Search results for: sampling algorithms

Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Amirhossein Safi

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Internet of things (IOT) is a kind of advanced information technology which has drawn societies’ attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously, IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission, and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually, the suggested encryption algorithm has been simulated by MATLAB software, and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Keywords: internet of things, security, hybrid algorithm, privacy

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Authors: Hazratullah Khattak, Abdul Waheed Mughal, Inamullah Khattak

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This study is envisaged as vital contribution as it intends to develop norms for the Sit and Reach Test in the Local Environment of Khyber Pakhtunkhwa Pakistan, for the age group between 12-14 years which will be used to measure the flexibility level of early adolescents (12-14 years). Sit and Reach test was applied on 2000 volunteers, 400 subjects from each selected district (Five (5) Districts, Peshawar, Nowshera, Karak, Dera Ismail Khan and Swat (20% percent of the total 25 districts) using convenient sampling technique. The population for this study is comprised of all the early adolescents aging 12-14 years (Age Mean 13 + 0.63, Height 154 + 046, Weight 46 + 7.17, BMI 19 + 1.45) representing various public and private sectors educational institutions of the Khyber Pakhtunkhwa. As for as the norms developed for Sit and Reach test, the score below 6.8 inches comes in the category of poor, 6.9 to 9.6 inches (below Average), 9.7 to 10.8 inches (Average), 10.9 to 13 inches (Above average) and above 13 inches score is considered as Excellent.

Keywords: fitness, flexibility, norms, sit and reach

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Authors: Baoshan Wei, Shuai Han, Xing Zhang

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Local obstacle avoidance is critical for mobile robot navigation. It is a challenging task to ensure path optimality and safety in cluttered environments. We proposed an Environment Aware Dynamic Window Approach in this paper to cope with the issue. The method integrates environment characterization into Dynamic Window Approach (DWA). Two strategies are proposed in order to achieve the integration. The local goal strategy guides the robot to move through openings before approaching the final goal, which solves the local minima problem in DWA. The adaptive control strategy endows the robot to adjust its state according to the environment, which addresses path safety compared with DWA. Besides, the evaluation shows that the path generated from the proposed algorithm is safer and smoother compared with state-of-the-art algorithms.

Keywords: adaptive control, dynamic window approach, environment aware, local obstacle avoidance, mobile robots

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Authors: Kunle Oparinde, Rachel Matteau-Matsha, Felix Awung

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In recent times, the issue of gender-based violence against women in South Africa is prevalent in headlines due to the high rate of attacks directed towards women. Ranging from teenagers to adults, women are continuously targeted indiscriminately in what is seemingly becoming a prolonged cycle in the country. To this end, human rights activists, organisations, and political leaders have managed to somewhat verbally condemn the atrocious acts. Further, interested people in South Africa, through walks and protests, have continued to speak against the swinging violence against women in the country. The thrust in this study is to explore and analyse how discourse (language) has been employed as a resounding voice against gender violence in the country. Through a purposive sampling of materials employed during walks and protests, collected from online sources, we examine how language is being used to combat and confront the issue of gender violence viz-a-viz how it continues to serve as a crucial tool in repelling gender violence.

Keywords: gender, violence, language, discourse, resistance

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: Sujay Kotwale, Ramasubba Reddy M.

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Electrocardiogram (ECG) is a non-invasive technique used to study and analyze various heart diseases. Cardiac arrhythmia is a serious heart disease which leads to death of the patients, when left untreated. An early-time detection of cardiac arrhythmia would help the doctors to do proper treatment of the heart. In the past, various algorithms and machine learning (ML) models were used to early-time detection of cardiac arrhythmia, but few of them have achieved better results. In order to improve the performance, this paper implements principal component analysis (PCA) along with XGBoost model. The PCA was implemented to the raw ECG signals which suppress redundancy information and extracted significant features. The obtained significant ECG features were fed into XGBoost model and the performance of the model was evaluated. In order to valid the proposed technique, raw ECG signals obtained from standard MIT-BIH database were employed for the analysis. The result shows that the performance of proposed method is superior to the several state-of-the-arts techniques.

Keywords: cardiac arrhythmia, electrocardiogram, principal component analysis, XGBoost

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Authors: Yohana Fessehazion

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Mercury is a prominent example of a heavy metal contaminant in the environment, and it has been extensively investigated for its potential health risk in humans and other organisms. In South Africa, massive mercury contamination happened in1980s when the England-based mercury reclamation processing plant relocated to Cato Ridge, KwaZulu-Natal Province, and discharged mercury waste into the Mngceweni River. This mercury waste discharge resulted in high mercury concentration that exceeded the acceptable levels in Mngceweni River, Umgeni River, and human hair of the nearby villagers. This environmental issue raised the alarm, and over the years, several environmental assessments were reported the dire environmental crises resulting from the Thor Chemicals (now known as Metallica Chemicals) and urged the immediate removal of the around 3,000 tons of mercury waste stored in the factory storage facility over two decades. Recently theft of some containers with the toxic substance from the Thor Chemicals warehouse and the subsequent fire that ravaged the facility furtherly put the factory on the spot escalating the urgency of left behind deadly mercury waste removal. This project aims to investigate the mercury contamination leaking from an old Thor Chemicals mercury processing plant. The focus will be on sediments, water, terrestrial plants, and aquatic weeds such as the prominent water hyacinth weeds in the nearby water systems of Mngceweni River, Umgeni River, and Inanda Dam as a bio-indicator and phytoremediator for mercury pollution. Samples will be collected in spring around October when the condition is favourable for microbial activity to methylate mercury incorporated in sediments and blooming season for some aquatic weeds, particularly water hyacinth. Samples of soil, sediment, water, terrestrial plant, and aquatic weed will be collected per sample site from the point of source (Thor Chemicals), Mngceweni River, Umgeni River, and the Inanda Dam. One-way analysis of variance (ANOVA) tests will be conducted to determine any significant differences in the Hg concentration among all sampling sites, followed by Least Significant Difference post hoc test to determine if mercury contamination varies with the gradient distance from the source point of pollution. The flow injection atomic spectrometry (FIAS) analysis will also be used to compare the mercury sequestration between the different plant tissues (roots and stems). The principal component analysis is also envisaged for use to determine the relationship between the source of mercury pollution and any of the sampling points (Umgeni and Mngceweni Rivers and the Inanda Dam). All the Hg values will be expressed in µg/L or µg/g in order to compare the result with the previous studies and regulatory standards. Sediments are expected to have relatively higher levels of Hg compared to the soils, and aquatic macrophytes, water hyacinth weeds are expected to accumulate a higher concentration of mercury than terrestrial plants and crops.

Keywords: mercury, phytoremediation, Thor chemicals, water hyacinth

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Authors: Rungnapa Chantra

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As health care rapidly changes, the nursing profession is also evolving to improve quality of care while maintaining competency in their practice. The purpose of this study was to investigate the factors of disaster nurse competencies and investigate the predictable variables in disaster nurse competencies in Suratthani Province, Thailand. The sample consisted of 305 nurses who were recruited by simple random sampling. The development questionnaires from ICN Framework and research contains Pre/Mitigation, Preparedness, Response and Recovery/Rehabilitation Competencies (α=0.87). The data were analyzed using Principle Components Extraction and Orthogonal Rotation with Varimax Method. The findings were as follows; four significant factors of disaster nurse competencies in Suratthani Province, Thailand were identified. These factors were described by 62 variables that accounted for 50.01% of the total variance. The results of this study could be for agencies that are responsible for the development of nursing competencies and should be aware of the development of knowledge and skills in disaster management.

Keywords: disaster nursing competency of nurses, nursing informatics, health science, medical

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Authors: Derek Brandon G. Yu, Clyde Vincent O. Pilapil, Christine F. Peña

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College students of Cebu province have been indoors since March 2020, and a challenge encountered is the sudden shift from face to face to online learning and with the lack of empirical data on online learning on Higher Education Institutions (HEIs) in the Philippines. Sentiments on face to face and online learning will be collected from University of San Carlos (USC), School of Arts and Sciences (SAS) students regarding Mathematics in the Modern World (MMW), a General Education (GE) course. Natural Language Processing with machine learning algorithms will be used to classify the sentiments of the students. Results of the research study are the themes identified through topic modelling and the overall sentiments of the students in USC SAS

Keywords: natural language processing, online learning, sentiment analysis, topic modelling

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Authors: Ludmila Polechonska, Agnieszka Klink

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The biogeochemical studies of macrophytes shed light on elements bioavailability, transfer through the food webs and their possible effects on the biota, and provide a basis for their practical application in aquatic monitoring and remediation. Measuring the accumulation of elements in plants can provide time-integrated information about the presence of chemicals in aquatic ecosystems. The aim of the study was to determine and compare the contents of micro- and macroelements in two cosmopolitan macrophytes, submerged Ceratophyllum demersum (hornworth) and free-floating Hydrocharis morsus-ranae (European frog-bit), in order to assess their bioaccumulation potential, elements stock accumulated in each plant and their role in nutrients cycling in small water reservoirs. Sampling sites were designated in 25 oxbow lakes in urban areas in Lower Silesia (SW Poland). In each sampling site, fresh whole plants of C. demersum and H. morsus-ranae were collected from squares of 1x1 meters each where the species coexisted. European frog-bit was separated into leaves, stems and roots. For biomass measurement all plants growing on 1 square meter were collected, dried and weighed. At the same time, water samples were collected from each reservoir and their pH and EC were determined. Water samples were filtered and acidified and plant samples were digested in concentrated nitric acid. Next, the content of Ca, Cu, Fe, K, Mg, Mn, Ni and Zn was determined using atomic absorption method (AAS). Statistical analysis showed that C. demersum and organs of H. morsus-ranae differed significantly in respect of metals content (Kruskal-Wallis Anova, p<0.05). Contents of Cu, Mn, Ni and Zn were higher in hornwort, while European frog-bit contained more Ca, Fe, K, Mg. Bioaccumulation Factors (BCF=content in plant/concentration in water) showed similar pattern of metal bioaccumulation – microelements were more intensively accumulated by hornwort and macroelements by frog-bit. Based on BCF values both species may be positively evaluated as good accumulators of Cu, Fe, Mn, Ni and Zn. However, the distribution of metals in H. morsus-ranae was uneven – the majority of studied elements were retained in roots, which may indicate to existence of physiological barriers developed for dealing with toxicity. Some percent of Ca and K was actively transported to stems, but to leaves Mg only. Although the biomass of C. demersum was two times greater than biomass of H. morsus-ranae, the element off-take was greater only for Cu, Mn, Ni and Zn. Nevertheless, it can be stated that despite a relatively small biomass, compared to other macrophytes, both species may have an influence on the removal of trace elements from aquatic ecosystems and, as they serve as food for some animals, also on the incorporation of toxic elements into food chains. There was a significant positive correlation between content of Mn and Fe in water and roots of H. morus-ranae (R=0.51 and R=0.60, respectively) as well as between Cu concentration in water and in C. demersum (R=0.41) (Spearman rank correlation, p<0.05). High bioaccumulation rates and correlation between plants and water elements concentrations point to their possible use as passive biomonitors of aquatic pollution.

Keywords: aquatic plants, bioaccumulation, biomonitoring, macroelements, phytoremediation, trace metals

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Authors: Mari Jaakkola, Jasmiina Haverinen, Tiina Tolonen, Vesa Virtanen

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These process monitoring of biogas plant gives valuable information of the function of the process and help to maintain a stable process. The costs of basic monitoring are often much lower than the costs associated with re-establishing a biologically destabilised plant. Reactor acidification through reactor overload is one of the most common reasons for process deterioration in anaerobic digesters. This occurs because of a build-up of volatile fatty acids (VFAs) produced by acidogenic and acetogenic bacteria. VFAs cause pH values to decrease, and result in toxic conditions in the reactor. Ammonia ensures an adequate supply of nitrogen as a nutrient substance for anaerobic biomass and increases system's buffer capacity, counteracting acidification lead by VFA production. However, elevated ammonia concentration is detrimental to the process due to its toxic effect. VFAs are considered the most reliable analytes for process monitoring. To obtain accurate results, sample storage and transportation need to be carefully controlled. This may be a challenge for off-line laboratory analyses especially when the plant is located far away from the laboratory. The aim of this study was to investigate the correlation between fatty acids, ammonium, and bacteria in the anaerobic digestion samples obtained from an industrial biogas factory. The stability of the analytes was studied comparing the results of the on-site analyses performed in the factory site to the results of the samples stored at room temperature and -18°C (up to 30 days) after sampling. Samples were collected in the biogas plant consisting of three separate mesofilic AD reactors (4000 m³ each) where the main feedstock was swine slurry together with a complex mixture of agricultural plant and animal wastes. Individual VFAs, ammonium, and nutrients (K, Ca, Mg) were studied by capillary electrophoresis (CE). Longer chain fatty acids (oleic, hexadecanoic, and stearic acids) and bacterial profiles were studied by GC-MSD (Gas Chromatography-Mass Selective Detector) and 16S rDNA, respectively. On-site monitoring of the analytes was performed by CE. The main VFA in all samples was acetic acid. However, in one reactor sample elevated levels of several individual VFAs and long chain fatty acids were detected. Also bacterial profile of this sample differed from the profiles of other samples. Acetic acid decomposed fast when the sample was stored in a room temperature. All analytes were stable when stored in a freezer. Ammonium was stable even at a room temperature for the whole testing period. One reactor sample had higher concentration of VFAs and long chain fatty acids than other samples. CE was utilized successfully in the on-site analysis of separate VFAs and NH₄ in the biogas production site. Samples should be analysed in the sampling day if stored in RT or freezed for longer storage time. Fermentation reject can be stored (and transported) at ambient temperature at least for one month without loss of NH₄. This gives flexibility to the logistic solutions when reject is used as a fertilizer.

Keywords: anaerobic digestion, capillary electrophoresis, ammonium, bacteria

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Authors: Zzibu Mark Brian

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As software systems become increasingly complex, ensuring code security is a growing concern. Traditional vulnerability detection methods often rely on manual code reviews or static analysis tools, which can be time-consuming and prone to errors. This paper presents a distinct approach to enhancing code security by leveraging artificial intelligence (AI) and machine learning (ML) techniques. Our proposed system utilizes a combination of natural language processing (NLP) and deep learning algorithms to identify and classify vulnerabilities in real-world codebases. By analyzing vast amounts of open-source code data, our AI-powered tool learns to recognize patterns and anomalies indicative of security weaknesses. We evaluated our system on a dataset of over 10,000 open-source projects, achieving an accuracy rate of 92% in detecting known vulnerabilities. Furthermore, our tool identified previously unknown vulnerabilities in popular libraries and frameworks, demonstrating its potential for improving software security.

Keywords: AI, machine language, cord security, machine leaning

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Authors: Tavee Cheausuwantavee

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: COVID-19 pandemic significantly has impacted everyone’s life. Persons with disabilities (PWDs) in Thailand have been also effected by COVID-19 situation in many aspects of their lives, while there have been no more appropriate services of the government and providers. Research projects had been only focused on health precaution and protection. Rapid need assessments on populations and vulnerable groups were limited and conducted via social media and an online survey. However, little is known about the real problems and needs of Thai PWDs during the COVID-19 pandemic for an effective plan and integral services for those PWDs. Therefore, this study aims to explore the diverse problems and needs of Thai PWDs in the COVID -19 pandemic. Results from the study can be used by the government and other stakeholders for further effective services. Methods: This study was used a mixed-method design that consisted of both quantitative and qualitative measures. In terms of the quantitative approach, there were 744 PWDs and caregivers of all types of PWDs selected by proportional multistage stratified random sampling according to their disability classification and geographic location. Questionnaires with 59 items regarding participant characteristics, problems, and needs in health, education, employment, and other social inclusion, were distributed to all participants and some caregivers completed questionnaires when PWDs were not able to due to limited communication and/or literacy skills. Completed questionnaires were analyzed by descriptive statistics. For qualitative design, 62 key informants who were PWDs or caregivers were selected by purposive sampling. Ten focus groups, each consisting of 5-6 participants and 7 in-depth interviews from all the groups identified above, were conducted by researchers across five regions. Focus group and in-depth interview guidelines with 6 items regarding problems and needs in health, education, employment, other social inclusion, and their coping during COVID -19 pandemic. Data were analyzed using a modification of thematic content analysis. Results: Both quantitative and qualitative studies showed that PWDs and their caregivers had significant problems and needs all aspects of their life, including income and employment opportunity, daily living and social inclusion, health, and education, respectively. These problems and needs were related to each other, forming a vicious cycle. Participants also learned from negative pandemic to more positive life aspects, including their health protection, financial plan, family cohesion, and virtual technology literacy and innovation. Conclusion and implications: There have been challenges facing all life aspects of PWDs in Thailand during the COVID -19 pandemic, particularly incomes and daily living. All challenges have been the vicious cycle and complicated. There have been also a positive lesson learned of participants from the pandemic. Recommendations for government and stakeholders in the COVID-19 pandemic for PWDs are the following. First, the health protection strategy and policy of PWDs should be promoted together with other quality of life development including income generation, education and social inclusion. Second, virtual technology and alternative innovation should be enhanced for proactive service providers. Third, accessible information during the pandemic for all PWDs must be concerned. Forth, lesson learned from the pandemic should be shared and disseminated for crisis preparation and a positive mindset in the disruptive world.

Keywords: challenge, COVID-19, disability, Thailand

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Authors: Rodrigo C. Belleza, Jr., Roselyn A. Maaño, Karl Patrick E. Camota, Darwin Kim Q. Bulawan

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Eyes are an essential and conspicuous organ of the human body. Human eyes are outward and inward portals of the body that allows to see the outside world and provides glimpses into ones inner thoughts and feelings. Inevitable blindness and visual impairments may result from eye-related disease, trauma, or congenital or degenerative conditions that cannot be corrected by conventional means. The study emphasizes innovative tools that will serve as an aid to the blind and visually impaired (VI) individuals. The researchers fabricated a prototype that utilizes the Microsoft Kinect for Windows and Arduino microcontroller board. The prototype facilitates advanced gesture recognition, voice recognition, obstacle detection and indoor environment navigation. Open Computer Vision (OpenCV) performs image analysis, and gesture tracking to transform Kinect data to the desired output. A computer vision technology device provides greater accessibility for those with vision impairments.

Keywords: algorithms, blind, computer vision, embedded systems, image analysis

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Authors: B. Falah, N. E. Abakouy

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Due to its high computational cost, mutation testing has been neglected by researchers. Recently, many cost and mutants’ reduction techniques have been developed, improved, and experimented, but few of them has relied the possibility of reducing the cost of mutation testing on the program type of the application under test. This paper is a comparative study between four operators’ selection techniques (mutants sampling, class level operators, method level operators, and all operators’ selection) based on the program code type of each application under test. It aims at finding an alternative approach to reveal the effect of code type on mutation testing score. The result of our experiment shows that the program code type can affect the mutation score and that the programs using polymorphism are best suited to be tested with mutation testing.

Keywords: equivalent mutant, killed mutant, mutation score, mutation testing, program code type, software testing

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Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.

Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks

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Authors: Behdoukht Mall Amiri, Zohreh Gheydar

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The thrust of the current study was to investigate the relationship among EFL learners' creativity (CR), emotional intelligence (EI), and self-efficacy (SE). To this end, a group of 120 male and female learners, between the ages of 19 and 35 studying BA in English Translation and MA in Teaching English at Islamic Azad University, Central Tehran were selected using convenient sampling and were given three questionnaires: Bar-On’s EQ-I questionnaire by Bar-On (1997), the General Self-Efficacy Scale questionnaire (SGSES) by Sherer et al. (1982), and a questionnaire of creativity (CR) by O'Neil, Abedi, and Spielberger (1992). Analysis of the results through Pearson Moment Correlation Coefficient showed that there was not a significant relationship between students’ CR and EI, and EI and SE. In addition, CR and SE were correlated significantly but negatively. Multiple regressions revealed that CR could significantly predict SE. Regarding the findings of the study, the obtained results may help EFL teachers, teacher trainers, materials developers, and educational policy makers to possess a broader perspective and heightened degree knowledge toward the TEFL practice and to take practical steps toward the attainments of the desired objectives of the profession.

Keywords: creativity, emotional intelligence, self-efficacy, learning

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Authors: Krisada Lekdee, Sunee Sammatat, Nittaya Boonsit

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This paper proposes a GLMM with spatial and temporal effects for malaria data in Thailand. A Bayesian method is used for parameter estimation via Gibbs sampling MCMC. A conditional autoregressive (CAR) model is assumed to present the spatial effects. The temporal correlation is presented through the covariance matrix of the random effects. The malaria quarterly data have been extracted from the Bureau of Epidemiology, Ministry of Public Health of Thailand. The factors considered are rainfall and temperature. The result shows that rainfall and temperature are positively related to the malaria morbidity rate. The posterior means of the estimated morbidity rates are used to construct the malaria maps. The top 5 highest morbidity rates (per 100,000 population) are in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4, 97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82). According to the DIC criterion, the proposed model has a better performance than the GLMM with spatial effects but without temporal terms.

Keywords: Bayesian method, generalized linear mixed model (GLMM), malaria, spatial effects, temporal correlation

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Authors: Saba Rahimi, Ozan Oktay, Javier Alvarez-Valle, Sujeeth Bharadwaj

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Successful application of deep learning in medical image analysis necessitates unprecedented amounts of labeled training data. Unlike conventional 2D applications, radiological images can be three-dimensional (e.g., CT, MRI), consisting of many instances within each image. The problem is exacerbated when expert annotations are required for effective pixel-wise labeling, which incurs exorbitant labeling effort and cost. Active learning is an established research domain that aims to reduce labeling workload by prioritizing a subset of informative unlabeled examples to annotate. Our contribution is a cost-effective approach for U-Net 3D models that uses Monte Carlo sampling to analyze pixel-wise uncertainty. Experiments on the AAPM 2017 lung CT segmentation challenge dataset show that our proposed framework can achieve promising segmentation results by using only 42% of the training data.

Keywords: image segmentation, active learning, convolutional neural network, 3D U-Net

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Authors: Lusungu Ndovi

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Radio propagation from point-to-point is affected by the physical channel in many ways. A signal arriving at a destination travels through a number of different paths which are referred to as multi-paths. Research in this area of wireless communications has progressed well over the years with the research taking different angles of focus. By this is meant that some researchers focus on ways of reducing or eluding Multipath effects whilst others focus on ways of mitigating the effects of Multipath through compensation schemes. Baseband processing is seen as one field of signal processing that is cardinal to the advancement of software-defined radio technology. This has led to wide research into the carrying out certain algorithms at baseband. This paper considers compensating for Multipath for Frequency Modulated signals. The compensation process is carried out at Radio frequency (RF) and at Quadrature baseband (QBB) and the results are compared. Simulations are carried out using MatLab so as to show the benefits of working at lower QBB frequencies than at RF.

Keywords: quadrature baseband, qadio frequency, qultipath compensation, frequency qodulation, signal processing

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Authors: Ionel Zagan, Vasile Gheorghita Gaitan

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The development of CPUs and of real-time systems based on them made it possible to use time at increasingly low resolutions. Together with the scheduling methods and algorithms, time organizing has been improved so as to respond positively to the need for optimization and to the way in which the CPU is used. This presentation contains both a detailed theoretical description and the results obtained from research on improving the performances of the nMPRA (Multi Pipeline Register Architecture) processor by implementing specific functions in hardware. The proposed CPU architecture has been developed, simulated and validated by using the FPGA Virtex-7 circuit, via a SoC project. Although the nMPRA processor hardware structure with five pipeline stages is very complex, the present paper presents and analyzes the tests dedicated to the implementation of the CPU and of the memory on-chip for instructions and data. In order to practically implement and test the entire SoC project, various tests have been performed. These tests have been performed in order to verify the drivers for peripherals and the boot module named Bootloader.

Keywords: hardware scheduler, nMPRA processor, real-time systems, scheduling methods

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Authors: Sadik Yigit

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The energy consumed in the buildings constitutes a large portion of the total energy consumption in the world. In this study, it was aimed to measure the impact of climate change on the energy consumption of residential building stock by analyzing a typical mid-rise residential building in four different climate regions of Turkey. An integrated system was developed using the "Distribution Evolutionary Algorithms in Python" tool and Energy Plus. By using the developed integrated system, the energy performance of the typical residential building was analyzed under the effect of different climate change scenarios. The results indicated that predicted overheating will be experienced in the future, which will significantly increase the cooling energy loads of the buildings. In addition, design solutions to improve the future energy performance of the buildings were proposed, considering budget constraints. The results of the study will guide researchers studying in this area of research and designers in the sector in finding climate change resilient design solutions.

Keywords: energy_efficient, residential buildings, climate change, energyplus

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Authors: Parampal Kaur, Deepak Aggarwal

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In the computational Grid, fault tolerance is an imperative issue to be considered during job scheduling. Due to the widespread use of resources, systems are highly prone to errors and failures. Hence, fault tolerance plays a key role in the grid to avoid the problem of unreliability. Scheduling the task to the appropriate resource is a vital requirement in computational Grid. The fittest resource scheduling algorithm searches for the appropriate resource based on the job requirements, in contrary to the general scheduling algorithms where jobs are scheduled to the resources with best performance factor. The proposed method is to improve the fault tolerance of the fittest resource scheduling algorithm by scheduling the job in coordination with job replication when the resource has low reliability. Based on the reliability index of the resource, the resource is identified as critical. The tasks are scheduled based on the criticality of the resources. Results show that the execution time of the tasks is comparatively reduced with the proposed algorithm using real-time approach rather than a simulator.

Keywords: computational grid, fault tolerance, task replication, job scheduling

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Authors: Kamyar Tolouei, Ehsan Moosavi

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In open-pit mines, the long-term production scheduling optimization problem (LTPSOP) is a complicated problem that contains constraints, large datasets, and uncertainties. Uncertainty in the output is caused by several geological, economic, or technical factors. Due to its dimensions and NP-hard nature, it is usually difficult to find an ideal solution to the LTPSOP. The optimal schedule generally restricts the ore, metal, and waste tonnages, average grades, and cash flows of each period. Past decades have witnessed important measurements of long-term production scheduling and optimal algorithms since researchers have become highly cognizant of the issue. In fact, it is not possible to consider LTPSOP as a well-solved problem. Traditional production scheduling methods in open-pit mines apply an estimated orebody model to produce optimal schedules. The smoothing result of some geostatistical estimation procedures causes most of the mine schedules and production predictions to be unrealistic and imperfect. With the expansion of simulation procedures, the risks from grade uncertainty in ore reserves can be evaluated and organized through a set of equally probable orebody realizations. In this paper, to synthesize grade uncertainty into the strategic mine schedule, a stochastic integer programming framework is presented to LTPSOP. The objective function of the model is to maximize the net present value and minimize the risk of deviation from the production targets considering grade uncertainty simultaneously while satisfying all technical constraints and operational requirements. Instead of applying one estimated orebody model as input to optimize the production schedule, a set of equally probable orebody realizations are applied to synthesize grade uncertainty in the strategic mine schedule and to produce a more profitable and risk-based production schedule. A mixture of metaheuristic procedures and mathematical methods paves the way to achieve an appropriate solution. This paper introduced a hybrid model between the augmented Lagrangian relaxation (ALR) method and the metaheuristic algorithm, the Harris Hawks optimization (HHO), to solve the LTPSOP under grade uncertainty conditions. In this study, the HHO is experienced to update Lagrange coefficients. Besides, a machine learning method called Random Forest is applied to estimate gold grade in a mineral deposit. The Monte Carlo method is used as the simulation method with 20 realizations. The results specify that the progressive versions have been considerably developed in comparison with the traditional methods. The outcomes were also compared with the ALR-genetic algorithm and ALR-sub-gradient. To indicate the applicability of the model, a case study on an open-pit gold mining operation is implemented. The framework displays the capability to minimize risk and improvement in the expected net present value and financial profitability for LTPSOP. The framework could control geological risk more effectively than the traditional procedure considering grade uncertainty in the hybrid model framework.

Keywords: grade uncertainty, metaheuristic algorithms, open-pit mine, production scheduling optimization

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Authors: Saleh Komies, Mona Alharbi, Razan Alhayyani, Mozah Almulhim, Roseanne Khawaja, Ahmed Alradhi

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One of the proposed solutions that faces some challenges is encouraging sustainable energy consumption across Saudi Arabia through crowdfunding platforms. To address these challenges, we need to determine the level of awareness of crowdfunding and green projects, as well as the preferences and willingness of Saudis to utilize crowdfunding as an alternative funding source for green projects in Saudi Arabia. In this study, we aim to determine the influence of environmental awareness and concern on the propensity to crowdfund green projects. The survey is being conducted as part of environmental initiatives to assess public perceptions and opinions on crowdfunding green projects in Saudi Arabia. A total of 450 responses to an online questionnaire distributed via convenience and snowball sampling were utilized for data analysis. The survey reveals that Saudis have a low understanding of crowdfunding concepts and a relatively high understanding of implementing green projects. The public is interested in crowdfunding green projects if there is a return on investment.

Keywords: crowdfunding, green projects, awareness, Saudi Arabia, energy, solar, wind

Procedia PDF Downloads 100

Authors: Fawehinmi Olabisi Alaba, O. R. Adeniyi

Abstract:

Farming households faces lots of disaster which contribute to endemic poverty. Anticipated increases in extreme weather events will exacerbate this. Primary data was administered to farming household using multi-stage random sampling technique. The result of the analysis shows that majority of the respondents (69.9%) are male, have mean household size, years of formal education and age of 5±1.14, 6±3.41, and 51.06±10.43 respectively. The major (48.9%) type of disaster experienced is flooding. Major coping mechanism adopted is sourcing for support from family and friends. Age, education, experience, access to extension agent, and mitigation control method contribute significantly to vulnerability to disaster. The major adaptation method (62.3%) is construction of drainage. The study revealed that the coping mechanisms employed may become less effective as increasingly fragile livelihood systems struggle to withstand disaster shocks. Thus there is need for training of the farmers on measures to adapt to mitigate the shock from disasters.

Keywords: adaptation, disasters, flooding, vulnerability

Procedia PDF Downloads 261

Authors: Anam Bhatti, Sumbal Arif, Mariam Mehar, Sohail Younas

Abstract:

CSR has become one of the imperative implements in satisfying customers. The impartial of this research is to calculate CSR, relationship marketing, and customer satisfaction. In Pakistan, there is not enough research work on the effect of CSR and relationship marketing on relationship maintainer and customer loyalty. To find out deductive approach and survey method is used as research approach and research strategy respectively. This research design is descriptive and quantitative study. For data, collection questionnaire method with semantic differential scale and seven point scales are adopted. Data has been collected by adopting the non-probability convenience technique as sampling technique and the sample size is 400. For factor confirmatory factor analysis, structure equation modeling and medication analysis, regression analysis Amos software were used. Strong empirical evidence supports that the customer’s perception of CSR performance is highly influenced by the values.

Keywords: CSR, Relationship marketing, Relationship maintainer, Customer loyalty, Customer satisfaction

Procedia PDF Downloads 486

Authors: Rania Alshikhe, Vinita Jindal

Abstract:

Digital innovation has played a crucial role in managing smart transportation. For this, big trajectory data collected from traveling vehicles, such as taxis through installed global positioning system (GPS)-enabled devices can be utilized. It offers an unprecedented opportunity to trace the movements of vehicles in fine spatiotemporal granularity. This paper aims to explore big trajectory data to measure the travel efficiency of road networks using the proposed statistical travel efficiency measure (STEM) across an entire city. Further, it identifies the cause of low travel efficiency by proposed least square approximation network-based causality exploration (LANCE). Finally, the resulting data analysis reveals the causes of low travel efficiency, along with the road segments that need to be optimized to improve the traffic conditions and thus minimize the average travel time from given point A to point B in the road network. Obtained results show that our proposed approach outperforms the baseline algorithms for measuring the travel efficiency of the road network.

Keywords: GPS trajectory, road network, taxi trips, digital map, big data, STEM, LANCE

Procedia PDF Downloads 158

Authors: Robert Pintaric, Joze Matela, Stefan Pintaric, Stanka Vadnjal

Abstract:

Introduction: This work is aimed to represent the use of the OPTI-JET CS MD1 MR prototype for application of neutral electrolyzed oxidizing water (NEOW) in magnetic resonance rooms. Material and Methods: We produced and used OPTI-JET CS MD1 MR aerosolisator whereby was performed aerosolization. The presence of microorganisms before and after the aerosolisation was recorded with the help of cyclone air sampling. Colony formed units (CFU) was counted. Results: The number of microorganisms in magnetic resonance 3T room was low as expected. Nevertheless, a possible CFU reduction of 87% was recorded. Conclusions: The research has shown that the use of EOW for the air and hard surface disinfection can considerably reduce the presence of microorganisms and consequently the possibility of hospital infections. It has also demonstrated that the use of OPTI-JET CS MD1 MR is very good. With this research, we started new guidelines for aerosolization in magnetic resonance rooms. Future work: We predict that presented technique works very good but we must focus also on time capacity sensors, and new appropriate toxicological studies.

Keywords: biocide, electrolyzed oxidizing water (EOW), disinfection, microorganisms, OPTI-JET CS MD1MR

Procedia PDF Downloads 393