Search results for: communication patterns

Authors: Seo-Hee Kim, Kee-Won Kim, Seung-Hoon Kim

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The most important elements of a novel are the characters, events and background. The background represents the time, place and situation that character appears, and conveys event and atmosphere more realistically. If readers have the proper knowledge about background of novels, it may be helpful for understanding the atmosphere of a novel and choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels because spatio-temporal background especially performs an important role in historical novels among the genre of Korean novels. To the best of our knowledge, we could not find previous study that was aimed at Korean novels. In this paper, we build a Korean historical national dictionary. Our dictionary has historical places and temple names of kings over many generations as well as currently existing spatial words or temporal words in Korean history. We also present a method for recognizing spatio-temporal background based on patterns of phrasal words in Korean sentences. Our rules utilize postposition for spatial background recognition and temple names for temporal background recognition. The knowledge of the recognized background can help readers to understand the flow of events and atmosphere, and can use to visualize the elements of novels.

Keywords: data mining, Korean historical novels, Korean linguistic feature, spatio-temporal background

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Authors: Maryam Jabeen

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In recent times, there has been a notable surge in attention towards diverse literacy concepts such as media literacy, information literacy, and digital literacy. These concepts have garnered escalating interest, spurring the emergence of novel approaches, particularly in the aftermath of the Covid-19 crisis. However, amidst discussions of crises, the domain of crisis literacy remains largely uncharted within academic exploration. Crisis literacy, also referred to as disaster literacy, denotes an individual's aptitude to not only comprehend but also effectively apply information, enabling well-informed decision-making and adherence to instructions about disaster mitigation, preparedness, response, and recovery. This theoretical and descriptive study seeks to transcend foundational literacy concepts, underscoring the urgency for an in-depth exploration of crisis literacy and its interplay with the realm of media communication. Given the profound impact of the pandemic experience and the looming uncertainty of potential future crises, there arises a pressing need to elevate crisis literacy, or disaster literacy, towards heightened autonomy and active involvement within the spheres of critical disaster preparedness, recovery initiatives, and media communication domains. This research paper is part of my ongoing Ph.D. research study, which explores on a broader level the Encoding and decoding of media communications in relation to crisis literacy. The primary objective of this research paper is to expound upon a descriptive, theoretical research endeavor delving into this domain. The emphasis lies in highlighting the paramount significance of media communications in literacy of crisis, coupled with an accentuated focus on its role in providing information to marginalized populations amidst crises. In conclusion, this research bridges the gap in crisis literacy correlation to media communications exploration, advocating for a comprehensive understanding of its dynamics and its symbiotic relationship with media communications. It intends to foster a heightened sense of crisis literacy, particularly within marginalized communities, catalyzing proactive participation in disaster preparedness, recovery processes, and adept media interactions.

Keywords: covid-19, crisis literacy, crisis, marginalized, media and communications, pandemic, vulnerable people

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Authors: Sopheak Sorn, Kwok Yip Szeto

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Reliability is one of the important measures of how well the system meets its design objective, and mathematically is the probability that a complex system will perform satisfactorily. When the system is described by a network of N components (nodes) and their L connection (links), the reliability of the system becomes a network design problem that is an NP-hard combinatorial optimization problem. In this paper, we address the network design problem for a random point set’s pattern in two dimensions. We make use of a Voronoi construction with each cell containing exactly one point in the point pattern and compute the reliability of the Voronoi’s dual, i.e. the Delaunay graph. We further investigate the communicability of the Delaunay network. We find that there is a positive correlation and a negative correlation between the homogeneity of a Delaunay's degree distribution with its reliability and its communicability respectively. Based on the correlations, we alter the communicability and the reliability by performing random edge flips, which preserve the number of links and nodes in the network but can increase the communicability in a Delaunay network at the cost of its reliability. This transformation is later used to optimize a Delaunay network with the optimum geometric mean between communicability and reliability. We also discuss the importance of the edge flips in the evolution of real soap froth in two dimensions.

Keywords: Communicability, Delaunay triangulation, Edge Flip, Reliability, Two dimensional network, Voronio

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Authors: Eman Alzahrani

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Efficient extraction of proteins by removing interfering materials is necessary in proteomics, since most instruments cannot handle such contaminated sample matrices directly. In this study, chitosan-coated magnetic nanoparticles (CS-MNPs) for purification of myoglobin were successfully fabricated. First, chitosan (CS) was prepared by a deacetylation reaction during its extraction from shrimp-shell waste. Second, magnetic nanoparticles (MNPs) were synthesised, using the coprecipitation method, from aqueous Fe2+ and Fe3+ salt solutions by the addition of a base under an inert atmosphere, followed by modification of the surface of MNPs with chitosan. The morphology of the formed nanoparticles, which were about 23 nm in average diameter, was observed by transmission electron microscopy (TEM). In addition, nanoparticles were characterised using X-ray diffraction patterns (XRD), which showed the naked magnetic nanoparticles have a spinel structure and the surface modification did not result in phase change of the Fe3O4. The coating of MNPs was also demonstrated by scanning electron microscopy (SEM) analysis, energy dispersive analysis of X-ray spectroscopy (EDAX), and Fourier transform infrared (FT-IR) spectroscopy. The adsorption behaviour of MNPs and CS-MNPs towards myoglobin was investigated. It was found that the difference in adsorption capacity between MNPs and CS-MNPs was larger for CS-MNPs. This result makes CS-MNPs good adsorbents and attractive for using in protein extraction from biological samples.

Keywords: chitosan, magnetic nanoparticles, coprecipitation, adsorption

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Authors: Mehdi Naserian, Mohammad Jooshaki, Mahmud Fotuhi-Firuzabad, Mohammad Hossein Mohammadi Sanjani, Ashknaz Oraee

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In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a recent solution is presented to uncover consumers with high air conditioner demand among large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: communication infrastructure, smart meters, power systems, HVAC system, residential HVAC systems

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Authors: Ramovatar, Neeraj Panwar

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Lead free Ba₀.₉₈Ca₀.₀₂SnxTi₁₋ₓO₃ (x = 0.01 and 0.05 mole %) ferroelectric ceramics have been synthesized by the solid-state reaction method with sintering at 1400 °C for 2 h. The room temperature x-ray diffraction (XRD) patterns identified the tetragonal phase for x = 0.01 composition whereas co-existence of tetragonal and orthorhombic phases for x =0.05 composition. Raman spectroscopy results corroborated with the XRD results at room temperature. The maximum dielectric properties (ɛm ~ 8591, tanδ ~ 0.018) were obtained for the compound with x = 0.01 at 5 kHz. Further, the tetragonal to cubic (TC) transition temperature was observed at 122 °C and 102 °C for the ceramics with x =0.01 and x = 0.05, respectively. The temperature dependent P-E loops also revealed the existence of TC at these particular temperature values. The energy storage density (Ed) of both compounds was calculated from room temperature P – E loops at an applied electric field of 20 kV/cm. The maximum Ed ~ 224 kJ/m³ was achieved for the sample with x = 0.01 as compared to 164 kJ/m³ for the x =0.05 composition. The value of Ed is comparable to other BaTiO₃ based lead free ferroelectric systems. Impedance spectroscopy analysis exhibited the bulk and grain boundary contributions above 300 °C under the frequency range 100 Hz to 1 MHz. The above properties make these ceramics suitable for energy storage devices.

Keywords: dielectric properties, energy storage properties, impedance spectroscopy, lead free ceramics

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Authors: A. El Hamdouni, J. Zbitou, A. Tajmouati, L. El Abdellaoui, A. Errkik, A. Tribak, M. Latrach

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This paper presents a novel fractal antenna structure proposed for UWB (Ultra – Wideband) applications. The frequency band 3.1-10.6 GHz released by FCC (Federal Communication Commission) as the commercial operation of UWB has been chosen as frequency range for this antenna based on coplanar waveguide (CPW) feed and circular shapes fulfilled according to fractal geometry. The proposed antenna is validated and designed by using an FR4 substrate with overall area of 34 x 43 mm2. The simulated results performed by CST-Microwave Studio and compared by ADS (Advanced Design System) show good matching input impedance with return loss less than -10 dB between 2.9 GHz and 11 GHz.

Keywords: Fractal antenna, Fractal Geometry, CPW Feed, UWB, FCC

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Authors: Chung-Ming Lo, Chung-Chien Lee

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In many countries, the lifetime prevalence of shoulder pain is up to 70%. In America, the health care system spends 7 billion per year about the healthy issues of shoulder pain. With respect to the origin, up to 70% of shoulder pain is attributed to rotator cuff lesions This study proposed a computer-aided diagnosis (CAD) system to assist radiologists classifying rotator cuff lesions with less operator dependence. Quantitative features were extracted from the shoulder ultrasound images acquired using an ALOKA alpha-6 US scanner (Hitachi-Aloka Medical, Tokyo, Japan) with linear array probe (scan width: 36mm) ranging from 5 to 13 MHz. During examination, the postures of the examined patients are standard sitting position and are followed by the regular routine. After acquisition, the shoulder US images were drawn out from the scanner and stored as 8-bit images with pixel value ranging from 0 to 255. Upon the sonographic appearance, the boundary of each lesion was delineated by a physician to indicate the specific pattern for analysis. The three lesion categories for classification were composed of 20 cases of tendon inflammation, 18 cases of calcific tendonitis, and 18 cases of supraspinatus tear. For each lesion, second-order statistics were quantified in the feature extraction. The second-order statistics were the texture features describing the correlations between adjacent pixels in a lesion. Because echogenicity patterns were expressed via grey-scale. The grey-scale co-occurrence matrixes with four angles of adjacent pixels were used. The texture metrics included the mean and standard deviation of energy, entropy, correlation, inverse different moment, inertia, cluster shade, cluster prominence, and Haralick correlation. Then, the quantitative features were combined in a multinomial logistic regression classifier to generate a prediction model of rotator cuff lesions. Multinomial logistic regression classifier is widely used in the classification of more than two categories such as the three lesion types used in this study. In the classifier, backward elimination was used to select a feature subset which is the most relevant. They were selected from the trained classifier with the lowest error rate. Leave-one-out cross-validation was used to evaluate the performance of the classifier. Each case was left out of the total cases and used to test the trained result by the remaining cases. According to the physician’s assessment, the performance of the proposed CAD system was shown by the accuracy. As a result, the proposed system achieved an accuracy of 86%. A CAD system based on the statistical texture features to interpret echogenicity values in shoulder musculoskeletal ultrasound was established to generate a prediction model for rotator cuff lesions. Clinically, it is difficult to distinguish some kinds of rotator cuff lesions, especially partial-thickness tear of rotator cuff. The shoulder orthopaedic surgeon and musculoskeletal radiologist reported greater diagnostic test accuracy than general radiologist or ultrasonographers based on the available literature. Consequently, the proposed CAD system which was developed according to the experiment of the shoulder orthopaedic surgeon can provide reliable suggestions to general radiologists or ultrasonographers. More quantitative features related to the specific patterns of different lesion types would be investigated in the further study to improve the prediction.

Keywords: shoulder ultrasound, rotator cuff lesions, texture, computer-aided diagnosis

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Authors: Meftah O. Bashir, Fatma A. Karkory

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Rapid prototyping is a new group of manufacturing processes, which allows fabrication of physical of any complexity using a layer by layer deposition technique directly from a computer system. The rapid prototyping process greatly reduces the time and cost necessary to bring a new product to market. The prototypes made by these systems are used in a range of industrial application including design evaluation, verification, testing, and as patterns for casting processes. These processes employ a variety of materials and mechanisms to build up the layers to build the part. The present work was to build a FDM prototyping machine that could control the X-Y motion and material deposition, to generate two-dimensional and three-dimensional complex shapes. This study focused on the deposition of wax material. This work was to find out the properties of the wax materials used in this work in order to enable better control of the FDM process. This study will look at the integration of a computer controlled electro-mechanical system with the traditional FDM additive prototyping process. The characteristics of the wax were also analysed in order to optimize the model production process. These included wax phase change temperature, wax viscosity and wax droplet shape during processing.

Keywords: rapid prototyping, wax, manufacturing processes, shape

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Authors: Emin Avcı, Çiydem Çatak

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The recent economic crisis have shown that procyclicality, which could threaten the stability and growth of the economy, is a major problem of financial and real sector. The term procyclicality refers here the cyclical behavior of banks that lead them to follow the same patterns as the real economy. In this study, leverage which demonstrate how a bank manage its debt, is chosen as bank specific variable to see the effect of changes in it over the economic cycle. The procyclical behavior of Turkish banking sector (commercial, participation, development-investment banks) is tried to explain with analyzing the relationship between leverage and asset growth. On the basis of theoretical explanations, eight different leverage ratios are utilized in eight different panel data models to demonstrate the procyclicality effect of Turkish banks leverage using monthly data covering the 2005-2014 period. It is tested whether there is an increasing (decreasing) trend in the leverage ratio of Turkish banks when there is an enlargement (contraction) in their balance sheet. The major finding of the study indicates that asset growth has a significant effect on all eight leverage ratios. In other words, the leverage of Turkish banks follow a cyclical pattern, which is in line with those of earlier literature.

Keywords: banking, economic cycles, leverage, procyclicality

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Authors: hassan gheisari

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Ferro silicate calcium nano particles are prepared through the sol-gel method using polyvinyl alcohol (PVA) as a chelating agent. The powder, as prepared, is annealed at three different temperatures (900 ºC, 1000 ºC, and 1100 ºC) for 3 h. The XRD patterns of the samples indicate broad peaks, and the full width at half maximum decreased with increasing annealing temperature. FTIR spectra of the samples confirm the presence of metal - oxygen complexes within the structure. The average particle size obtained from PSA curve demonstrates ultrafine particles. SEM micrographs indicate the particles synthesized have spherical morphology. The saturation magnetization (Ms) and remnant magnetization (Mr) of the samples show dependence on particle size and crystallinity of the samples. The highest saturation magnetization is achieved for the sample annealed at 1100 ºC having maximum average particle size. The high saturation magnetization of the samples suggests the present method is suitable for obtaining nano particles magnetic ferro bioceramic, which is desirable for practical applications such as hyperthermia bone cancer therapy.

Keywords: hyperthermia, bone cancer, bio ceramic; magnetic materials; sol– gel, silicate calcium

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Authors: Hassan Gheisari

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Ferro silicate calcium nano particles are prepared through the sol-gel method using polyvinyl alcohol (PVA) as a chelating agent. The powder as prepared is annealed at three different temperatures (900 ºC, 1000 ºC and 1100 ºC) for 3 h. The XRD patterns of the samples indicate broad peaks and the full width at half maximum decreased with increasing annealing temperature. FTIR spectra of the samples confirm the presence of metal - oxygen complexes within the structure. The average particle size obtained from PSA curve demonstrates ultrafine particles. SEM micrographs indicate the particles synthesized have spherical morphology. The saturation magnetization (Ms) and remnant magnetization (Mr) of the samples show dependence on particle size and crystallinity of the samples. The highest saturation magnetization is achieved for the sample annealed at 1100 ºC having maximum average particle size. The high saturation magnetization of the samples suggests the present method is suitable for obtaining nano particles magnetic ferro bioceramic which is desirable for practical applications such as hyperthermia bone cancer therapy.

Keywords: hyperthermia, bone cancer, bio ceramic, magnetic materials, sol– gel, silicate calcium

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Authors: Josephine K. Mule, Levi Obonyo

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Technology has changed human life over time. The COVID-19 pandemic has altered the work set-up, the school system, the shopping experience, church attendance, and even the way athletes train in Kenya. Although the use of technology to communicate and maintain interactions has been on the rise in the last 30 years, the uptake during the COVID-19 pandemic has been unprecedented. Traditionally, ‘paid’ work has been considered to take place outside the “home house” but COVID-19 has resulted in what is now being referred to as “the world’s largest work-from-home experiment” with up to 43 percent of employees working at least some of the time remotely. This study was conducted on 90 respondents from across remote work set-ups, school systems, merchants and customers of online shopping, church leaders and congregants and athletes, and their coaches. Data were collected by questionnaires and interviews that were conducted online. The data is based on the first three months since the first case of coronavirus was reported in Kenya. This study found that the use of technology is in the center of working remotely with work interactions being propelled on various online platforms including, Zoom, Microsoft Teams, and Google Meet, among others. The school system has also integrated the use of technology, including students defending their thesis/dissertations online and university graduations being conducted virtually. Kenya is known for its long-distance runners, due to the directives to reduce interactions; coaches have taken to providing their athletes with guidance on training on social media using applications such as WhatsApp. More local stores are now offering the shopping online option to their customers. Churches have also felt the brunt of the situation, especially because of the restrictions on crowds resulting in online services becoming more popular in 2020 than ever before. Artists, innovatively have started online musical concerts. The findings indicate that one of the outcomes in the Kenyan society that is evident as a result of the COVID-19 period is a population that is using technology more to communicate and get work done. Vices that have thrived in this season where the use of technology has increased, include the spreading of rumors on social media and cyberbullying. The place of technology seems to have been cemented by demand during this period.

Keywords: communication, coronavirus, COVID-19, Kenya, technology

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Parveen Kumar

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The cope the rapid change of technology and to control the ephemeral rate of information generation, librarians along with their professional colleagues need to equip themselves as per the requirement of the electronic information society. E-learning is purely based on computer and communication technologies. The terminologies like computer based learning. It is the delivery of content via all electronic media through internet, internet, Extranets television broadcast, CD-Rom documents, etc. E-learning poses lot of issues in the transformation of literature or knowledge from the conventional medium to ICT based format and web based services.

Keywords: e-learning, digital libraries, online learning, electronic information society

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Authors: Jorge Duarte de Sá

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The appearance of the new media technologies has opened new fields of intervention in architecture creating a new dynamic communication in the relationship between public and space, where are present technological devices that enable a new sensory experience, aesthetic and even spiritual. This connection makes relevant the idea of rehabilitate architectonic spaces with new media technologies such as sacred spaces. This research aims to create a media project integrated in sacred spaces that combine Architecture, Art and New Technologies, exploring new perspectives and different dynamics in space.

Keywords: media, architecture, religious spaces, projections, contemplation

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Authors: Malgorzata Wojcik

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Groups are a powerful and significant part of human development. They serve as major emergent microsocial structures in children’s and youth’s ecological system. During middle and secondary school, peer groups become a particularly salient influence. While they promote a range of prosocial and positive emotional and behavioral attributes, they can also elicit negative or antisocial attributes, effectively “bringing out the worst” in some individuals. The grounded theory approach was employed to guide data collection and analysis, as it allows for a deeper understanding of the group processes and students’ perspectives on complex intragroup relations. Students’ perspectives on bullying cases were investigated by observing daily interactions among those involved and interviewing 47 students. The results complement theories of labeling in bullying by showing that all students self-label themselves and find it difficult to break patterns of behaviors related to bullying, such as supporting the bully or not defending the victim. In terms of the practical implications, the findings indicate that it could be beneficial to use non-punitive, restorative anti-bullying interventions that implement peer influence to transform bullying relations by removing behavioral labels.

Keywords: bullying, peer group, victimization, class reputation

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Authors: Ridoy Das, Myriam Neaimeh, Yue Wang, Ghanim Putrus

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Electric vehicles are a popular transportation medium renowned for potential environmental benefits. However, large and uncontrolled charging volumes can impact distribution networks negatively. Smart charging is widely recognized as an efficient solution to achieve both improved renewable energy integration and grid relief. Nevertheless, different decision-makers may pursue diverse and conflicting objectives. In this context, this paper proposes a multi-objective optimization framework to control electric vehicle charging to achieve both energy cost reduction and peak shaving. A weighted-sum method is developed due to its intuitiveness and efficiency. Monte Carlo simulations are implemented to investigate the impact of uncertain electric vehicle driving patterns and provide decision-makers with a robust outcome in terms of prospective cost and network loading. The results demonstrate that there is a conflict between energy cost efficiency and peak shaving, with the decision-makers needing to make a collaborative decision.

Keywords: electric vehicles, multi-objective optimization, uncertainty, mixed integer linear programming

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Authors: Adji Achmad Rinaldo Fernandes, Usriatur Rohma

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Nonparametric path analysis is a statistical method that does not rely on the assumption that the curve is known. The purpose of this study is to determine the best truncated spline nonparametric path function between linear and quadratic polynomial degrees with 1, 2, and 3 knot points and to determine the significance of estimating the best truncated spline nonparametric path function in the model of the effect of perceived benefits and perceived convenience on behavior to convert waste into economic value through the intention variable of changing people's mindset about waste using the t test statistic at the jackknife resampling stage. The data used in this study are primary data obtained from research grants. The results showed that the best model of nonparametric truncated spline path analysis is quadratic polynomial degree with 3 knot points. In addition, the significance of the best truncated spline nonparametric path function estimation using jackknife resampling shows that all exogenous variables have a significant influence on the endogenous variables.

Keywords: nonparametric path analysis, truncated spline, linear, kuadratic, behavior to turn waste into economic value, jackknife resampling

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Authors: Dania Baaboud, Renad Al-zahrani, Mahnoor Khan, Riya Afroz

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Flo is a smart period-tracking tool that uses artificial intelligence (AI) to offer individualized reproductive health predictions and insights. Flo makes very accurate predictions about menstrual cycles, ovulation, and fertility windows by evaluating user inputs, including cycle duration, symptoms, and patterns. Its machine learning algorithms are constantly evolving, providing personalized health recommendations, instructional materials, and early identification of possible health abnormalities such as reproductive problems and hormone imbalances. Flo, which was introduced in 2015 and upgraded with AI in 2017, is a revolutionary use of technology in healthcare that empowers people to make knowledgeable decisions regarding their well-being. Despite its advantages, our study included drawbacks, such as limited access to premium services and a small sample size. While highlighting unique characteristics, a comparative comparison with similar applications such as Clue and Glow confirmed Flo's outstanding AI integration for individualized healthcare. All things considered, Flo is a prime example of how AI can be used to tackle intricate biological processes, giving consumers the ability to efficiently control their reproductive health and opening the door for improvements in individualized medical technology.

Keywords: Flo, period-tracking app, period symptoms, women’s health, machinery

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Authors: Ramzi Rihane, Yassine Benayed

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Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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Authors: Dedah Ahmed Babou, Nicolas Bez

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The Min-Max autocorrelation factor (MAF) approach makes it possible to express in a space formed by spatially independent factors, spatiotemporal observations. These factors are ordered in decreasing order of spatial autocorrelation. The starting observations are thus expressed in the space formed by these factors according to temporal coordinates. Each vector of temporal coefficients expresses the temporal evolution of the weight of the corresponding factor. Applying this approach has enabled us to achieve the following results: (i) Define a spatially orthogonal space in which the projections of the raw data are determined; (ii) Define a limit threshold for the factors with the strongest structures in order to analyze the weight, and the temporal evolution of these different structures (iii) Study the correlation between the temporal evolution of the persistent spatial structures and that of the observed average abundance (iv) Propose prototypes of campaigns reflecting a high vs. low abundance (v) Propose a classification of campaigns that highlights seasonal and/or temporal similarities. These results were obtained by analyzing the octopus yield during the scientific campaigns of the oceanographic vessel Al Awam during the period 1989-2017 in the Mauritanian exclusive economic zone.

Keywords: spatiotemporal , autocorrelation, kriging, variogram, Octopus vulgaris

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Authors: Kherafa Abdennasser

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The application of Information and Communication Technologies (ICT) to the training area led to the creation of this new reality called E-learning. That last one is described like the marriage of multi- media (sound, image and text) and of the internet (diffusion on line, interactivity). Distance learning became an important totality for training and that last pass in particular by the setup of a distance learning platform. In our memory, we will use an open source platform named Dokeos for the management of a distance training of GPS called e-GPS. The learner is followed in all his training. In this system, trainers and learners communicate individually or in group, the administrator setup and make sure of this system maintenance.

Keywords: ICT, E-learning, learning plate-forme, Dokeos, GPS

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Authors: Navid Zanganeh, Hafez Balavi, Farbod Sharif, Mahla Zabet, Marzieh Bakhtiary Noodeh

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Cerium oxide (CeO2) also known as cerium dioxide or ceria is a pale yellow-white powder with various applications in the industry from wood coating to cosmetics, filtration, fuel cell electrolytes, gas sensors, hybrid solar cells and catalysts. In this research, attempts were made to synthesize and characterization of CeO2 nano-particles via sol-gel method. In addition, the effect of aging time on the size of particles was investigated. For this purpose, the aging times adjusted 48, 56, 64, and 72 min. The obtained particles were characterized by x-ray diffraction spectroscopy (XRD), scanning electron microscopy (SEM), transmitted electron microscopy (TEM), and Brunauer–Emmett–Teller (BET). As a result, XRD patterns confirmed the formation of CeO2 nanoparticles. SEM and TEM images illustrated the nano-particles with cluster shape, spherical and a nano-size range which was in agreement with XRD results. The finest particles (7.3 nm) was obtained at the optimum condition which was aging time of 48 min, calcination temperature at 400 ⁰C, and cerium concentration of 0.004 mol. Average specific surface area of the particles at optimum condition was measured by BET analysis and recorded as 47.57 m2/g.

Keywords: aging time, CeO2 nanoparticles, size distribution, sol-gel

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Authors: Barby Jennette A. Florano

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Dietary intake has been associated with the health and wellbeing of adults, and lifestyle related diseases. The aim of this study was to investigate whether nutrition knowledge, food label use, and food preference are associated with the dietary intake in a sample of San Jose Del Monte City, Bulacan (SJDM) adults. A sample of 148 adults, with a mean age of 20 years, completed a validated questionnaire related to their demographic, dietary intake, nutrition knowledge, food label use and food preference. Data were analyzed using Pearson correlation and there was no association between dietary intake and nutrition knowledge. However, there were positive relationships between dietary intake and food label use (r=0.1276, p<0.10), and dietary intake and food preference (r=0.1070, p<0.10). SJDM adults who use food label and have extensive food preference had better diet quality. This finding magnifies the role of nutrition education as a potential tool in health campaigns to promote healthy eating patterns and reading food labels among students and adults. Results of this study can give information for the design of future nutrition education intervention studies to assess the efficacy of nutrition knowledge and food label use among a similar sample population.

Keywords: dietary intake, nutrition knowledge, food preference, food label use

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Eduardo Álvarez, Gerardo Quiroga, Jorge Orozco, Gabriel Chavira

Abstract:

AmI proposes a new way of thinking about computers, which follows the ideas of the Ubiquitous Computing vision of Mark Weiser. In these, there is what is known as a Disappearing Computer Initiative, with users immersed in intelligent environments. Hence, technologies need to be adapted so that they are capable of replacing the traditional inputs to the system by embedding these in every-day artifacts. In this work, we present an approach, which uses Radiofrequency Identification (RFID) and Near Field Communication (NFC) technologies. In the latter, a new form of interaction appears by contact. We compare both technologies by analyzing their requirements and advantages. In addition, we propose using a combination of RFID and NFC.

Keywords: touching interaction, ambient intelligence, ubiquitous computing, interaction, NFC and RFID

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Authors: Raquel Rossini, Edelvais Caldeira

Abstract:

The aim of this work is to investigate the motivation for the metaphorical uses of two verb combinations: come out and take over. Drawing from cognitive semantics theories, image schemas and metaphors, it was attempted to demonstrate that: a) the metaphorical senses of both 'come out' and 'take over' extend from both the verbs and the particles central (spatial) senses in such verb combinations; and b) the particles 'out' and 'over' also contribute to the whole meaning of the verb combinations. In order to do so, a random selection of 579 concordance lines for come out and 1,412 for take over was obtained from the Corpus of Contemporary American English – COCA. One of the main procedures adopted in the present work was the establishment of verb and particle central senses. As per the research questions addressed in this study, they are as follows: a) how does the identification of trajector and landmark help reveal patterns that contribute for the identification of the semantic network of these two verb combinations?; b) what is the relationship between the schematic structures attributed to the particles and the metaphorical uses found in empirical data?; and c) what conceptual metaphors underlie the mappings from the source to the target domains? The results demonstrated that not only the lexical verbs come and take, but also the particles out and over play an important whole in the different meanings of come out and take over. Besides, image schemas and conceptual metaphors were found to be helpful in order to establish the motivations for the metaphorical uses of these linguistic structures.

Keywords: cognitive linguistics, English syntax, multi-word verbs, prepositions

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Authors: Mohammad Anwarul Kabir, Fayezul Islam

Abstract:

Language invariably is learned / taught to be used primarily as means of communications. Teaching a language for its native audience differs from teaching it to non-native audience. Moreover, teaching a language for communication only is different from teaching it for specific purposes. Arabic language is primarily regarded as the language of the Quran and the Sunnah (Prophetic tradition). Arabic is, therefore, learnt and spread all over the globe. However, Arabic is also a cultural heritage shared by all Islamic nations which has used Arabic for a long period to record the contributions of Muslim thinkers made in the field of wide spectrum of knowledge and scholarship. That is why the phenomenon of teaching Arabic by different educational institutes became quite rife, and the idea of teaching Arabic for specific purposes is heavily discussed in the academic sphere. Although the number of learners of Arabic is increasing consistently, yet their purposes vary. These include religious purpose, international trade, diplomatic purpose, better livelihood in the Arab world extra. By virtue of this high demand for learning Arabic, numerous institutes have been established all over the world including Bangladesh. This paper aims at focusing on the current status of the language institutes which has been established for learning Arabic for specific purposes in Bangladesh including teaching methodology, curriculum, and teachers’ quality. Such curricula and using its materials resulted in a lot of problems. The least, it confused teachers and students as well. Islamic educationalists have been working hard to professionally meet the need. They are following a systematic approach of stating clear and achievable goals, building suitable content, and applying new technology to present these learning experiences and evaluate them. It also suggests a model for designing instructional systems that responds to the need of non-Arabic speaking Islamic communities and provide the knowledge needed in both linguistic and cultural aspects. It also puts forward a number of suggestions for the improvement of the teaching / learning Arabic for specific purposes in Bangladesh after a detailed investigation in the following areas: curriculum, teachers’ skills, method of teaching and assessment policy.

Keywords: communication, Quran, sunnah, educational institutes, specific purposes, curriculum, method of teaching

Procedia PDF Downloads 284