Search results for: volatile memory

Authors: Basem Kamal Abasakhiroun Farag

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Fashion, like many other areas of design, has undergone numerous developments over the centuries. The aim of the article is to recognize and evaluate the importance of advanced technologies in fashion design and to examine how they are transforming the role of contemporary fashion designers by transforming the creative process. It also discusses how contemporary culture is involved in such developments and how it influences fashion design in terms of conceptualization and production. The methodology used is based on examining various examples of the use of technology in fashion design and drawing parallels between what was feasible then and what is feasible today. Comparison of case studies, examples of existing fashion designs and experiences with craft methods; We therefore observe patterns that help us predict the direction of future developments in this area. Discussing the technological elements in fashion design helps us understand the driving force behind the trend. The research presented in the article shows that there is a trend towards significantly increasing interest and progress in the field of fashion technology, leading to the emergence of hybrid artisanal methods. In summary, as fashion technologies advance, their role in clothing production is becoming increasingly important, extending far beyond the humble sewing machine.

Keywords: fashion, identity, such, textiles ambient intelligence, proximity sensors, shape memory materials, sound sensing garments, wearable technology bio textiles, fashion trends, nano textiles, new materials, smart textiles, techno textiles fashion design, functional aesthetics, 3D printing.

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Authors: Ayanda Ndokwana, Stanley Fore

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Industrial prosperity and rapid expansion of human population in South Africa over the past two decades, have increased the use of conventional fossil fuels such as crude oil, coal and natural gas to meet the country’s energy demands. However, the inevitable depletion of fossil fuel reserves, global volatile oil price and large carbon footprint are some of the crucial reasons the South African Government needs to make a considerable investment in the development of the biofuel industry. In South Africa, this industry is still at the introductory stage with no large scale manufacturing plant that has been commissioned yet. Bioethanol is a potential replacement of gasoline which is a fossil fuel that is used in motor vehicles. Using bioethanol for the transport sector as a source of fuel will help Government to save heavy foreign exchange incurred during importation of oil and create many job opportunities in rural farming. In 2007, the South African Government developed the National Biofuels Industrial Strategy in an effort to make provision for support and attract investment in bioethanol production. However, capital investment in the production of bioethanol on a large scale, depends on the sound economic assessment of the available manufacturing technologies. The aim of this study is to evaluate the profitability of an advanced bioethanol manufacturing technology which uses maize as a feedstock in South Africa. The impact of fiber or bran fractionation in this technology causes it to possess a number of merits such as energy efficiency, low capital expenditure, and profitability compared to a conventional dry-mill bioethanol technology. Quantitative techniques will be used to collect and analyze numerical data from suitable organisations in South Africa. The dependence of three profitability indicators such as the Discounted Payback Period (DPP), Net Present Value (NPV) and Return On Investment (ROI) on plant capacity will be evaluated. Profitability analysis will be done on the following plant capacities: 100 000 ton/year, 150 000 ton/year and 200 000 ton/year. The plant capacity with the shortest Discounted Payback Period, positive Net Present Value and highest Return On Investment implies that a further consideration in terms of capital investment is warranted.

Keywords: bioethanol, economic evaluation, maize, profitability indicators

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Authors: Bitan Kumar Sarkar, Akashdeep Agarwal, Rajib Dey, Gopes Chandra Das

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The rapid depletion of high-grade iron ore (Fe₂O₃) has gained attention on the use of other sources of iron ore. Titaniferous magnetite ore (TMO) is a special type of magnetite ore having high titania content (23.23% TiO₂ present in this case). Due to high TiO₂ content and high density, TMO cannot be treated by the conventional smelting reduction. In this present work, the TMO has been collected from high-grade metamorphic terrain of the Precambrian Chotanagpur gneissic complex situated in the eastern part of India (Shaltora area, Bankura district, West Bengal) and the hematite ore has been collected from Visakhapatnam Steel Plant (VSP), Visakhapatnam. At VSP, iron ore is received from Bailadila mines, Chattisgarh of M/s. National Mineral Development Corporation. The preliminary characterization of TMO and hematite ore (HMO) has been investigated by WDXRF, XRD and FESEM analyses. Similarly, good quality of coal (mainly coking coal) is also getting depleted fast. The basic purpose of this work is to find how lean grade coal can be utilised along with TMO for smelting to produce pig iron. Lean grade coal has been characterised by using TG/DTA, proximate and ultimate analyses. The boiler grade coal has been found to contain 28.08% of fixed carbon and 28.31% of volatile matter. TMO fines (below 75 μm) and HMO fines (below 75 μm) have been separately agglomerated with lean grade coal fines (below 75 μm) in the form of briquettes using binders like bentonite and molasses. These green briquettes are dried first in oven at 423 K for 30 min and then reduced isothermally in tube furnace over the temperature range of 1323 K, 1373 K and 1423 K for 30 min & 60 min. After reduction, the reduced briquettes are characterized by XRD and FESEM analyses. The best reduced TMO and HMO samples are taken and blended in three different weight percentage ratios of 1:4, 1:8 and 1:12 of TMO:HMO. The chemical analysis of three blended samples is carried out and degree of metallisation of iron is found to contain 89.38%, 92.12% and 93.12%, respectively. These three blended samples are briquetted using binder like bentonite and lime. Thereafter these blended briquettes are separately smelted in raising hearth furnace at 1773 K for 30 min. The pig iron formed is characterized using XRD, microscopic analysis. It can be concluded that 90% yield of pig iron can be achieved when the blend ratio of TMO:HMO is 1:4.5. This means for 90% yield, the maximum TMO that could be used in the blend is about 18%.

Keywords: briquetting reduction, lean grade coal, smelting reduction, TMO

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Authors: Taysir Soliman

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One of the current popular clustering techniques is Spectral Clustering (SC) because of its advantages over conventional approaches such as hierarchical clustering, k-means, etc. and other techniques as well. However, one of the disadvantages of SC is the time consuming process because it requires computing the eigenvectors. In the past to overcome this disadvantage, a number of attempts have been proposed such as the Power Iteration Clustering (PIC) technique, which is one of versions from SC; some of PIC advantages are: 1) its scalability and efficiency, 2) finding one pseudo-eigenvectors instead of computing eigenvectors, and 3) linear combination of the eigenvectors in linear time. However, its worst disadvantage is an inter-class collision problem because it used only one pseudo-eigenvectors which is not enough. Previous researchers developed Deflation-based Power Iteration Clustering (DPIC) to overcome problems of PIC technique on inter-class collision with the same efficiency of PIC. In this paper, we developed Parallel DPIC (PDPIC) to improve the time and memory complexity which is run on apache spark framework using sparse matrix. To test the performance of PDPIC, we compared it to SC, ESCG, ESCALG algorithms on four small graph benchmark datasets and nine large graph benchmark datasets, where PDPIC proved higher accuracy and better time consuming than other compared algorithms.

Keywords: spectral clustering, power iteration clustering, deflation-based power iteration clustering, Apache spark, large graph

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Authors: Parker Townes, Prabdeep Panesar, Chunlin Liu, Soo Youn Lee, Dan Devoe, Paul D. Arnold, Jennifer Crosbie, Russell Schachar

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Attention-deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are impairing childhood neurodevelopmental disorders with problems in executive functions. Executive functions are higher-level mental processes essential for daily functioning and goal attainment. There is genetic and neural overlap between ADHD and ASD. The aim of this meta-analysis was to evaluate if pediatric ASD and ADHD have distinct executive function profiles. This review was completed following Cochrane guidelines. Fifty-eight articles were identified through database searching, followed by a blinded screening in duplicate. A meta-analysis was performed for all task performance metrics evaluated by at least two articles. Forty-five metrics from 24 individual tasks underwent analysis. No differences were found between youth with ASD and ADHD in any domain under direct comparison. However, individuals with ASD and ADHD exhibited deficient attention, flexibility, visuospatial abilities, working memory, processing speed, and response inhibition compared to controls. No deficits in planning were noted in either disorder. Only 11 studies included a group with comorbid ASD+ADHD, making it difficult to determine whether common executive function deficits are a function of comorbidity. Further research is needed to determine if comorbidity accounts for the apparent commonality in executive function between ASD and ADHD.

Keywords: autism spectrum disorder, ADHD, neurocognition, executive function, youth

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Authors: Poteet Frances, Glovinski Ira

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INTRODUCTION: The interoceptive nervous system continuously senses chemical and anatomical changes and helps you recognize, understand, and feel what’s going on inside your body so it is important for energy regulation, memory, affect, and sense of self. A newborn needs predictable routines rather than confusion/chaos to make connections between internal experiences and emotions. AIM: Current legal protocols of removing babies from drug-addicted mothers impact the critical window of bonding. The newborn’s brain is social and the attachment process influences a child’s development which begins immediately after birth through nourishment, comfort, and protection. DESCRIPTION: Our project aims to educate drug-addicted mothers, and medical, nursing, and social work professionals on interoceptive concepts and practices to sustain the mother/newborn relationship. A mother’s interoceptive knowledge predicts children’s emotion regulation and social skills in middle childhood. CONCLUSION: When mothers develop an awareness of their inner bodily sensations, they can self-regulate and be emotionally available to co-regulate (support their newborn during distressing emotions and sensations). Our project has enhanced relationship preservation (mothers understand how their presence matters) and the overall mother/newborn connection.

Keywords: drug-addiction, interoception, legal, mothers, newborn, self-regulation

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Authors: Esmail Sadipour

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The use of social networks is increasing day by day in all societies. The purpose of this research was to know the relationship between the use of social networks (Instagram, WhatsApp, and Telegram) with executive functions and academic performance in first-year female high school students. This research was applied in terms of purpose, quantitative in terms of data type, and correlational in terms of technique. The population of this research consisted of all female high school students in the first year of district 2 of Tehran. Using Green's formula, the sample size of 150 people was determined and selected by cluster random method. In this way, from all 17 high schools in district 2 of Tehran, 5 high schools were selected by a simple random method and then one class was selected from each high school, and a total of 155 students were selected. To measure the use of social networks, a researcher-made questionnaire was used, the Barclay test (2012) was used for executive functions, and last semester's GPA was used for academic performance. Pearson's correlation coefficient and multivariate regression were used to analyze the data. The results showed that there is a negative relationship between the amount of use of social networks and self-control, self-motivation and time self-management. In other words, the more the use of social networks, the fewer executive functions of students, self-control, self-motivation, and self-management of their time. Also, with the increase in the use of social networks, the academic performance of students has decreased.

Keywords: social networks, executive function, academic performance, working memory

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Authors: José de Jesús Rivero Oliva, Jesús Salomón Llanes, Manuel Perdomo Ojeda, Antonio Torres Valle

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Combinatorial explosion is a common problem to both predominant methods for solving fault trees: Minimal Cut Set (MCS) approach and Binary Decision Diagram (BDD). High memory consumption impedes the complete solution of very complex fault trees. Only approximated non-conservative solutions are possible in these cases using truncation or other simplification techniques. The paper proposes a method (CSolv+) for solving complex fault trees, without any possibility of combinatorial explosion. Each individual MCS is immediately discarded after its contribution to the basic events importance measures and the Top gate Upper Bound Probability (TUBP) has been accounted. An estimation of the Top gate Exact Probability (TEP) is also provided. Therefore, running in a computer cluster, CSolv+ will guarantee the complete solution of complex fault trees. It was successfully applied to 40 fault trees from the Aralia fault trees database, performing the evaluation of the top gate probability, the 1000 Significant MCSs (SMCS), and the Fussell-Vesely, RRW and RAW importance measures for all basic events. The high complexity fault tree nus9601 was solved with truncation probabilities from 10-²¹ to 10-²⁷ just to limit the execution time. The solution corresponding to 10-²⁷ evaluated 3.530.592.796 MCSs in 3 hours and 15 minutes.

Keywords: system reliability analysis, probabilistic risk assessment, fault tree analysis, basic events importance measures

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Authors: Pedro Dias, Lurdes Verissimo, Maria Joao Baptista, Ana Pinheiro, Patricia Oliveira-Silva, Sofia Serra, Daniela Coimbra

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To achieve a high standard in performance, a musician must be well in all aspects of health (physical, mental and social). Anxiety in performance is related to the high level of coordination and skill needed in performance, as well as to the public evaluation of the performer. It affects some key elements of performance, such as concentration, memory, motor coordination, and relaxation. This work presents two studies focused on the adaptation and evaluation of the psychometric properties of the Music Performance Anxiety Inventory (MPAI-A) in young Portuguese music students. The first study was conducted with a sample of 161 adolescent music students, who responded to the Portuguese version of this instrument, and to the State-Trait Anxiety Inventory for Children (STAIC-c2). Validity and reliability were examined, and this measure revealed robust psychometric properties in this sample. The second study aimed to adapt the MPAI to a younger population (one hundred 8-10 years-old music students). Again, the MPAI and the STAIC c-2 were used in this study. Exploratory factor analysis, correlations, and internal consistency were used to evaluate the final children version of the instrument (MPAI-C), presenting a different factor structure compared to the adolescent version (10 items organized in 2 factors) and high levels of reliability and convergent validity.

Keywords: anxiety, assessment, children and adolescents, music performance

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Authors: Luisa Maria Arrechea Fajardo, Luz Stella Cadavid Rodriguez

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Fish is one of the most commercialized foods worldwide. However, this industry only takes advantage of about 55% of the product's weight, the rest is converted into waste, which is mainly composed of viscera, gills, scales and spines. Consequently, if these wastes are not used or disposed of properly, they cause serious environmental impacts. This is the case of Tumaco (Colombia), the second largest producer of marine fisheries on the Colombian Pacific coast, where artisanal fishermen process more than 50% of the commercialized volume. There, fishing waste is disposed primarily in the ocean, causing negative impacts on the environment and society. Therefore, in the present research, a proposal was made to take advantage of fishing waste through anaerobic treatments, through which it is possible to obtain products with high added value from organic waste. The research was carried out in four stages. First, the production of volatile fatty acids (VFA) in semi-continuous 4L reactors was studied, evaluating three hydraulic retention times (HRT) (10, 7 and 5 days) with four organic loading rates (OLR) (16, 14, 12 and 10 gVS/L/day), the experiment was carried out for 150 days. Subsequently, biogas production was evaluated from the solid digestate generated in the VFA production reactors, initially evaluating the biochemical methane potential (BMP) of 4 total solid concentrations (1, 2, 4 and 6% TS), for 40 days and then, with the optimum TS concentration (2 gVS/L/day), 2 HRT (15 and 20 days) in semi-continuous reactors, were evaluated for 100 days. Finally, the integration of the processes was carried out with the best conditions found, a first phase of VFA production from fishing waste and a second phase of biogas production from unrecovered VFAs and unprocessed material Additionally, an VFA membrane extraction system was included. In the first phase, a liquid digestate with a concentration and VFA production yield of 59.04 gVFA/L and 0.527 gVFA/gVS, respectively, was obtained, with the best condition found (HRT:7 days and OLR: 16 gVS/L/día), where acetic acid and isobutyric acid were the predominant acids. In the second phase of biogas production, a BMP of 0.349 Nm3CH4/KgVS was reached, and it was found as best HRT 20 days. In the integration, the isovaleric, butyric and isobutyric acid were the VFA with the highest percentage of extraction, additionally a 106.67% increase in biogas production was achieved. This research shows that anaerobic treatments are a promising technology for an environmentally safe management of fishing waste and presents the basis of a possible biorefinery.

Keywords: biogas production, fishing waste, VFA membrane extraction, VFA production

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Authors: Theodorou Kyriaki, Ypsilantis George

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Vocabulary learning has attracted a lot of attention in recent years, contrary to the neglected part of the past. Along with the interest in finding successful vocabulary teaching strategies, many scholars focused on locating learning strategies used by language learners. As a result, more and more studies in the area of language pedagogy have been investigating the use of strategies in vocabulary learning by different types of learners. A common instrument in this field is the questionnaire, a tool of work that was enriched by questions involving current technology, and it was further implemented to a sample of 300 Greek students whose age varied from 9 and 17 years. Strategies located were grouped into the three categories of memory, cognitive, and compensatory type and associations between these dependent variables were investigated. In addition, relations between dependent and independent variables (such as age, sex, type of school, cultural background, and grade in English) were pursued to investigate the impact on strategy selection. Finally, results were compared to findings of other studies in the same field to contribute to a hypothesis of ethnic differences in strategy selection. Results initially discuss preferred strategies of all participants and further indicate that: a) technology affects strategy selection while b) differences between ethnic groups are not statistically significant. A number of successful strategies are presented, resulting from correlations of strategy selection and final school grade in English.

Keywords: acquisition of English, internet technology, research among Greek students, vocabulary learning strategies

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: P. Joris, E. Lombard, X. Cameleyre, G. Navarro, A. Paillet, N. Gorret, S. E. Guillouet

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Today, on the international space station, multiple supplies are needed per year to supply food and spare parts and to take out waste. But as it is planned to go longer and further into space these supplies will no longer be possible. The astronaut life support system must be able of continuously transform waste into valuable compounds. Two types of production were identified as critical and could be be supplemented by microorganisms. On the one hand, since microgravity causes rapid muscle loss, single cell proteins (SCPs) could be used as protein rich feed or food. On the other hand, having enough building materials to build an advanced habitat will not be possible only by transporting space goods from earth to mars for example. The bacterium Cupriavidus. necator is well known for its ability to produce a large amount of proteins or of polyhydroxyalkanoate biopolymers (PHAs) depending on its implementation. By coupling the life support system to a 3D-printer, astronauts could be supplied with an unlimited amount of building materials. Additionally, based on the design of the life support system, waste streams have been identified: urea from the crew urine and volatile fatty acids (VFAs) from a first stage of organic waste (excrement and food waste) treatment through anaerobic digestion. Thus, the objective of this, within the Spaceship.Fr project, was to demonstrate the feasibility of producing SCPs and PHAs from VFAs and urea in bioreactor. Because life support systems operate continuously as loops, continuous culture experiments were chosen and the effect of the bioreactor dilution rate on biomass composition was investigated. Total transformation of the carbon source into biomass with high SCP or PHA content was achieved in all cases. We will present the transformation performances of VFAs and urea by the bacteria in bioreactor in terms of titers, yields and productivities but also in terms of the quality of SCP and PHA produced, nucleic acid content. We will further discuss the envisioned integration of our process within life support systems.

Keywords: life support system, space travel, waste treatment, single cell proteins, polyhydroxyalkanoates, bioreactor

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Authors: Ashish Jaiswal, Ashwin Ramesh Babu, Mohammad Zaki Zadeh, Fillia Makedon, Glenn Wylie

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Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the problem of predicting the state of cognitive fatigue in a person has not been investigated to its full extent. This paper proposes tackling this issue as a multi-class classification problem by dividing the state of cognitive fatigue into six different levels, ranging from no-fatigue to extreme fatigue conditions. We built a spatio-temporal model that uses convolutional neural networks (CNN) for spatial feature extraction and a long short-term memory (LSTM) network for temporal modeling of 4D fMRI scans. We also applied a self-supervised method called MoCo (Momentum Contrast) to pre-train our model on a public dataset BOLD5000 and fine-tuned it on our labeled dataset to predict cognitive fatigue. Our novel dataset contains fMRI scans from Traumatic Brain Injury (TBI) patients and healthy controls (HCs) while performing a series of N-back cognitive tasks. This method establishes a state-of-the-art technique to analyze cognitive fatigue from fMRI data and beats previous approaches to solve this problem.

Keywords: fMRI, brain imaging, deep learning, self-supervised learning, contrastive learning, cognitive fatigue

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Authors: A. Zurraini, Syed Alwi Sar, H. Helmy, H. Nazeefah

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Early Dementia Questionnaire (EDQ) was developed as a screening tool to detect patients with early dementia in primary care. It was developed based on 20 symptoms of dementia. From a preliminary study, EDQ had been shown to be a promising alternative for screening of early dementia. This study was done to further test on EDQ’s reliability and validity. Using a systematic random sampling, 200 elderly patients attending primary health care centers in Kuching, Sarawak had consented to participate in the study and were administered the EDQ. Geriatric Depression Scale (GDS) was used to exclude patients with depression. Those who scored >21 MMSE, were retested using the EDQ. Reliability was determined by Cronbach’s alpha for internal consistency and construct validity was assessed using confirmatory factor analysis (principle component with varimax rotation). The result showed that the overall Cronbach’s alpha coefficient was good which was 0.874. Confirmatory factor analysis on 4 factors indicated that the Cronbach’s alpha for each domain were acceptable with memory (0.741), concentration (0.764), emotional and physical symptoms (0.754) and lastly sleep and environment (0.720). Pearson correlation coefficient between the first EDQ score and the retest EDQ score among those with MMSE of >21 showed a very strong, positive correlation between the two variables, r = 0.992, N=160, P <0.001. The results of the validation study showed that Early Dementia Questionnaire (EDQ) is a valid and reliable tool to be used as a screening tool to detect early dementia in primary care.

Keywords: Early Dementia Questionnaire (EDQ), screening, primary care, construct validity

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Authors: Lal Hussain, Wajid Aziz, Sajjad Ahmed Nadeem, Saeed Arif Shah, Abdul Majid

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Brain electrical activity as reflected in Electroencephalography (EEG) have been analyzed and diagnosed using various techniques. Among them, complexity measure, nonlinearity, disorder, and unpredictability play vital role due to the nonlinear interconnection between functional and anatomical subsystem emerged in brain in healthy state and during various diseases. There are many social and economical issues of alcoholic abuse as memory weakness, decision making, impairments, and concentrations etc. Alcoholism not only defect the brains but also associated with emotional, behavior, and cognitive impairments damaging the white and gray brain matters. A recently developed signal analysis method i.e. Multiscale Permutation Entropy (MPE) is proposed to estimate the complexity of long-range temporal correlation time series EEG of Alcoholic and Control subjects acquired from University of California Machine Learning repository and results are compared with MSE. Using MPE, coarsed grained series is first generated and the PE is computed for each coarsed grained time series against the electrodes O1, O2, C3, C4, F2, F3, F4, F7, F8, Fp1, Fp2, P3, P4, T7, and T8. The results computed against each electrode using MPE gives higher significant values as compared to MSE as well as mean rank differences accordingly. Likewise, ROC and Area under the ROC also gives higher separation against each electrode using MPE in comparison to MSE.

Keywords: electroencephalogram (EEG), multiscale permutation entropy (MPE), multiscale sample entropy (MSE), permutation entropy (PE), mann whitney test (MMT), receiver operator curve (ROC), complexity measure

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Authors: Himalaya Patir, Bitupon Baruah, Sanjay Gayary, Subhajit Ray

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In recent age significant importance is given for the development of nutritious and health beneficial foods. Fruit juices collected from different fruits when blended that improves not only the physicochemical and nutritional properties but also enhance the sensorial or organoleptic properties. The study was carried out to determine the physico-chemical, nutritional, microbiological analysis and sensory evaluation of mixed fruit juice blend. Juice of orange (Citrus sinensis), apple (Malus domestica), mosambi (Citrus limetta) were blended in the ratio of sample-I (30% apple:30% orange:40% mosambi), sample-II ( 40% apple :30% orange :30% mosambi), sample-III (30% apple :40% orange :30% mosambi) , sample-IV (50% apple :30% orange :20% mosambi), sample-V (30% apple:20% orange:50% mosambi), sample-VI (20% apple :50% orange :30% mosambi) to evaluate all quality characteristics. Their colour characteristics in terms of hue angle, chroma and colour difference (∆E) were evaluated. The physico-chemical parameters analysis carried out were total soluble solids (TSS), total titratable acidity (TTA), pH, acidity (FA), volatile acidity (VA), pH, and vitamin C. There were significant differences (p˂0.05) in the TSS of the samples. However, sample-V (30% apple: 20% orange: 50% mosambi) provides the highest TSS of 9.02gm and significantly differed from other samples (p˂0.05). Sample-IV (50% apple: 30% orange: 20% mosambi) was shown the highest titratable acidity (.59%) in comparison to other samples. The highest value of pH was found as 5.01 for sample-IV (50% apple: 30% orange: 20% mosambi). Sample-VI (20% apple: 50% orange :30% mosambi) blend has the highest hue angle, chroma and colour changes of 72.14,25.29 and 54.48 and vitamin C, i.e. Ascorbic acid (.33g/l) content compared to other samples. The nutritional compositions study showed that, sample- VI (20% apple: 50% orange: 30% mosambi) has the significantly higher carbohydrate (51.67%), protein (.78%) and ash (1.24%) than other samples, while sample-V (30% apple: 20% orange: 50% mosambi) has higher dietary fibre (12.84%) and fat (2.82%) content. Microbiological analysis of all samples in terms of total plate count (TPC) ranges from 44-60 in 101 dilution and 4-5 in 107 dilutions and was found satisfactory. Moreover, other pathogenic bacterial count was found nil. The general acceptability of the mixed fruit juice blend samples were moderately liked by the panellists, and sensorial quality studies showed that sample-V (30% apple: 20% orange: 50% mosambi) contains highest overall acceptability of 8.37 over other samples and can be considered good for consumption.

Keywords: microbiological, nutritional, physico-chemical, sensory properties

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Authors: Zhou Luchen, Wu Yubing, Burra Venkata Durga Kumar

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As the scale of the network becomes larger and more complex than before, the density of user devices is also increasing. The development of Unmanned Aerial Vehicle (UAV) networks is able to collect and transform data in an efficient way by using software-defined networks (SDN) technology. This paper proposed a three-layer distributed and dynamic cluster architecture to manage UAVs by using an AI-based resource allocation calculation algorithm to address the overloading network problem. Through separating services of each UAV, the UAV hierarchical cluster system performs the main function of reducing the network load and transferring user requests, with three sub-tasks including data collection, communication channel organization, and data relaying. In this cluster, a head node and a vice head node UAV are selected considering the Central Processing Unit (CPU), operational (RAM), and permanent (ROM) memory of devices, battery charge, and capacity. The vice head node acts as a backup that stores all the data in the head node. The k-means clustering algorithm is used in order to detect high load regions and form the UAV layered clusters. The whole process of detecting high load areas, forming and selecting UAV clusters, and moving the selected UAV cluster to that area is proposed as offloading traffic algorithm.

Keywords: k-means, resource allocation, SDN, UAV network, unmanned aerial vehicles

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Authors: Rudolf Egger

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This article shows some results of an ongoing project in Kosova. This project deals with the meaning of social transformation processes in the life-courses of Kosova people. One goal is to create an oral history archive in this country. In the last seven years we did some interpretative work (using narrative interviews) concerning the experiences and meanings of social changes from the perspective of life course. We want to reconstruct the individual possibilities in creating one's life in new social structures. After the terrible massacres of ethnical-territorially defined nationalism in former Yugoslavia it is the main focus to find out something about the many small daily steps which must be done, to build up a kind of “normality” in this country. These steps can be very well reconstructed by narrations, by life stories, because personal experiences are naturally linked with social orders. Each individual story is connected with further stories, in which the collective history will be negotiated and reflected. The view on the biographical narration opens the possibility to analyze the concreteness of the “individual case” in the complexity of collective history. Life stories contain thereby a kind of a transition character, that’s why they can be used for the reconstruction of periods of political transformation. For example: In the individual story we can find very clear the national or mythological character of the Albanian people in Kosova. The shown narrations can be read also as narrative lines in relation to the (re-)interpretation of the past, in which lived life is fixed into history in the so-called collective memory in Kosova.

Keywords: biographical learning, adult education, social change, post war societies

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Authors: João Gago dos Santos, Paulo Pereira Almeida

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The present study intends to deepen and understand the reasons that led to the decline and disappearance of wooden construction systems in Portugal, for that reason, its use in history must be analyzed. It is observed that this material was an integral part of the construction systems in Europe and Portugal for centuries, and it is possible to conclude that its decline happens with the appearance of hybrid construction and later with the emergence and development of reinforced concrete technology. It is also verified that wood as a constructive element, and for that reason, an element of development had great importance in national construction, with its peak being the Pombaline period, after the 1755 earthquake. In this period, the great scarcity of materials in the metropolis led to the import wood from Brazil for the reconstruction of Lisbon. This period is linked to an accentuated exploitation of forests, resulting in laws and royal decrees aimed at protecting them, guaranteeing the continued existence of profitable forests, crucial to the reconstruction effort. The following period, with the gradual loss of memory of the catastrophe, resulted in a construction that was weakened structurally as a response to a time of real estate speculation and great urban expansion. This was the moment that precluded the inexistence of the use of wood in construction. At the beginning of the 20th century and in the 30s and 40s, with the appearance and development of reinforced concrete, it became part of the great structures of the state, and it is considered a versatile material capable of resolving issues throughout the national territory. It is at this point that the wood falls into disuse and practically disappears from the new works produced.

Keywords: construction history, construction in portugal, construction systems, wood construction

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Authors: Mehrshad Khosraviani, Faramarz Abbaspour Leyl Abadi

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The fundamental component of the computer network of modern information society will be considered. These networks are connected to the network of the internet generally. Due to the fact that the primary purpose of the Internet is not designed for, in recent decades, none of these networks in many of the attacks has been very important. Today, for the provision of security, different security tools and systems, including intrusion detection systems are used in the network. A common diagnosis system based on artificial immunity, the designer, the Adhasaz Foundation has been evaluated. The idea of using artificial safety methods in the diagnosis of abnormalities in computer networks it has been stimulated in the direction of their specificity, there are safety systems are similar to the common needs of m, that is non-diagnostic. For example, such methods can be used to detect any abnormalities, a variety of attacks, being memory, learning ability, and Khodtnzimi method of artificial immune algorithm pointed out. Diagnosis of the common system of education offered in this paper using only the normal samples is required for network and any additional data about the type of attacks is not. In the proposed system of positive selection and negative selection processes, selection of samples to create a distinction between the colony of normal attack is used. Copa real data collection on the evaluation of ij indicates the proposed system in the false alarm rate is often low compared to other ir methods and the detection rate is in the variations.

Keywords: artificial immune system, abnormality detection, intrusion detection, computer networks

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Authors: Hung-Yu Lin

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Background: Parts of researchers assert that external hyperactivity behaviors of ADHD children interfere with their abilities to perform internal cognitive tasks; however, there are still other researchers hold the opposite viewpoint, the external high level of activity may serve as the role of improving internal executive function.Objectives: Thisstudy explored the effects of external motor behavior of ADHD on internal visual attentional performance. Methods: A randomized, two-period crossover design was used in this study, a total of 80 children (aged 6-12) were recruited in this study. 40participants have received ADHD diagnosis, and others are children with typically developing. These children were measured through the visual edition of TOVA (The Test of Variables of Attention) when they wore actigraphy, their testing behavior and movement data werecollected through closely observation and the actigraphies under different research conditions. Result: According to the research result, the author found (1) Higherfrequencyof movement under attentional testing condition was found in children with ADHD, comparing to children with typically developing, and (2) Higher frequency of foot movement showed better attentional performance of the visual attentional test in children with ADHD. However, these results were not showed in children with typically developing. Conclusions: The findings support the functional working memory model, which advocated that a positive relation between gross motor activity and attentional performance within the context of attentive behavior in children with ADHD.

Keywords: ADHD, movement, visual attention, children

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Authors: M. Hadavi, Z. Hashemi

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Learning strategies play an important role in the development of language skills. Vocabulary learning strategies as the backbone of these strategies have become a major part of English language teaching. This study is a comparative analysis of Vocabulary Learning Strategies (VLS) use and preference among freshmen and senior EFL medical sciences students with different fields of study. 449 students (236 freshman and 213 seniors) participated in the study. 64.6% were female and 35.4% were male. The instrument utilized in this research was a questionnaire consisting of 41 items related to the students’ approach to vocabulary learning. The items were classified under eight sections as dictionary strategies, guessing strategies, study preferences, memory strategies, autonomy, note- taking strategies, selective attention, and social strategies. The participants were asked to answer each item with a 5-point Likert-style frequency scale as follows:1) I never or almost never do this, 2) I don’t usually do this, 3) I sometimes do this, 4) I usually do this, and 5)I always or almost always do this. The results indicated that freshmen students and particularly surgical technology students used more strategies compared to the seniors. Overall guessing and dictionary strategies were the most frequently used strategies among all the learners (p=0/000). The mean and standard deviation of using VLS in the students who had no previous history of participating in the private English language classes was less than the students who had attended these type of classes (p=0/000). Female students tended to use social and study preference strategies whereas male students used mostly guessing and dictionary strategies. It can be concluded that the senior students under instruction from the university have learned to rely on themselves and choose the autonomous strategies more, while freshmen students use more strategies that are related to the study preferences.

Keywords: vocabulary leaning strategies, medical sciences, students, linguistics

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Authors: Scholz Heiko, Kuhne Petra, Heckenberger Gerd

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Problems during the calving period (December to May) often result in a high body condition score (BCS) at this time. At the end of the grazing period (frequently after early weaning), however, an increase of BCS can often be observed under German conditions. In the last eight weeks before calving, the body condition should be reduced or at least not increased. Rations with a higher amount of crude fiber can be used (rations with straw or late mowed grass silage). Fermentative digestion of fiber is slow and incomplete; that’s why the fermentative process in the rumen can be reduced over a long feeding time. Viewed in this context, feed intake of suckler cows (8 weeks before calving) in different rations and fermentation in the rumen should be checked by taking rumen fluid. Eight suckler cows (Charolais) were feeding a Total Mixed Ration (TMR) in the last eight weeks before calving and grass silage after calving. By the addition of straw (30 % [TMR1] vs. 60 % [TMR2] of dry matter) was varied the amount of crude fiber in the TMR (grass silage, straw, mineral) before calving. After calving of the cow's grass, silage [GS] was fed ad libitum, and the last measurement of rumen fluid took place on the pasture [PS]. Rumen fluid, plasma, body weight, and backfat thickness were collected. Rumen fluid pH was assessed using an electronic pH meter. Volatile fatty acids (VFA), sedimentation, methylene-blue and amount of infusorians were measured. From these 4 parameters, an “index of rumen fermentation” [IRF] in the rumen was formed. Fixed effects of treatment (TMR1, TMR2, GS and PS) and a number of lactations (3-7 lactations) were analyzed by ANOVA using SPSS Version 25.0 (significant by p ≤ 5 %). Rumen fluid pH was significant influenced by variants (TMR 1 by 6.6; TMR 2 by 6.9; GS by 6.6 and PS by 6.9) but was not affected by other effects. The IRF showed disturbed fermentation in the rumen by feeding the TMR 1+2 with a high amount of crude fiber (Score: > 10.0 points) and a very good environment for fermentation during grazing the pasture (Score: 6.9 points). Furthermore, significant differences were found for VFA, methylene blue and the number of infusorians. The use of rations with the high amount of crude fiber from weaning to calving may cause deviations from undisturbed fermentation in the rumen and adversely affect the utilization of the feed in the rumen.

Keywords: suckler cow, feeding systems, crude fiber, digestibilty of organic matter

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Authors: Akinbo Razak Yinka, Adesanya Kehinde Kazeem, Oladokun Oluwagbenga Peter

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Time series data are sequences of observations collected over a period of time. Such data can be used to predict health outcomes, such as disease progression, mortality, hospitalization, etc. The Statistical approach is based on mathematical models that capture the patterns and trends of the data, such as autocorrelation, seasonality, and noise, while Neural methods are based on artificial neural networks, which are computational models that mimic the structure and function of biological neurons. This paper compared both parametric and non-parametric time series models of patients treated for malaria in Maternal and Child Health Centres in Lagos State, Nigeria. The forecast methods considered linear regression, Integrated Moving Average, ARIMA and SARIMA Modeling for the parametric approach, while Multilayer Perceptron (MLP) and Long Short-Term Memory (LSTM) Network were used for the non-parametric model. The performance of each method is evaluated using the Mean Absolute Error (MAE), R-squared (R2) and Root Mean Square Error (RMSE) as criteria to determine the accuracy of each model. The study revealed that the best performance in terms of error was found in MLP, followed by the LSTM and ARIMA models. In addition, the Bootstrap Aggregating technique was used to make robust forecasts when there are uncertainties in the data.

Keywords: ARIMA, bootstrap aggregation, MLP, LSTM, SARIMA, time-series analysis

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Authors: Hamdi Sana, Emna Bouazizi, Sami Faiz

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In recent years, there is a huge increase in the use of spatio-temporal applications where data and queries are continuously moving. As a result, the need to process real-time spatio-temporal data seems clear and real-time stream data management becomes a hot topic. Sliding window model and frequent itemset mining over dynamic data are the most important problems in the context of data mining. Thus, sliding window model for frequent itemset mining is a widely used model for data stream mining due to its emphasis on recent data and its bounded memory requirement. These methods use the traditional transaction-based sliding window model where the window size is based on a fixed number of transactions. Actually, this model supposes that all transactions have a constant rate which is not suited for real-time applications. And the use of this model in such applications endangers their performance. Based on these observations, this paper relaxes the notion of window size and proposes the use of a timestamp-based sliding window model. In our proposed frequent itemset mining algorithm, support conditions are used to differentiate frequents and infrequent patterns. Thereafter, a tree is developed to incrementally maintain the essential information. We evaluate our contribution. The preliminary results are quite promising.

Keywords: real-time spatial big data, frequent itemset, transaction-based sliding window model, timestamp-based sliding window model, weighted frequent patterns, tree, stream query

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Authors: Bessaha Hassiba, Bouraada Mohamed

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Layered double hydroxide with Zn/(Al+Fe) molar ratio of 3:1 was synthesized by co-precipitation method and their calcined product was obtained by heating treatment of ZAF-HT at 500°C. The calcined and uncalcined materials were used to remove weak acid dyes: indigo carmine (IC) and green bezanyl-F2B (F2B) in aqueous solution. The synthesized materials were characterized by XRD, SEM, FTIR and TG/DTA analysis confirming the formation of pure layered structure of ZAF-HT, the destruction of the original structure after calcination and the intercalation of the dyes molecules. Moreover, the interlayer distance increases from 7.645 Å in ZAF-HT to 19.102 Å after the dyes sorption. The dose of the adsorbents was chosen 0.5 g/l while the initial concentrations were 250 and 750 mg/l for indigo carmine and green bezanyl-F2B respectively. The sorption experiments were carried out at ambient temperature and without adjusting the initial solution pH (pHi = 6.10 for IC and pHi = 5.01 for F2B). In addition, the maximum adsorption capacities obtained by ZAF-HT and CZAF for both dyes followed the order: CZAF-F2B (1501.4 mg.g-1) > CZAF-IC (617.3 mg.g-1) > ZAF-HT-IC (41.4 mg.g-1) > ZAF-HT-F2B (28.9 mg.g-1). The removal of indigo carmine and green bezanyl-F2B by ZAF-HT was due to the anion exchange and/or the adsorption on the surface. By using the calcined material (CZAF), the removal of the dyes was based on a particular property, called ‘memory effect’. CZAF recover the pristine structure in the presence anionic molecules such as acid dyes where they occupy the interlayer space. The sorption process was spontaneous in nature and followed pseudo-second-order. The isotherms showed that the removal of IC and F2B by ZAF-HT and CZAF were consistent with Langmiur model.

Keywords: acid dyes, adsorption, calcination, layered double hydroxides

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Authors: Milagros Jaén-Vargas, Javier García Martínez, Karla Miriam Reyes Leiva, María Fernanda Trujillo-Guerrero, Francisco Fernandes, Sérgio Barroso Gonçalves, Miguel Tavares Silva, Daniel Simões Lopes, José Javier Serrano Olmedo

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Human Activity Recognition (HAR) is having a growing impact in creating new applications and is responsible for emerging new technologies. Also, the use of wearable sensors is an important key to exploring the human body's behavior when performing activities. Hence, the use of these dispositive is less invasive and the person is more comfortable. In this study, a database that includes three activities is used. The activities were acquired from inertial measurement unit sensors (IMU) and motion capture systems (MOCAP). The main objective is differentiating the performance from four Deep Learning (DL) models: Deep Neural Network (DNN), Convolutional Neural Network (CNN), Recurrent Neural Network (RNN) and hybrid model Convolutional Neural Network-Long Short-Term Memory (CNN-LSTM), when considering acceleration, velocity and position and evaluate if integrating the IMU acceleration to obtain velocity and position represent an increment in performance when it works as input to the DL models. Moreover, compared with the same type of data provided by the MOCAP system. Despite the acceleration data is cleaned when integrating, results show a minimal increase in accuracy for the integrated signals.

Keywords: HAR, IMU, MOCAP, acceleration, velocity, position, feature maps

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Authors: Min-Chih Yang, Shih-Jen Feng, Bo-Tsang Li

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The concept of “Brownfield” has been developed for nearly 35 years since it was put forward in 《Comprehensive Environmental Response, Compensation, and Liability Act, CERCLA》of USA in 1980 for solving the problem of soil contamination of those old industrial lands, and later, many countries have put forward relevant policies and researches continuously. But the related concept in Taiwan, a country has developed its industry for 60 years, is still in its infancy. This leads to the slow development of Brownfield related research and policy in Taiwan. When it comes to build the foundation of Brownfield development, we have to depend on the related experience and research of other countries. They are four aspects about Brownfield: 1. Contaminated Land; 2. Derelict Land; 3. Vacant Land; 4. Previously Development Land. This study will focus on and deeply investigate the Vacant land and contaminated land. The subject of this study is Formosa Chemicals & Fibre Corporation, Changhua branch in Taiwan. It has been operating for nearly 50 years and contributing a lot to the local economy. But under the influence of the toxic waste and sewage which was drained regularly or occasionally out from the factory, the environment has been destroyed seriously. There are three factors of pollution: 1. environmental toxicants, carbon disulfide, released from producing processes and volatile gases which is hard to monitor; 2. Waste and exhaust gas leakage caused by outdated equipment; 3. the wastewater discharge has seriously damage the ecological environment of the Dadu river estuary. Because of all these bad influences, the factory has been closed nowadays and moved to other places to spare the opportunities for the contaminated lands to re-develop. So we collect information about related Brownfield management experience and policies in different countries as background information to investigate the current Taiwanese Brownfield redevelopment issues and built the environmental assessment framework for it. We hope that we can set the environmental assessment indexes for Formosa Chemicals & Fibre Corporation, Changhua branch according to the framework. By investigating the theory and environmental pollution factors, we will carry out deep analysis and expert questionnaire to set those indexes and prove a sample in Taiwan for Brownfield redevelopment and remediation in the future.

Keywords: brownfield, industrial land, redevelopment, assessment index

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Authors: Salako Emmanuel Adekunle

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With numerous advantages of ICT in teaching such as using images to improve the retentive memory of students, academic staff is yet to deliver instructions adequately and effectively due to no power supply, lack of technical supports and non-availability of functional ICT tools. This study was conducted to investigate the attitudes of academic staff towards the use of information communication technology as a pedagogical tool for effective teaching in FCT College of Education, Zuba-Abuja, Nigeria. A sample of 200 academic staff from five schools/faculties was involved in the study. The respondents were selected by using simple random sampling technique (SRST). A questionnaire was developed and validated by the experts in Measurement and Evaluation, and reliability co-efficient of 0.85 was obtained. It was used to gather relevant data from the respondents. This study revealed that the respondents had positive attitudes towards the use of ICT as a pedagogical tool for effective teaching. Also, the uses of ICT by the academic staff included: to encourage closer relationship for attainment of higher academic, and to deliver instructions effectively. The study also revealed that there is a significant relationship between the attitudes and the uses of ICT by the academic staff. Based on these findings, some recommendations were made which include: power supply should be provided to operate ICT facilities for effective teaching, and technical assistance on ICT usage for effective delivery of instructions should be provided among other recommendations.

Keywords: academic staff, attitudes, information communication technology, pedagogical tool, teaching, use

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