Search results for: information warfare techniques

Authors: Irakli Manvelidze, Genadi Iashvili, Giga Phartenadze, Giorgi Katamadze

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Establishment of electronic governance in the region is facing serious problems. Organizational, technical, social and methodological problems have been identified after the research. These problems currently create serious barriers and prevent the development of effective e-governance. Lack of human resources, difference in program targets of the centre and the region, lack of citizens’ awareness about the project of electronic governance are other issues that should be mentioned. In spite of positive changes the overall situation concerning development of modern information-communication technologies in Adjara is not satisfactory. The information systems in the region can be described as transforming in a democratic way which needs serious reforms. Current situation shows that unsystematic, uncoordinated actions were made which overall represents more chaotic rather than coordinated systematic process. Therefore, a strategic document ‘Adjarian Electronic Government’ should be created which will ensure systematic development of electronic governance in the region. The implementation of the strategy of ‘Adjarian Electronic Government’ should be based on not only conceptual and instrumental but also legal basics. A legal normative basis should be created which will include formation of electronic government’s instrumental basis as well as creation of united regional system of electronic document management. Meanwhile types of documents which would be used in inter institutional relations should be defined under a legal norm. Creation of regional united system of e-filing will regulate regional public institutions, relations between local self-government and public organizations as well as it will ensure coordinated work of all regional public institutions.

Keywords: e-government, information society, public administration, reforming state governance, public institutions

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Authors: Chia Yen Li, Wen Huei Chou, Mieko Ohsuga, Tsuyoshi Inoue

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The evolution of the digital age has led to people’s lives being pervaded by both facts and misinformation, challenging media literacy (ML). Middle-aged and elderly persons (MEPs) are prone to disseminating large amounts of misinformation, which often endangers their lives due to erroneously believing such information. At present, several countries have actively established fact-checking platforms to combat misinformation, but they are unable to keep pace with the rapid proliferation of such information on social media. In this study, the questionnaire survey method was used to collect data on MEPs’ behavior, cognition, attitudes, and concepts of social media when using a mobile instant messaging app called LINE; analyze their behavioral patterns and reasons for sharing misinformation; and summarize design strategies for improving their ML. The findings can serve as a reference in future related research.

Keywords: media literacy, middle-aged and elderly persons, social media, misinformation

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Authors: Abeer Heider

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This paper explores and classifies the different kinds of avoidances that students commonly make in the acquisition of Arabic as a second/foreign language, and suggests specific strategies to help students lessen their avoidance trends in hopes of streamlining the learning process. Students most commonly use avoidance strategies in grammar, and word choice. These different types of strategies have different implications and naturally require different approaches. Thus the question remains as to the most effective way to help students improve their Arabic, and how teachers can efficiently utilize these techniques. It is hoped that this research will contribute to understand the role of avoidance in the field of the second language acquisition in general, and as a type of input. Yet some researchers also note that similarity between L1 and L2 may be problematic as well since the learner may doubt that such similarity indeed exists and consequently avoid the identical constructions or elements (Jordens, 1977; Kellermann, 1977, 1978, 1986). In an effort to resolve this issue, a case study is being conducted. The present case study attempts to provide a broader analysis of what is acquired than is usually the case, analyzing the learners ‘accomplishments in terms of three –part framework of the components of communicative competence suggested by Michele Canale: grammatical competence, sociolinguistic competence and discourse competence. The subjects of this study are 15 students’ 22th year who came to study Arabic at Qatar University of Cairo. The 15 students are in the advanced level. They were complete intermediate level in Arabic when they arrive in Qatar for the first time. The study used discourse analytic method to examine how the first language affects students’ production and output in the second language, and how and when students use avoidance methods in their learning. The study will be conducted through Fall 2015 through analyzing audio recordings that are recorded throughout the entire semester. The recordings will be around 30 clips. The students are using supplementary listening and speaking materials. The group will be tested at the end of the term to assess any measurable difference between the techniques. Questionnaires will be administered to teachers and students before and after the semester to assess any change in attitude toward avoidance and selectivity methods. Responses to these questionnaires are analyzed and discussed to assess the relative merits of the aforementioned strategies to avoidance and selectivity to further support on. Implications and recommendations for teacher training are proposed.

Keywords: the second language acquisition, learning languages, selectivity, avoidance

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Authors: Rian Diana, Naufal Muharam Nurdin, Faisal Anwar, Hadi Riyadi, Ali Khomsan

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The use of traditional medicine (herbs and medicinal plants) are common among Indonesian people especially the elderly. Few study explore the use of medicinal plants in middle aged people. This study aims to collect information on the use of medicinal plants in middle aged people in rural areas. This cross sectional study included 224 subjects aged 45-59 years old and conducted in Cianjur District, West Java in 2014. Semi-structured questionnaires were used to collect information about preference in treatment of illness, the use of medicinal plants, and their purposes. Information also recorded plant names, parts used, mode of preparation, and dosage. Buying drugs in stall (83.9%) is the first preference in treatment of illness, followed by modern treatment 19.2% (doctors) and traditional treatment 17.0% (herbs/medicinal plants). 87 subjects (38.8%) were using herbs and medicinal plants for curative (66.7%), preventive (31.2%), and rehabilitative (2.1%) purposes. In this study, 48 species are used by the subjects. Physalis minima L. 'cecenet', Orthosiphon aristatus Mic. 'kumis kucing', and Annona muricata 'sirsak' are commonly used for the treatment of hypertension and stiffness. Leaves (64.6%) are the most common part used. Medicinal plants were washed and boiled in a hot water. Subject drinks the herbs with a different dosage. One in three middle aged people used herbal and medicinal plants for curative and preventive treatment particularly hypertension and stiffness. Increasing knowledge about herbal or medicinal plants dosage and their interaction with medical drugs are important to do.Doses vary between 1-3 glasses/day for treatment and 1-2 glasses/months for prevention of diseases.

Keywords: herbs, hypertension, medicinal plants, middle age, rural

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Authors: Arslan Ellahi, Syed Amjad Hussain, Fawaz Saleem Bokhari

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Optimization of software architecture can be done with respect to a quality attributes (QA). In this paper, there is an analysis of multiple research papers from different dimensions that have been used to classify those attributes. We have proposed a technique of swarm intelligence Meta heuristic ant colony optimization algorithm as a contribution to solve this critical optimization problem of software architecture. We have ranked quality attributes and run our algorithm on every QA, and then we will rank those on the basis of accuracy. At the end, we have selected the most accurate quality attributes. Ant colony algorithm is an effective algorithm and will perform best in optimizing the QA’s and ranking them.

Keywords: complexity, rapid evolution, swarm intelligence, dimensions

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Authors: Ashraf Nawaz Khan, R. Alagirusamy, Apurba Das, Puneet Mahajan

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The thermoplastic-based fibre composites are acquiring a market sector of conventional as well as thermoset composites. However, replacing the thermoset with a thermoplastic composite has never been an easy task. The inherent high viscosity of thermoplastic resin reveals poor interface properties. In this work, a homo-polymer towpreg is produced through an electrostatic powder spray coating methodology. The produced flexible towpreg offers a low melt-flow distance during the consolidation of the laminate. The reduced melt-flow distance demonstrates a homogeneous fibre/matrix distribution (and low void content) on consolidation. The composite laminate has been fabricated with two manufacturing techniques such as conventional film stack (FS) and powder-coated (PC) technique. This helps in understanding the distinct response of produced laminates on applying load since the laminates produced through the two techniques are comprised of the same constituent fibre and matrix (constant fibre volume fraction). The changed behaviour is observed mainly due to the different fibre/matrix configurations within the laminate. The interface adhesion influences the load transfer between the fibre and matrix. Therefore, it influences the elastic, plastic, and failure patterns of the laminates. Moreover, the effect of preform geometries (plain weave and satin weave structure) are also studied for corresponding composite laminates in terms of various mechanical properties. The fracture analysis is carried out to study the effect of resin at the interlacement points through micro-CT analysis. The PC laminate reveals a considerably small matrix-rich and deficient zone in comparison to the FS laminate. The different load tensile, shear, fracture toughness, and drop weight impact test) is applied to the laminates, and corresponding damage behaviour is analysed in the successive stage of failure. The PC composite has shown superior mechanical properties in comparison to the FS composite. The damage that occurs in the laminate is captured through the SEM analysis to identify the prominent mode of failure, such as matrix cracking, fibre breakage, delamination, debonding, and other phenomena.

Keywords: composite, damage, fibre, manufacturing

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Authors: Abbas Teimouri, Leila Ghorbanian, Iren Dabirian

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This work focused on preparation and characterizations of silk fibroin (SF)/nanodiopside nanoceramic via electrospinning process. Nanofibrous scaffolds were characterized by combined techniques of scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD). The results confirmed that fabricated SF/diopside scaffolds improved cell attachment and proliferation. The results indicated that the electrospun of SF/nanodiopside nanofibrous scaffolds could be considered as ideal candidates for tissue engineering.

Keywords: electrospinning, nanofibers, silk fibroin, diopside, composite scaffold

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Faiz N. K. Yusufi, Aquil Ahmed, Jamal Ahmad

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Predicting the risk of diabetic retinopathy (DR) in Indian type 2 diabetes patients is immensely necessary. India, being the second largest country after China in terms of a number of diabetic patients, to the best of our knowledge not a single risk score for complications has ever been investigated. Diabetic retinopathy is a serious complication and is the topmost reason for visual impairment across countries. Any type or form of DR has been taken as the event of interest, be it mild, back, grade I, II, III, and IV DR. A sample was determined and randomly collected from the Rajiv Gandhi Centre for Diabetes and Endocrinology, J.N.M.C., A.M.U., Aligarh, India. Collected variables include patients data such as sex, age, height, weight, body mass index (BMI), blood sugar fasting (BSF), post prandial sugar (PP), glycosylated haemoglobin (HbA1c), diastolic blood pressure (DBP), systolic blood pressure (SBP), smoking, alcohol habits, total cholesterol (TC), triglycerides (TG), high density lipoprotein (HDL), low density lipoprotein (LDL), very low density lipoprotein (VLDL), physical activity, duration of diabetes, diet control, history of antihypertensive drug treatment, family history of diabetes, waist circumference, hip circumference, medications, central obesity and history of DR. Cox proportional hazard regression is used to design risk scores for the prediction of retinopathy. Model calibration and discrimination are assessed from Hosmer Lemeshow and area under receiver operating characteristic curve (ROC). Overfitting and underfitting of the model are checked by applying regularization techniques and best method is selected between ridge, lasso and elastic net regression. Optimal cut off point is chosen by Youden’s index. Five-year probability of DR is predicted by both survival function, and Markov chain two state model and the better technique is concluded. The risk scores developed can be applied by doctors and patients themselves for self evaluation. Furthermore, the five-year probabilities can be applied as well to forecast and maintain the condition of patients. This provides immense benefit in real application of DR prediction in T2DM.

Keywords: Cox proportional hazard regression, diabetic retinopathy, ROC curve, type 2 diabetes mellitus

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Authors: Matheus Madureira Matos, Alexandre Rodrigues Farias

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Magnetic Resonance Imaging (MRI) is a vital imaging technique used in both clinical and pre-clinical areas to obtain detailed anatomical and functional information. However, MRI scans can be expensive, time-consuming, and often require the use of anesthetics to keep animals still during the imaging process. Anesthetics are commonly administered to animals undergoing MRI scans to ensure they remain still during the imaging process. However, prolonged or repeated exposure to anesthetics can have adverse effects on animals, including physiological alterations and potential toxicity. Minimizing the duration and frequency of anesthesia is, therefore, crucial for the well-being of research animals. In recent years, various sampling trajectories have been investigated to reduce the number of MRI measurements leading to shorter scanning time and minimizing the duration of animal exposure to the effects of anesthetics. Compressed sensing (CS) and sampling trajectories, such as cartesian, spiral, and radial, have emerged as powerful tools to reduce MRI data while preserving diagnostic quality. This work aims to apply CS and cartesian, spiral, and radial sampling trajectories for the reconstruction of MRI of the abdomen of mice sub-sampled at levels below that defined by the Nyquist theorem. The methodology of this work consists of using a fully sampled reference MRI of a female model C57B1/6 mouse acquired experimentally in a 4.7 Tesla MRI scanner for small animals using Spin Echo pulse sequences. The image is down-sampled by cartesian, radial, and spiral sampling paths and then reconstructed by CS. The quality of the reconstructed images is objectively assessed by three quality assessment techniques RMSE (Root mean square error), PSNR (Peak to Signal Noise Ratio), and SSIM (Structural similarity index measure). The utilization of optimized sampling trajectories and CS technique has demonstrated the potential for a significant reduction of up to 70% of image data acquisition. This result translates into shorter scan times, minimizing the duration and frequency of anesthesia administration and reducing the potential risks associated with it.

Keywords: compressed sensing, magnetic resonance, sampling trajectories, small animals

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Authors: Md Monoarul Haque

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Nutritional status is a sensitive indicator of community health and nutrition among preschool children, especially the prevalence of undernutrition that affects all dimensions of human development and leads to growth faltering in early life. The present study is an attempt to assess the food intake pattern and nutritional status of pre-school Chakma tribe children. It was a cross-sectional community based study. The subjects were selected purposively. This study was conducted at Savar Upazilla of Rangamati. Rangamati is located in the Chittagong Division. Anthropometric data height and weight of the study subjects were collected by standard techniques. Nutritional status was measured using Z score according WHO classification. χ2 test, independent t-test, Pearson’s correlation, multiple regression and logistic regression was performed as P<0.05 level of significance. Statistical analyses were performed by appropriate univariate and multivariate techniques using SPSS windows 11.5. Moderate (-3SD to <-2SD) to severe underweight (<-3SD) were 23.8% and 76.2% study subjects had normal weight for their age. Moderate (-3SD to <-2SD) to severe (<-3SD) stunted children were only 25.6% and 74.4% children were normal and moderate to severe wasting were 14.7% whereas normal child was 85.3%. Significant association had been found between child nutritional status and monthly family income, mother education and occupation of father and mother. Age, sex and incomes of the family, education of mother and occupation of father were significantly associated with WAZ and HAZ of the study subjects (P=0.0001, P=0.025, P=0.001 and P=0.0001, P=0.003, P=0.031, P=0.092, P=0.008). Maximum study subjects took local small fish and some traditional tribal food like bashrool, jhijhipoka and pork very much popular food among tribal children. Energy, carbohydrate and fat intake was significantly associated with HAZ, WAZ, BAZ and MUACZ. This study demonstrates that malnutrition among tribal children in Bangladesh is much better than national scenario in Bangladesh. Significant association was found between child nutritional status and family monthly income, mother education and occupation of father and mother. Most of the study subjects took local small fish and some traditional tribal food. Significant association was also found between child nutritional status and dietary intake of energy, carbohydrate and fat.

Keywords: food intake pattern, nutritional status, preschool children, Chakma ethnic community

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Authors: Akshay Agrawal, Anand K. Srivastava

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The increasing amount of XML datasets available to casual users increases the necessity of investigating techniques to extract knowledge from these data. Data mining is widely applied in the database research area in order to extract frequent correlations of values from both structured and semi-structured datasets. The increasing availability of heterogeneous XML sources has raised a number of issues concerning how to represent and manage these semi structured data. In recent years due to the importance of managing these resources and extracting knowledge from them, lots of methods have been proposed in order to represent and cluster them in different ways.

Keywords: XML, similarity measure, clustering, cluster quality, semantic clustering

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Authors: Stevens Phaphadi Mamorobela

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The Covid-19 pandemic has accelerated the use of social media in SMEs to stay abreast with information about the latest news and developments and to predict the future world of business. The national shutdown regulations for curbing the spread of the Covid-19 virus resulted in SMEs having to distribute large volumes of information through social media platforms to collaborate and conduct business remotely. How much of the information shared on social media is used by SMEs as significant knowledge for economic rent is yet to be known. This study aims to investigate the facilitating conditions that enable SMEs’ intention to use social media as a knowledge-sharing platform to create economic rent and to cope with the Covid-19 challenges. A qualitative research approach was applied where semi-structured interviews were conducted with 13 SME owners located in the Gauteng province in South Africa to identify and explain the facilitating conditions of SMEs towards their intention to use social media as a knowledge-sharing tool in the Covid-19 era. The study discovered that the national lockdown regulations towards curbing the spread of the Covid-19 pandemic had compelled SMEs to adopt digital technologies that enabled them to quickly transform their business processes to cope with the challenges of the pandemic. The facilitating conditions, like access to high bandwidth internet coverage in the Gauteng region, enable SMEs to have strong intentions to use social media to distribute content and to reach out to their target market. However, the content is shared informally using diverse social media platforms without any guidelines for transforming content into rent-yielding knowledge.

Keywords: facilitating conditions, knowledge sharing, social media, intention to use, SME

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Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

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The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

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Authors: Catherine Thompson, Maryam Jalali, Peter Hills

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The allocation of visual attention is critical when driving and anything that limits attention will have a detrimental impact on safety. Engaging in a secondary task reduces the amount of attention directed to the road because drivers allocate resources towards this task, leaving fewer resources to process driving-relevant information. Yet the dangers associated with a secondary task do not end when the driver returns their attention to the road. Instead, the attentional settings adopted to complete a secondary task may persist to the road, affecting attention, and therefore affecting driver performance. This 'attentional inertia' effect was investigated in the current work. Forty drivers searched for hazards in driving video clips while their eye-movements were recorded. At varying intervals they were instructed to attend to a secondary task displayed on a tablet situated to their left-hand side. The secondary task consisted of three separate computer games that induced horizontal, vertical, and random eye movements. Visual search and hazard detection in the driving clips were compared across the three conditions of the secondary task. Results showed that the layout of information in the secondary task, and therefore the allocation of attention in this task, had an impact on subsequent search in the driving clips. Vertically presented information reduced the wide horizontal spread of search usually associated with accurate driving and had a negative influence on the detection of hazards. The findings show the additional dangers of engaging in a secondary task while driving. The attentional inertia effect has significant implications for semi-autonomous and autonomous vehicles in which drivers have greater opportunity to direct their attention away from the driving task.

Keywords: attention, eye-movements, hazard perception, visual search

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Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Mohadese Oghbaee, Borna Firouzi

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The emergence of the Internet and more specifically the formation of social media has provided the ground for paying attention to new types of content dissemination. In recent years, Social media users share information, communicate with others, and exchange opinions on social events in this space. Many of the information published in this space are suspicious and produced with the intention of deceiving others. These contents are often called "fake news". Fake news, by disrupting the circulation of the concept and similar concepts such as fake news with correct information and misleading public opinion, has the ability to endanger the security of countries and deprive the audience of the basic right of free access to real information; Competing governments, opposition elements, profit-seeking individuals and even competing organizations, knowing about this capacity, act to distort and overturn the facts in the virtual space of the target countries and communities on a large scale and influence public opinion towards their goals. This process of extensive de-truthing of the information space of the societies has created a wave of harm and worries all over the world. The formation of these concerns has led to the opening of a new path of research for the timely containment and reduction of the destructive effects of fake news on public opinion. In addition, the expansion of this phenomenon has the potential to create serious and important problems for societies, and its impact on events such as the 2016 American elections, Brexit, 2017 French elections, 2019 Indian elections, etc., has caused concerns and led to the adoption of approaches It has been dealt with. In recent years, a simple look at the growth trend of research in "Scopus" shows an increasing increase in research with the keyword "false information", which reached its peak in 2020, namely 524 cases, reached, while in 2015, only 30 scientific-research contents were published in this field. Considering that one of the capabilities of social media is to create a context for the dissemination of news and information, both true and false, in this article, the classification of strategies for spreading fake news in social networks was investigated in social events. To achieve this goal, thematic analysis research method was chosen. In this way, an extensive library study was first conducted in global sources. Then, an in-depth interview was conducted with 18 well-known specialists and experts in the field of news and media in Iran. These experts were selected by purposeful sampling. Then by analyzing the data using the theme analysis method, strategies were obtained; The strategies achieved so far (research is in progress) include unrealistically strengthening/weakening the speed and content of the event, stimulating psycho-media movements, targeting emotional audiences such as women, teenagers and young people, strengthening public hatred, calling the reaction legitimate/illegitimate. events, incitement to physical conflict, simplification of violent protests and targeted publication of images and interviews were introduced.

Keywords: fake news, social network, social events, thematic analysis

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Authors: Buse T. Aydın, Enver Ozdemir

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In this study, a double layer authentication scheme between the aircraft and the Air Traffic Control (ATC) tower is designed to prevent any unauthorized aircraft from introducing themselves as friends. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or foe according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as a friend. In this method, even if embedded key is captured by the enemy aircraft, without the information of the second layer, the enemy can easily be determined. Overall, in this work, we present a more reliable system by adding a physical layer in the authentication process.

Keywords: ADS-B, communication with physical layer security, cryptography, identification friend or foe

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Authors: Nicoleta Simona Vedeanu, Rares Stiufiuc, Dana Alina Magdas

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A detailed knowledge of the teeth structure is mandatory to understand and explain the defects and the dental pathology, but especially to take a correct decision regarding dental prophylaxis and treatment. The present work is an alternative study to the traditional investigation methods used in dentistry, a study based on the use of modern, sensitive physical methods to investigate human enamel and dentin. For the present study, several teeth collected from patients of different ages were used for structural and dietary investigation. The samples were investigated by Raman spectroscopy for the molecular structure analysis of dentin and enamel, atomic force microscopy (AFM) to view the dental topography at the micrometric size and mass spectrometry for isotopic ratios as a fingerprint of patients’ personal diet. The obtained Raman spectra and their interpretation are in good correlation with the literature and may give medical information by comparing affected dental structures with healthy ones. AFM technique gave us the possibility to study in details the dentin and enamel surface to collect information about dental hardness or dental structural changes. δ¹³C values obtained for the studied samples can be classified in C4 category specific to young people and children diet (sweets, cereals, juices, pastry). The methods used in this attempt furnished important information about dentin and enamel structure and dietary habits and each of the three proposed methods can be extended at a larger level in the study of the teeth structure.

Keywords: AFM, dentine, enamel, Raman spectroscopy

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Authors: Hilary Joseph Watsilla

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Research work is a vital part of the university system; in Nigeria public universities, research is used in measuring the development of individuals and departments within the academic system. Information technology has impacted the way research is carried out by providing easy access to information and improved collaboration between research and other instruments necessary for research activities. However, access to some of these IT facilities is not readily available in most of the public institutions in Nigeria. Research activities are usually tedious and rigorous and any inadequacy in research resources might affect the quality of research outcome. This study aims to identify the IT capability and knowledge management capabilities necessary for academic researchers in public universities in Nigeria, as it will provide more incite to the knowledge creation processes of research. The research will be conducted using an interpretive lens, which will provide a more qualitative understanding of the subject matter. The outcome of the research will provide an empirical understanding of the IT capabilities, which help in the optimization of the knowledge management capabilities of the university.

Keywords: IT capabilities, KM capabilities, universities, academic research

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Authors: C. Amrane, D. Haman

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Aluminum-magnesium alloys are widely used in industry thanks to their mechanical properties and corrosion resistivity. These properties are related to the magnesium content and to the applied heat treatments. Although they are already well studied, questions concerning the microstructural stability and the effect of different heat treatments are still being asked. In this work we have presented a comparative study on the behavior of the precipitation reactions during different heat treatment in two different Al-Mg alloys (Al–8 wt. % Mg and Al–12 wt. % Mg). For this purpose, we have used various experimental techniques as dilatometry, calorimetry, optical microscopy, and microhardness measurements. The obtained results shown that, the precipitation kinetics and the mechanical responses to the applied heat treatments, of the two studied alloys, are different.

Keywords: Al-Mg alloys, precipitation, hardness, heat treatments

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Authors: D. Benatiallah, A. Benatiallah, K. Bouchouicha, A. Harouz

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The development and operation of renewable energy known an important development in the world with significant growth potential. Estimate the solar radiation on terrestrial geographic locality is of extreme importance, firstly to choose the appropriate site where to place solar systems (solar power plants for electricity generation, for example) and also for the design and performance analysis of any system using solar energy. In addition, solar radiation measurements are limited to a few areas only in Algeria. Thus, we use theoretical approaches to assess the solar radiation on a given location. The Adrar region is one of the most favorable sites for solar energy use with a medium flow that exceeds 7 kWh / m2 / d and saddle of over 3500 hours per year. Our goal in this work focuses on the creation of a data bank for the given data in the energy field of the Adrar region for the period of the year and the month then the integration of these data into a geographic Information System (GIS) to estimate the solar flux on a location on the map.

Keywords: Adrar, flow, GIS, deposit potential

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Authors: Perizat Balkhimbekova

Abstract:

Evolutionary changes in cognitive world view taking place in the last decades are followed by changes in perception of the key concepts which are related to the certain lingua-cultural sphere. Also, such concepts reflect the person’s attitude to essential processes in the sphere of concepts, e.g. the opposite operations like creation and destruction. These changes in people’s life and thinking are displayed in a language world view. In order to open the maintenance of mental structures and concepts we should use language means as observable results of people’s cognitive activity. Semantics of words, free phrases and idioms should be considered as an authoritative source of information concerning concepts. The regularized set of concepts in people consciousness forms the sphere of concepts. Cognitive linguistics widely discusses the sphere of concepts as its crucial category defining it as the field of knowledge which is made of concepts. It is considered that a sphere of concepts comprises the various types of association and forms conceptual fields. As a material for the given research, the data from Russian National Corpus and British National Corpus were used. In is necessary to point out that data provided by computational studies, are intrinsic and verifiable; so that we have used them in order to get the reliable results. The procedure of study was based on such techniques as extracting of the context containing concepts of creation|destruction from the Russian National Corpus (RNC), and British National Corpus (BNC); analyzing and interpreting of those context on the basis of cognitive approach; finding of correspondence between the given concepts in the Russian and English world view. The key problem of our study is to find the correspondence between the elements of world view represented by opposite concepts such as creation and destruction. Findings: The concept of "destruction" indicates a process which leads to full or partial destruction of an object. In other words, it is a loss of the object primary essence: structures, properties, distinctive signs and its initial integrity. The concept of "creation", on the contrary, comprises positive characteristics, represents the activity aimed at improvement of the certain object, at the creation of ideal models of the world. On the other hand, destruction is represented much more widely in RNC than creation (1254 cases of the first concept by comparison to 192 cases for the second one). Our hypothesis consists in the antinomy represented by the aforementioned concepts. Being opposite both in respect of semantics and pragmatics, and from the point of view of axiology, they are at the same time complementary and interrelated concepts.

Keywords: creation, destruction, concept, world view

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Authors: Wan Nur'ashiqin Wan Mohamad, Zarina Othman, Mohd Azman Abas, Azizah Ya'acob, Rozmel Abdul Latiff

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Effective doctor-patient interaction is vital to both doctor and patient relationship. It is the cornerstone of good practice and an integral quality of a healthcare institution. This paper presented the hierarchy of the communication elements in doctor-patient interaction during medical consultations in a medical centre in Malaysia. This study adapted The Picker Patient Experience Questionnaire (2002) to obtain the information from patients. The questionnaire survey was responded by 100 patients between the ages of 20 and 50. Data collected were analysed using Rasch Measurement Model to yield the hierarchy of the communication elements in doctor-patient interaction. The findings showed that the three highest ranking on the doctor-patient interaction were doctor’s treatment, important information delivery and patient satisfaction of doctor’s responses. The results are valuable in developing the framework for communication ethics of doctors.

Keywords: communication elements, doctor-patient interaction, hierarchy, Rasch measurement model

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Authors: Zakaria Kharbouch, Mustapha Bouchaara, F. Elkouihen, A. Habbal, A. Ratnani, A. Faik

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Solid-state lithium-ion batteries have garnered increasing interest in modern energy research due to their potential for safer, more efficient, and sustainable energy storage systems. Among the critical components of these batteries, the electrolyte plays a pivotal role, with LLZO garnet-based electrolytes showing significant promise. Garnet materials offer intrinsic advantages such as high Li-ion conductivity, wide electrochemical stability, and excellent compatibility with lithium metal anodes. However, optimizing ionic conductivity in garnet structures poses a complex challenge, primarily due to the multitude of potential dopants that can be incorporated into the LLZO crystal lattice. The complexity of material design, influenced by numerous dopant options, requires a systematic method to find the most effective combinations. This study highlights the utility of machine learning (ML) techniques in the materials discovery process to navigate the complex range of factors in garnet-based electrolytes. Collaborators from the materials science and ML fields worked with a comprehensive dataset previously employed in a similar study and collected from various literature sources. This dataset served as the foundation for an extensive data refinement phase, where meticulous error identification, correction, outlier removal, and garnet-specific feature engineering were conducted. This rigorous process substantially improved the dataset's quality, ensuring it accurately captured the underlying physical and chemical principles governing garnet ionic conductivity. The data refinement effort resulted in a significant improvement in the predictive performance of the machine learning model. Originally starting at an accuracy of 0.32, the model underwent substantial refinement, ultimately achieving an accuracy of 0.88. This enhancement highlights the effectiveness of the interdisciplinary approach and underscores the substantial potential of machine learning techniques in materials science research.

Keywords: lithium batteries, all-solid-state batteries, machine learning, solid state electrolytes

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Authors: N. Ben-Mahmoud, M. Elfandi, A. Shallof

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This paper presents a methodology to design multivariable PID controllers for multi-input and multi-output systems. The proposed control strategy, which is centralized, combines of PID controllers. The proportional gains in the P controllers act as tuning parameters of (SISO) in order to modify the behavior of the loops almost independently. The design procedure consists of three steps: first, an ideal decoupler including integral action is determined. Second, the decoupler is approximated with PID controllers. Third, the proportional gains are tuned to achieve the specified performance. The proposed method is applied to representative processes.

Keywords: boiler turbine, MIMO, PID controller, control by decoupling, anti wind-up techniques

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Authors: H. Chabalala, A. Grootboom, M. Tang

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The innovative development, production, and clinical utilisation of African natural medicines requires frameworks from systematisation, innovation, registration. Afrika faces challenges when it comes to these sectors. The opposite is the case as is is evident in ancient Asian (Traditional Chinese Medicine and Indian Ayurveda and Siddha) medical systems, which are interfaced into their respective national health and educational systems. Afrikan Natural Medicines (ANMs) are yet to develop systematisation frameworks, i.e. disease characterisation and medicines classification. This paper explores classical medical systems drawn from Afrikan and Chinese experts in natural medicines. An Afrikological research methodology was used to conduct in-depth interviews with 20 key respondents selected through purposeful sampling technique. Data was summarised into systematisation frameworks for classical disease theories, patient categorisation, medicine classification, aetiology and pathogenesis of disease, diagnosis and prognosis techniques and treatment methods. It was discovered that ancient Afrika had systematic medical cosmologies, remnants of which are evident in most Afrikan cultural health practices. Parallels could be drawn from classical medical concepts of antiquity, like Chinese Taoist and Indian tantric health systems. Data revealed that both the ancient and contemporary ANM systems were based on living medical cosmologies. The study showed that African Natural Healing Systems have etiological systems, general pathogenesis knowledge, differential diagnostic techniques, comprehensive prognosis and holistic treatment regimes. Systematisation models were developed out of these frameworks, and this could be used for evaluation of clinical research, medical application including development of curriculum for high-education. It was envisaged that frameworks will pave way towards the development, production and commercialisation of ANMs. This was piloted in inclusive innovation, technology transfer and commercialisation of South African natural medicines, cosmeceuticals, nutraceuticals and health infusions. The central model presented here in will assist in curriculum development and establishment of Afrikan Medicines Hospitals and Pharmaceutical Industries.

Keywords: African Natural Medicines, Indigenous Knowledge Systems, Medical Cosmology, Clinical Application

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Authors: Abdullah Al Mamun, Talal Alkharobi

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As data size is growing up, people are became more familiar to store big amount of secret information into cloud storage. Companies are always required to need transfer massive business files from one end to another. We are going to lose privacy if we transmit it as it is and continuing same scenario repeatedly without securing the communication mechanism means proper encryption. Although asymmetric key encryption solves the main problem of symmetric key encryption but it can only encrypt limited size of data which is inapplicable for large data encryption. In this paper we propose a probable approach of pretty good privacy for encrypt big data using both symmetric and asymmetric keys. Our goal is to achieve encrypt huge collection information and transmit it through a secure communication channel for committing the business and personal privacy. To justify our method an experimental dataset from three different platform is provided. We would like to show that our approach is working for massive size of various data efficiently and reliably.

Keywords: big data, cloud computing, cryptography, hadoop, public key

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Authors: Marcos Bosques-Perez, Walter Izquierdo, Harold Martin, Liangdon Deng, Josue Rodriguez, Thony Yan, Mercedes Cabrerizo, Armando Barreto, Naphtali Rishe, Malek Adjouadi

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Aerial imagery is a powerful tool when it comes to analyzing temporal changes in ecosystems and extracting valuable information from the observed scene. It allows us to identify and assess various elements such as objects, structures, textures, waterways, and shadows. To extract meaningful information, multispectral cameras capture data across different wavelength bands of the electromagnetic spectrum. In this study, the collected multispectral aerial images were subjected to principal component analysis (PCA) to identify independent and uncorrelated components or features that extend beyond the visible spectrum captured in standard RGB images. The results demonstrate that these principal components contain unique characteristics specific to certain wavebands, enabling effective object identification and image segmentation.

Keywords: big data, image processing, multispectral, principal component analysis

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Authors: Khulud M. Rahuma, Ibrahim B. Younis

Abstract:

Assessment of petrophysical parameters are very essential for reservoir engineer. Three techniques can be used to predict reservoir properties: well logging, well testing, and core analysis. Cementation factor and saturation exponent are very required for calculation, and their values role a great effect on water saturation estimation. In this study a sensitive analysis was performed to investigate the influence of cementation factor and saturation exponent variation applying logs, and core analysis. Measurements of water saturation resulted in a maximum difference around fifteen percent.

Keywords: porosity, cementation factor, saturation exponent, formation factor, water saturation

Procedia PDF Downloads 688