Search results for: randomized response model

Authors: Julio Macedo

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Several methodologies are now available to conceive the improvements of a process so that it becomes competitive as for example total quality, process reengineering, six sigma, define measure analysis improvement control method. These improvements are of different nature and can be external to the process represented by an optimization model or a discrete simulation model. In addition, the process stakeholders are several and have different desired performances for the process. Hence, the methodologies above do not have a tool to aid in the conception of the required improvements. In order to fill this void we suggest the use of intelligent reference models. A reference model is a set of qualitative differential equations and an objective function that minimizes the gap between the current and the desired performance indexes of the process. The reference models are intelligent so when they receive the current state of the problematic process and the desired performance indexes they generate the required improvements for the problematic process. The reference models are fuzzy cognitive maps added with an objective function and trained using the improvements implemented by the high performance firms. Experiments done in a set of students show the reference models allow them to conceive more improvements than students that do not use these models.

Keywords: continuous improvement, fuzzy cognitive maps, process competitiveness, qualitative simulation, system dynamics

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Authors: Valeriu Mihai But, Sorana Daniela Bolboacă, Adriana Elena Bulboacă

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The nutraceutical compound Curcumin (Curcuma longa L.) is known for its anti-inflammatory, anti-cancer, and antioxidant effects. This study aimed to evaluate the antioxidative and analgesic effects of Curcumin (CC) compared to Tramadol (T) in chemical-induced nociceptive pain in rats. Thirty-five rats were randomly divided into five groups of seven rats each and were treated as follows: C group (control group): treated with saline solution 0.9%, (1 ml, i.p. administration), ethanoic acid (EA) group: pretreated with saline solution 0.9% - 30 min before EA nociceptive pain induction, (1 ml, i.p. administration), T group: pretreated with Tramadol, 10 mg/kg body weight (bw), i.p. administration - 30 min before EA nociceptive pain induction, CC1-group: pretreated with 1 mg/100g bw Curcumin i.p. administration - 2 days before EA pain induction and CC2-group: pretreated with Curcumin 2 mg/100g bw i.p. administration - 2 days before EA nociceptive pain induction. The following oxidative stress parameters were assessed: malondialdehyde (MDA), nitric oxide (NOx), total oxidative status (TOS), total antioxidative capacity (TAC), and thiol (Th). The antalgic activity was measured by the ethanoic acid writhing test. Treatment with Curcumin, both 1 mg/100g bw, and 2 mg/100g bw, showed significant differences as compared with the control group (p<0.001) regarding malondialdehyde (MDA), nitric oxide (NOx), and total oxidative status (TOS) oxidative biomarkers. Pretreatment with 2 mg/100g bw of Curcumin presented a significant decrease in MDA values compared with Tramadol (p<0.001). The TAC significantly increased in pretreatment with Curcumin compared with group control. (p<0.001) The nociceptive response to EA was significantly reduced in Curcumin and Tramadol groups. Treatment with Curcumin at a higher concentration was more effective. In an experimental pain model, this study demonstrates an important antioxidant and antinociceptive activity of Curcumin comparable with Tramadol treatment.

Keywords: curcumin, nociception, oxidative stress, pain

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Authors: P. Valdez, M. Pelissero, A. Haim, F. Muiño, F. Galia, R. Tula

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As a result of the studies performed on the wave energy resource worldwide, a research project was set up to harvest wave energy for its conversion into electrical energy. Within this framework, a theoretical model of the electromechanical energy harvesting system, developed with MATLAB’s Simulink software, will be provided. This tool recreates the site conditions where the device will be installed and offers valuable information about the amount of energy that can be harnessed. This research provides a deeper understanding of the utilization of wave energy in order to improve the efficiency of a 1:1 scale prototype of the device.

Keywords: electromechanical device, modeling, renewable energy, sea wave energy, simulation

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Authors: Sameh Abaza, Mohamed Ibrahim, Tarek Mahmoud

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Due to the development in the digital image processing, its wide use in many applications such as medical, security, and others, the need for more accurate techniques that are reliable, fast and robust is vehemently demanded. In the field of security, in particular, speed is of the essence. In this paper, a pattern recognition technique that is based on the use of Hidden Markov Model (HMM), K-means and the Sobel operator method is developed. The proposed technique is proved to be fast with respect to some other techniques that are investigated for comparison. Moreover, it shows its capability of recognizing the normal face (center part) as well as face boundary.

Keywords: HMM, K-Means, Sobel, accuracy, face recognition

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Authors: R. O. Osaseri, A. R. Usiobaifo

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The power transformer which is responsible for the voltage transformation is of great relevance in the power system and oil-immerse transformer is widely used all over the world. A prompt and proper maintenance of the transformer is of utmost importance. The dissolved gasses content in power transformer, oil is of enormous importance in detecting incipient fault of the transformer. There is a need for accurate prediction of the incipient fault in transformer oil in order to facilitate the prompt maintenance and reducing the cost and error minimization. Study on fault prediction and diagnostic has been the center of many researchers and many previous works have been reported on the use of artificial intelligence to predict incipient failure of transformer faults. In this study machine learning technique was employed by using gradient decent algorithms and Support Vector Machine (SVM) in predicting incipient fault diagnosis of transformer. The method focuses on creating a system that improves its performance on previous result and historical data. The system design approach is basically in two phases; training and testing phase. The gradient decent algorithm is trained with a training dataset while the learned algorithm is applied to a set of new data. This two dataset is used to prove the accuracy of the proposed model. In this study a transformer fault diagnostic model based on Support Vector Machine (SVM) and gradient decent algorithms has been presented with a satisfactory diagnostic capability with high percentage in predicting incipient failure of transformer faults than existing diagnostic methods.

Keywords: diagnostic model, gradient decent, machine learning, support vector machine (SVM), transformer fault

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Authors: Polvasut Mahaiamsiri, Piraphong Foosiri

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The purpose of this research is to explore the model of factors affecting decision making to select successor in family business of Thailand. A Structural Equation Model (SEM) was created from relevant theories and researches. Consequently, examine and analyse, the causal relation factors of Succession Plan, Recruitment Process and Strategic Planning, whether they have direct or indirect effects on Decision Making to Select Successor in family business. Units of analysis are selected from the family business, totalling 300 sampling. Population sampling is current owners or CEO from the percentage of six district areas in Thailand with multi-stage sampling. A set of questionnaires is used to collect data. An analysis of structural equation modelling (SEM) technique using AMOS 21 program is conducted to test the hypotheses and confirmatory factor analysis is performed and shows that these variables can be tested. The finding of this study revealed that these factors are separate constructs that combine to determine decision making to select successors.

Keywords: succession plan, family business, recruitment process, strategic planning, decision making to select successor

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Authors: Monalisa Pal, Kalyan Mandal

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Herein we report the molecular functionalization of promising transition metal oxide nanostructures, such as Co3O4 nanocubes, using nontoxic and biocompati-ble organic ligand sodium tartrate. The electronic structural modification of the nanocubes imparted through functionalization and subsequent water solubilization reveals multiple absorption bands in the UV-vis region. Further surface modification of the solubilized nanocubes, leads to the emergence of intrinsic multi-color fluorescence (from blue, cyan, green to red region of the spectrum), upon excitation at proper wavelengths, where the respective excitation wavelengths have a direct correlation with the observed UV-vis absorption bands. Using a multitude of spectroscopic tools we have investigated the mechanistic insight behind the origin of different UV-vis absorption bands and emergence of multicolor photoluminescence from the functionalized nanocubes. Our detailed study shows that ligand to metal charge transfer (LMCT) from tartrate ligand to Co2+/Co3+ ions and d-d transitions involving Co2+/Co3+ ions are responsible for generation of this novel optical properties. Magnetic study reveals that, antiferromagnetic nature of Co3O4 nanocubes changes to ferromagnetic behavior upon functionalization, however, the overall magnetic response was very weak. To combine strong magnetism with this novel optical property, we followed the same surface modification strategy in case of CoFe2O4 nanoparticles, which reveals that irrespective of size and shape, all Co-based oxides can develop intrinsic multi-color fluorescence upon facile functionalization with sodium tartrate ligands and the magnetic response was significantly higher. Surface modified Co-based oxide nanostructures also show excellent catalytic activity in degradation of biologically and environmentally harmful dyes. We hope that, our developed facile functionalization strategy of Co-based oxides will open up new opportunities in the field of biomedical applications such as bio-imaging and targeted drug delivery.

Keywords: co-based oxide nanostructures, functionalization, multi-color fluorescence, catalysis

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Authors: Hanieh Mohammadi, Sarah Fraser, Anil Nigam, Frederic Lesage, Louis Bherer

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A chronically higher cerebral pulsatility is thought to damage cerebral microcirculation, leading to cognitive decline in older adults. Although it is widely known that regular physical activity is linked to improvement in some cognitive domains, including executive functions, the mediating role of cerebral pulsatility on this link remains to be elucidated. This study assessed the impact of 6 months of regular physical activity upon changes in an optical index of cerebral pulsatility and the role of physical activity for the improvement of executive functions. 27 older adults (aged 57-79, 66.7% women) with cardiovascular risk factors (CVRF) were enrolled in the study. The participants completed the behavioral Stroop test, which was extracted from the Delis-Kaplan executive functions system battery at baseline (T0) and after 6 months (T6) of physical activity. Near-infrared spectroscopy (NIRS) was applied for an innovative approach to indexing cerebral pulsatility in the brain microcirculation at T0 and T6. The participants were at standing rest while a NIRS device recorded hemodynamics data from frontal and motor cortex subregions at T0 and T6. The cerebral pulsatility index of interest was cerebral pulse amplitude, which was extracted from the pulsatile component of NIRS data. Our data indicated that 6 months of physical activity was associated with a reduction in the response time for the executive functions, including inhibition (T0: 56.33± 18.2 to T6: 53.33± 15.7,p= 0.038)and Switching(T0: 63.05± 5.68 to T6: 57.96 ±7.19,p< 0.001) conditions of the Stroop test. Also, physical activity was associated with a reduction in cerebral pulse amplitude (T0: 0.62± 0.05 to T6: 0.55± 0.08, p < 0.001). Notably, cerebral pulse amplitude was a significant mediator of the link between physical activity and response to the Stroop test for both inhibition (β=0.33 (0.61,0.23),p< 0.05)and switching (β=0.42 (0.69,0.11),p <0.01) conditions. This study suggests that regular physical activity may support cognitive functions through the improvement of cerebral pulsatility in older adults with CVRF.

Keywords: near-infrared spectroscopy, cerebral pulsatility, physical activity, cardiovascular risk factors, executive functions

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Authors: Gholamhossein Hosseini

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Two earliness cotton genotypes I and II, which had been developed by hybridization and backcross methods between sindise-80 as an early maturing gene parent and two other lines i.e. Red leaf and Bulgare-557 as a second parent, are subjected to different environmental conditions. The early maturing genotypes with coded names of I and II were compared with four native cotton cultivars in randomized complete block design (RCBD) with four replications in three ecological regions of Iran from 2016-2017. Two early maturing genotypes along with four native cultivars viz. Varamin, Oltan, Sahel and Arya were planted in Agricultural Research Station of Varamin, Moghan and Kashmar for evaluation. Earliness data were collected for six treatments during two years in the three regions except missing data for the second year of Kashmar. Therefore, missed data were estimated and imputed. For testing the homogeneity of error variances, each experiment at a given location or year is analyzed separately using Hartley and Bartlett’s Chi-square tests and both tests confirmed homogeneity of variance. Combined analysis of variance showed that genotypes I and II were superior in Varamin, Moghan and Kashmar regions. Earliness means and their interaction effects were compared with Duncan’s multiple range tests. Finally combined analysis of variance showed that genotypes I and II were superior in Varamin, Moghan and Kashmar regions. Earliness means and their interaction effects are compared with Duncan’s multiple range tests.

Keywords: cotton, combined, analysis, earliness

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Authors: Zhi Hao Chow, Cian Mulligan, Jack Walsh, Antonio Garzon Vico, Dimitar Krastev

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Drug development is resource-intensive, time-consuming, and increasingly expensive with each developmental stage. The success rates of drug development are also relatively low, and the resources committed are wasted with each failed candidate. As such, a reliable method of predicting the success of drug development is in demand. The hypothesis was that some examples of failed drug candidates are pushed through developmental pipelines based on false confidence and may possess common linguistic features identifiable through sentiment analysis. Here, the concept of using text analysis to discover such features in research publications and investor reports as predictors of success was explored. R studios were used to perform text mining and lexicon-based sentiment analysis to identify affective phrases and determine their frequency in each document, then using SPSS to determine the relationship between our defined variables and the accuracy of predicting outcomes. A total of 161 publications were collected and categorised into 4 groups: (i) Cancer treatment, (ii) Neurodegenerative disease treatment, (iii) Vaccines, and (iv) Others (containing all other drugs that do not fit into the 3 categories). Text analysis was then performed on each document using 2 separate datasets (BING and AFINN) in R within the category of drugs to determine the frequency of positive or negative phrases in each document. A relative positivity and negativity value were then calculated by dividing the frequency of phrases with the word count of each document. Regression analysis was then performed with SPSS statistical software on each dataset (values from using BING or AFINN dataset during text analysis) using a random selection of 61 documents to construct a model. The remaining documents were then used to determine the predictive power of the models. Model constructed from BING predicts the outcome of drug performance in clinical trials with an overall percentage of 65.3%. AFINN model had a lower accuracy at predicting outcomes compared to the BING model at 62.5% but was not effective at predicting the failure of drugs in clinical trials. Overall, the study did not show significant efficacy of the model at predicting outcomes of drugs in development. Many improvements may need to be made to later iterations of the model to sufficiently increase the accuracy.

Keywords: data analysis, drug development, sentiment analysis, text-mining

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Authors: Essam Amerian

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The aim of this study was to investigate the effects of improving waist-to-hip ratio (WHR) and visceral fat components on the health of shift workers in an offshore petrochemical company. A total of 100 male shift workers participated in the study, with an average age of 40.5 years and an average BMI of 28.2 kg/m². The study employed a randomized controlled trial design, with participants assigned to either an intervention group or a control group. The intervention group received a 12-week program that included dietary counseling, physical activity recommendations, and stress management techniques. The control group received no intervention. The outcomes measured were changes in WHR, visceral fat components, blood pressure, and lipid profile. The results showed that the intervention group had a statistically significant improvement in WHR (p<0.001) and visceral fat components (p<0.001) compared to the control group. Furthermore, there were statistically significant improvements in systolic blood pressure (p=0.015) and total cholesterol (p=0.034) in the intervention group compared to the control group. These findings suggest that implementing a 12-week program that includes dietary counseling, physical activity recommendations, and stress management techniques can effectively improve WHR, visceral fat components, and cardiovascular health among shift workers in an offshore petrochemical company.

Keywords: body composition, waist-hip-ratio, visceral fat, shift worker, work efficiency

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Authors: Violina R. Angelova, Mariana N. Perifanova-Nemska, Galina P. Uzunova, Krasimir I. Ivanov, Huu Q. Lee

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A field study was conducted to evaluate the efficacy of the sunflower (Helianthus annuus L.) for phytoremediation of contaminated soils. The experiment was performed on an agricultural field contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. Field experiments with a randomized, complete block design with five treatments (control, compost amendments added at 20 and 40 t/daa, and vemicompost amendments added at 20 and 40 t/daa) were carried out. The accumulation of heavy metals in the sunflower plant and the quality of the sunflower oil (heavy metals and fatty acid composition) were determined. The tested organic amendments significantly influenced the uptake of Pb, Zn and Cd by the sunflower plant. The incorporation of 40 t/decare of compost and 20 t/decare of vermicompost to the soil led to an increase in the ability of the sunflower to take up and accumulate Cd, Pb and Zn. Sunflower can be subjected to the accumulators of Pb, Zn and Cd and can be successfully used for phytoremediation of contaminated soils with heavy metals. The 40 t/daa compost treatment led to a decrease in heavy metal content in sunflower oil to below the regulated limits. Oil content and fatty acids composition were affected by compost and vermicompost amendment treatments. Adding compost and vermicompost increased the oil content in the seeds. Adding organic amendments increased the content of stearic, palmitoleic and oleic acids, and reduced the content of palmitic and gadoleic acids in sunflower oil. The possibility of further industrial processing of seeds to oil and use of the obtained oil will make sunflowers economically interesting crops for farmers of phytoremediation technology.

Keywords: heavy metals, phytoremediation, polluted soils, sunflower

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Authors: Hui Ling Chen

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This article describes the experience of caring for a 68-year-old lung cancer patient undergoing the initial stage of concurrent chemotherapy and radiation therapy during the period of October 21 to November 16. In this study, the author collected data through observation, interviews, medical examination, and the use of Roy’s adaptation model as a guide for data collection and assessment. This study confirmed that chemotherapy induced nausea and vomiting, and radiation therapy impaired skin integrity. At the same time, the patient experienced an anxious reaction to the initial cancer diagnosis and the insertion of subcutaneous infusion ports at the start of medical treatment. Similarly, the patient’s wife shares his anxiety, not to mention the feeling of inadequacy from the lack of training in cancer care. In response, the nursing intervention strategy has included keeping the patient and his family informed of his treatment progress, transfer of cancer care knowledge, and providing them with spiritual support. For example, the nursing staff has helped them draw up a mutually agreeable dietary plan that best suits the wife’s cooking skills, provided them with knowledge in pre- and post-radiation skin care, as well as means to cope with nausea and vomiting reactions. The nursing staff has also worked on building rapport with the patient and his spouse, providing them with encouragement, caring attention and companionship. After the patient was discharged from the hospital, the nursing staff followed up with caring phone calls to help the patient and his family make life-style adjustments to normalcy. The author hopes that his distinctive nursing experience can be useful as a reference for the clinical care of lung cancer patients undergoing the initial stage of concurrent chemotherapy and radiation therapy treatment.

Keywords: lung cancer, initiate diagnosis, concurrent chemotherapy and radiation therapy, nursing care

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Authors: Rima Abu Jaber Bransi, Rawya Jarjoura Burbara

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This study deals with two pioneering approaches in teaching Arabic as a mother tongue: first, computerization of literary and functional texts in the mother tongue; second, the pioneering model in teaching writing skills by computerization. The significance of the study lies in its treatment of a serious problem that is faced in the era of technology, which is the widening gap between the pupils and their mother tongue. The innovation in the study is that it introduces modern methods and tools and a pioneering instructional model that turns the process of mother tongue teaching into an effective, meaningful, interesting and motivating experience. In view of the Arabic language diglossia, standard Arabic and spoken Arabic, which constitutes a serious problem to the pupil in understanding unused words, and in order to bridge the gap between the pupils and their mother tongue, we resorted to computerized techniques; we took texts from the pre-Islamic period (Jahiliyya), starting with the Mu'allaqa of Imru' al-Qais and other selected functional texts and computerized them for teaching in an interesting way that saves time and effort, develops high thinking strategies, expands the literary good taste among the pupils, and gives the text added values that neither the book, the blackboard, the teacher nor the worksheets provide. On the other hand, we have developed a pioneering computerized model that aims to develop the pupil's ability to think, to provide his imagination with the elements of growth, invention and connection, and motivate him to be creative, and raise level of his scores and scholastic achievements. The model consists of four basic stages in teaching according to the following order: 1. The Preparatory stage, 2. The reading comprehension stage, 3. The writing stage, 4. The evaluation stage. Our lecture will introduce a detailed description of the model with illustrations and samples from the units that we built through highlighting some aspects of the uniqueness and innovation that are specific to this model and the different integrated tools and techniques that we developed. One of the most significant conclusions of this research is that teaching languages through the employment of new computerized strategies is very likely to get the Arabic speaking pupils out of the circle of passive reception into active and serious action and interaction. The study also emphasizes the argument that the computerized model of teaching can change the role of the pupil's mind from being a store of knowledge for a short time into a partner in producing knowledge and storing it in a coherent way that prevents its forgetfulness and keeping it in memory for a long period of time. Consequently, the learners also turn into partners in evaluation by expressing their views, giving their notes and observations, and application of the method of peer-teaching and learning.

Keywords: classical poetry, computerization, diglossia, writing skill

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Authors: Yanqun Li, Hong Geng

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The occurrence of Wenchuan earthquake in 2008 has led to severe damage to the rural areas of Chengdu city, such as the rupture of the social network, the stagnation of economic production and the rupture of living space. The post-disaster reconstruction has become a sustainable issue. As an important link to maintain the order of rural social development, social network should be an important content of post-disaster reconstruction. Therefore, this paper takes rural reconstruction communities in earthquake-stricken areas of Chengdu as the research object and adopts sociological research methods such as field survey, observation and interview to try to understand the transformation of rural social relations network under the influence of earthquake and its impact on rural space. It has found that rural societies under the earthquake generally experienced three phases: the break of stable social relations, the transition of temporary non-normal state, and the reorganization of social networks. The connotation of phased rural social relations also changed accordingly: turn to a new division of labor on the social orientation, turn to a capital flow and redistribution in new production mode on the capital orientation, and turn to relative decentralization after concentration on the spatial dimension. Along with such changes, rural areas have emerged some social issues such as the alienation of competition in the new industry division, the low social connection, the significant redistribution of capital, and the lack of public space. Based on a comprehensive review of these issues, this paper proposes the corresponding response mechanism. First of all, a reasonable division of labor should be established within the villages to realize diversified commodity supply. Secondly, the villages should adjust the industrial type to promote the equitable participation of capital allocation groups. Finally, external public spaces should be added to strengthen the field of social interaction within the communities.

Keywords: social relations, social support networks, industrial division, capital allocation, public space

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Authors: Seyed Mohammadbagher Jafari, Izmeera Shiham, Masoud Arianfar

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The increased usage of Social media for different uses in turn makes it important to develop an understanding of users and their attitudes toward these sites, and moreover, the uses of such sites in a broader perspective such as broadcasting. This quantitative study addressed the problem of factors influencing the adoption of social media as a medium of public service broadcasting in the Republic of Maldives. These powerful and increasingly usable tools, accompanied by large public social media datasets, are bringing in a golden age of social science by empowering researchers to measure social behavior on a scale never before possible. This was conducted by exploring social responses on the use of social media. Research model was developed based on the previous models such as TAM, DOI and Trust combined model. It evaluates the influence of perceived ease of use, perceived usefulness, trust, complexity, compatibility and relative advantage influence on the adoption of social Media. The model was tested on a sample of 365 Maldivian people using survey method via questionnaire. The result showed that perceived usefulness, trust, relative advantage and complexity would highly influence the adoption of social media.

Keywords: adoption, broadcasting, maldives, social media

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Authors: Alaa El-Din Rezk

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For organic xenobiotics, sorption to Aldrich humic acid is a key process controlling their mobility, bioavailability, toxicity and fate in the soil. Hydrophobic organic compounds possessing either acid or basic groups can be partially ionized (deprotonated or protonated) within the range of natural soil pH. For neutral and ionogenicxenobiotics including (neutral, acids and bases) sorption coefficients normalized to organic carbon content, Koc, have measured at different pH values. To this end, the batch equilibrium technique has been used, employing SPME combined with GC-MSD as an analytical tool. For most ionogenic compounds, sorption has been affected by both pH and pKa and can be explained through Henderson-Hasselbalch equation. The results demonstrate that when assessing the environmental fate of ionogenic compounds, their pKa and speciation under natural conditions should be taken into account. A new model has developed to predict the relationship between log Koc and pH with full statistical evaluation against other existing predictive models. Neutral solutes have displayed a good fit with the classical model using log Kow as log Koc predictor, whereas acidic and basic compounds have displayed a good fit with the LSER approach and the new proposed model. Measurement limitations of the Batch technique and SPME-GC-MSD have been found with ionic compounds.

Keywords: humic acid, log Koc, pH, pKa, SPME-GCMSD

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Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

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The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

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Authors: Todd Pennington, Carol Wilkinson, Keven Prusak

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Traditional models of student teaching practices typically involve the placement of a student teacher with an experienced mentor teacher. However, due to the ever-decreasing number of quality placements, an alternative triad approach is the paired placement of student teachers with one mentor teacher in a community of practice. This study examined the paired-placement of student teachers in physical education to determine the benefits and drawbacks after a 14-week student teaching experience. PETE students (N = 22) at a university in the United States were assigned to work in a triad with a student teaching partner and a mentor teacher, making up eleven triads for the semester. The one exception was a pair that worked for seven weeks at an elementary school and then for seven weeks at a junior high school, thus having two mentor teachers and participating in two triads. A total of 12 mentor teachers participated in the study. All student teachers and mentor teachers volunteered and agreed to participate. The student teaching experience was structured so that students engaged in: (a) individual teaching (one teaching the lesson with the other observing), (b) co-planning, and (c) peer coaching. All students and mentor teachers were interviewed at the conclusion of the experience. Using interview data, field notes, and email response data, the qualitative data was analyzed using the constant comparative method. The benefits of the paired placement experience emerged into three categories (a) quality feedback, (b) support, and (c) collaboration. The drawbacks emerged into four categories (a) unrealistic experience, (b) laziness in preparation, (c) lack of quality feedback, and (d) personality mismatch. Recommendations include: providing in-service training prior to student teaching to optimize the triad experience, ongoing seminars throughout the experience specifically designed for triads, and a hybrid model of paired placement for the first half of student teaching followed by solo student teaching for the second half of the experience.

Keywords: community of practice, paired placement, physical education, student teaching

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Authors: Adekunle Kolawole Ojo, Idowu Peter Adebayo, Egwuche Sylvester O.

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Chronic Kidney Disease (CKD) is a significant cause of morbidity and mortality across developed and developing nations and is associated with increased risk. There are no existing electronic means of capturing and monitoring CKD in Nigeria. The work is aimed at developing a spatial data model that can be used to implement renal registries required for tracking and monitoring the spatial distribution of renal diseases by public health officers and patients. In this study, we have developed a spatial data model for a functional renal registry.

Keywords: renal registry, health informatics, chronic kidney disease, interface

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Authors: Leyla Noroozbabaee, David Nickerson

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We introduce a modular, consistent, reusable bond graph model of the renal nephron’s proximal convoluted tubule (PCT), which can reproduce biological behaviour. In this work, we focus on ion and volume transport in the proximal convoluted tubule of the renal nephron. Modelling complex systems requires complex modelling problems to be broken down into manageable pieces. This can be enabled by developing models of subsystems that are subsequently coupled hierarchically. Because they are based on a graph structure. In the current work, we define two modular subsystems: the resistive module representing the membrane and the capacitive module representing solution compartments. Each module is analyzed based on thermodynamic processes, and all the subsystems are reintegrated into circuit theory in network thermodynamics. The epithelial transport system we introduce in the current study consists of five transport membranes and four solution compartments. Coupled dissipations in the system occur in the membrane subsystems and coupled free-energy increasing, or decreasing processes appear in solution compartment subsystems. These structural subsystems also consist of elementary thermodynamic processes: dissipations, free-energy change, and power conversions. We provide free and open access to the Python implementation to ensure our model is accessible, enabling the reader to explore the model through setting their simulations and reproducibility tests.

Keywords: Bond Graph, Epithelial Transport, Water Transport, Mathematical Modeling

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Authors: Adriana Postal, Silvio C. Sampaio, Marcio A. Villas Boas, Josué P. Castro

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This study deals with the estimation of reference evapotranspiration (ET₀) in an agricultural context, focusing on efficient irrigation management to meet the growing interest in the sustainable management of water resources. Given the importance of water in agriculture and its scarcity in many regions, efficient use of this resource is essential to ensure food security and environmental sustainability. The methodology used involved the application of artificial intelligence techniques, specifically Multilayer Perceptron (MLP) Artificial Neural Networks (ANNs), to predict ET₀ in the state of Paraná, Brazil. The models were trained and validated with meteorological data from the Brazilian National Institute of Meteorology (INMET), together with data obtained from a producer's weather station in the western region of Paraná. Two optimizers (SGD and Adam) and different meteorological variables, such as temperature, humidity, solar radiation, and wind speed, were explored as inputs to the models. Nineteen configurations with different input variables were tested; amidst them, configuration 9, with 8 input variables, was identified as the most efficient of all. Configuration 10, with 4 input variables, was considered the most effective, considering the smallest number of variables. The main conclusions of this study show that MLP ANNs are capable of accurately estimating ET₀, providing a valuable tool for irrigation management in agriculture. Both configurations (9 and 10) showed promising performance in predicting ET₀. The validation of the models with cultivator data underlined the practical relevance of these tools and confirmed their generalization ability for different field conditions. The results of the statistical metrics, including Mean Absolute Error (MAE), Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Coefficient of Determination (R²), showed excellent agreement between the model predictions and the observed data, with MAE as low as 0.01 mm/day and 0.03 mm/day, respectively. In addition, the models achieved an R² between 0.99 and 1, indicating a satisfactory fit to the real data. This agreement was also confirmed by the Kolmogorov-Smirnov test, which evaluates the agreement of the predictions with the statistical behavior of the real data and yields values between 0.02 and 0.04 for the producer data. In addition, the results of this study suggest that the developed technique can be applied to other locations by using specific data from these sites to further improve ET₀ predictions and thus contribute to sustainable irrigation management in different agricultural regions. The study has some limitations, such as the use of a single ANN architecture and two optimizers, the validation with data from only one producer, and the possible underestimation of the influence of seasonality and local climate variability. An irrigation management application using the most efficient models from this study is already under development. Future research can explore different ANN architectures and optimization techniques, validate models with data from multiple producers and regions, and investigate the model's response to different seasonal and climatic conditions.

Keywords: agricultural technology, neural networks in agriculture, water efficiency, water use optimization

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Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

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Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

Procedia PDF Downloads 46

Authors: Stefano Sorace, Gloria Terenzi, Giulia Mazzieri, Iacopo Costoli

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The prolonged earthquake sequence that struck several urban agglomerations and villages in Central Italy, starting from 24 August 2016 through January 2017, highlighted once again the seismic vulnerability of pre-normative reinforced concrete (R/C) structures. At the same time, considerable damages were surveyed in recently retrofitted R/C buildings too, one of which also by means of a dissipative bracing system. The solution adopted for the latter did not expressly take into account the performance of non-structural elements, and namely of infills and partitions, confirming the importance of their dynamic interaction with the structural skeleton. Based on this consideration, an alternative supplemental damping-based retrofit solution for this representative building, i.e., a school with an R/C structure situated in the municipality of Norcia, is examined in this paper. It consists of the incorporation of dissipative braces equipped with pressurized silicone fluid viscous (FV) dampers, instead of the BRAD system installed in the building, the delayed activation of which -caused by the high stiffness of the constituting metallic dampers- determined the observed non-structural damages. Indeed, the alternative solution proposed herein, characterized by dissipaters with mainly damping mechanical properties, guarantees an earlier activation of the protective system. A careful assessment analysis, preliminarily carried out to simulate and check the case study building performance in originally BRAD-retrofitted conditions, confirms that the interstorey drift demand related to the Norcia earthquake's mainshock and aftershocks is beyond the response capacity of infills. The verification analyses developed on the R/C structure, including the FV-damped braces, highlight their higher performance, giving rise to a completely undamaged response both of structural and non-structural elements up to the basic design earthquake normative level of seismic action.

Keywords: dissipative technologies, performance assessment analysis, concrete structures, seismic retrofit

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Authors: Muhammad Saleem Akhtar, Mushtaq Hussain Lashari, Ejaz Ahmad, Tanveer Ahmad, Laeeq Akbar Lodhi, Ijaz Ahmad, Masood Akhtar

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The objective of this study was to determine the effect of bull exposure continuously or intermittently or its excretory products after calving on postpartum interval to estrus, in Nili-Ravi buffalo. Forty-eight buffaloes of Nili-Ravi breed were allocated one of the four treatments in a totally randomized plan using a 4 x 1 factorial design. The four treatment groups were BEC (Bull Exposed Continuously), BEI (Bull Exposed Intermittently), EPB (Excretory Products of Bull) and BNE (Bull Not Exposed). BEC; buffaloes (n = 12) were exposed continuously to the physical presence of a bull whereas in BEI; buffaloes (n = 12) were exposed intermittently to the physical presence of bull. EPB; buffaloes (n = 12) were exposed to discharge waste (urine and feces) of bull and BNE buffaloes (n = 12) were not exposed to a bull or discharge waste of bulls. Buffaloes were exposed on day 15 after parturition. Day 15 postpartum represented d 0 for each treatment. The postpartum interval from calving to first behavioural estrus was 66.88 days in BEC, 75.12 days in BEI, 77.28 days in EPB and 76.5 days in BNE treatments. Postpartum interval to first behavioural estrus was shorter in BEC than BEI, EPB, and BNE treatments. There was no significant difference in postpartum interval to estrus between BEI, EPB and BNE treatments. In present study, the percentage of buffaloes showing estrus during experimental period was 75.0%, 66.66%, 66.66% and 58.33% in BEC, BEI, EPB and BNE treatments, respectively. The mean serum progesterone concentration did not differ significantly between BEC and other (BEI, EPB, and BNE) treatments. It was concluded that presence of bull has positive effect in reducing calving interval in Nili Ravi buffalo.

Keywords: calving interval, biostimulation, buffalo, bull exposure

Procedia PDF Downloads 235

Authors: Hong Yu, Ion Matei

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Carbon fiber reinforced composites (CFRP) used as aircraft structure are subject to lightning strike, putting structural integrity under risk. Indirect damage may occur after a lightning strike where the internal structure can be damaged due to excessive heat induced by lightning current, while the surface of the structures remains intact. Three damage modes may be observed after a lightning strike: fiber breakage, inter-ply delamination and intra-ply cracks. The assessment of internal damage states in composite is challenging due to complicated microstructure, inherent uncertainties, and existence of multiple damage modes. In this work, a model based approach is adopted to diagnose faults in carbon composites after lighting strikes. A resistor network model is implemented to relate the overall electrical and thermal conduction behavior under simulated lightning current waveform to the intrinsic temperature dependent material properties, microstructure and degradation of materials. A fault detection and identification (FDI) module utilizes the physics based model and a particle filtering algorithm to identify damage mode as well as calculate the probability of structural failure. Extensive simulation results are provided to substantiate the proposed fault diagnosis methodology with both single fault and multiple faults cases. The approach is also demonstrated on transient resistance data collected from a IM7/Epoxy laminate under simulated lightning strike.

Keywords: carbon composite, fault detection, fault identification, particle filter

Procedia PDF Downloads 181

Authors: Barenten Suciu

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In this work, effects of the friction and truncation on the dynamics of a double-cone gravitational motor, self-propelled on a straight V-shaped horizontal rail, are evaluated. Such mechanism has a variable radius of contact, and, on one hand, it is similar to a pulley mechanism that changes the potential energy into the kinetic energy of rotation, but on the other hand, it is similar to a pendulum mechanism that converts the potential energy of the suspended body into the kinetic energy of translation along a circular path. Movies of the self- propelled double-cones, made of S45C carbon steel and wood, along rails made of aluminum alloy, were shot for various opening angles of the rails. Kinematical features of the double-cones were estimated through the slow-motion processing of the recorded movies. Then, a kinematical model is derived under assumption that the distance traveled by the contact points on the rectilinear rails is identical with the distance traveled by the contact points on the truncated conical surface. Additionally, a dynamic model, for this particular contact problem, was proposed and validated against the experimental results. Based on such model, the traction force and the traction torque acting on the double-cone are identified. One proved that the rolling traction force is always smaller than the sliding friction force; i.e., the double-cone is rolling without slipping. Results obtained in this work can be used to achieve the proper design of such gravitational motor.

Keywords: Truncated double-cone, friction, rolling and sliding, dynamic model, gravitational motor

Procedia PDF Downloads 259

Authors: Yangrae Cho, Jinseok Kim, Yongtae Park

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Mobile app service ecosystem has been abruptly emerged, explosively grown, and dynamically transformed. In contrast with product markets in which product sales directly cause increment in firm’s income, customer’s usage is less visible but more valuable in service market. Especially, the market situation with cutthroat competition in mobile app store makes securing and keeping of users as vital. Although a few service firms try to manage their apps’ usage patterns by fitting on S-curve or applying other forecasting techniques, the time series approaches based on past sequential data are subject to fundamental limitation in the market where customer’s attention is being moved unpredictably and dynamically. We therefore propose a new conceptual approach for detecting usage pattern of mobile app service with Hidden Markov Model (HMM) which is based on the dual stochastic structure and mainly used to clarify unpredictable and dynamic sequential patterns in voice recognition or stock forecasting. Our approach could be practically utilized for app service firms to manage their services’ lifecycles and academically expanded to other markets.

Keywords: mobile app service, usage pattern, Hidden Markov Model, pattern detection

Procedia PDF Downloads 323

Authors: Fawzi Srairi, Abderrahmane Dib

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Recently, the desire for a self-powered micro and nanodevices has attracted a great interest of using sustainable energy sources. Further, the ultimate goal of nanogenerator is to harvest energy from the ambient environment in which a self-powered device based on these generators is needed. With the development of nanogenerator-based circuits design and optimization, the building of new device simulator is necessary for the study and the synthesis of electromechanical parameters of this type of models. In the present article, both numerical modeling and optimization of piezoelectric nanogenerator based on zinc oxide have been carried out. They aim to improve the electromechanical performances, robustness, and synthesis process for nanogenerator. The proposed model has been developed for a systematic study of the nanowire morphology parameters in stretching mode. In addition, heuristic optimization technique, namely, particle swarm optimization has been implemented for an analytic modeling and an optimization of nanogenerator-based process in stretching mode. Moreover, the obtained results have been tested and compared with conventional model where a good agreement has been obtained for excitation mode. The developed nanogenerator model can be generalized, extended and integrated into simulators devices to study nanogenerator-based circuits.

Keywords: electrical potential, heuristic algorithms, numerical modeling, nanogenerator

Procedia PDF Downloads 290

Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: dynamic area requirements, facility layout problem, optimization model, product assembly

Procedia PDF Downloads 218