Search results for: multiple data

Authors: Hamed Zolfaghari, Mojtaba Kord

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After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

Procedia PDF Downloads 97

Authors: Zunnu Raen Akhtar

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Brevicoryne brassicae, aphid feeds on cabbage and Brassica sp. as preferred host. Brassica plants usually ripen when maize starts growing in multiple cropping systems. Experiment was conducted to observe suitability of B. brassicae by rearing it on maize as host. In a tritrophic eco-system, predator coccinellids can be found in the fields of brassica and maize. This experiment emphasized on issue of aphids growing incidence in a cropping system. Brassica is sown and harvested earlier than maize and is attacked by aphids, while maize is also attacked by aphids. Five mortality tests were conducted of B. brassicae fed on maize. Out of five mortality tests, 3 tests were conducted using 1st instar, while in two mortality tests, 2nd instars of aphids were used. Mortality tests revealed that first instar mortality was quite high on the second day, while in second instar larvae mortality was delayed up to third to the fourth day. These experiments reveal that aphids can use maize as substitute host at later instars as compared to young ones. These experiments can be foundation for studying further crop-insect interaction and sampling techniques used for this purpose.

Keywords: host suitability, B. brassicae, maize, tritrophic interaction

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Authors: Luvisa Kusuma, Panji Yudha Prakasa

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Cloud storage, as a subservice of infrastructure as a service (IaaS) in Cloud Computing, is the model of nerworked storage where data can be stored in server. In this paper, we propose a secure cloud storage system consisting of two main components; client as a user who uses the cloud storage service and server who provides the cloud storage service. In this system, we propose the protocol schemes to guarantee against security attacks in the data transmission. The protocols are login protocol, upload data protocol, download protocol, and push data protocol, which implement hybrid cryptographic mechanism based on data encryption before it is sent to the cloud, so cloud storage provider does not know the user's data and cannot analysis user’s data, because there is no correspondence between data and user.

Keywords: cloud storage, security, cryptographic protocol, artificial intelligence

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Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

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Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

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Authors: Raya Al Khayari, Rasha Al Jassim, Muna Al Balushi, Fatma Al Moqbali, Said El Hajjar

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This study utilizes linear regression analysis to investigate the correlation between user account passwords and the probability of civil ID exposure, offering statistical insights into civil ID security. The study employs multiple linear regression (MLR) analysis to further investigate the elements that influence consumers’ views of civil ID security. This aims to increase awareness and improve preventive measures. The results obtained from the MLR analysis provide a thorough comprehension and can guide specific educational and awareness campaigns aimed at promoting improved security procedures. In summary, the study’s results offer significant insights for improving existing security measures and developing more efficient tactics to reduce risks related to civil ID security in Oman. By identifying key factors that impact consumers’ perceptions, organizations can tailor their strategies to address vulnerabilities effectively. Additionally, the findings can inform policymakers on potential regulatory changes to enhance civil ID security in the country.

Keywords: civil-id disclosure, awareness, linear regression, multiple regression

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Authors: Winnie Wing Mui So, Yu Chen

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This study investigated primary school teachers’ and students’ perceptions of science learning in an e-learning environment. This study used a multiple case study design and involved eight science teachers and their students from four Hong Kong primary schools. The science topics taught included ‘season and weather’ ‘force and movement’, ‘solar and lunar eclipse’ and ‘living things and habitats’. Data were collected through lesson observations, interviews with teachers, and interviews with students. Results revealed some differences between the teachers’ and the students’ perceptions regarding the usefulness of e-learning resources, the organization of student-centred activities, and the impact on engagement and interactions in lessons. The findings have implications for the more effective creation of e-learning environments for science teaching and learning in primary schools.

Keywords: e-learning, science education, teacher' and students' perceptions, primary schools

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Authors: Vahid Rashedi, Banafsheh Ebrahimi, Mahtab Sharif Mohseni, Mohammadali Hosseini

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Introduction: One of the metrics used to evaluate health status is life expectancy. This index alters as people age as a result of several events, illnesses, stress, and anxiety. One of the issues that might develop into a lethal phobia is death anxiety. This study looked at older persons in Tehran, Iran, to see if there was any correlation between life expectancy and fear of dying. Methods: Cluster random sampling was used to select 208 older persons (age 60) who had been sent to adult daycare facilities in Tehran for this correlational descriptive study. A demographic questionnaire, Temper's death anxiety scale, and Snyder's life expectancy scale were used to gather the data. Statistical Package for the Social Sciences softwear version 22 was used to conduct the data analysis. Results: The average age of the senior citizens was 66.60 (6.58) years. With a mean life expectancy of 24.94, it was discovered that the average death anxiety was 12.21. Additionally, Pearson's correlation coefficient demonstrated a bad correlation between fear of dying and life expectancy. Age, residential status, and death fear were the three primary predictors of a decline in life expectancy, according to multiple regression analysis. Conclusion: The findings suggest that there is a link between death fear and a lower life expectancy, which calls for the use of appropriate strategies to increase older individuals' life expectancies as well as the teaching of anxiety coping mechanisms.

Keywords: aged, frailty, death, anxiety, life

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Authors: Carlos Huertas, Reyes Juarez-Ramirez

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Public health is one of the most critical issues today; therefore, there is great interest to improve technologies in the area of diseases detection. With machine learning and feature selection, it has been possible to aid the diagnosis of several diseases such as cancer. In this work, we present an extension to the Heat Map Based Feature Selection algorithm, this modification allows automatic threshold parameter selection that helps to improve the generalization performance of high dimensional data such as mass spectrometry. We have performed a comparison analysis using multiple cancer datasets and compare against the well known Recursive Feature Elimination algorithm and our original proposal, the results show improved classification performance that is very competitive against current techniques.

Keywords: biomarker discovery, cancer, feature selection, mass spectrometry

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Authors: Abdeljalil Metioui

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The purpose of this article is to present the results of two-stage qualitative research. The first involved the identification of the alternative conceptions of 80 elementary pre-service teachers from Quebec in Canada about the operation of simple electrical circuits. To do this, they completed a two-choice questionnaire (true or false) with justification. Data analysis identifies many conceptual difficulties. For example, for their majority, whatever the electrical device that composes an electrical circuit, the current source (power supply), and the generated electrical power is constant. The second step was to develop a double multiple-choice questionnaire based on the identified designs. It allows teachers to quickly diagnose their students' conceptions and take them into account in their teaching.

Keywords: development, electrical circuits, two-tier diagnostic test, secondary and high school

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Authors: Junjun Chen, Yingxiu Li

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The occupational well-being of school principals has played a vital role in the pursuit of individual and school wellness and success. However, principals’ well-being worldwide is under increasing threat because of the challenging and complex nature of their work and growing demands for school standardisation and accountability. Pressure is particularly acute in the post-pandemicfuture as principals attempt to deal with the impact of the pandemic on top of more regular demands. This is particularly true in Hong Kong, as school principals are increasingly wedged between unparalleled political, social, and academic responsibilities. Recognizing the semantic breadth of well-being, scholars have not determined a single, mutually agreeable definition but agreed that the concept of well-being has multiple dimensions across various disciplines. The multidimensional approach promises more precise assessments of the relationships between well-being and other concepts than the ‘affect-only’ approach or other single domains for capturing the essence of principal well-being. The multiple-dimension well-being concept is adopted in this project to understand principal well-being in this study. This study aimed to understand the situation of principal well-being and its influential drivers with a sample of 670 principals from Hong Kong and Mainland China. An online survey was sent to the participants after the breakout of COVID-19 by the researchers. All participants were well informed about the purposes and procedure of the project and the confidentiality of the data prior to filling in the questionnaire. Confirmatory factor analysis and structural equation modelling performed with Mplus were employed to deal with the dataset. The data analysis procedure involved the following three steps. First, the descriptive statistics (e.g., mean and standard deviation) were calculated. Second, confirmatory factor analysis (CFA) was used to trim principal well-being measurement performed with maximum likelihood estimation. Third, structural equation modelling (SEM) was employed to test the influential factors of principal well-being. The results of this study indicated that the overall of principal well-being were above the average mean score. The highest ranking in this study given by the principals was to their psychological and social well-being (M = 5.21). This was followed by spiritual (M = 5.14; SD = .77), cognitive (M = 5.14; SD = .77), emotional (M = 4.96; SD = .79), and physical well-being (M = 3.15; SD = .73). Participants ranked their physical well-being the lowest. Moreover, professional autonomy, supervisor and collegial support, school physical conditions, professional networking, and social media have showed a significant impact on principal well-being. The findings of this study will potentially enhance not only principal well-being, but also the functioning of an individual principal and a school without sacrificing principal well-being for quality education in the process. This will eventually move one step forward for a new future - a wellness society advocated by OECD. Importantly, well-being is an inside job that begins with choosing to have wellness, whilst supports to become a wellness principal are also imperative.

Keywords: well-being, school principals, quantitative, influential factors

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Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

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Authors: Amanda Cristina da Silva Reis, Bruno Paulino Venâncio, Cristina Theada Ferreira, Andrea Fialho do Prado, Lucimara Guedes dos Santos, Aline de Souza Gravatá, Larissa Lima Gonçalves, Isabella Aparecida Ferreira Moretto, João Carlos Ferrari Corrêa, Fernanda Ishida Corrêa

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Objective: To compare two protocols of Transcranial Magnetic Stimulation (TMS) on quadriceps muscle spasticity in individuals diagnosed with Multiple Sclerosis (MS). Method: Clinical, crossover study, in which six adult individuals diagnosed with MS and spasticity in the lower limbs were randomized to receive one session of high-frequency (≥5Hz) and low-frequency (≤ 1Hz) TMS on motor cortex (M1) hotspot for quadriceps muscle, with a one-week interval between the sessions. To assess the spasticity was applied the Ashworth scale and were analyzed the latency time (ms) of the motor evoked potential (MEP) and the central motor conduction time (CMCT) of the bilateral quadriceps muscle. Assessments were performed before and after each intervention. The difference between groups was analyzed using the Friedman test, with a significance level of 0.05 adopted. Results: All statistical analyzes were performed using the SPSS Statistic version 26 programs, with a significance level established for the analyzes at p<0.05. Shapiro Wilk normality test. Parametric data were represented as mean and standard deviation for non-parametric variables, median and interquartile range, and frequency and percentage for categorical variables. There was no clinical change in quadriceps spasticity assessed using the Ashworth scale for the 1 Hz (p=0.813) and 5 Hz (p= 0.232) protocols for both limbs. Motor Evoked Potential latency time: in the 5hz protocol, there was no significant change for the contralateral side from pre to post-treatment (p>0.05), and for the ipsilateral side, there was a decrease in latency time of 0.07 seconds (p<0.05 ); for the 1Hz protocol there was an increase of 0.04 seconds in the latency time (p<0.05) for the contralateral side to the stimulus, and for the ipsilateral side there was a decrease in the latency time of 0.04 seconds (p=<0.05), with a significant difference between the contralateral (p=0.007) and ipsilateral (p=0.014) groups. Central motor conduction time in the 1Hz protocol, there was no change for the contralateral side (p>0.05) and for the ipsilateral side (p>0.05). In the 5Hz protocol for the contralateral side, there was a small decrease in latency time (p<0.05) and for the ipsilateral side, there was a decrease of 0.6 seconds in the latency time (p<0.05) with a significant difference between groups (p=0.019). Conclusion: A high or low-frequency session does not change spasticity, but it is observed that when the low-frequency protocol was performed, there was an increase in latency time on the stimulated side, and a decrease in latency time on the non-stimulated side, considering then that inhibiting the motor cortex increases cortical excitability on the opposite side.

Keywords: multiple sclerosis, spasticity, motor evoked potential, transcranial magnetic stimulation

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Authors: B. X. Tchomeni, A. A. Alugongo, L. M. Masu

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This paper presents a 4-DOF nonlinear model of a cracked of Laval rotor established based on Energy Principles. The model has been used to simulate coupled torsional-lateral response of the cracked rotor stator-system with multiple parametric excitations, namely, rotor-stator-rub, a breathing transverse crack, unbalanced mass, and an axial force. Nonlinearity due to a “breathing” crack is incorporated by considering a simple hinge model which is suitable for small breathing crack. The vibration response of a cracked rotor passing through its critical speed with rotor-stator interaction is analyzed, and an attempt for crack detection and monitoring explored. Effects of unbalanced eccentricity with phase and acceleration are investigated. By solving the motion equations, steady-state vibration response is obtained in presence of several rotor faults. The presence of a crack is observable in the power spectrum despite the excitation by the axial force and rotor-stator rub impact. Presented results are consistent with existing literature and could be adopted into rotor condition monitoring strategies

Keywords: rotor, crack, rubbing, axial force, non linear

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Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

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This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

Procedia PDF Downloads 362

Authors: Marjeta Misigoj Durakovic, Maroje Soric, Lovro Stefan

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Background and aim: Physical inactivity has been linked with increased morbidity and premature mortality and adolescence has been recognised as the critical period for a decline in physical activity (PA) level. In order to properly direct interventions aimed at increasing PA, high-risk groups of individuals should be identified. Therefore, the aim of this study is to describe gender differences in: a) PA level; b) weekly PA patterns. Methods: This investigation is a part of the CRO-PALS study which is an on-going longitudinal study conducted in a representative sample of urban youth in Zagreb (Croatia). CRO-PALS involves 903 adolescents and for the purpose of this study data from a subgroup of 190 participants with information on objective PA level were analysed (116 girls; mean age [SD]=15.6[0.3] years). Duration of moderate and vigorous PA was measured during 5 consecutive by a multiple-sensor physical activity monitor (SenseWear Armband, BodyMedia inc., Pittsburgh, USA). Gender differences in PA level were evaluated using independent samples t-test. Differences in school week and weekend levels of activity were assessed using mixed ANOVA with gender as between-subjects factor. The amount of vigorous PA had to be log-transformed to achieve normality in the distribution. Results: Boys were more active than girls. Duration of moderate-to-vigorous PA averaged 111±44 min/day in boys and 80±38 min/day in girls (mean difference=31 min/day, 95%CI=20-43 min/day). Vigorous PA was 2.5 times higher in boys compared to girls (95%CI=1.9-3.5). Participants were more active during school days than on weekends. The magnitude of the difference in moderate-to-vigorous PA was similar in both gender (p value for time*gender interaction = 0.79) and averaged 19 min/day (95%CI=11-27 min/day). Similarly, vigorous PA was 36% lower on weekends compared with school days (95%CI=22-46%) with no gender difference (p value for time*gender interaction = 0.52). Conclusion: PA level was higher in boys than in girls throughout the week. Still, in both boys and girls, the amount of PA reduced markedly on weekends compared with school days.

Keywords: adolescence, multiple-sensor physical activity monitor, physical activity level, weekly physical activity pattern

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Authors: W. Hashim, H. Burok, N. Ghazaly, H. Ahmad Nasir, N. Mohamad Anas, A. F. Ismail, K. L. Yau

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Future communication networks require devices that are able to work on a single platform but support heterogeneous operations which lead to service diversity and functional flexibility. This paper proposes two cognitive mechanisms termed cognitive hybrid function which is applied in multiple broadband user terminals in order to maintain reliable connectivity and preventing unnecessary interferences. By employing such mechanisms especially for future hyper-dense network, we can observe their performances in terms of optimized speed and power saving efficiency. Results were obtained from several empirical laboratory studies. It was found that selecting reliable network had shown a better optimized speed performance up to 37% improvement as compared without such function. In terms of power adjustment, our evaluation of this mechanism can reduce the power to 5dB while maintaining the same level of throughput at higher power performance. We also discuss the issues impacting future telecommunication standards whenever such devices get in place.

Keywords: dense network, intelligent network selection, multiple networks, transmit power adjustment

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Authors: Frederic Jumelle, Kelvin So, Didan Deng

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In this paper, we are introducing a model of artificial general intelligence (AGI), the functional neural network (FNN), for modeling human decision-making processes. The FNN is composed of multiple artificial mirror neurons (AMN) racing in the network. Each AMN has a similar structure programmed independently by the users and composed of an intention wheel, a motor core, and a sensory core racing at a specific velocity. The mathematics of the node’s formulation and the racing mechanism of multiple nodes in the network will be discussed, and the group decision process with fuzzy logic and the transformation of these conceptual methods into practical methods of simulation and in operations will be developed. Eventually, we will describe some possible future research directions in the fields of finance, education, and medicine, including the opportunity to design an intelligent learning agent with application in AGI. We believe that FNN has a promising potential to transform the way we can compute decision-making and lead to a new generation of AI chips for seamless human-machine interactions (HMI).

Keywords: neural computing, human machine interation, artificial general intelligence, decision processing

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Authors: Norman Sinnigen, Igor Izyurov, Marina Krylova, Hamidreza Jamalabadi, Sarah Alizadeh, Martin Walter

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Background: EEG is a non-invasive brain activity recording technique with a high temporal resolution that allows the use of real-time applications, such as neurofeedback. However, EEG data are susceptible to electrooculographic (EOG) and electromyography (EMG) artifacts (i.e., jaw clenching, teeth squeezing and forehead movements). Due to their non-stationary nature, these artifacts greatly obscure the information and power spectrum of EEG signals. Many EEG artifact correction methods are too time-consuming when applied to low-density EEG and have been focusing on offline processing or handling one single type of EEG artifact. A software-only real-time method for correcting multiple types of EEG artifacts of high-density EEG remains a significant challenge. Methods: We demonstrate an improved approach for automatic real-time EEG artifact correction of EOG and EMG artifacts. The method was tested on three healthy subjects using 64 EEG channels (Brain Products GmbH) and a sampling rate of 1,000 Hz. Captured EEG signals were imported in MATLAB with the lab streaming layer interface allowing buffering of EEG data. EMG artifacts were detected by channel variance and adaptive thresholding and corrected by using channel interpolation. Real-time independent component analysis (ICA) was applied for correcting EOG artifacts. Results: Our results demonstrate that the algorithm effectively reduces EMG artifacts, such as jaw clenching, teeth squeezing and forehead movements, and EOG artifacts (horizontal and vertical eye movements) of high-density EEG while preserving brain neuronal activity information. The average computation time of EOG and EMG artifact correction for 80 s (80,000 data points) 64-channel data is 300 – 700 ms depending on the convergence of ICA and the type and intensity of the artifact. Conclusion: An automatic EEG artifact correction algorithm based on channel variance, adaptive thresholding, and ICA improves high-density EEG recordings contaminated with EOG and EMG artifacts in real-time.

Keywords: EEG, muscle artifacts, ocular artifacts, real-time artifact correction, real-time ICA

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Authors: Diksha Kadam

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The study of images of women in literature and women writers has been a significant area of concern for the last four decades because it is as ‘the study of signification and meaning production’ play a vital role in shaping the perceptions and consciousness of various segment of society in relation to the lives, roles, problems and experiences of different categories of women as women and as autonomous citizen of society. In the history of worlds English literature the status of women and representation of her in the writings is an issue of discussion always. The essence of her existence in the literature is felt; the ecstasy of her feelings is always seen. The literature is full of facts and figures. She is one of them. Her contribution to the literature is undoubtedly a beginning of a new era. Multiple challenges and multiple identities as represented in majority of the literary texts and in real provide much hope and assurance to the new generation of mothers and daughters in the direction of transformation of the individual and collective consciousness of society paving way for the emergence of an actually empowered new woman. This paper will focus on some of the prominent Indian and American women writers in English literature and the various dimensions of her image through some of the prominent works. This attempt of mine will be merely a salute to those women who have struggled to prove their identity as one of the members of society.

Keywords: role of women’s writing, new era, contribution to the literature, consciousness, existence

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Authors: Ippei Kamihira, Takashi Nakajima, Taiyo Matsumura, Hikaru Miura, Takashi Ono

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In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy). Using this information to judge such conditions as a bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as 'normal' when the person was in a good physical condition or as 'abnormal' when the person was in a bad physical condition.

Keywords: sensors, elderly living alone, abnormality detection, iifestyle habit

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Authors: Carol Leroy

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This presentation focuses on the analysis qualitative case studies in the graduate education of reading specialists. The presentation describes the development and application of an integrated conceptual framework for reading specialist education, drawing on Robert Stake’s work on case study research, Kenneth Zeichner’s work on professional learning, and various tools for reading assessment (e.g. the Qualitative Reading Inventory). Social constructivist theory is used to provide intersecting links between the various influences on the processes used to assess and teaching reading within the case study framework. Illustrative examples are described to show the application of the framework in reading specialist education in a teaching clinic at a large urban university. Central to education of reading specialists in this teaching clinic is the collection, analysis and interpretation of data for the design and implementation of reading and writing programs for struggling readers and writers. The case study process involves the integrated interpretation of data, which is central to qualitative case study inquiry. An emerging theme in this approach to graduate education is the ambiguity and uncertainty that governs work with the adults and children who attend the clinic for assistance. Tensions and contradictions are explored insofar as they reveal overlapping but intersecting frameworks for case study analysis in the area of literacy education. An additional theme is the interplay of multiple layers of data with a resulting depth that goes beyond the practical need of the client and toward the deeper pedagogical growth of the reading specialist. The presentation makes a case for the value of qualitative case studies in reading specialist education. Further, the use of social constructivism as a unifying paradigm provides a robustness to the conceptual framework as a tool for understanding the pedagogy that is involved.

Keywords: assessment, case study, professional education, reading

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Authors: Mohamed Elkholy, Ahmed Elfatatry

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Cloud computing has emerged as a flexible computing paradigm that reshaped the Information Technology map. However, cloud computing brought about a number of security challenges as a result of the physical distribution of computational resources and the limited control that users have over the physical storage. This situation raises many security challenges for data integrity and confidentiality as well as authentication and access control. This work proposes a security mechanism for data integrity that allows a data owner to be aware of any modification that takes place to his data. The data integrity mechanism is integrated with an extended Kerberos authentication that ensures authorized access control. The proposed mechanism protects data confidentiality even if data are stored on an untrusted storage. The proposed mechanism has been evaluated against different types of attacks and proved its efficiency to protect cloud data storage from different malicious attacks.

Keywords: access control, data integrity, data confidentiality, Kerberos authentication, cloud security

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Authors: Issam Aouari, Abdelmalek Abdelhamid

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For seismologists, the characterization of seismic demand should include the amplitude and duration of strong shaking in the system. The duration of ground shaking is one of the key parameters in earthquake resistant design of structures. This paper proposes a nonlinear statistical model to estimate earthquake ground motion duration in soft soils using multiple seismicity indicators. Three definitions of ground motion duration proposed by literature have been applied. With a comparative study, we select the most significant definition to use for predict the duration. A stochastic model is presented for the McCann and Shah Method using nonlinear regression analysis based on a data set for moment magnitude, source to site distance and site conditions. The data set applied is taken from PEER strong motion databank and contains shallow earthquakes from different regions in the world; America, Turkey, London, China, Italy, Chili, Mexico...etc. Main emphasis is placed on soft site condition. The predictive relationship has been developed based on 600 records and three input indicators. Results have been compared with others published models. It has been found that the proposed model can predict earthquake ground motion duration in soft soils for different regions and sites conditions.

Keywords: duration, earthquake, prediction, regression, soft soil

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Authors: R. M. López-Gutiérrez, J. A. Michel-Macarty, H. Cervantes-De Avila, J. I. Nieto-Hipólito, C. Cruz-Hernández, L. Cardoza-Avendaño, S. Cortiant-Velez

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It is well know that mankind benefits from the application of robot control by virtual handlers in industrial environments. In recent years, great interest has emerged in the control of multiple robots in order to carry out collective tasks. One main trend is to copy the natural organization that some organisms have, such as, ants, bees, school of fish, birds’ migration, etc. Surely, this collaborative work, results in better outcomes than those obtain in an isolated or individual effort. This topic has a great drive because collaboration between several robots has the potential capability of carrying out more complicated tasks, doing so, with better efficiency, resiliency and fault tolerance, in cases such as: coordinate navigation towards a target, terrain exploration, and search-rescue operations. In this work, synchronization of multiple autonomous robots is shown over a variety of coupling topologies: star, ring, chain, and global. In all cases, collective synchronous behavior is achieved, in the complex networks formed with mobile robots. Nodes of these networks are modeled by a mass using Matlab to simulate them.

Keywords: robots, synchronization, bidirectional, coordinate navigation

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Authors: Yan Wang, Yasushi Asami, Yukio Sadahiro

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In urban context, urban nodes such as amenity or hazard will certainly affect house price, while classic hedonic analysis will employ distance variables measured from each urban nodes. However, effects from distances to facilities on house prices generally do not represent the true price of the property. Distance variables measured on the same surface are suffering a problem called multicollinearity, which is usually presented as magnitude variance and mean value in regression, errors caused by instability. In this paper, we provided a theoretical framework to identify and gather the data with less bias, and also provided specific sampling method on locating the sample region to avoid the spatial multicollinerity problem in three distance variable’s case.

Keywords: hedonic regression, urban node, distance variables, multicollinerity, collinearity

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Authors: Alaa G. M. Osman, Khaled Y. AbouelFadl, Angela Krüger, Werner Kloas

Abstract:

In Egypt, no previous records are available regarding possible multiple hormonal activities in the aquatic systems and especially the river Nile. In this paper, the in vitro yeast estrogen screen (YES) and yeast androgen screen (YAS) were used to assess the multiple hormonal activities in surface waters and sediment from the Egyptian river Nile for the first time. This study sought to determine if river Nile water caused changes in gonadal histology of Nile tilapia (Oreochromis niloticus niloticus). All water samples exhibited extremely low levels of estrogenicity. Estrogenicity was not detected nearly in any of the sediment samples. Unlike the estrogenicity, significant androgenic activities were recorded in the water and sediment samples along the Nile course. The present study reports for the first time quantified anti-estrogenic and anti-androgenic activities with high levels in both water and sediment of the river Nile. The greatest anti-estrogenic and anti-androgenic activities were observed in sample from downstream river Nile. These results indicated that the anti-estrogenic and anti-androgenic activities along the Nile course were great and the pollution of the sites at the downstream was more serious than the upstream sites due to industrial activities at theses sites. Good correlations were observed among some hormonal activities, suggesting coexistence of these contaminants in the environmental matrices. There were no signs of sexual disruption in any of the gonads analysed from either male or female Nile tilapia, demonstrating that any hormonal activity present along the Nile course was not sufficient to induce adverse effects on reproductive development. Further investiga¬tion is necessary to identify the chemicals responsible for the hormonal activities in the river Nile and to examine the effect of very low levels of hormonally active chemicals on gonadal histology, as well as in the development of more sensitive biomarkers.

Keywords: multiple hormonal activities, YES, YAS, river Nile, Nile tilapia, gonadal histology

Procedia PDF Downloads 483

Authors: Lin Yunuo, Seow Xing Quan, Burra Venkata Durga Kumar

Abstract:

In this modern era, the cloud operating system is the world trend applied in various industries such as business, healthy, etc. In order to deal with the large capacity of requirements in cloud computing, research come up with multi-tenant cloud computing to maximize the benefits of server providers and clients. However, there are still issues in multi-tenant cloud computing especially regarding resource allocation. Issues such as inefficient resource utilization, large latency, lack of scalability and elasticity and poor data isolation had caused inefficient resource allocation in multi-tenant cloud computing. Without a doubt, these issues prevent multitenancy reaches its best condition. In fact, there are multiple studies conducted to determine the optimal resource allocation to solve these problems these days. This article will briefly introduce the cloud operating system, Multi-tenant cloud computing and resource allocation in cloud computing. It then discusses resource allocation in multi-tenant cloud computing and the current challenges it faces. According to the issue ‘ineffective resource utilization’, we will discuss an efficient dynamic scheduling technique for multitenancy, namely Multi-tenant Dynamic Resource Scheduling Model (MTDRSM). Moreover, there also have some recommendations to improve the shortcoming of this model in this paper’s final section.

Keywords: cloud computing, cloud operation system, multitenancy, resource allocation, utilization of cloud resources

Procedia PDF Downloads 84

Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

Abstract:

At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

Procedia PDF Downloads 175

Authors: Nazura Abdul Manap, Siti Nur Farah Atiqah Salleh

Abstract:

For decades, the misuse of personal data has been a critical issue. Malaysia has accepted responsibility by implementing the Malaysian Personal Data Protection Act 2010 to secure personal data (PDPA 2010). After more than a decade, this legislation is set to be revised by the current PDPA 2023 Amendment Bill to align with the world's key personal data protection regulations, such as the European Union General Data Protection Regulations (GDPR). Among the other suggested adjustments is the Data User's appointment of a Data Protection Officer (DPO) to ensure the commercial entity's compliance with the PDPA 2010 criteria. The change is expected to be enacted in parliament fairly soon; nevertheless, based on the experience of the Personal Data Protection Department (PDPD) in implementing the Act, it is projected that there will be a slew of additional concerns associated with the DPO mandate. Consequently, the goal of this article is to highlight the issues that the DPO will encounter and how the Personal Data Protection Department should respond to this subject. The study result was produced using a qualitative technique based on an examination of the current literature. This research reveals that there are probable obstacles experienced by the DPO, and thus, there should be a definite, clear guideline in place to aid DPO in executing their tasks. It is argued that appointing a DPO is a wise measure in ensuring that the legal data security requirements are met.

Keywords: guideline, law, data protection officer, personal data

Procedia PDF Downloads 78