Search results for: vector information

Authors: Iliuta Cumpanasu, Veronica Oana Cumpanasu

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This paper focuses on studying the conjunction between the new emerged theory of “Memory Effect” in Irregular Migration and Related Criminality and the notion of securitization, and its impact on border management, bringing about a scientific advancement in the field by identifying the patterns corresponding to the linkage of the two concepts, for the first time, and developing a theoretical explanation, with respect to the effects of the non-military threats on border security. Over recent years, irregular migration has experienced a significant increase worldwide. The U.N.'s refugee agency reports that the number of displaced people is at its highest ever - surpassing even post-World War II numbers when the world was struggling to come to terms with the most devastating event in history. This is also the fresh reality within the core studied coordinate, the Balkan Route of Irregular Migration, which starts from Asia and Africa and continues to Turkey, Greece, North Macedonia or Bulgaria, Serbia, and ends in Romania, where thousands of migrants find themselves in an irregular situation concerning their entry to the European Union, with its important consequences concerning the related criminality. The data from the past six years was collected by making use of semi-structured interviews with experts in the field of migration and desk research within some organisations involved in border security, pursuing the gathering of genuine insights from the aforementioned field, which was constantly addressed the existing literature and subsequently subjected to the mixed methods of analysis, including the use of the Vector Auto-Regression estimates model. Thereafter, the analysis of the data followed the processes and outcomes in Grounded Theory, and a new Substantive Theory emerged, explaining how the phenomena of irregular migration and cross-border criminality are the decisive impetus for implementing the concept of securitization in border management by using the proposed pattern. The findings of the study are therefore able to capture an area that has not yet benefitted from a comprehensive approach in the scientific community, such as the seasonality, stationarity, dynamics, predictions, or the pull and push factors in Irregular Migration, also highlighting how the recent ‘Pandemic’ interfered with border security. Therefore, the research uses an inductive revelatory theoretical approach which aims at offering a new theory in order to explain a phenomenon, triggering a practically handy contribution for the scientific community, research institutes or Academia and also usefulness to organizational practitioners in the field, among which UN, IOM, UNHCR, Frontex, Interpol, Europol, or national agencies specialized in border security. The scientific outcomes of this study were validated on June 30, 2021, when the author defended his dissertation for the European Joint Master’s in Strategic Border Management, a two years prestigious program supported by the European Commission and Frontex Agency and a Consortium of six European Universities and is currently one of the research objectives of his pending PhD research at the West University Timisoara.

Keywords: migration, border, security, memory effect

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Lu Ren, You-Liang Fang, Yan-Gang Zhao

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In recent years, the application of BIM (Building Information Modelling) to construction schedule plan has been the focus of more and more researchers. In order to assess the reasonable level of the BIM-based construction schedule plan, that is whether the schedule can be completed on time, some researchers have introduced reliability theory to evaluate. In the process of evaluation, the uncertain factors affecting the construction schedule plan are regarded as random variables, and probability distributions of the random variables are assumed to be normal distribution, which is determined using two parameters evaluated from the mean and standard deviation of statistical data. However, in practical engineering, most of the uncertain influence factors are not normal random variables. So the evaluation results of the construction schedule plan will be unreasonable under the assumption that probability distributions of random variables submitted to the normal distribution. Therefore, in order to get a more reasonable evaluation result, it is necessary to describe the distribution of random variables more comprehensively. For this purpose, cubic normal distribution is introduced in this paper to describe the distribution of arbitrary random variables, which is determined by the first four moments (mean, standard deviation, skewness and kurtosis). In this paper, building the BIM model firstly according to the design messages of the structure and making the construction schedule plan based on BIM, then the cubic normal distribution is used to describe the distribution of the random variables due to the collecting statistical data of the random factors influencing construction schedule plan. Next the reliability analysis of the construction schedule plan based on BIM can be carried out more reasonably. Finally, the more accurate evaluation results can be given providing reference for the implementation of the actual construction schedule plan. In the last part of this paper, the more efficiency and accuracy of the proposed methodology for the reliability analysis of the construction schedule plan based on BIM are conducted through practical engineering case.

Keywords: BIM, construction schedule plan, cubic normal distribution, reliability analysis

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Authors: Marisa Chrysochoou, James Mahoney, Kay Wille

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Pyrrhotite is an iron-sulfide mineral which releases sulfuric acid when exposed to water and oxygen. The presence of this mineral in concrete foundations across Connecticut and Massachusetts in the US is causing in some cases premature failure. This has resulted in a devastating crisis for all parties affected by this type of failure which can take up to 15-25 years before internal damage becomes visible on the surface. This study shares laboratory results aimed to investigate the fundamental mechanisms of pyrrhotite reaction and to further the understanding of its deterioration kinetics within concrete. This includes the following analyses: total sulfur, wavelength dispersive X-ray fluorescence, expansion, reaction rate combined with ion-chromatography, as well as damage evolution using electro-chemical acceleration. This information is coupled to a statistical analysis of over 150 analyzed concrete foundations. Those samples were obtained and process using a developed and validated sampling method that is minimally invasive to the foundation in use, provides representative samples of the concrete matrix across the entire foundation, and is time and cost-efficient. The processed samples were then analyzed using a developed modular testing method based on total sulfur and wavelength dispersive X-ray fluorescence analysis to quantify the amount of pyrrhotite. As part of the statistical analysis the results were grouped into the following three categories: no damage observed and no pyrrhotite detected, no damage observed and pyrrhotite detected and damaged observed and pyrrhotite detected. As expected, a strong correlation between amount of pyrrhotite, age of the concrete and damage is observed. Information from the laboratory investigation and from the statistical analysis of field samples will aid in forming a scientific basis to support the decision process towards sustainable financial and administrative solutions by state and local stakeholders.

Keywords: concrete, pyrrhotite, risk of failure, statistical analysis

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Authors: Sinead Impey, Gaye Stephens, Lucy Hederman, Declan O'Sullivan

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Continued paper use in the clinical area post-Electronic Health Record (EHR) adoption is regularly linked to hardware and software usability challenges. Although paper is used as a workaround to circumvent challenges, including limited availability of a computer, this perspective does not consider the important role paper, such as the nurses’ handover sheet, play in practice. The purpose of this study is to confirm the hypothesis that paper use post-EHR adoption continues as paper provides both a cognitive tool (that assists with workflow) and a compensation tool (to circumvent usability challenges). Distinguishing the different motivations for continued paper-use could assist future evaluations of electronic record systems. Methods: Qualitative data were collected from three clinical care environments (ICU, general ward and specialist day-care) who used an electronic record for at least 12 months. Data were collected through semi-structured interviews with 22 nurses. Data were transcribed, themes extracted using an inductive bottom-up coding approach and a thematic index constructed. Findings: All nurses interviewed continued to use paper post-EHR adoption. While two distinct motivations for paper use post-EHR adoption were confirmed by the data - paper as a cognitive tool and paper as a compensation tool - further finding was that there was an overlap between the two uses. That is, paper used as a compensation tool could also be adapted to function as a cognitive aid due to its nature (easy to access and annotate) or vice versa. Rather than present paper persistence as having two distinctive motivations, it is more useful to describe it as presenting on a continuum with compensation tool and cognitive tool at either pole. Paper as a cognitive tool referred to pages such as nurses’ handover sheet. These did not form part of the patient’s record, although information could be transcribed from one to the other. Findings suggest that although the patient record was digitised, handover sheets did not fall within this remit. These personal pages continued to be useful post-EHR adoption for capturing personal notes or patient information and so continued to be incorporated into the nurses’ work. Comparatively, the paper used as a compensation tool, such as pre-printed care plans which were stored in the patient's record, appears to have been instigated in reaction to usability challenges. In these instances, it is expected that paper use could reduce or cease when the underlying problem is addressed. There is a danger that as paper affords nurses a temporary information platform that is mobile, easy to access and annotate, its use could become embedded in clinical practice. Conclusion: Paper presents a utility to nursing, either as a cognitive or compensation tool or combination of both. By fully understanding its utility and nuances, organisations can avoid evaluating all incidences of paper use (post-EHR adoption) as arising from usability challenges. Instead, suitable remedies for paper-persistence can be targeted at the root cause.

Keywords: cognitive tool, compensation tool, electronic record, handover sheet, nurse, paper persistence

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Authors: Jongtae Rhee, Sangkwon Han, Seungbin Ji, Junhyeong Park, Byeonghun Kim, Taekyung Kim, Byeonghyeon Jeon, Jiwoo Yang

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The shared kitchen is a concept that transfers the value of the sharing economy to the kitchen. It is a type of kitchen equipped with cooking facilities that allows multiple companies or chefs to share time and space and use it jointly. These shared kitchens provide economic benefits and convenience, such as reduced investment costs and rent, but also increase the risk of safety management, such as cross-contamination of food ingredients. Therefore, to manage the safety of food ingredients and finished products in a shared kitchen where several entities jointly use the kitchen and handle various types of food ingredients, it is critical to manage followings: the freshness of food ingredients, user hygiene and safety and cross-contamination of cooking equipment and facilities. In this study, it propose a machine learning-based system for hygiene safety and cross-contamination management, which are highly difficult to manage. User clothing management and user access management, which are most relevant to the hygiene and safety of shared kitchens, are solved through machine learning-based methodology, and cutting board usage management, which is most relevant to cross-contamination management, is implemented as an integrated safety management system based on artificial intelligence. First, to prevent cross-contamination of food ingredients, we use images collected through a real-time camera to determine whether the food ingredients match a given cutting board based on a real-time object detection model, YOLO v7. To manage the hygiene of user clothing, we use a camera-based facial recognition model to recognize the user, and real-time object detection model to determine whether a sanitary hat and mask are worn. In addition, to manage access for users qualified to enter the shared kitchen, we utilize machine learning based signature recognition module. By comparing the pairwise distance between the contract signature and the signature at the time of entrance to the shared kitchen, access permission is determined through a pre-trained signature verification model. These machine learning-based safety management tasks are integrated into a single information system, and each result is managed in an integrated database. Through this, users are warned of safety dangers through the tablet PC installed in the shared kitchen, and managers can track the cause of the sanitary and safety accidents. As a result of system integration analysis, real-time safety management services can be continuously provided by artificial intelligence, and machine learning-based methodologies are used for integrated safety management of shared kitchens that allows dynamic contracts among various users. By solving this problem, we were able to secure the feasibility and safety of the shared kitchen business.

Keywords: artificial intelligence, food safety, information system, safety management, shared kitchen

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Authors: Barbara Pittau, Piergiorgio Palla, Antonio Mastino

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Communication is fundamental to health education. The proper use of medicinal products is a crucial aspect of the health of citizens that affects both safety and health care spending. Therefore, encouraging/promoting communication, concerning the importance of proper use of pharmaceuticals, has substantial implications in terms of individual health, health care, and health care system sustainability. In view of these considerations, in the context of two projects, one of which is still in progress, a relational database-backed web application named COLLABORAFARMACISOLA has been designed and developed as a tool to analyze and visualize how people approach the use of medicinal products, with the aim of improving and enhancing communication efficacy. The software application is being used to collect information (anonymously and voluntarily) from the citizens of Sardinia, an Italian region, regarding their knowledge, experiences, and opinions towards pharmaceuticals. This study that was conducted to date on thousand of interviewed people, has focused on different aspects such as: the treatment interruption and the "self-prescription” without medical consultation, the attention paid to reading the leaflets, the awareness of the economic value of the pharmaceuticals, the importance of avoiding the waste of medicinal products and the attitudes towards the use of generics. To this purpose, our software application provides a set of ad hoc parsing routines, to store information into the structure of a relational database and to process and visualize it through a set of interactive tools aimed to emphasize the findings and the insights obtained. The results of our preliminary analysis show the efficacy of the awareness plan and, at the same time, the criticality and the needs of the territory under examination. The ultimate goal of our study is to provide a contribution to the community by improving communication that can result in a benefit for public health in a context strictly connected to the reality of the territory.

Keywords: communication, pharmaceuticals, public health, relational database, tool, web application

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Authors: Hanin Suleiman Alqam

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The knowledge-based economy, as its name implies relies on knowledge, information and high levels of skills made available for all economic agents. Delving a bit more deeply, the concept of a knowledge-based economy is showcasing four main pillars, which are: Education and Training, Information and Communication Technology, Economic incentives and Institutional regimes, and Research and Development (R&D) and Innovation system. A good number of researches are showing its positive contribution to economic diversification underpinning sustainable development and growth. The present paper aimed at assessing the role of SMEs in moving Oman’s economy from a traditional economy to a knowledge-based economy. To lay down a groundwork that should lead to future studies, the methodology selected is based on exploratory research. Hence, the interview was conducted as a data collection tool. Based on a purposive sampling technique, seven handpicked experts have partaken in the study as they are working in different key organizations considered to be directly or indirectly the backbone of the Omani national economy. A thematic approach is employed for the purpose of data analysis. Results of the study showed that SMEs are not really contributing in the knowledge-based economy due to a lack of awareness about its importance to the country and to the enterprise within SMEs in Oman. However, it was shown that SMEs owners are interested in innovation and are trying to support innovative individuals by attracting them to their enterprises. On the other hand, the results revealed that SMEs' performance in e-solution is still not up to the level as 32% of SMEs only are using e-solutions in their internal processes and procedures like accounting systems. It is recommended to SMEs owners to use new and modern technologies in marketing and customer relation, encourage creativity, research and development, and allow the youth to have opportunities and facilitate the procedure in terms of innovation so that their role in contributing to the knowledge-based economy could be improved.

Keywords: knowledge-based economy, SMEs, ICT pillars, research and innovation

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Authors: Seongjun Kim, Jinwooung Kim, Sung-Ah Kim

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The development of information and communication technology also affects human cognition and thinking, especially in the field of design, new techniques are being tried. In architecture, new design methodologies such as machine learning or data-driven design are being applied. In particular, these methodologies are used in analyzing the factors related to the value of real estate or analyzing the feasibility in the early planning stage of the apartment housing. However, since the value of apartment buildings is often determined by external factors such as location and traffic conditions, rather than the interior elements of buildings, data is rarely used in the design process. Therefore, although the technical conditions are provided, the internal elements of the apartment are difficult to apply the data-driven design in the design process of the apartment. As a result, the designers of apartment housing were forced to rely on designer experience or modular design alternatives rather than data-driven design at the design stage, resulting in a uniform arrangement of space in the apartment house. The purpose of this study is to propose a methodology to support the designers to design the apartment unit plan with high consumer preference by deriving the correlation and importance of the floor plan elements of the apartment preferred by the consumers through the machine learning and reflecting this information from the early design process. The data on the pre-sale competition rate and the elements of the floor plan are collected as data, and the correlation between pre-sale competition rate and independent variables is analyzed through machine learning. This analytical model can be used to review the apartment unit plan produced by the designer and to assist the designer. Therefore, it is possible to make a floor plan of apartment housing with high preference because it is possible to feedback apartment unit plan by using trained model when it is used in floor plan design of apartment housing.

Keywords: apartment unit plan, data-driven design, design methodology, machine learning

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Authors: Camille Lacan, Pierre Desmet

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In the crowdfunding model, a campaign succeeds by collecting the funds required over a predefined duration. The success of a CF campaign depends both on the capacity to attract members of the online communities concerned, and on the community members’ involvement in online word-of-mouth recommendations. To maximize the campaign's success probability, project creators (i.e., an organization appealing for financial resources) send messages to contributors to ask them to issue word of mouth. Internet users relay information about projects through Word of Mouth which is defined as “a critical tool for facilitating information diffusion throughout online communities”. The effectiveness of these messages depends on the message framing and the time at which they are sent to contributors (i.e., at the start of the campaign or close to the deadline). This article addresses the following question: What are the effect of message framing and temporal distance on the willingness to share word of mouth? Drawing on Perspectives Theory and Construal Level Theory, this study examines the interplay between message framing (Gains vs. Losses) and temporal distance (message while the deadline is coming vs. far) on intention to share word of mouth. A between-subject experimental design is conducted to test the research model. Results show significant differences between a loss-framed message (lack of benefits if the campaign fails) associated with a short deadline (ending tomorrow) compared to a gain-framed message (benefits if the campaign succeeds) associated with a distant deadline (ending in three months). However, this effect is moderated by the anticipated regret of a campaign failure and the temporal orientation. These moderating effects contribute to specifying the boundary condition of the framing effect. Handling the message framing and the temporal distance are thus the key decisions to influence the willingness to share word of mouth.

Keywords: construal levels, crowdfunding, message framing, word of mouth

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Authors: Izabel Cristina Zattar, Gilberto Passos Lima, Guilherme Schünemann de Oliveira

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In Brazil, there are several institutions committed to the development of new businesses based on product innovation. Among them are business incubators, universities and science institutes. Business incubators can be defined as nurseries for new companies, which may be in the technology segment, discussed in this article. Business incubators provide services related to infrastructure, such as physical space and meeting rooms. Besides these services, incubators also offer assistance in the form of information and communication, access to finance, relationship networks and business monitoring and mentoring processes. Business incubators support not all technology companies. One of the business incubators tasks is to assess the nature and feasibility of new business proposals. To assist in this goal, this paper proposes a methodology for evaluating new business using the Analytic Hierarchy Process (AHP). This paper presents the concepts used in the assessing methodology application for new business, concepts that have been tested with positive results in practice. This study counts on three main steps: first, a hierarchy was built, based on new business manuals used by the business incubators. These books and manuals relate business selection requirements, such as the innovation status and other technological aspects. Then, a questionnaire was generated, in order to guide incubator experts in the parity comparisons at all hierarchy levels. The weights of each requirement are calculated from information obtained from the questionnaire responses. Finally, the proposed method was applied to evaluate five new business proposals, which were applying to be part of a company incubator. The main result is the classification of these new businesses, which helped the incubator experts to decide what companies were more eligible to work with. This classification may also be helpful to the decision-making process of business incubators in future selection processes.

Keywords: Analytic Hierarchy Process (AHP), Brazilian companies incubators, technology companies, incubator

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Authors: Po-Ching Chou, Wen-Chen Liang, I. Chen Chen, Jong-Hau Hsu, Yuh-Jyh Jong

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Background：Cardiopulmonary complications seem to cause high morbidity and mortality in patients with neuromuscular diseases (NMD) but so far there is no domestic data reported in Taiwan. We, therefore attempted to analyze the factors to cause the death in NMD patients from our cohort. Methods：From 1998 to 2013, we retrospectively collected the information of the NMD patients treated and followed up in Kaohsiung Medical University Hospital. Forty-two patients with NMD who expired during these fifteen years were enrolled. The medical records of these patients were reviewed and the causes of death and the associated affecting factors were analyzed. Results：Eighteen patients with NMD (mean age=13.3, SD=12.4) with complete medical record and detailed information were finally included in this study, including spinal muscular atrophy (SMA) (n=9, 7/9: type 1), Duchenne muscular dystrophy (n=6), congenital muscular dystrophy (n=1), carnitine acyl-carnitine translocase (CACT) deficiency (n=1) and spinal muscular atrophy with respiratory distress (SMARD)(n=1). The place of death was in ICU (n=11, 61%), emergency room (n=3, 16.6%) or home (n=4, 22.2%). For SMA type 1 patients, most of them (71.4%, 5/7) died in emergency room or home and the other two expired during an ICU admission. The causes of death included acute respiratory failure due to pneumonia (n=13, 72.2 %), ventilator failure or dislocation (n=2, 11.1%), suffocation/choking (n=2, 11.1%), and heart failure with hypertrophic cardiomyopathy (n=1, 5.55%). Among the 15 patients died of respiratory failure or choking, 73.3% of the patients (n=11) received no ventilator care at home. 80% of the patients (n=12) received no cough assist at home. The patient died of cardiomyopathy received no medications for heart failure until the last admission. Conclusion: Respiratory failure and choking are the leading causes of death in NMD patients. Appropriate respiratory support and airway clearance play the critical role to reduce the mortality.

Keywords: neuromuscular disease, cause of death, tertiary care hospital, medical sciences

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Authors: Yao-Ying Lai, Maria Pinango, Ashwini Deo

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While grammatical devices are essential to language processing, how comprehension utilizes cognitive mechanisms is less emphasized. This study addresses this issue by probing the complement coercion phenomenon: an entity-denoting complement following verbs like begin and finish receives an eventive interpretation. For example, (1) “The queen began the book” receives an agentive reading like (2) “The queen began [reading/writing/etc.…] the book.” Such sentences engender additional processing cost in real-time comprehension. The traditional account attributes this cost to an operation that coerces the entity-denoting complement to an event, assuming that these verbs require eventive complements. However, in closer examination, examples like “Chapter 1 began the book” undermine this assumption. An alternative, Structured Individual (SI) hypothesis, proposes that the complement following aspectual verbs (AspV; e.g. begin, finish) is conceptualized as a structured individual, construed as an axis along various dimensions (e.g. spatial, eventive, temporal, informational). The composition of an animate subject and an AspV such as (1) engenders an ambiguity between an agentive reading along the eventive dimension like (2), and a constitutive reading along the informational/spatial dimension like (3) “[The story of the queen] began the book,” in which the subject is interpreted as a subpart of the complement denotation. Comprehenders need to resolve the ambiguity by searching contextual information, resulting in additional cost. To evaluate the SI hypothesis, a questionnaire was employed. Method: Target AspV sentences such as “Shakespeare began the volume.” were preceded by one of the following types of context sentence: (A) Agentive-biasing, in which an event was mentioned (…writers often read…), (C) Constitutive-biasing, in which a constitutive meaning was hinted (Larry owns collections of Renaissance literature.), (N) Neutral context, which allowed both interpretations. Thirty-nine native speakers of English were asked to (i) rate each context-target sentence pair from a 1~5 scale (5=fully understandable), and (ii) choose possible interpretations for the target sentence given the context. The SI hypothesis predicts that comprehension is harder for the Neutral condition, as compared to the biasing conditions because no contextual information is provided to resolve an ambiguity. Also, comprehenders should obtain the specific interpretation corresponding to the context type. Results: (A) Agentive-biasing and (C) Constitutive-biasing were rated higher than (N) Neutral conditions (p< .001), while all conditions were within the acceptable range (> 3.5 on the 1~5 scale). This suggests that when lacking relevant contextual information, semantic ambiguity decreases comprehensibility. The interpretation task shows that the participants selected the biased agentive/constitutive reading for condition (A) and (C) respectively. For the Neutral condition, the agentive and constitutive readings were chosen equally often. Conclusion: These findings support the SI hypothesis: the meaning of AspV sentences is conceptualized as a parthood relation involving structured individuals. We argue that semantic representation makes reference to spatial structured-ness (abstracted axis). To obtain an appropriate interpretation, comprehenders utilize contextual information to enrich the conceptual representation of the sentence in question. This study connects semantic structure to human’s conceptual structure, and provides a processing model that incorporates contextual retrieval.

Keywords: ambiguity resolution, contextual retrieval, spatial structured-ness, structured individual

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Authors: Alexander Norbach

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The script in this paper describes the use of advanced simulation environment using electronic systems (Microcontroller, Operational Amplifiers, and FPGA). The simulation may be used for all dynamic systems with the diffusion and the ionisation behaviour also. By additionally required observer structure, the system works with parallel real-time simulation based on diffusion model and the state-space representation for other dynamics. The proposed deposited model may be used for electrodynamic effects, including ionising effects and eddy current distribution also. With the script and proposed method, it is possible to calculate the spatial distribution of the electromagnetic fields in real-time. For further purpose, the spatial temperature distribution may be used also. With upon system, the uncertainties, unknown initial states and disturbances may be determined. This provides the estimation of the more precise system states for the required system, and additionally, the estimation of the ionising disturbances that occur due to radiation effects. The results have shown that a system can be also developed and adopted specifically for space systems with the real-time calculation of the radiation effects only. Electronic systems can take damage caused by impacts with charged particle flux in space or radiation environment. In order to be able to react to these processes, it must be calculated within a shorter time that ionising radiation and dose is present. All available sensors shall be used to observe the spatial distributions. By measured value of size and known location of the sensors, the entire distribution can be calculated retroactively or more accurately. With the formation, the type of ionisation and the direct effect to the systems and thus possible prevent processes can be activated up to the shutdown. The results show possibilities to perform more qualitative and faster simulations independent of kind of systems space-systems and radiation environment also. The paper gives additionally an overview of the diffusion effects and their mechanisms. For the modelling and derivation of equations, the extended current equation is used. The size K represents the proposed charge density drifting vector. The extended diffusion equation was derived and shows the quantising character and has similar law like the Klein-Gordon equation. These kinds of PDE's (Partial Differential Equations) are analytically solvable by giving initial distribution conditions (Cauchy problem) and boundary conditions (Dirichlet boundary condition). For a simpler structure, a transfer function for B- and E- fields was analytically calculated. With known discretised responses g₁(k·Ts) and g₂(k·Ts), the electric current or voltage may be calculated using a convolution; g₁ is the direct function and g₂ is a recursive function. The analytical results are good enough for calculation of fields with diffusion effects. Within the scope of this work, a proposed model of the consideration of the electromagnetic diffusion effects of arbitrary current 'waveforms' has been developed. The advantage of the proposed calculation of diffusion is the real-time capability, which is not really possible with the FEM programs available today. It makes sense in the further course of research to use these methods and to investigate them thoroughly.

Keywords: advanced observer, electrodynamics, systems, diffusion, partial differential equations, solver

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Authors: Mohd Zaimmudin Mohd Zain, Patsy Perry, Lee Quinn

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This study explores how fashion consumers are influenced by fashion bloggers towards pre-purchase decision for online fashion products in a non-Western context. Malaysians rank among the world’s most avid online shoppers, with apparel the third most popular purchase category. However, extant research on fashion blogging focuses on the developed Western market context. Numerous international fashion retailers have entered the Malaysian market from luxury to fast fashion segments of the market; however Malaysian fashion consumers must balance religious and social norms for modesty with their dress style and adoption of fashion trends. Consumers increasingly mix and match Islamic and Western elements of dress to create new styles enabling them to follow Western fashion trends whilst paying respect to social and religious norms. Social media have revolutionised the way that consumers can search for and find information about fashion products. For online fashion brands with no physical presence, social media provide a means of discovery for consumers. By allowing the creation and exchange of user-generated content (UGC) online, they provide a public forum that gives individual consumers their own voices, as well as access to product information that facilitates their purchase decisions. Social media empower consumers and brands have important roles in facilitating conversations among consumers and themselves, to help consumers connect with them and one another. Fashion blogs have become an important fashion information sources. By sharing their personal style and inspiring their followers with what they wear on popular social media platforms such as Instagram, fashion bloggers have become fashion opinion leaders. By creating UGC to spread useful information to their followers, they influence the pre-purchase decision. Hence, successful Western fashion bloggers such as Chiara Ferragni may earn millions of US dollars every year, and some have created their own fashion ranges and beauty products, become judges in fashion reality shows, won awards, and collaborated with high street and luxury brands. As fashion blogging has become more established worldwide, increasing numbers of fashion bloggers have emerged from non-Western backgrounds to promote Islamic fashion styles, such as Hassanah El-Yacoubi and Dian Pelangi. This study adopts a qualitative approach using netnographic content analysis of consumer comments on two famous Malaysian fashion bloggers’ Instagram accounts during January-March 2016 and qualitative interviews with 16 Malaysian Generation Y fashion consumers during September-October 2016. Netnography adapts ethnographic techniques to the study of online communities or computer-mediated communications. Template analysis of the data involved coding comments according to the theoretical framework, which was developed from the literature review. Initial data analysis shows the strong influence of Malaysian fashion bloggers on their followers in terms of lifestyle and morals as well as fashion style. Followers were guided towards the mix and match trend of dress with Western and Islamic elements, for example, showing how vivid colours or accessories could be worked into an outfit whilst still respecting social and religious norms. The blogger’s Instagram account is a form of online community where followers can communicate and gain guidance and support from other followers, as well as from the blogger.

Keywords: fashion bloggers, Malaysia, qualitative, social media

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Authors: Bernice Badal

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This article addresses a persistent challenge related to teacher agency in knowledge acquisition in professional development (PD) workshops in contexts of educational change, given that scholarship identifies a need for more teacher involvement and amplification of teacher's voices. Theoretical concepts are drawn from Bandura’s Social cognitive theory, incorporating the triadic causation model of agency to examine the reciprocal nature of the context, teacher characteristics, and systemic influences that shape how knowledge is transmitted and acquired in PD workshops. This qualitative study, using a mix of classroom observations and interviews, explored the political, contextual, and personal characteristics of teacher agency in PD through an analysis of data extracted from a PhD study. The narratives of six teachers from three township schools are examined to show how PD efforts in South Africa have failed to take account of the holistic development of teacher agency in knowledge dissemination and how this shapes teacher self-efficacy beliefs about being able to masterfully apply the tenets of the reform. Agency, teacher voice, and contextual considerations were used as markers of the quality of the training provided to understand how knowledge is acquired and meaning is made. The findings suggest that systemic influences of institutionally imposed PD offer partial understandings of the reform, which is offered in traditional formats that do not consider teacher empowerment in knowledge production and the development of teacher agency. Common in all the participants’ responses is the need for more information and training on the prescribed approach for teaching English as a second language; however, this paper holds the view that more information may not solve teachers’ dilemmas. Accordingly, it recommends a restructuring of the programme with facilitators being more cognisant of teacher agency for the development of transformative teachers. The findings of the study contribute to the field of teacher knowledge, teacher training, and professional development in the context of educational reforms.

Keywords: teacher professional development, teacher voice, teacher agency, educational reforms, teacher knowledge

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Authors: Jeronimo Cox, Tomonari Furukawa

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Magnetometers have become more popular in inertial measurement units (IMU) for their ability to correct estimations using the earth's magnetic field. Accelerometer and gyroscope-based packages fail with dead-reckoning errors accumulated over time. Localization in robotic applications with magnetometer-inclusive IMUs has become popular as a way to track the odometry of slower-speed robots. With high-speed motions, the accumulated error increases over smaller periods of time, making them difficult to track with IMU. Tracking a high-speed motion is especially difficult with limited observability. Visual obstruction of motion leaves motion-tracking cameras unusable. When motions are too dynamic for estimation techniques reliant on the observability of the gravity vector, the use of magnetometers is further justified. As available magnetometer calibration methods are limited with the assumption that background magnetic fields are uniform, estimation in nonuniform magnetic fields is problematic. Hard iron distortion is a distortion of the magnetic field by other objects that produce magnetic fields. This kind of distortion is often observed as the offset from the origin of the center of data points when a magnetometer is rotated. The magnitude of hard iron distortion is dependent on proximity to distortion sources. Soft iron distortion is more related to the scaling of the axes of magnetometer sensors. Hard iron distortion is more of a contributor to the error of attitude estimation with magnetometers. Indoor environments or spaces inside ferrite-based structures, such as building reinforcements or a vehicle, often cause distortions with proximity. As positions correlate to areas of distortion, methods of magnetometer localization include the production of spatial mapping of magnetic field and collection of distortion signatures to better aid location tracking. The goal of this paper is to compare magnetometer methods that don't need pre-productions of magnetic field maps. Mapping the magnetic field in some spaces can be costly and inefficient. Dynamic measurement fusion is used to track the motion of a multi-link system with us. Conventional calibration by data collection of rotation at a static point, real-time estimation of calibration parameters each time step, and using two magnetometers for determining local hard iron distortion are compared to confirm the robustness and accuracy of each technique. With opposite-facing magnetometers, hard iron distortion can be accounted for regardless of position, Rather than assuming that hard iron distortion is constant regardless of positional change. The motion measured is a repeatable planar motion of a two-link system connected by revolute joints. The links are translated on a moving base to impulse rotation of the links. Equipping the joints with absolute encoders and recording the motion with cameras to enable ground truth comparison to each of the magnetometer methods. While the two-magnetometer method accounts for local hard iron distortion, the method fails where the magnetic field direction in space is inconsistent.

Keywords: motion tracking, sensor fusion, magnetometer, state estimation

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Authors: Ali Alsawayeh, Ibrahim Eldanfour

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This paper examines the extent of disclosure of oil and gas reserve quantum in annual reports of international oil and gas exploration and production companies, particularly companies in untested international markets, such as Canada, the UK and the US, and seeks to determine the underlying factors that affect the level of disclosure on oil reserve quantum. The study is concerned with the usefulness of disclosure of oil and gas reserves quantum to investors and other users. Given the primacy of the annual report (10-k) as a source of supplemental reserves data about the company and as the channel through which companies disseminate information about their performance, the annual reports for one year (2009) were the central focus of the study. This comparative study seeks to establish whether differences exist between the sample companies, based on new disclosure requirements by the Securities and Exchange Commission (SEC) in respect of reserves classification and definition. The extent of disclosure of reserve is provided and compared among the selected companies. Statistical analysis is performed to determine whether any differences exist in the extent of disclosure of reserve under the determinant variables. This study shows that some factors would affect the extent of disclosure of reserve quantum in the above-mentioned countries, namely: company’s size, leverage and quality of auditor. Companies that provide reserves quantum in detail appear to display higher size. The findings also show that the level of leverage has affected companies’ reserves quantum disclosure. Indeed, companies that provide detailed reserves quantum disclosure tend to employ a ‘high-quality auditor’. In addition, the study found significant independent variable such as Profit Sharing Contracts (PSC). This factor could explain variations in the level of disclosure of oil reserve quantum between the contractor and host governments. The implementation of SEC oil and gas reporting requirements do not enhance companies’ valuation because the new rules are based only on past and present reserves information (proven reserves); hence, future valuation of oil and gas companies is missing for the market.

Keywords: comparison, company characteristics, disclosure, reserve quantum, regulation

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Authors: Jaouadi Imen, Ben Djemaa Raoudha, Ben Abdallah Hanene

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The access to relevant information that is adapted to users’ needs, preferences and environment is a challenge in many applications running. That causes an appearance of context-aware systems. To facilitate the development of this class of applications, it is necessary that these applications share a common context meta-model. In this article, we will present our context meta-model that is defined using the OMG Meta Object facility (MOF). This meta-model is based on the analysis and synthesis of context concepts proposed in literature.

Keywords: context, meta-model, MOF, awareness system

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Authors: Young Ik Suh, Tywan G. Martin

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Sports apps in a smartphone provide up-to-date information and fast and convenient access to live games. The market of sports apps has emerged as the second fastest growing app category worldwide. Further, many sports fans use their smartphones to know the schedule of sporting events, players’ position and bios, videos and highlights. In recent years, a growing number of scholars and practitioners alike have emphasized the importance of interactivity with sports apps, hypothesizing that interactivity plays a significant role in enticing sports apps users and that it is a key component in measuring the success of sports apps. Interactivity in sports apps focuses primarily on two functions: (1) two-way communication and (2) active user control, neither of which have been applicable through traditional mass media and communication technologies. Therefore, the purpose of this study is to examine whether the interactivity function on sports apps leads to positive outcomes such as intent to revisit. More specifically, this study investigates how three major functions of interactivity (i.e., two-way communication, active user control, and real-time information) influence the attitude of sports apps users and their intent to revisit the sports apps. The following hypothesis is proposed; interactivity functions will be positively associated with both attitudes toward sports apps and intent to revisit sports apps. The survey questionnaire includes four parts: (1) an interactivity scale, (2) an attitude scale, (3) a behavioral intention scale, and (4) demographic questions. Data are to be collected from ESPN apps users. To examine the relationships among the observed and latent variables and determine the reliability and validity of constructs, confirmatory factor analysis (CFA) is conducted. Structural equation modeling (SEM) is utilized to test hypothesized relationships among constructs. Additionally, this study compares the proposed interactivity model with a rival model to identify the role of attitude as a mediating factor. The findings of the current sports apps study provide several theoretical and practical contributions and implications by extending the research and literature associated with the important role of interactivity functions in sports apps and sports media consumption behavior. Specifically, this study may improve the theoretical understandings of whether the interactivity functions influence user attitudes and intent to revisit sports apps. Additionally, this study identifies which dimensions of interactivity are most important to sports apps users. From practitioners’ perspectives, this findings of this study provide significant implications. More entrepreneurs and investors in the sport industry need to recognize that high-resolution photos, live streams, and up-to-date stats are in the sports app, right at sports fans fingertips. The result will imply that sport practitioners may need to develop sports mobile apps that offer greater interactivity functions to attract sport fans.

Keywords: interactivity, two-way communication, active user control, real time information, sports apps, attitude, intent to revisit

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Authors: Nguyen Manh Hien

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Service quality is the highest requirement from users, especially for the service in electronic government. During the past decades, it has become a major area of academic investigation. Considering this issue, there are many researches that evaluated the dimensions and e-service contexts. This study also identified the dimensions of service quality but focused on a new conceptual and provides a new methodological in developing measurement scales of e-service quality such as information quality, service quality and organization quality. Finally, the study will suggest a key factor to evaluate e-government service quality better.

Keywords: dimensionality, e-government, e-service, e-service quality

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Authors: Zhi-Zhong Chen, Jun-Hao Lu, Jr., Shih-Ying Chueh

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Based on Unified Theory of Acceptance and Use of Technology (UTAUT), the study investigates people’s intention on using smart phones. The study additionally incorporates two new variables: 'self-efficacy' and 'attitude toward using'. Samples are collected by questionnaire survey, in which 240 are valid. After Correlation Analysis, Reliability Test, ANOVA, t-test and Multiple Regression Analysis, the study finds that social impact and self-efficacy have positive effect on use intentions, and the use intentions also have positive effect on use behavior.

Keywords: [1] Ajzen & Fishbein (1975), “Belief, attitude, intention and behavior: An introduction to theory and research”, Reading MA: Addison-Wesley. [2] Bandura (1977) Self-efficacy: toward a unifying theory of behavioural change. Psychological Review , 84, 191–215. [3] Bandura( 1986) A. Bandura, Social foundations of though and action, Prentice-Hall. Englewood Cliffs. [4] Ching-Hui Huang (2005). The effect of Regular Exercise on Elderly Optimism: The Self-efficacy and Theory of Reasoned Action Perspectives.(Master's dissertation, National Taiwan Sport University, 2005).National Digital Library of Theses and Dissertations in Taiwan。 [5] Chun-Mo Wu (2007).The Effects of Perceived Risk and Service Quality on Purchase Intention - an Example of Taipei City Long-Term Care Facilities. (Master's dissertation, Ming Chuan University, 2007).National Digital Library of Theses and Dissertations in Taiwan. [6] Compeau, D.R., and Higgins, C.A., (1995) “Application of social cognitive theory to training for computer skills.”, Information Systems Research, 6(2), pp.118-143. [7] computer-self-efficacy and mediators of the efficacy-performance relationship. International Journal of Human-Computer Studies, 62, 737-758. [8] Davis et al(1989), “User acceptance of computer technology: A comparison of two theoretical models ”, Management Science, 35(8), p.982-1003. [9] Davis et al(1989), “User acceptance of computer technology:A comparison of two theoretical models ”, Management Science, 35(8), p.982-1003. [10] Davis, F.D. (1989). Perceived Usefulness, Perceived Ease of Use and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319-340。 [11] Davis. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319–340. doi:10.2307/249008 [12] Johnson, R. D. (2005). An empirical investigation of sources of application-specific [13] Mei-yin Hsu (2010).The Study on Attitude and Satisfaction of Electronic Documents System for Administrators of Elementary Schools in Changhua County.(Master's dissertation , Feng Chia University, 2010).National Digital Library of Theses and Dissertations in Taiwan. [14] Ming-Chun Hsieh (2010). Research on Parents’ Attitudes Toward Electronic Toys： The case of Taichung City.(Master's dissertation, Chaoyang University of Technology，2010).National Digital Library of Theses and Dissertations in Taiwan. [15] Moon and Kim（2001）. Extending the TAM for a World-Wide-Web context, Information and Management, v.38 n.4, p.217-230. [16] Shang-Yi Hu (2010).The Impacts of Knowledge Management on Customer Relationship Management – Enterprise Characteristicsand Corporate Governance as a Moderator.(Master's dissertation, Leader University, 2010)。National Digital Library of Theses and Dissertations in Taiwan. [17] Sheng-Yi Hung (2013, September10).Worldwide sale of smartphones to hit one billion IDC：Android dominate the market. ETtoday. Retrieved data form the available protocol:2013/10/3. [18] Thompson, R.L., Higgins, C.A., and Howell, J.M.(1991), “Personal Computing: Toward a Conceptual Model of Utilization”, MIS Quarterly(15:1), pp. 125-143. [19] Venkatesh, V., M.G. Morris, G.B. Davis, and F. D. Davis (2003), “User acceptance of information technology: Toward a unified view, ” MIS Quarterly, 27, No. 3, pp.425-478. [20] Vijayasarathy, L. R. (2004), Predicting Consumer Intentions to Use On-Line Shopping： The Case for an Augmented Technology Acceptance Model, Information and Management, Vol.41, No.6, pp.747-762. [21] Wikipedia - smartphone (http://zh.wikipedia.org/zh-tw/%E6%99%BA%E8%83%BD%E6%89%8B%E6%9C%BA)。 [22] Wu-Minsan (2008).The impacts of self-efficacy, social support on work adjustment with hearing impaired. (Master's dissertation, Southern Taiwan University of Science and Technology, 2008).National Digital Library of Theses and Dissertations in Taiwan. [23] Yu-min Lin (2006). The Influence of Business Employee’s MSN Self-efficacy On Instant Messaging Usage Behavior and Communicaiton Satisfaction.(Master's dissertation, National Taiwan University of Science and Technology, 2006).National Digital Library of Theses and Dissertations in Taiwan.

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Authors: M. Nekri, A. Khelladi

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The world wide web network is a network with a complex topology, the main properties of which are the distribution of degrees in power law, A low clustering coefficient and a weak average distance. Modeling the web as a graph allows locating the information in little time and consequently offering a help in the construction of the research engine. Here, we present a model based on the already existing probabilistic graphs with all the aforesaid characteristics. This work will consist in studying the web in order to know its structuring thus it will enable us to modelize it more easily and propose a possible algorithm for its exploration.

Keywords: clustering coefficient, preferential attachment, small world, web community

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Authors: Arsalan Ansari, Muhammad Dawood Idrees, Maria Hafeez

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Use of mobile phones has been increasing considerably over the past decade. Currently, it is one of the main sources of communication and information. Initially, mobile phones were limited to calls and messages, but with the advent of new technology smart phones were being used for many other purposes including video games. Despite of positive outcomes, addiction to video games on mobile phone has become a leading cause of psychological and physiological problems among many people. Several researchers examined the different aspects of behavior addiction with the use of different scales. Objective of this study is to examine any distinction between mobile game addicted and non-addicted players with the use of electroencephalography (EEG), based upon psycho-physiological indicators. The mobile players were asked to play a mobile game and EEG signals were recorded by BIOPAC equipment with AcqKnowledge as data acquisition software. Electrodes were places, following the 10-20 system. EEG was recorded at sampling rate of 200 samples/sec (12,000samples/min). EEG recordings were obtained from the frontal (Fp1, Fp2), parietal (P3, P4), and occipital (O1, O2) lobes of the brain. The frontal lobe is associated with behavioral control, personality, and emotions. The parietal lobe is involved in perception, understanding logic, and arithmetic. The occipital lobe plays a role in visual tasks. For this study, a 60 second time window was chosen for analysis. Preliminary analysis of the signals was carried out with Acqknowledge software of BIOPAC Systems. From the survey based on CGS manual study 2010, it was concluded that five participants out of fifteen were in addictive category. This was used as prior information to group the addicted and non-addicted by physiological analysis. Statistical analysis showed that by applying clustering analysis technique authors were able to categorize the addicted and non-addicted players specifically on theta frequency range of occipital area.

Keywords: mobile game, addiction, psycho-physiology, EEG analysis

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Authors: Sergio A. Navarro Tuch, Martin Rogelio Bustamante Bello, Leopoldo Julian Lechuga Lopez

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In recent years, Mexico’s population has seen a rise of different physiological and mental negative states. Two main consequences of this problematic are deficient work performance and high levels of stress generating and important impact on a person’s physical, mental and emotional health. Several approaches, such as the use of audiovisual stimulus to induce emotions and modify a person’s emotional state, can be applied in an effort to decreases these negative effects. With the use of different non-invasive physiological sensors such as EEG, luminosity and face recognition we gather information of the subject’s current emotional state. In a controlled environment, a subject is shown a series of selected images from the International Affective Picture System (IAPS) in order to induce a specific set of emotions and obtain information from the sensors. The raw data obtained is statistically analyzed in order to filter only the specific groups of information that relate to a subject’s emotions and current values of the physical variables in the controlled environment such as, luminosity, RGB light color, temperature, oxygen level and noise. Finally, a neural network based control algorithm is given the data obtained in order to feedback the system and automate the modification of the environment variables and audiovisual content shown in an effort that these changes can positively alter the subject’s emotional state. During the research, it was found that the light color was directly related to the type of impact generated by the audiovisual content on the subject’s emotional state. Red illumination increased the impact of violent images and green illumination along with relaxing images decreased the subject’s levels of anxiety. Specific differences between men and women were found as to which type of images generated a greater impact in either gender. The population sample was mainly constituted by college students whose data analysis showed a decreased sensibility to violence towards humans. Despite the early stage of the control algorithm, the results obtained from the population sample give us a better insight into the possibilities of emotional domotics and the applications that can be created towards the improvement of performance in people’s lives. The objective of this research is to create a positive impact with the application of technology to everyday activities; nonetheless, an ethical problem arises since this can also be applied to control a person’s emotions and shift their decision making.

Keywords: data analysis, emotional domotics, performance improvement, neural network

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Authors: Rachael Ojima Agarry, Raheemat Opeyemi Omosidi

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Over-schooling children is an abuse of the fundamental provisions of the National Policy on Education in Nigeria. The practice overburdens or places unwarranted academic demands on children, particularly preschoolers. This study was carried out to ascertain the prevalence of over-schooling preschoolers as perceived by teachers in the Kwara Central Senatorial District. One research question and two null hypotheses were formulated to guide the study. A descriptive survey design was employed. The population of the study consists of all preschool teachers in both private and public schools in Kwara Central. A validated instrument tagged “Questionnaire on Prevalence of Over-schooling of Preschoolers (QPOP)” with a reliability index of 0.76 was used for data collection. The questionnaire consists of sections A and B. Section A solicited the respondents’ demographic information, and Section B sought the prevalence of over-schooling as perceived by teachers. Data collected were analyzed using descriptive statistics of frequency and percentage. Mean and standard deviation were used to analyze the demographic information and the research question. The two research hypotheses were analyzed using a t-test and Analysis of Variance (ANCOVA) at a 0.05 level of significance. The results revealed that there is a high level of prevalence of over-schooling of preschoolers in Kwara Central. Also, there is a significant difference in teachers' perception of the prevalence of over-schooling preschoolers based on school type and school location. It was concluded that both private and public schools in Kwara Central practice over-schooling of preschoolers at a high level. Hence, it was recommended that the government, through the State and/or Federal Ministry of Education, should enact and enforce a law that would ensure children in this category spend only the stipulated time in school as well as strict adherence to the recommended curriculum contents by proprietors and teachers.

Keywords: over-schooling, preschoolers, school type, school location

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Authors: Fernanda Bravo Cornejo, Camilo Cerda Sarabia, Belén Díaz Díaz, Diego Santibañez Oyarce, Esteban Gómez Terán, Hugo Osses Prado, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Streptococcus pyogenes is a gram-positive bacteria involved in a wide range of diseases and is a major-human-specific bacterial pathogen. In Chile, this year the 'Ministerio de Salud' declared an alert due to the increase in strains throughout the year. This increase can be attributed to the multitude of factors including antimicrobial resistance (AMR) and Virulence Factors (VF). Understanding these VF and AMR is crucial for developing effective strategies and improving public health responses. Moreover, experimental identification and characterization of these pathogenic mechanisms are labor-intensive and time-consuming. Therefore, new computational methods are required to provide robust techniques for accelerating this identification. Advances in Machine Learning (ML) algorithms represent the opportunity to refine and accelerate the discovery of VF associated with Streptococcus pyogenes. In this work, we evaluate the accuracy of various machine learning models in predicting the virulence factors and antimicrobial resistance of Streptococcus pyogenes, with the objective of providing new methods for identifying the pathogenic mechanisms of this organism.Our comprehensive approach involved the download of 32,798 genbank files of S. pyogenes from NCBI dataset, coupled with the incorporation of data from Virulence Factor Database (VFDB) and Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. These datasets provided labeled examples of both virulent and non-virulent genes, enabling a robust foundation for feature extraction and model training. We employed preprocessing, characterization and feature extraction techniques on primary nucleotide/amino acid sequences and selected the optimal more for model training. The feature set was constructed using sequence-based descriptors (e.g., k-mers and One-hot encoding), and functional annotations based on database prediction. The ML models compared are logistic regression, decision trees, support vector machines, neural networks among others. The results of this work show some differences in accuracy between the algorithms, these differences allow us to identify different aspects that represent unique opportunities for a more precise and efficient characterization and identification of VF and AMR. This comparative analysis underscores the value of integrating machine learning techniques in predicting S. pyogenes virulence and AMR, offering potential pathways for more effective diagnostic and therapeutic strategies. Future work will focus on incorporating additional omics data, such as transcriptomics, and exploring advanced deep learning models to further enhance predictive capabilities.

Keywords: antibiotic resistance, streptococcus pyogenes, virulence factors., machine learning

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Authors: Dena A. Hussain

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The objective of this project is to design an Information and Communication Technologies (ICT) tool based on a standardized platform to assist the work-integrated learning process of caretakers of disabled children. The tool should assist the intercommunication between caretakers and improve the learning process through knowledge bridging between all involved caretakers. Some children are born with disabilities while others have special needs after an illness or accident. Special needs children often need help in their learning process and require tools and services in a different way. In some cases the child has multiple disabilities that affect several capabilities in different ways. These needs are to be transformed into different learning techniques that the staff or personal (called caretakers in this project) caring for the child needs to learn and adapt. The caretakers involved are also required to learn new learning or training techniques and utilities specialized for the child’s needs. In many cases the number of people caring for the child’s development is rather large; the parents, specialist pedagogues, teachers, therapists, psychologists, personal assistants, etc. Each group of specialists has different objectives and in some cases the merge between theses specifications is very unique. This makes the synchronization between different caretakers difficult, resulting often in low level cooperation. By better intercommunication between professions both the child’s development could be improved but also the caretakers’ methods and knowledge of each other’s work processes and their own profession. This introduces a unique work integrated learning environment for all personnel involve, merging learning and knowledge in the work environment and at the same time assist the children’s development process. Creating an iterative process generates a unique learning experience for all involved. Using a work integrated platform will help encourage and support the process of all the teams involved in the process.We believe that working with children who have special needs is a continues learning/working process that is always integrated to achieve one main goal, which is to make a better future for all children.

Keywords: information and communication technologies (ICT), work integrated learning (WIL), sustainable learning, special needs children

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Authors: Ani Demetrashvili

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As online learning continues to reshape the landscape of education, questions arise regarding its efficacy for diverse learning styles, particularly for visual learners. This abstract delves into the impact of online learning on visual learners, exploring how digital mediums influence their educational experience and how educational platforms can be optimized to cater to their needs. Visual learners comprise a significant portion of the student population, characterized by their preference for visual aids such as diagrams, charts, and videos to comprehend and retain information. Traditional classroom settings often struggle to accommodate these learners adequately, relying heavily on auditory and written forms of instruction. The advent of online learning presents both opportunities and challenges in addressing the needs of visual learners. Online learning platforms offer a plethora of multimedia resources, including interactive simulations, virtual labs, and video lectures, which align closely with the preferences of visual learners. These platforms have the potential to enhance engagement, comprehension, and retention by presenting information in visually stimulating formats. However, the effectiveness of online learning for visual learners hinges on various factors, including the design of learning materials, user interface, and instructional strategies. Research into the impact of online learning on visual learners encompasses a multidisciplinary approach, drawing from fields such as cognitive psychology, education, and human-computer interaction. Studies employ qualitative and quantitative methods to assess visual learners' preferences, cognitive processes, and learning outcomes in online environments. Surveys, interviews, and observational studies provide insights into learners' preferences for specific types of multimedia content and interactive features. Cognitive tasks, such as memory recall and concept mapping, shed light on the cognitive mechanisms underlying learning in digital settings. Eye-tracking studies offer valuable data on attentional patterns and information processing during online learning activities. The findings from research on the impact of online learning on visual learners have significant implications for educational practice and technology design. Educators and instructional designers can use insights from this research to create more engaging and effective learning materials for visual learners. Strategies such as incorporating visual cues, providing interactive activities, and scaffolding complex concepts with multimedia resources can enhance the learning experience for visual learners in online environments. Moreover, online learning platforms can leverage the findings to improve their user interface and features, making them more accessible and inclusive for visual learners. Customization options, adaptive learning algorithms, and personalized recommendations based on learners' preferences and performance can enhance the usability and effectiveness of online platforms for visual learners.

Keywords: online learning, visual learners, digital education, technology in learning

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Authors: Cath Grimley, Debra Bick, Sarah Hillman, Louise Clarke, Helen Atherton, Jo Parsons

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The problem: Women in the UK are offered influenza (flu), pertussis (whooping cough) and COVID-19 vaccinations during their pregnancy but uptake of all three vaccines is below the desired rate. These vaccines are offered during pregnancy as pregnant women are at an increased risk of hospitalisation, morbidity, and mortality from these illnesses. Exposure to these diseases during pregnancy can also have a negative impact on the unborn baby with an increased risk of serious complications both while in utero and following birth. The research aims to explore perceptions about the vaccinations offered in pregnancy both from the perspectives of pregnant women and midwives. To determine factors that influence pregnant women’s decisions about whether or not to accept the vaccines following the Covid-19 pandemic and to explore midwives’ experiences of recommending and delivering vaccines. The approach: This research follows a qualitative design involving semi-structured interviews with pregnant women and midwives in the UK. Interviews with midwives explored vaccination discussions they routinely have with pregnant women and identified some of the barriers to vaccination that pregnant women discuss with them. Interviews with pregnant women explored their views since the COVID-19 pandemic about vaccinations offered during pregnancy, and whether the pandemic has influenced perceptions of vulnerability to illness in pregnant women. Midwives were recruited via participating hospitals and midwife specific social media groups. Pregnant women were recruited via participating hospitals and community groups. All interviews were conducted remotely (using telephone or Microsoft Teams) and analysed using thematic analysis. Findings: 43 pregnant women and 16 midwives were recruited and interviewed. The findings presented here will focus on data from midwives. Topics identified included three key themes for midwives. These were 1) Delivery of vaccinations which includes the convenience of offering vaccinations while attending standard antenatal appointments and practical barriers faced in delivering these vaccinations at hospital. 2) Messages and guidance included the importance of up-to-date informational needs for midwives to deliver vaccines and that uncertainty and conflicting messages about the COVID-19 vaccine during pregnancy were a barrier to delivery. 3) Recommendations to have vaccines look at all aspects of recommendations such as how recommendations are communicated, the contents of the recommendation, the importance of the vaccine and the impact of those recommendations on whether women accept the vaccine. Implications: Findings highlight the importance for midwives to receive clear and consistent information so they can feel confident in relaying this information while recommending and delivering vaccines to pregnant women. Emphasising why vaccines are important when recommending vaccinations to pregnant women in addition to standard information on the availability and timing will add to the strength and impact of that recommendation in helping women to make informed decisions about accepting vaccines. The findings of this study will inform the development of an intervention to increase vaccination uptake amongst pregnant women.

Keywords: vaccination, pregnancy, qualitative, interviews, Covid-19, midwives

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