Search results for: applications of big data

Authors: Muhammad Shahid, Muhammad Mansoor

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Increasing demands of contemporary applications for high strength and lightweight materials prompted the development of metal-matrix composites (MMCs). After the discovery of carbon nanotubes (CNTs) in 1991 (revealing an excellent set of mechanical properties) became one of the most promising strengthening materials for MMC applications. Additionally, the relatively low density of the nanotubes imparted high specific strengths, making them perfect strengthening material to reinforce MMCs. In the present study, aluminum-multiwalled carbon nanotubes (Al-MWCNTs) composite was prepared in an air induction furnace. The dispersion of the nanotubes in molten aluminum was assisted by inherent string action of induction heating at 790°C. During the fabrication process, multifunctional fluxes were used to avoid oxidation of the nanotubes and molten aluminum. Subsequently, the melt was cast in to a copper mold and cold rolled to 0.5 mm thickness. During metallographic examination using a scanning electron microscope, it was observed that the nanotubes were effectively dispersed in the matrix. The mechanical properties of the composite were significantly increased as compared to pure aluminum specimen i.e. the yield strength from 65 to 115 MPa, the tensile strength from 82 to 125 MPa and hardness from 27 to 30 HV for pure aluminum and Al-CNTs composite, respectively. To recognize the associated strengthening mechanisms in the nanocomposites, three foremost strengthening models i.e. shear lag model, Orowan looping and Hall-Petch have been critically analyzed; experimental data were found to be closely satisfying the shear lag model.

Keywords: carbon nanotubes, induction melting, strengthening mechanism, nanocomposite

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Authors: Eric A. Morris, Xia Liu, Yee Ka Wong, Greg J. Evans, Jeff R. Brook

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Air quality monitoring stations tend to be widely distributed and are often located far from major roadways, thus, determining where, when, and which traffic-related air pollutants (TRAPs) have the greatest impact on public health becomes a matter of extrapolation. Compact, multipollutant sensor systems are an effective solution as they enable several TRAPs to be monitored in a geospatially dense network, thus filling in the gaps between conventional monitoring stations. This work describes two applications of one such system named AirSENCE for gathering actionable air quality data relevant to smart city infrastructures. In the first application, four AirSENCE devices were co-located with traffic monitors around the perimeter of a city block in Oshawa, Ontario. This study, which coincided with the COVID-19 outbreak of 2020 and subsequent lockdown measures, demonstrated a direct relationship between decreased traffic volumes and TRAP concentrations. Conversely, road construction was observed to cause elevated TRAP levels while reducing traffic volumes, illustrating that conventional smart city sensors such as traffic counters provide inadequate data for inferring air quality conditions. The second application used two AirSENCE sensors on opposite sides of a major 2-way commuter road in Toronto. Clear correlations of TRAP concentrations with wind direction were observed, which shows that impacted areas are not necessarily static and may exhibit high day-to-day variability in air quality conditions despite consistent traffic volumes. Both of these applications provide compelling evidence favouring the inclusion of air quality sensors in current and future smart city infrastructure planning. Such sensors provide direct measurements that are useful for public health alerting as well as decision-making for projects involving traffic mitigation, heavy construction, and urban renewal efforts.

Keywords: distributed sensor network, continuous ambient air quality monitoring, Smart city sensors, Internet of Things, traffic-related air pollutants

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Authors: Sagri Sharma

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Analysis of diseases integrating multi-factors increases the complexity of the problem and therefore, development of frameworks for the analysis of diseases is an issue that is currently a topic of intense research. Due to the inter-dependence of the various parameters, the use of traditional methodologies has not been very effective. Consequently, newer methodologies are being sought to deal with the problem. Supervised Learning Algorithms are commonly used for performing the prediction on previously unseen data. These algorithms are commonly used for applications in fields ranging from image analysis to protein structure and function prediction and they get trained using a known dataset to come up with a predictor model that generates reasonable predictions for the response to new data. Gene expression profiles generated by DNA analysis experiments can be quite complex since these experiments can involve hypotheses involving entire genomes. The application of well-known machine learning algorithm - Support Vector Machine - to analyze the expression levels of thousands of genes simultaneously in a timely, automated and cost effective way is thus used. The objectives to undertake the presented work are development of a methodology to identify genes relevant to Hepatocellular Carcinoma (HCC) from gene expression dataset utilizing supervised learning algorithms and statistical evaluations along with development of a predictive framework that can perform classification tasks on new, unseen data.

Keywords: artificial intelligence, biomarker, gene expression datasets, hepatocellular carcinoma, machine learning, supervised learning algorithms, support vector machine

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Authors: Masomeh Jamshid Nejad

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Nowadays, statistical literacy is no longer a necessary skill but an essential skill with broad applications across diverse fields, especially in operational decision areas such as business management, finance, and economics. As such, learning and deep understanding of statistical concepts are essential in the context of business studies. One of the crucial topics in statistical theory and its application is the normal distribution, often called a bell-shaped curve. To interpret data and conduct hypothesis tests, comprehending the properties of normal distribution (the mean and standard deviation) is essential for business students. This requires undergraduate students in the field of economics and business management to visualize and work with data following a normal distribution. Since technology is interconnected with education these days, it is important to teach statistics topics in the context of Python, R-studio, and Microsoft Excel to undergraduate students. This research endeavours to shed light on the effect of Excel-based instruction on learners’ knowledge of statistics, specifically the central concept of normal distribution. As such, two groups of undergraduate students (from the Business Management program) were compared in this research study. One group underwent Excel-based instruction and another group relied only on traditional teaching methods. We analyzed experiential data and BBA participants’ responses to statistic-related questions focusing on the normal distribution, including its key attributes, such as the mean and standard deviation. The results of our study indicate that exposing students to Excel-based learning supports learners in comprehending statistical concepts more effectively compared with the other group of learners (teaching with the traditional method). In addition, students in the context of Excel-based instruction showed ability in picturing and interpreting data concentrated on normal distribution.

Keywords: statistics, excel-based instruction, data visualization, pedagogy

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Authors: Carine Platat, Fatima Qshadi, Ghofran Kayed, Nour Hussein, Amjad Jarrar, Habiba Ali

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Nowadays, smartphones are very popular. They are offering a variety of easy-to-use and free applications among which step counters and fitness tests. The number of users is huge making of such applications a potentially efficient new strategy to encourage people to become more active. Nonetheless, data on their reliability and validity are very scarce and when available, they are often negative and contradictory. Besides, weight status, which is likely to introduce a bias in the physical activity assessment, was not often considered. Hence, the use of these applications as motivational tool, assessment tool and in research is questionable. PACER is one of the free step counters application. Even though it is one of the best rated free application by users, it has never been tested for reliability and validity. Prior any use of PACER, this remains to be investigated. The objective of this work is to investigate the reliability and validity of the smartphone application PACER in measuring the number of steps and in assessing the cardiorespiratory fitness by the 6 minutes walking test. 20 overweight or obese students (10 male and 10 female) were recruited at the United Arab Emirate University, aged between 18 and 25 years old. Reliability and validity were tested in real life conditions and in controlled conditions by using a treadmill. Test-retest experiments were done with PACER on 2 days separated by a week in real life conditions (24 hours each time) and in controlled conditions (30 minutes on treadmill, 3km/h). Validity was tested against the pedometer OMRON in the same conditions. During treadmill test, video was recorded and steps numbers were compared between PACER, pedometer and video. The validity of PACER in estimating the cardiorespiratory fitness (VO2max) as part of the 6 minutes walking test (6MWT) was studied against the 20m shuttle running test. Reliability was studied by calculating intraclass correlation coefficients (ICC), 95% confidence interval (95%CI) and by Bland-Altman plots. Validity was studied by calculating Spearman correlation coefficient (rho) and Bland-Altman plots. PACER reliability was good in both male and female in real life conditions (p≤10-3) but only in female in controlled conditions (p=0.01). PACER was valid against OMRON pedometer in male and female in real life conditions (rho=0.94, p≤10-3 ; rho=0.64, p=0.01, in male and female respectively). In controlled conditions, PACER was not valid against pedometer. But, PACER was valid against video in female (rho=0.72, p≤10-3). PACER was valid against the shuttle run test in male and female (rho-=0.66, p=0.01 ; rho=0.51, p=0.04) to estimate VO2max. This study provides data on the reliability and viability of PACER in overweight or obese male and female young adults. Globally, PACER was shown as reliable and valid in real life conditions in overweight or obese male and female to count steps and assess fitness. This supports the use of PACER to assess and promote physical activity in clinical follow-up and community interventions.

Keywords: smartphone application, pacer, reliability, validity, steps, fitness, physical activity

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Authors: Jiwon Lee, Si-hwan Jang, Sanghyun Joo

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The popularity of emoticons are on the rise since the mobile messengers are generalized. At the same time, few problems of emoticons are also occurred due to innate characteristics of emoticons. Too many emoticons make difficult people to select one which is well-suited for user's intention. On the contrary to this, sometimes user cannot find the emoticon which expresses user's exact intention. Poor information delivery of emoticon is another problem due to a major part of current emoticons are focused on emotion delivery. In this situation, we propose a new concept of emoticons, editable emoticons, to solve above drawbacks of emoticons. User can edit the components inside the proposed editable emoticon and send it to express his exact intention. By doing so, the number of editable emoticons can be maintained reasonable, and it can express user's exact intention. Further, editable emoticons can be used as information deliverer according to user's intention and editing skills. In this paper, we propose the concept of editable emoticons and schema based editable emoticon description method. The proposed description method is 200 times superior to the compared screen capturing method in the view of transmission bandwidth. Further, the description method is designed to have compatibility since it follows MPEG-UD international standard. The proposed editable emoticons can be exploited not only mobile applications, but also various fields such as education and medical field.

Keywords: description schema, editable emoticon, emoticon transmission, mobile applications

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Authors: Akhilesh G. Naik, Dipankar Pal

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In today’s scenario, the complexity of digital signal processing (DSP) applications and various microcontroller architectures have been increasing to such an extent that the traditional approaches to multiplier design in most processors are becoming outdated for being comparatively slow. Modern processing applications require suitable pipelined approaches, and therefore, algorithms that are friendlier with pipelined architectures. Traditional algorithms like Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda architectures have been proven to be comparatively slow for pipelined architectures. These architectures, therefore, need to be optimized or combined with other architectures amongst them to enhance its performances and to be made suitable for pipelined hardware/architectures. Recently, Vedic algorithm mathematically has proven to be efficient by appearing to be less complex and with fewer steps for its output establishment and have assumed renewed importance. This paper describes and shows how the Vedic algorithm can be better suited for pipelined architectures and also can be combined with traditional architectures and algorithms for enhancing its ability even further. In this paper, we also established that for complex applications on DSP and other microcontroller architectures, using Vedic approach for multiplication proves to be the best available and efficient option.

Keywords: Wallace Tree, Radix-4 Booth, Radix-8 Booth, Dadda, Vedic, Single-Stage Karatsuba (SSK), Looped Karatsuba (LK)

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Authors: Igor V. Grigoriev

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Understanding of biological processes encoded in fungi is instrumental in addressing future food, feed, and energy demands of the growing human population. Genomics is a powerful and quickly evolving tool to understand these processes. The Fungal Genomics Program of the US Department of Energy Joint Genome Institute (JGI) partners with researchers around the world to explore fungi in several large scale genomics projects, changing the fungal genomics landscape. The key trends of these changes include: (i) rapidly increasing scale of sequencing and analysis, (ii) developing approaches to go beyond culturable fungi and explore fungal ‘dark matter,’ or unculturables, and (iii) functional genomics and multi-omics data integration. Power of comparative genomics has been recently demonstrated in several JGI projects targeting mycorrhizae, plant pathogens, wood decay fungi, and sugar fermenting yeasts. The largest JGI project ‘1000 Fungal Genomes’ aims at exploring the diversity across the Fungal Tree of Life in order to better understand fungal evolution and to build a catalogue of genes, enzymes, and pathways for biotechnological applications. At this point, at least 65% of over 700 known families have one or more reference genomes sequenced, enabling metagenomics studies of microbial communities and their interactions with plants. For many of the remaining families no representative species are available from culture collections. To sequence genomes of unculturable fungi two approaches have been developed: (a) sequencing DNA from fruiting bodies of ‘macro’ and (b) single cell genomics using fungal spores. The latter has been tested using zoospores from the early diverging fungi and resulted in several near-complete genomes from underexplored branches of the Fungal Tree, including the first genomes of Zoopagomycotina. Genome sequence serves as a reference for transcriptomics studies, the first step towards functional genomics. In the JGI fungal mini-ENCODE project transcriptomes of the model fungus Neurospora crassa grown on a spectrum of carbon sources have been collected to build regulatory gene networks. Epigenomics is another tool to understand gene regulation and recently introduced single molecule sequencing platforms not only provide better genome assemblies but can also detect DNA modifications. For example, 6mC methylome was surveyed across many diverse fungi and the highest among Eukaryota levels of 6mC methylation has been reported. Finally, data production at such scale requires data integration to enable efficient data analysis. Over 700 fungal genomes and other -omes have been integrated in JGI MycoCosm portal and equipped with comparative genomics tools to enable researchers addressing a broad spectrum of biological questions and applications for bioenergy and biotechnology.

Keywords: fungal genomics, single cell genomics, DNA methylation, comparative genomics

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Authors: Amir Hajian, Sepehr Damavandinejadmonfared

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In this paper the issue of dimensionality reduction is investigated in finger vein recognition systems using kernel Principal Component Analysis (KPCA). One aspect of KPCA is to find the most appropriate kernel function on finger vein recognition as there are several kernel functions which can be used within PCA-based algorithms. In this paper, however, another side of PCA-based algorithms -particularly KPCA- is investigated. The aspect of dimension of feature vector in PCA-based algorithms is of importance especially when it comes to the real-world applications and usage of such algorithms. It means that a fixed dimension of feature vector has to be set to reduce the dimension of the input and output data and extract the features from them. Then a classifier is performed to classify the data and make the final decision. We analyze KPCA (Polynomial, Gaussian, and Laplacian) in details in this paper and investigate the optimal feature extraction dimension in finger vein recognition using KPCA.

Keywords: biometrics, finger vein recognition, principal component analysis (PCA), kernel principal component analysis (KPCA)

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

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In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: biomedical data, learning, classifier, algorithms decision tree, knowledge extraction

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Authors: Usama Ahmed

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Data mining is the process of analyze data which are used to predict helpful information. It is the field of research which solve various type of problem. In data mining, classification is an important technique to classify different kind of data. Diabetes is most common disease. This paper implements different classification technique using Waikato Environment for Knowledge Analysis (WEKA) on diabetes dataset and find which algorithm is suitable for working. The best classification algorithm based on diabetic data is Naïve Bayes. The accuracy of Naïve Bayes is 76.31% and take 0.06 seconds to build the model.

Keywords: data mining, classification, diabetes, WEKA

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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In this paper, we propose a new distributed environment for High Performance Computing (HPC) based on mobile agents. It allows us to perform parallel programs execution as distributed one over a flexible grid constituted by a cooperative mobile agent team works. The distributed program to be performed is encapsulated on team leader agent which deploys its team workers as Agent Virtual Processing Unit (AVPU). Each AVPU is asked to perform its assigned tasks and provides the computational results which make the data and team works tasks management difficult for the team leader agent and that influence the performance computing. In this work we focused on the implementation of the Mobile Provider Agent (MPA) in order to manage the distribution of data and instructions and to ensure a load balancing model. It grants also some interesting mechanisms to manage the others computing challenges thanks to the mobile agents several skills.

Keywords: image processing, distributed environment, mobile agents, parallel and distributed computing

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Faizan Khan, Xiaodong Yang

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Internet Service Providers are driving endless demands for higher bandwidth and data throughput as new services and applications require higher bandwidth. Users want immediate and accurate data delivery. This article focuses on converting old conventional networks into passive optical networks based on time division and wavelength division multiplexing. The main focus of this research is to use a hybrid of time-division multiplexing and wavelength-division multiplexing to improve network efficiency and performance. In this paper, we design an 80 Gbps Passive Optical Network (PON), which meets the need of the Next Generation PON Stage 2 (NGPON2) proposed in this paper. The hybrid of the Time and Wavelength division multiplexing (TWDM) is said to be the best solution for the implementation of NGPON2, according to Full-Service Access Network (FSAN). To co-exist with or replace the current PON technologies, many wavelengths of the TWDM can be implemented simultaneously. By utilizing 8 pairs of wavelengths that are multiplexed and then transmitted over optical fiber for 40 Kms and on the receiving side, they are distributed among 256 users, which shows that the solution is reliable for implementation with an acceptable data rate. From the results, it can be concluded that the overall performance, Quality Factor, and bandwidth of the network are increased, and the Bit Error rate is minimized by the integration of this approach.

Keywords: bit error rate, fiber to the home, passive optical network, time and wavelength division multiplexing

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Authors: Nur Aziza Luxfiati

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Clustering is partitioning data sets into sub-sets or groups in such a way that elements certain properties have shared property settings with a high level of similarity within one group and a low level of similarity between groups. . The K-Means algorithm is one of thealgorithmsclustering as a grouping tool that is most widely used in scientific and industrial applications because the basic idea of the kalgorithm is-means very simple. In this research, applying the technique of clustering using the k-means algorithm as a method of solving the problem of national development imbalances between regions in Central Java Province based on macroeconomic indicators. The data sample used is secondary data obtained from the Central Java Provincial Statistics Agency regarding macroeconomic indicator data which is part of the publication of the 2019 National Socio-Economic Survey (Susenas) data. score and determine the number of clusters (k) using the elbow method. After the clustering process is carried out, the validation is tested using themethodsBetween-Class Variation (BCV) and Within-Class Variation (WCV). The results showed that detection outlier using z-score normalization showed no outliers. In addition, the results of the clustering test obtained a ratio value that was not high, namely 0.011%. There are two district/city clusters in Central Java Province which have economic similarities based on the variables used, namely the first cluster with a high economic level consisting of 13 districts/cities and theclustersecondwith a low economic level consisting of 22 districts/cities. And in the cluster second, namely, between low economies, the authors grouped districts/cities based on similarities to macroeconomic indicators such as 20 districts of Gross Regional Domestic Product, with a Poverty Depth Index of 19 districts, with 5 districts in Human Development, and as many as Open Unemployment Rate. 10 districts.

Keywords: clustering, K-Means algorithm, macroeconomic indicators, inequality, national development

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Authors: Artion Kashuri, Rozana Liko

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In this paper, some generalization integral inequalities of Hermite–Hadamard type for functions whose derivatives are s–convex in modulus are given by using k–fractional integrals. Some applications to special means are obtained as well. Some known versions are recovered as special cases from our results. We note that our inequalities can be viewed as new refinements of the previous results. Finally, our results have a deep connection with various fractional integral operators and interested readers can find new interesting results using our idea and technique as well.

Keywords: Hermite-Hadamard's inequalities, Hölder's inequality, k-Riemann-Liouville fractional integral, special means

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Authors: Bagireanu Astrid, Bros-Williamson Julio, Duncheva Mila, Currie John

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Digital Twins (DT) are an innovative concept of cyber-physical integration of data between an asset and its virtual replica. They have originated in established industries such as manufacturing and aviation and have garnered increasing attention as a potentially transformative technology within the built environment. With the potential to support decision-making, real-time simulations, forecasting abilities and managing operations, DT do not fall under a singular scope. This makes defining and leveraging the potential uses of DT a potential missed opportunity. Despite its recognised potential in established industries, literature on DT in the built environment remains limited. Inadequate attention has been given to the implementation of DT in construction projects, as opposed to its operational stage applications. Additionally, the absence of a standardised definition has resulted in inconsistent interpretations of DT in both industry and academia. There is a need to consolidate research to foster a unified understanding of the DT. Such consolidation is indispensable to ensure that future research is undertaken with a solid foundation. This paper aims to present a comprehensive systematic literature review on the role of DT in the built environment. To accomplish this objective, a review and thematic analysis was conducted, encompassing relevant papers from the last five years. The identified papers are categorised based on their specific areas of focus, and the content of these papers was translated into a through classification of DT. In characterising DT and the associated data processes identified, this systematic literature review has identified 6 DT opportunities specifically relevant to the built environment: Facilitating collaborative procurement methods, Supporting net-zero and decarbonization goals, Supporting Modern Methods of Construction (MMC) and off-site manufacturing (OSM), Providing increased transparency and stakeholders collaboration, Supporting complex decision making (real-time simulations and forecasting abilities) and Seamless integration with Internet of Things (IoT), data analytics and other DT. Finally, a discussion of each area of research is provided. A table of definitions of DT across the reviewed literature is provided, seeking to delineate the current state of DT implementation in the built environment context. Gaps in knowledge are identified, as well as research challenges and opportunities for further advancements in the implementation of DT within the built environment. This paper critically assesses the existing literature to identify the potential of DT applications, aiming to harness the transformative capabilities of data in the built environment. By fostering a unified comprehension of DT, this paper contributes to advancing the effective adoption and utilisation of this technology, accelerating progress towards the realisation of smart cities, decarbonisation, and other envisioned roles for DT in the construction domain.

Keywords: built environment, design, digital twins, literature review

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Authors: Shivani A. Singh, Pravin S. More

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In the present inspection, we indicate the falsification of Fe-doped graphene nanoparticles by modified Hummers method. Structural and physiochemical properties of the resulting pallets were explored with the help of ultraviolet-visible spectroscopy (UV-Vis), Fourier transform infrared spectroscopy (FTIR), X-ray powder diffraction (XRD) and scanning electron microscopy (SEM), Photoluminescence spectroscopy (PL) for graphene sample exhibits absorption peaks ~248nm. Pure graphene shows PL peak at 348 nm. After doping of Fe with graphene the PL peak shifted from 348 nm to 332 nm. The oxidation degree, i.e. the relative amount of oxygen functional groups was estimated from the relative intensities of the oxygen related bands (ORB) in the FTIR measurements. These analyses show that this modified material can be useful for gas sensing applications and to be used in diverse areas.

Keywords: chemical doping, graphene, gas sensing, sensing

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Authors: Seyed Ebrahim Hosseini, Shahbaz Pervez

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As people go through aging, maintenance and improvement of the quality of life become more important for them. To know the role of smartphone technology and communications applications on quality of life, a sample group of old people living in Dar-Iran was selected for a quasi-experimental study. The participants were registered senior inhabitants from public health centers in Dar, Iran in 2022. The number of participants was 39. Participants were randomly categorized into intervention and control groups. A validated Persian version of the Control, Autonomy, Self-realisation, Pleasure scale (CASP-19) scale questionnaire was provided for them which answers were used for the quality of life assessment. The paired t-test between pre-and post-test (t= -8.45, p<.00), post-and follow-up-test (t= -2.12, p=.01), and pre-test and the follow-up test (t= -8.27, p<.00) in the intervention group revealed a considerable mean difference. Based on the results of paired t-test for the control group, this was not significant between pre-test and post-test (t= 1.26, p=.15), post-test and follow-up test (t= .33, p=.67) and pre-test and follow-up test (t= 1.85, p=.08) for quality of life. Considering the educational training associated with it, this study aimed at helping families and aging field practitioners to understand the essentiality of modern communication technology teaching in promoting a greater life quality of the elderly’s community.

Keywords: Iranian elderly, quality of life, smartphone, social applications, CASP-19

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Authors: Olusegun F. Adebowale

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Research has confirmed that the emergence of information technology is significantly reflected in the field of psychology and its related disciplines due to its widespread use at reasonable price and its user-friendliness. It is consequently affecting ordinary life in many areas like shopping, advertising, corresponding and educating. Specifically the innovations of computer technology led to several new forms of communication, all with implications and applicability for counselling and psychotherapy practices. This is premise on which online counselling is based. Most institutions of higher learning in Nigeria have established their presence on the Internet and have deployed a variety of applications through ICT. Some are currently attempting to include counselling services in such applications with the belief that many counselling needs of students are likely to be met. This study therefore explored different challenges and preferences students present in online counselling interaction in a given Nigerian university with the view to guide new universities that may want to invest into these areas as to necessary preparations and referral requirements. The study is a mixed method research incorporating qualitative and quantitative methodologies to sample the preferences and concerns students express in online interaction. The sample comprised all the 876 students who visited the university online counselling platform either voluntarily, by invitation or by referral. The instrument for data collection was the online counselling platform of the university 'OAU Online counsellors'. The period of data collection spanned between January 2011 and October 2012. Data were analysed quantitatively (using percentages and Mann-Whitney U test) and qualitatively (using Interpretative Phenomenological Analysis (IPA)). The results showed that the students seem to prefer real-time chatting as their online medium of communicating with the online counsellor. The majority of students resorted to e-mail when their effort to use real-time chatting were becoming thwarted. Also, students preferred to enter into online counselling relationships voluntarily to other modes of entry. The results further showed that the prevalent counselling needs presented by students during online counselling sessions were mainly in the areas of social interaction and academic/educational concerns. Academic concerns were found to be prevalent, in form of course offerings, studentship matters and academic finance matters. The personal/social concerns were in form of students’ welfare, career related concerns and relationship matters. The study concludes students’ preferences include voluntary entry into online counselling, communication by real-time chatting and a specific focus on their academic concerns. It also recommends that all efforts should be made to encourage students’ voluntary entry into online counselling through reliable and stable internet infrastructure that will be able to support real-time chatting.

Keywords: online, counselling, needs, preferences

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Authors: I. McAndrew, K. L. Witcher, E. Navarro

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This paper presents the theory and application of low-speed flight for unmanned aerial vehicles when subjected to surface environmental conditions such as ice on the leading edge and upper surface. A model was developed and tested in a wind tunnel to see how theory compares with practice at various speed including take-off, landing and operational applications where head winds substantially alter parameters. Furthermore, a comparison is drawn with maned operations and how that this subject is currently under-supported with accurate theory or knowledge for designers or operators to make informed decision or accommodate individual applications. The effects of ice formation for lift and drag are determined for a range of different angles of attacks.

Keywords: aerodynamics, environmental influences, glide path ratio, unmanned vehicles

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Authors: Ardavan Zamanpour, Somaieh Yassari

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ZigBee protocol network was developed in industries and MIT laboratory in 1997. ZigBee is a wireless networking technology by alliance ZigBee which is designed to low board and low data rate applications. It is a Protocol which connects between electrical devises with very low energy and cost. The first version of IEEE 802.15.4 which was formed ZigBee was based on 2.4GHZ MHZ 912MHZ 868 frequency band. The name of system is often reminded random directions that bees (BEES) traversing during pollination of products. Such as alloy of the ways in which information packets are traversed within the mesh network. This paper aims to study the performance and effectiveness of this protocol in wireless networks.

Keywords: ZigBee, protocol, wireless, networks

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Authors: K. Akherfi, H. Harroud

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Cloud Computing (CC) and Mobile Cloud Computing (MCC) have advanced rapidly the last few years. Today, MCC undergoes fast improvement and progress in terms of hardware (memory, embedded sensors, power consumption, touch screen, etc.) software (more and more sophisticated mobile applications) and transmission (higher data transmission rates achieved with different technologies such as 3Gs). This paper presents a review on the concept of CC and MCC. Then, it discusses what has been done regarding middleware in CC and MCC. Later, it shows the architecture of our proposed middleware along with its functionalities which will be provided to mobile clients in order to overcome the well-known problems (such as low battery power, slow CPU speed and, little memory etc.).

Keywords: context-aware, cloud computing, middleware, mobile cloud computing

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Authors: Hanan. Al Chaghouri, Mohammad Azad Malik, P. John Thomas, Paul O’Brien

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The process of assembling metal nanoparticles at the interface of two liquids has received a great interest over the past few years due to a wide range of important applications and their unusual properties compared to bulk materials. We present a low cost, simple and cheap synthesis of metal nanoparticles, core/shell structures and semiconductors followed by assembly of these particles between immiscible liquids. The aim of this talk is divided to three parts: firstly, to describe the achievement of a closed loop recycling for producing cadmium sulphide as powders and/or nanostructured thin films for solar cells or other optoelectronic devices applications by using a different chain length of commercially available secondary amines of dithiocarbamato complexes. The approach can be extended to other metal sulphides such as those of Zn, Pb, Cu, or Fe and many transition metals and oxides. Secondly, to synthesis significantly cheaper magnetic particles suited for the mass market. Ni/NiO nanoparticles with ferromagnetic properties at room temperature were among the smallest and strongest magnets (5 nm) were made in solution. The applications of this work can be applied to produce viable storage devices and the other possibility is to disperse these nanocrystals in solution and use it to make ferro-fluids which have a number of mature applications. The third part is about preparing and assembling of submicron silver, cobalt and nickel particles by using polyol methods and liquid/liquid interface, respectively. Noble metal like gold, copper and silver are suitable for plasmonic thin film solar cells because of their low resistivity and strong interactions with visible light waves. Silver is the best choice for solar cell application since it has low absorption losses and high radiative efficiency compared to gold and copper. Assembled cobalt and nickel as films are promising for spintronic, magnetic and magneto-electronic and biomedics.

Keywords: assembling nanoparticles, liquid/liquid interface, thin film, core/shell, solar cells, recording media

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Authors: Vojtěch Gybas, Libor Klubal, Kateřina Kostolányová

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This case study responds to the current trends in ICT. Mobile Touch iPads can provide very good assistance to disabled seniors. The intuitive tablet environment, the possibility of the formation environment and its portability, has a very positive effect on the use of particular communication. For comparison, using a conventional PC/notebook, word processor, keyboard and computer mouse compared to the iPad and selected applications. The results of this case study show that the use of mobile touch devices iPad for seniors with mental retardation is a great benefit. These devices do not require high demands on graphomotorics like a standard PC devices.

Keywords: ICT, iPad, handicapped seniors, communication, computer/notebook, applications, text editor

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Authors: Ioannis Andrianakis, Vasileios Gkatas, Nikos Eleftheriadis, Alexios Ellinidis, Ermioni Avramidou

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pscmsForecasting is an open-source web service that implements a variety of time series forecasting algorithms and exposes them to the user via the ubiquitous HTTP protocol. It allows developers to enhance their applications by adding time series forecasting functionalities through an intuitive and easy-to-use interface. This paper provides some background on time series forecasting and gives details about the implemented algorithms, aiming to enhance the end user’s understanding of the underlying methods before incorporating them into their applications. A detailed description of the web service’s interface and its various parameterizations is also provided. Being an open-source project, pcsmsForecasting can also be easily modified and tailored to the specific needs of each application.

Keywords: time series, forecasting, web service, open source

Procedia PDF Downloads 71

Authors: Roberta Mugellesi Dow

Abstract:

As the climate crisis becomes unignorable, it is imperative that new services are developed addressing not only the needs of customers but also taking into account its impact on the environment. The Telecommunication and Integrated Application (TIA) Directorate of ESA is supporting the green transition with particular attention to the sustainable mobility.“Accelerating the shift to sustainable and smart mobility” is at the core of the European Green Deal strategy, which seeks a 90% reduction in related emissions by 2050 . Transforming the way that people and goods move is essential to increasing mobility while decreasing environmental impact, and transport must be considered holistically to produce a shared vision of green intermodal mobility. The use of space technologies, integrated with terrestrial technologies, is an enabler of smarter traffic management and increased transport efficiency for automated and connected multimodal mobility. Satellite connectivity, including future 5G networks, and digital technologies such as Digital Twin, AI, Machine Learning, and cloud-based applications are key enablers of sustainable mobility.SatCom is essential to ensure that connectivity is ubiquitously available, even in remote and rural areas, or in case of a failure, by the convergence of terrestrial and SatCom connectivity networks, This is especially crucial when there are risks of network failures or cyber-attacks targeting terrestrial communication. SatCom ensures communication network robustness and resilience. The combination of terrestrial and satellite communication networks is making possible intelligent and ubiquitous V2X systems and PNT services with significantly enhanced reliability and security, hyper-fast wireless access, as well as much seamless communication coverage. SatNav is essential in providing accurate tracking and tracing capabilities for automated vehicles and in guiding them to target locations. SatNav can also enable location-based services like car sharing applications, parking assistance, and fare payment. In addition to GNSS receivers, wireless connections, radar, lidar, and other installed sensors can enable automated vehicles to monitor surroundings, to ‘talk to each other’ and with infrastructure in real-time, and to respond to changes instantaneously. SatEO can be used to provide the maps required by the traffic management, as well as evaluate the conditions on the ground, assess changes and provide key data for monitoring and forecasting air pollution and other important parameters. Earth Observation derived data are used to provide meteorological information such as wind speed and direction, humidity, and others that must be considered into models contributing to traffic management services. The paper will provide examples of services and applications that have been developed aiming to identify innovative solutions and new business models that are allowed by new digital technologies engaging space and non space ecosystem together to deliver value and providing innovative, greener solutions in the mobility sector. Examples include Connected Autonomous Vehicles, electric vehicles, green logistics, and others. For the technologies relevant are the hybrid satcom and 5G providing ubiquitous coverage, IoT integration with non space technologies, as well as navigation, PNT technology, and other space data.

Keywords: sustainability, connectivity, mobility, satellites

Procedia PDF Downloads 116

Authors: Azadeh Bashiri

Abstract:

Introduction: Lack of proper diagnosis and inadequate treatment of asthma leads to physical and financial complications. This study aimed to use data mining techniques and creating a neural network intelligent system for diagnosis of asthma. Methods: The study population is the patients who had visited one of the Lung Clinics in Tehran. Data were analyzed using the SPSS statistical tool and the chi-square Pearson's coefficient was the basis of decision making for data ranking. The considered neural network is trained using back propagation learning technique. Results: According to the analysis performed by means of SPSS to select the top factors, 13 effective factors were selected, in different performances, data was mixed in various forms, so the different models were made for training the data and testing networks and in all different modes, the network was able to predict correctly 100% of all cases. Conclusion: Using data mining methods before the design structure of system, aimed to reduce the data dimension and the optimum choice of the data, will lead to a more accurate system. Therefore, considering the data mining approaches due to the nature of medical data is necessary.

Keywords: asthma, data mining, Artificial Neural Network, intelligent system

Procedia PDF Downloads 262

Authors: Maanav M. Patel, Aarsh S. Mistry, Yash A. Dhaduk

Abstract:

Nowadays, only a small percentage of waste tyres are being land-filled. The Recycled Tyres Rubber is being used in new tyres, in tyre-derived fuel, in civil engineering applications and products, in molded rubber products, in agricultural uses, recreational and sports applications and in rubber modified asphalt applications. The benefits of using rubber modified asphalts are being more widely experienced and recognized, and the incorporation of tyres into asphalt is likely to increase. The technology with much different evidence of success demonstrated by roads built in the last 40 years is the rubberised asphalt mixture obtained through the so-called ‘‘wet process’’ which involves the utilisation of the Recycled Tyre Rubber Modified Bitumen (RTR-MBs). Since 1960s, asphalt mixtures produced with RTRMBs have been used in different parts of the world as solutions for different quality problems and, despite some downsides, in the majority of the cases they have demonstrated to enhance performance of road’s pavement. The present study aims in investigating the experimental performance of the bitumen modified with 15% by weight of crumb rubber varying its sizes. Four different categories of size of crumb rubber will be used, which are coarse (1 mm - 600 μm); medium size (600 μm - 300 μm); fine (300 μm150 μm); and superfine (150 μm - 75 μm). Common laboratory tests will be performed on the modified bitumen using various sizes of crumb rubber and thus analyzed. Marshall Stability method is adopted for mix design.

Keywords: Bitumen, CRMB, Marshall Stability Test, Pavement

Procedia PDF Downloads 136

Authors: Somoshree Datta, Chithra A. V., Sandeep Nithyanandan, Smitha K. K.

Abstract:

Space exploration has always been at the forefront of technological innovation, pushing the boundaries of human knowledge and capabilities. In recent years, the integration of Artificial Intelligence (AI) has revolutionized the field, offering unprecedented opportunities to enhance the efficiency, autonomy and intelligence of space missions. This survey paper aims to provide a comprehensive overview of the multifaceted applications of AI in space exploration, exploring the evolution of this synergy and its impact on mission success, scientific discovery, and the future of space endeavors. Indian Space Research Organization (ISRO) has achieved great feats in the recent moon mission (Chandrayaan-3) and sun mission (Aditya L1) by using artificial intelligence to enhance moon navigation as well as help young scientists to study the Sun even before the launch by creating AI-generated image visualizations. Throughout this survey, we will review key advancements, challenges and prospects in the intersection of AI and space exploration. As humanity continues its quest to explore the cosmos, the integration of AI promises to unlock new frontiers, reshape mission architectures, and redefine our understanding of the universe. This survey aims to serve as a comprehensive resource for researchers, engineers and enthusiasts interested in the dynamic and evolving landscape of AI applications in space exploration.

Keywords: artificial intelligence, space exploration, space missions, deep learning

Procedia PDF Downloads 12

Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

Abstract:

The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

Procedia PDF Downloads 159