the texts that had around 200 words were awarded the highest scores. The highest number of words that earned the highest scores was about 225, and from then onwards, the scores were either stable or lower. A positive low to moderate correlation was found between the number of words and scores awarded to the texts. We understand that the idea of ‘the longer, the better’ did not apply here. The results also showed that words between 101 to about 225 were sufficient to fulfill the writing task to fully display writing skills and language ability in the specific case of this exam.

Keywords: English proficiency exam, number of words, scoring, writing task

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Authors: Ana Hol

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Digital systems are in the cognitive wave of the eTransformations and are now extensively aimed at meeting the individuals’ demands, both those of customers requiring services and those of service providers. It is also apparent that successful future systems will not just simply open doors to the traditional owners/users to offer and receive services such as Uber for example does today, but will in the future require more customized and cognitively enabled infrastructures that will be responsive to the system user’s needs. To be able to identify what is required for such systems, this research reviews the historical and the current effects of the eTransformation process by studying: 1. eTransitions of company websites and mobile applications, 2. Emergence of new sheared economy business models as Uber and, 3. New requirements for demand driven, cognitive systems capable of learning and just in time decision making. Based on the analysis, this study proposes a Cognitive eTransformation Framework capable of guiding implementations of new responsive and user aware systems.

Keywords: system implementations, AI supported systems, cognitive systems, eTransformation

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Authors: Collins Molua

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This paper investigated the effect of Teaching Strategies on Academic Achievement in Secondary Physics Education as a quality assurance process for the teaching and learning of the subject. Teaching strategies investigated were the interactive, independent and dependent strategies. Three null hypotheses were tested at p< 0.05 using one instrument, physics achievement test(PAT).The data were analyzed using analysis of covariance (ANCOVA).Results showed that teaching strategies have significant effect on students achievement; the joint effect of the teaching strategies was also significant on students achievement in Physics. The interactive teaching strategies was recommended for teaching the subject and the students should be exposed to practical, computer literacy to stimulate interest and curiosity to enhance quality.

Keywords: quality, assurance, secondary education, strategies, physics

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Authors: Langa Hendrick Musawenkosi, Twala Bhekisipho

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The success or failure of students is a concern for every academic institution, college, university, governments and students themselves. Several approaches have been researched to address this concern. In this paper, a view is held that when a student enters a university or college or an academic institution, he or she enters an academic environment. The academic environment is unique concept used to develop the solution for making predictions effectively. This paper presents a model to determine the propensity of a student to succeed or fail in the French South African Schneider Electric Education Center (FSASEC) at the Vaal University of Technology (VUT). The Decision Tree algorithm is used to implement the model at FSASEC.

Keywords: FSASEC, academic environment model, decision trees, k-nearest neighbor, machine learning, popularity index, support vector machine

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Authors: Gałka Aleksandra, Jelińska Justyna, Masiak Albert, Walentukiewicz Krzysztof

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An offline signature is well-known however not the safest way to verify identity. Nowadays, to ensure proper authentication, i.e. in banking systems, multimodal verification is more widely used. In this paper the online signature analysis based on dynamic time warping (DTW) coupled with machine learning approaches has been presented. In our research signatures made with biometric pens were gathered. Signature features as well as their forgeries have been described. For verification of authenticity various methods were used including convolutional neural networks using DTW matrix and multilayer perceptron using sums of DTW matrix paths. System efficiency has been evaluated on signatures and signature forgeries collected on the same day. Results are presented and discussed in this paper.

Keywords: dynamic time warping, handwritten signature verification, feature-based recognition, online signature

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Authors: Gianna Zou

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Propensity score matching (PSM), introduced by Paul R. Rosenbaum and Donald Rubin in 1983, is a popular statistical matching technique which tries to estimate the treatment effects by taking into account covariates that could impact the efficacy of study medication in clinical trials. PSM can be used to reduce the bias due to confounding variables. However, PSM assumes that the response values are normally distributed. In some cases, this assumption may not be held. In this paper, a machine learning method - Bayesian Additive Regression Tree (BART), is used as a more robust method of matching. BART can work well when models are misspecified since it can be used to model heterogeneous treatment effects. Moreover, it has the capability to handle non-linear main effects and multiway interactions. In this research, a BART Matching Method (BMM) is proposed to provide a more reliable matching method over PSM. By comparing the analysis results from PSM and BMM, BMM can perform well and has better prediction capability when the response values are not normally distributed.

Keywords: BART, Bayesian, matching, regression

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Authors: Maria E. Eggink

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Human capital is one of the essential factors in an innovation system and innovation is the driving force of economic growth and development. Schumpeter focused on the entrepreneur as innovator, but the evolutionary economists shifted the focus to all participants in the innovation system. Education and training institutions are important participants in an innovation system, but there is a gap in literature on competence building as part of the analysis of innovation systems. In this paper the education and training institutions’ competence building role in the innovation system is examined. The Mpumalanga Province of South Africa is used as a case study. It was found that the absence of a university, the level of education, the quality and performance in the education sector and the condition of the education infrastructure have not been conducive to learning.

Keywords: education institutions, human capital, innovation systems, Mpumalanga Province

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Authors: Jugal Bhandari, K. Hari Priya

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The ECG signal provides important clinical information which could be used to pretend the diseases related to heart. Accordingly, delineation of ECG signal is an important task. Whereas delineation of P and T waves is a complex task. This paper deals with the Study of ECG signal and analysis of signal by means of Verilog Design of efficient filters and MATLAB tool effectively. It includes generation and simulation of ECG signal, by means of real time ECG data, ECG signal filtering and processing by analysis of different algorithms and techniques. In this paper, we design a basic particle filter which generates a dynamic model depending on the present and past input samples and then produces the desired output. Afterwards, the output will be processed by MATLAB to get the actual shape and accurate values of the ranges of P-wave and T-wave of ECG signal. In this paper, Questasim is a tool of mentor graphics which is being used for simulation and functional verification. The same design is again verified using Xilinx ISE which will be also used for synthesis, mapping and bit file generation. Xilinx FPGA board will be used for implementation of system. The final results of FPGA shall be verified with ChipScope Pro where the output data can be observed.

Keywords: ECG, MATLAB, Bayesian filtering, particle filter, Verilog hardware descriptive language

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Authors: Hsiao-Yung Wang

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This paper aims to elaborate the rhetorical strategies and its inherent dialectical tensions between transgender movement and gay movement in Taiwan; thereby, a radical/populist democratic model will be reproblematized for theorizing the internal dialogicity of the 'umbrella metaphor' of the so-called 'LGBT' label. Firstly, it examined how the representative gay community in Taiwan defined the category of 'LGBT' by its visual rhetoric of pride parade during the last two decades, and how the imaginary of 'transgender' was systematically precluded or even silenced by 'cisgender privilege' or 'cisnormativity' of the gay community in general. Secondly, it employed Laclau & Mouffe’s (1985) perspective of 'empty signifier' which derives from their radical democratic theorization and populist reason, to explore the rhetorical strategies and language tactics on which transgender activists relied for arguing or mapping both the cooperative and competitive relationship with cisgender allies intentionally. Based on research findings, this paper argued that a relationship between rather than an amalgamation of sexual orientation and gender identity should be recognized. Moreover, that resisting defining transgender as other and everyone else as normal could be the critical issue of LGBT community as a whole, especially while it proceeds toward to a radical/populist democracy.

Keywords: empty signifier, LGBT, populist reason, radical democracy, rhetoric, transgender

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Authors: Aditi Kashi

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While educational technologies have taken great strides, especially in Musical Instrument Digital Interface (MIDI) composition, teachers across the world are still adjusting to incorporate such technology into their curricula. While using MIDI in the classroom has become more common, limited class time and a strong focus on performance have made composition a lesser priority. The balance between music theory, performance time, and composition learning is delicate and difficult to maintain for many music educators. This makes including MIDI in the classroom. To address this issue, this paper aims to outline a general conceptual framework centered around a key element of music theory to integrate MIDI composition into the music classroom to not only introduce students to digital composition but also enhance their understanding of music theory and its applicability.

Keywords: educational framework, education technology, MIDI, music education

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Authors: Jamil Ahmed

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Left to Right-Right Most (LR) parsing algorithm is a widely used algorithm of syntax analysis. It is contingent on a parsing table, whereas the parsing tables are extracted from the grammar. The parsing table specifies the actions to be taken during parsing. It requires that the parsing table should have no action conflicts for the same input symbol. This requirement imposes a condition on the class of grammars over which the LR algorithms work. However, there are grammars for which the parsing tables hold action conflicts. In such cases, the algorithm needs a capability of scanning (looking-ahead) next input symbols ahead of the current input symbol. In this paper, a ‘Left to Right’-‘Right Most’ parsing algorithm with lookahead capability is introduced. The 'look-ahead' capability in the LR parsing algorithm is the major contribution of this paper. The practicality of the proposed algorithm is substantiated by the parser implementation of the Context Free Grammar (CFG) of an already proposed programming language 'State Controlled Object Oriented Programming' (SCOOP). SCOOP’s Context Free Grammar has 125 productions and 192 item sets. This algorithm parses SCOOP while the grammar requires to ‘look ahead’ the input symbols due to action conflicts in its parsing table. Proposed LR parsing algorithm with lookahead capability can be viewed as an optimization of ‘Simple Left to Right’-‘Right Most’ (SLR) parsing algorithm.

Keywords: left to right-right most parsing, syntax analysis, bottom-up parsing algorithm

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Authors: E. Verduci, I. Aguglia, A. Filocamo, I. Macrì, R. Scala, A. Vinci

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One of the first indicator of autism spectrum disorder (ASD) is a decreasing tendency or failure to respond to name (RTN) call. Despite RTN is important for social and language developmentand it’s a common target for early interventions for children with ASD, research on specific treatments is insufficient and does not consider the importance of the discrimination between the own name and other names. The purpose of the current study was to replicate an assessment and treatment model proposed by Conine et al. (2020) to teach children with ASD to respond to their own name and to not respond to other names (RTO). The model includes three different phases (baseline/screening, treatment, and generalization), and itgradually introduces the different treatment components, starting with the most naturalistic ones (such as social interaction) and adding more intrusive components (such as tangible reinforcements, prompt and fading procedures) if necessary. The participants of this study were three children with ASD diagnosis: D. (5 years old) with a low frequency of RTN, M. (7 years old) with a RTN unstable and no ability of discrimination between his name and other names, S. (3 years old) with a strong RTN but a constant response to other names. Moreover, the treatment for D. and M. consisted of social and tangible reinforcements (treatment T1), for S. the purpose of the treatment was to teach the discrimination between his name and the others. For all participants, results suggest the efficacy of the model to acquire the ability to selectively respond to the own name and the generalization of the behavior with other people and settings.

Keywords: response to name, autism spectrum disorder, progressive training, ABA

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Authors: Margarita Zavala, Gabriel Chavira, José González, Jorge Orozco, Julio Rolón, Roberto Pichardo

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Adolescence is a neuralgic stage in the formation of every human being, generally this stage is when the middle school level is studied. In 2006, Mexico incorporated 'mentoring' space to assist students in their integration and participation in life. In public middle schools, it is sometimes difficult to be aware of situations that affect students because of the number of them and traditional records management. With this, they lose the opportunity to provide timely support as a preventive way. In order to provide this support, it is required to know the students by detecting the relevant information that has greater impact on their learning process. This research is looking to check if it is possible to identify student’s relevant information to detect when it is at risk, and then to propose a model to manage in a proper way such information.

Keywords: adolescence, mentoring, middle school students, mentoring system support

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Authors: Hengameh Hosseini

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Design of large healthcare facilities – such as hospitals, multi-service line clinics, and nursing facilities - that can accommodate patients with wide-ranging disabilities is a challenging endeavor and one that is poorly understood among healthcare facility managers, administrators, and executives. An even less-understood extension of this problem is the implications of weakly or insufficiently accommodative design of facilities for healthcare workers in physically-intensive jobs who may also suffer from a range of disabilities and who are therefore at increased risk of workplace accident and injury. Combine this reality with the vast range of facility types, ages, and designs, and the problem of universal accommodation becomes even more daunting and complex. In this study, we focus on the implication of facility design for healthcare workers suffering with low vision who also have physically active jobs. The points of difficulty are myriad and could span health service infrastructure, the equipment used in health facilities, and transport to and from appointments and other services can all pose a barrier to health care if they are inaccessible, less accessible, or even simply less comfortable for people with various disabilities. We conduct a series of surveys and interviews with employees and administrators of 7 facilities of a range of sizes and ownership models in the Northeastern United States and combine that corpus with in-facility observations and data collection to identify five major points of failure common to all the facilities that we concluded could pose safety threats to employees with vision impairments, ranging from very minor to severe. We determine that lack of design empathy is a major commonality among facility management and ownership. We subsequently propose three methods for remedying this lack of empathy-informed design, to remedy the dangers posed to employees: the use of an existing open-sourced Augmented Reality application to simulate the low-vision experience for designers and managers; the use of a machine learning model we develop to automatically infer facility shortcomings from large datasets of recorded patient and employee reviews and feedback; and the use of a computer vision model fine tuned on images of each facility to infer and predict facility features, locations, and workflows, that could again pose meaningful dangers to visually impaired employees of each facility. After conducting a series of real-world comparative experiments with each of these approaches, we conclude that each of these are viable solutions under particular sets of conditions, and finally characterize the range of facility types, workforce composition profiles, and work conditions under which each of these methods would be most apt and successful.

Keywords: artificial intelligence, healthcare workers, facility design, disability, visually impaired, workplace safety

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Authors: Hanane Sarnou, Sabri Koç

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In this paper, the interconnection between curriculum development for basic education and the use of information and communication technologies (ICTs) in the classroom referring to the Licence, Master's and Doctorate (LMD) benefits under such link will be presented and analysed. This study seeks to achieve to what extent LMD, competency-based approach (CBA) and ICTs use are interrelated. Likewise, the data collected from the responses of our teachers and learners who are concerned with LMD impact on their learning and teaching through interviews will be discussed, analysed, and classified. This paper is divided into two sections. The first section is about the curriculum development for basic education and its relation with higher education under the LMD and its link with ICTs in the university while the second section is about the classification of learners’ and teachers’ positive/negative responses concerning their positive or negative attitudes towards the ICT integration. The focus will be on the positive aspects of students’ expectations, opinions and assumptions regarding the integration of ICTs into the classroom under LMD and CBA.

Keywords: LMD system, CBA approach, curriculum development, ICT

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Authors: Sima Najafzadehkhoei, George Vega Yon

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This paper presents an approach for calibrating Agent-Based Models (ABMs) efficiently, utilizing Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks. These machine learning techniques are applied to Susceptible-Infected-Recovered (SIR) models, which are a core framework in the study of epidemiology. Our method replicates parameter values from observed trajectory curves, enhancing the accuracy of predictions when compared to traditional calibration techniques. Through the use of simulated data, we train the models to predict epidemiological parameters more accurately. Two primary approaches were explored: one where the number of susceptible, infected, and recovered individuals is fully known, and another using only the number of infected individuals. Our method shows promise for application in other ABMs where calibration is computationally intensive and expensive.

Keywords: ABM, calibration, CNN, LSTM, epidemiology

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Authors: Ali Nouri

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Neuroeducation is one of the most exciting research fields which is continually evolving. However, there is a need to develop its theoretical bases in connection to practice. The present paper is a starting attempt in this regard to provide a space from which to think about neuroeducational theory and invoke more investigation in this area. Accordingly, a comprehensive theory of neuroeducation could be defined as grouping or clustering of concepts and propositions that describe and explain the nature of human learning to provide valid interpretations and implications useful for educational practice in relation to philosophical aspects or values. Whereas it should be originated from the philosophical foundations of the field and explain its normative significance, it needs to be testable in terms of rigorous evidence to fundamentally advance contemporary educational policy and practice. There is thus pragmatically a need to include a course on neuroeducational theory into the curriculum of the field. In addition, there is a need to articulate and disseminate considerable discussion over the subject within professional journals and academic societies.

Keywords: neuroeducation studies, neuroeducational theory, theory building, neuroeducation research

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Authors: Jaeyoung Lee

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

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

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Authors: Nino Damenia

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E-commerce opens a new horizon for business development, which is why the presence of e-commerce is a necessary condition for the formation, growth, and development of the country's economy. Worldwide, e-commerce turnover is growing at a high rate every year, as the electronic environment provides great opportunities for product promotion. E-commerce in Georgia is developing at a fast pace, but it is still a relatively young direction in the country's economy. Movement restrictions and other public health measures caused by the COVID-19 pandemic have reduced economic activity in most economic sectors and countries, significantly affecting production, distribution, and consumption. The pandemic has accelerated digital transformation. Digital solutions enable people and businesses to continue part of their economic and social activities remotely. This has also led to the growth of e-commerce. According to the data of the National Statistics Service of Georgia, the share of online trade is higher in cities (27.4%) than in rural areas (9.1%). The COVID-19 pandemic has forced local businesses to expand their digital offerings. The size of the local market increased 3.2 times in 2020 to 138 million GEL. And in 2018-2020, the share of local e-commerce increased from 11% to 23%. In Georgia, the state is actively engaged in the promotion of activities based on information technologies. Many measures have been taken for this purpose, but compared to other countries, this process is slow in Georgia. The purpose of the study is to determine development prospects for the economy of Georgia based on the analysis of electronic commerce. Research was conducted around the issues using Georgian and foreign scientists' articles, works, reports of international organizations, collections of scientific conferences, and scientific electronic databases. The empirical base of the research is the data and annual reports of the National Statistical Service of Georgia, internet resources of world statistical materials, and others. While working on the article, a questionnaire was developed, based on which an electronic survey of certain types of respondents was conducted. The conducted research was related to determining how intensively Georgian citizens use online shopping, including which age category uses electronic commerce, for what purposes, and how satisfied they are. Various theoretical and methodological research tools, as well as analysis, synthesis, comparison, and other types of methods, are used to achieve the set goal in the research process. The research results and recommendations will contribute to the development of e-commerce in Georgia and economic growth based on it.

Keywords: e-commerce, information technology, pandemic, digital transformation

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: ShuHui Yang, ChingChing Lu

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Measuring event-related potentials (ERPs) has been fundamental to our understanding of how people process language. One specific ERP component, a P600, has been hypothesized to be associated with syntactic reanalysis processes. We, however, propose that the P600 is not restricted to reanalysis processes, but is the index of the structural pattern processing. To investigate the structural pattern processing, we utilized the effects of stimulus degradation in structural priming. To put it another way, there was no P600 effect if the structure of the prime was the same with the structure of the target. Otherwise, there would be a P600 effect if the structure were different between the prime and the target. In the experiment, twenty-two participants were presented with four sentences of Tang poetry. All of the first two sentences, being prime, were conducted with SVO+VP. The last two sentences, being the target, were divided into three types. Type one of the targets was SVO+VP. Type two of the targets was SVO+VPVP. Type three of the targets was VP+VP. The result showed that both of the targets, SVO+VPVP and VP+VP, elicited positive-going brainwave, a P600 effect, at 600~900ms time window. Furthermore, the P600 component was lager for the target’ VP+VP’ than the target’ SVO+VPVP’. That meant the more dissimilar the structure was, the lager the P600 effect we got. These results indicate that P600 was the index of the structure processing, and it would affect the P600 effect intensity with the degrees of structural heterogeneity.

Keywords: ERPs, P600, structural pattern, structural priming, Tang poetry

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Authors: Raju K. Thadikkaran

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Introduction: The IPR have come to the centre stage of development discourse today for a variety of reasons: It ranges from the arbitrariness in the enforcement, overlapping and mismatch with various international agreements and conventions, divergence in the definition, nature and content and the duration as well as severe adverse consequences to technologically weak developing countries. In turn, the IPR have acquired prominence in the foreign policy making as well as in the relations among nations. Quite naturally, there is ample scope for an examination of the correlation between Technology, IPR and International Relations in the contemporary world. Nature and Scope: A cursory examination of the realm of IPR and its protection shall reveals the acute divergence that exists in the perspectives, on all matters related to the very definition, nature, content, scope and duration. The proponents of stronger protection, mostly technologically advanced countries, insist on a stringent IP Regime whereas technologically weak developing countries seem to advocate for flexibilities. From the perspective of developing countries like India, one of the most crucial concerns is related to the patenting of life forms and the protection of TK and BD. There have been several instances of Bio-piracy and Bio-prospecting of the resources related to BD and TK from the Bio-rich Global South. It is widely argued that many provisions in the TRIPS are capable of offsetting the welcome provisions in the CBD such as the Access and Benefit Sharing and Prior Informed Consent. The point that is being argued out is as to how the mismatch between the provisions in the TRIPS Agreement and the CBD could be addressed in a healthy manner so that the essential minimum legitimate interests of all stakeholders could be secured thereby introducing a new direction to the international relations. The findings of this study reveal that the challenges roused by the TRIPS Regime over-weigh the opportunities. The mismatch in the provisions in this regard has generated various crucial issues such as Bio-piracy and Bio-prospecting. However, there is ample scope for managing and protecting IP through institutional innovation, legislative, executive and administrative initiative at the global, national and regional levels. The Indian experience is quite reflective of the same and efforts are being made through the new national IPR policy. This paper, employing Historical Analytical Method, has Three Sections. The First Section shall trace the correlation between the Technology, IPR and international relations. The Second Section shall review the issues and potential concerns in the protection and management of IP related to the BD and TK in the developing countries in the wake of the TRIPS and the CBD. The Final Section shall analyze the Indian Experience in this regard and the experience of the bio-rich Kerala in particular.

Keywords: IPR, technology and international relations, bio-diversity, traditional knowledge

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Authors: Athanase Gahungu, Karen Freeman

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Different groups of stakeholders expect the evaluation of an international, grant-funded program to inform them of the worth of the program - the funder, the agency operating the program and its community, and the citizens of the country where the program is implemented. This paper summarizes the challenges that intercultural teams of researchers faced as they crisscrossed a host country while evaluating a teaching and learning materials program, and offers useful tips for effective collaboration. Firstly, was recommended that the teams be representative of the cultures involved, and have the required research and program evaluation skills. Secondly, cultures involved must consistently establish and maintain a shared performance system. Thirdly, successful team members must be self-aware, inter-culturally knowledgeable, not just in communication, but in conceptualizing the political and social context of international grant-funded projects.

Keywords: program evaluation, international collaboration, intercultural, shared performance

Procedia PDF Downloads 533

Authors: Ran Goldblatt, Nicholas Jones, Jennifer Mannix, Brad Bottoms

Abstract:

Accurate, complete, and up-to-date geospatial information is the foundation of successful disaster management. When the 2010 Haiti Earthquake struck, accurate and timely information on the distribution of critical infrastructure was essential for the disaster response community for effective search and rescue operations. Existing geospatial datasets such as Google Maps did not have comprehensive coverage of these features. In the days following the earthquake, many organizations released high-resolution satellite imagery, catalyzing a worldwide effort to map Haiti and support the recovery operations. Of these organizations, OpenStreetMap (OSM), a collaborative project to create a free editable map of the world, used the imagery to support volunteers to digitize roads, buildings, and other features, creating the most detailed map of Haiti in existence in just a few weeks. However, large portions of the island are still not fully covered by OSM. There is an increasing need for a tool to automatically identify which areas in Haiti, as well as in other countries vulnerable to disasters, that are not fully mapped. The objective of this project is to leverage different types of remote sensing measurements, together with machine learning approaches, in order to identify geographical areas where OSM coverage of building footprints is incomplete. Several remote sensing measures and derived products were assessed as potential predictors of OSM building footprints coverage, including: intensity of light emitted at night (based on VIIRS measurements), spectral indices derived from Sentinel-2 satellite (normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), soil-adjusted vegetation index (SAVI), urban index (UI)), surface texture (based on Sentinel-1 SAR measurements)), elevation and slope. Additional remote sensing derived products, such as Hansen Global Forest Change, DLR`s Global Urban Footprint (GUF), and World Settlement Footprint (WSF), were also evaluated as predictors, as well as OSM street and road network (including junctions). Using a supervised classification with a random forest classifier resulted in the prediction of 89% of the variation of OSM building footprint area in a given cell. These predictions allowed for the identification of cells that are predicted to be covered but are actually not mapped yet. With these results, this methodology could be adapted to any location to assist with preparing for future disastrous events and assure that essential geospatial information is available to support the response and recovery efforts during and following major disasters.

Keywords: disaster management, Haiti, machine learning, OpenStreetMap, remote sensing

Procedia PDF Downloads 119

Authors: N. Coskun

Abstract:

Australia has received over 840,000 refugees since its establishment as a federation. Despite the long history of refugee intake, Australia appears to have prolonged problems in refugee education such as academic and social isolations of refugee background students (RBS), the discriminations towards RBS and the high number of RBS drop-outs. This paper examines the place of RBS in educational policies, which can help to identify the problems and set a foundation for solutions. This paper investigates the educational provisions for RBS in three stages. First, the paper identifies the needs of RBS through a comprehensive literature review, using the framework of Bronfenbrenner’s bio-ecological model. Second, the study explores the place of these needs in Australian national and state educational policies which are informed by multiculturalism. The findings conclude that social, academic and psychological needs of RBS hardly find a place in multicultural educational policies. The students and their specific needs are mostly invisible and are placed under a general category of newly arrived immigrants who learn English as a second language. Third, the study explores the possible reasons for the overlook on RBS and their needs with examining the general socio-political context surrounding refugees in Australia. The overall findings suggest that Australian multiculturalism policy in education are inadequate to address RBS' social, academic and psychological needs due to the disadvantaging socio-political context where refugees are placed.

Keywords: Australia, bio-ecological model, multiculturalism, refugee education

Procedia PDF Downloads 131

Authors: Chen Xi, Lao Xuerui, Li Junjie, Jiang Yike, Wang Hanwei, Zeng Zihao

Abstract:

To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behaviour recognition models, to provide empirical data such as 'pedestrian flow data and human behavioural characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, convolutional neural network

Procedia PDF Downloads 136