Search results for: Comprehensive learning Particle Swarmoptimization

Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, Mujeeb Ur Rehman, Saifur Rahman Sabuj

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This paper examines relationships between solar activity and earthquakes, it applied machine learning techniques: K-nearest neighbour, support vector regression, random forest regression, and long short-term memory network. Data from the SILSO World Data Center, the NOAA National Center, the GOES satellite, NASA OMNIWeb, and the United States Geological Survey were used for the experiment. The 23rd and 24th solar cycles, daily sunspot number, solar wind velocity, proton density, and proton temperature were all included in the dataset. The study also examined sunspots, solar wind, and solar flares, which all reflect solar activity, and earthquake frequency distribution by magnitude and depth. The findings showed that the long short-term memory network model predicts earthquakes more correctly than the other models applied in the study, and solar activity is more likely to effect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth

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Keywords: K-Nearest Neighbour, Support Vector Regression, Random Forest Regression, Long Short-Term Memory Network, earthquakes, solar activity, sunspot number, solar wind, solar flares.

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Authors: Tatiani D. Mousoura

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Specific learning disability (SLD) in higher education has been partially explored in Greece so far. Moreover, opinions on professional perspectives for university students with SLD, is scarcely encountered in Greek research. The perceptions of the hidden character of SLD along with the university policy towards it and professional perspectives that result from this policy have been examined in the present research. This study has applied the paradigm of a Greek Tertiary Pedagogical Education Department (Early Childhood Education). Via mixed methods, data have been collected from different groups of people in the Pedagogical Department: students with SLD and without SLD, academic staff and administration staff, all of which offer the opportunity for triangulation of the findings. Qualitative methods include ten interviews with students with SLD and 15 interviews with academic staff and 60 hours of observation of the students with SLD. Quantitative methods include 165 questionnaires completed by third and fourth-year students and five questionnaires completed by the administration staff. Thematic analyses of the interviews’ data and descriptive statistics on the questionnaires’ data have been applied for the processing of the results. The use of medical terms to define and understand SLD was common in the student cohort, regardless of them having an SLD diagnosis. However, this medical model approach is far more dominant in the group of students without SLD who, by majority, hold misconceptions on a definitional level. The academic staff group seems to be leaning towards a social approach concerning SLD. According to them, diagnoses may lead to social exclusion. The Pedagogical Department generally endorses the principles of inclusion and complies with the provision of oral exams for students with SLD. Nevertheless, in practice, there seems to be a lack of regular academic support for these students. When such support does exist, it is only through individual initiatives. With regards to their prospective profession, students with SLD can utilize their personal experience, as well as their empathy; these appear to be unique weapons in their hands –in comparison with other educators− when it comes to teaching students in the future. In the Department of Pedagogy, provision towards SLD results sporadic, however the vision of an inclusive department does exist. Based on their studies and their experience, pedagogy students with SLD claim that they have an experiential internalized advantage for their future career as educators.

Keywords: Specific learning disability, dyslexia, pedagogy department, inclusion, professional role of SLDed educators, higher education, university policy.

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Authors: Keivan Karimlou, Nemat Hassani, Abdollah Rashidi Mehrabadi

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Climate change, industrial bloom, population growth and mismanagement are the most important factors that lead to water shortages around the world. Water shortages often lead to forced immigration, war, and thirst and hunger, especially in developing countries. One of the simplest solutions to solve the water shortage issues around the world is transferring water from one watershed to another; however it may not be a suitable solution. Water managers around the world use supply and demand management methods to decrease the incidence of water shortage in a sustainable manner. But as a matter of economic constraints, they must define a method to select the best possible action to reduce and limit water shortages. The following paper recognizes different kinds of criteria to select the best possible policy for reducing water shortage in mega cities by examining a comprehensive literature review.

Keywords: Criteria, management, shortage, sustainable, water.

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Authors: Larry Powell, Seth Polsley, Drew Casey, Tracy Hammond

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Human activity recognition (HAR) systems have shown positive performance when recognizing repetitive activities like walking, running, and sleeping. Water-based activities are a reasonably new area for activity recognition. However, water-based activity recognition has largely focused on supporting the elite and competitive swimming population, which already has amazing coordination and proper form. Beginner swimmers are not perfect, and activity recognition needs to support the individual motions to help beginners. Activity recognition algorithms are traditionally built around short segments of timed sensor data. Using a time window input can cause performance issues in the machine learning model. The window’s size can be too small or large, requiring careful tuning and precise data segmentation. In this work, we present a method that uses a time window as the initial segmentation, then separates the data based on the change in the sensor value. Our system uses a multi-phase segmentation method that pulls all peaks and valleys for each axis of an accelerometer placed on the swimmer’s lower back. This results in high recognition performance using leave-one-subject-out validation on our study with 20 beginner swimmers, with our model optimized from our final dataset resulting in an F-Score of 0.95.

Keywords: Time window, peak/valley segmentation, feature extraction, beginner swimming, activity recognition.

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Authors: Abdul Halim Abdullah, Nur Liyana Zainal Abidin, Mahani Mokhtar

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Problem-solving is an activity which can encourage students to use Higher Order Thinking Skills (HOTS). Learning fractions can be challenging for students since empirical evidence shows that students experience difficulties in solving the fraction problems. However, visual methods can help students to overcome the difficulties since the methods help students to make meaningful visual representations and link abstract concepts in Mathematics. Therefore, the purpose of this study was to investigate whether there were any changes in students’ HOTS at the four highest levels when learning the fractions by using Thinking Blocks. 54 students participated in a quasi-experiment using pre-tests and post-tests. Students were divided into two groups. The experimental group (n=32) received a treatment to improve the students’ HOTS and the other group acted as the control group (n=22) which used a traditional method. Data were analysed by using Mann-Whitney test. The results indicated that during post-test, students who used Thinking Blocks showed significant improvement in their HOTS level (p=0.000). In addition, the results of post-test also showed that the students’ performance improved significantly at the four highest levels of HOTS; namely, application (p=0.001), analyse (p=0.000), evaluate (p=0.000), and create (p=0.000). Therefore, it can be concluded that Thinking Blocks can effectively encourage students to use the four highest levels of HOTS which consequently enable them to solve fractions problems successfully.

Keywords: Thinking blocks, higher order thinking skills, fractions, problem solving.

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Authors: Jack R. McKenzie, Peter A. Appleby, Thomas House, Neil Walton

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Cold-start is a notoriously difficult problem which can occur in recommendation systems, and arises when there is insufficient information to draw inferences for users or items. To address this challenge, a contextual bandit algorithm – the Fast Approximate Bayesian Contextual Cold Start Learning algorithm (FAB-COST) – is proposed, which is designed to provide improved accuracy compared to the traditionally used Laplace approximation in the logistic contextual bandit, while controlling both algorithmic complexity and computational cost. To this end, FAB-COST uses a combination of two moment projection variational methods: Expectation Propagation (EP), which performs well at the cold start, but becomes slow as the amount of data increases; and Assumed Density Filtering (ADF), which has slower growth of computational cost with data size but requires more data to obtain an acceptable level of accuracy. By switching from EP to ADF when the dataset becomes large, it is able to exploit their complementary strengths. The empirical justification for FAB-COST is presented, and systematically compared to other approaches on simulated data. In a benchmark against the Laplace approximation on real data consisting of over 670, 000 impressions from autotrader.co.uk, FAB-COST demonstrates at one point increase of over 16% in user clicks. On the basis of these results, it is argued that FAB-COST is likely to be an attractive approach to cold-start recommendation systems in a variety of contexts.

Keywords: Cold-start, expectation propagation, multi-armed bandits, Thompson sampling, variational inference.

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Authors: B. Dikici, I. Ozdemir, M. Topuz

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The corrosion behaviour of 316L stainless steel coatings obtained by cold spray method was investigated in this study. 316L powders were deposited onto Al5052 aluminum substrates. The coatings were produced using nitrogen (N₂) process gas. In order to further improve the corrosion and mechanical properties of the coatings, heat treatment was applied at 250 and 750 °C. The corrosion performances of the coatings were compared using the potentiodynamic scanning (PDS) technique under in-vitro conditions (in Ringer’s solution at 37 °C). In addition, the hardness and porosity tests were carried out on the coatings. Microstructural characterization of the coatings was carried out by using scanning electron microscopy attached with energy dispersive spectrometer (SEM-EDS) and X-ray diffraction (XRD) technique. It was found that clean surfaces and a good adhesion were achieved for particle/substrate bonding. The heat treatment process provided both elimination of the anisotropy in the coating and resulting in healing-up of the incomplete interfaces between the deposited particles. It was found that the corrosion potential of the annealed coatings at 750 °C was higher than that of commercially 316 L stainless steel. Moreover, the microstructural investigations after the corrosion tests revealed that corrosion preferentially starts at inter-splat boundaries.

Keywords: 316L, biomaterials, cold spray, heat treatment.

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Authors: Xiaoqing Wang, Junfeng Wang, Xiaolan Zhu

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Android operating system has been recognized by most application developers because of its good open-source and compatibility, which enriches the categories of applications greatly. However, it has become the target of malware attackers due to the lack of strict security supervision mechanisms, which leads to the rapid growth of malware, thus bringing serious safety hazards to users. Therefore, it is critical to detect Android malware effectively. Generally, the permissions declared in the AndroidManifest.xml can reflect the function and behavior of the application to a large extent. Since current Android system has not any restrictions to the number of permissions that an application can request, developers tend to apply more than actually needed permissions in order to ensure the successful running of the application, which results in the abuse of permissions. However, some traditional detection methods only consider the requested permissions and ignore whether it is actually used, which leads to incorrect identification of some malwares. Therefore, a machine learning detection method based on the actually used permissions combination and API calls was put forward in this paper. Meanwhile, several experiments are conducted to evaluate our methodology. The result shows that it can detect unknown malware effectively with higher true positive rate and accuracy while maintaining a low false positive rate. Consequently, the AdaboostM1 (J48) classification algorithm based on information gain feature selection algorithm has the best detection result, which can achieve an accuracy of 99.8%, a true positive rate of 99.6% and a lowest false positive rate of 0.

Keywords: Android, permissions combination, API calls, machine learning.

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Authors: S. Kulsri, M. Jaroensutasinee, K. Jaroensutasinee

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We developed a method based on quasi-molecular modelling to simulate the fall of water drops on horizontally smooth and rough surfaces. Each quasi-molecule was a group of particles that interacted in a fashion entirely analogous to classical Newtonian molecular interactions. When a falling water droplet was simulated at low impact velocity on both smooth and rough surfaces, the droplets moved periodically (i.e. the droplets moved up and down for a certain period, finally they stopped moving and reached a steady state), spreading and recoiling without splash or break-up. Spreading rates of falling water droplets increased rapidly as time increased until the spreading rate reached its steady state at time t ~ 0.25 s for rough surface and t ~ 0.40 s for smooth surface. The droplet height above both surfaces decreased as time increased, remained constant after the droplet diameter attained a maximum value and reached its steady state at time t ~ 0.4 s. However, rough surface had higher spreading rates of falling water droplets and lower height on the surface than smooth one.

Keywords: Quasi-molecular modelling, particle modelling, molecular aggregate approach.

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Authors: H. Abdizadeh, Y. Vahidshad

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The present paper discusses the selection of process parameters for obtaining optimal nanocrystallites size in the CuOZrO2 catalyst. There are some parameters changing the inorganic structure which have an influence on the role of hydrolysis and condensation reaction. A statistical design test method is implemented in order to optimize the experimental conditions of CuO-ZrO2 nanoparticles preparation. This method is applied for the experiments and L16 orthogonal array standard. The crystallites size is considered as an index. This index will be used for the analysis in the condition where the parameters vary. The effect of pH, H2O/ precursor molar ratio (R), time and temperature of calcination, chelating agent and alcohol volume are particularity investigated among all other parameters. In accordance with the results of Taguchi, it is found that temperature has the greatest impact on the particle size. The pH and H2O/ precursor molar ratio have low influences as compared with temperature. The alcohol volume as well as the time has almost no effect as compared with all other parameters. Temperature also has an influence on the morphology and amorphous structure of zirconia. The optimal conditions are determined by using Taguchi method. The nanocatalyst is studied by DTA-TG, XRD, EDS, SEM and TEM. The results of this research indicate that it is possible to vary the structure, morphology and properties of the sol-gel by controlling the above-mentioned parameters.

Keywords: CuO-ZrO2 Nanoparticles, Sol-gel, Taguchi method.

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Authors: Kooshina Koosha, Sima Habibi, Azam Talebian

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Electrospinning is a simple, versatile and widely accepted technique to produce ultra-fine fibers ranging from nanometer to micron. Recently there has been great interest in developing this technique to produce nanofibers with novel properties and functionalities. The electrospinning field is extremely broad, and consequently there have been many useful reviews discussing various aspects from detailed fiber formation mechanism to the formation of nanofibers and to discussion on a wide range of applications. On the other hand, the focus of this study is quite narrow, highlighting electrospinning parameters. This work will briefly cover the solution and processing parameters (for instance; concentration, solvent type, voltage, flow rate, distance between the collector and the tip of the needle) impacting the morphological characteristics of nanofibers, such as diameter. In this paper, a comprehensive work would be presented on the research of producing nanofibers from natural polymer entitled Gelatin.

Keywords: Electro spinning, solution parameters, process parameters, natural fiber.

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Authors: M. M. Shabani, O. J. Nydal, R. Larsen

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Gas hydrates can agglomerate and block multiphase oil and gas pipelines when water is present at hydrate forming conditions. Using "Cold Flow Technology", the aim is to condition gas hydrates so that they can be transported as a slurry mixture without a risk of agglomeration. During the pipeline shut down however, hydrate particles may settle in bends and build hydrate plugs. An experimental setup has been designed and constructed to study the flow of such plugs at start up operations. Experiments have been performed using model fluid and model hydrate particles. The propagations of initial plugs in a bend were recorded with impedance probes along the pipe. The experimental results show a dispersion of the plug front. A peak in pressure drop was also recorded when the plugs were passing the bend. The evolutions of the plugs have been simulated by numerical integration of the incompressible mass balance equations, with an imposed mixture velocity. The slip between particles and carrier fluid has been calculated using a drag relation together with a particle-fluid force balance.

Keywords: Cold Flow Technology, Gas Hydrate Plug Flow Experiments, One Dimensional Incompressible Two Fluid Model, Slurry Flow in Inclined Pipes and Bends, Transient Slurry Flow.

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Authors: Ali Mohaghar, Iman Ghasemian Sahebi, Alireza Arab

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In the last decades, increasing in human and natural disaster occurrence had very irreparable effects on human life. Hence, one of the important issues in humanitarian supply chain management is identifying and prioritizing the different risks and finding suitable solutions for encountering them at the time of disaster occurrence. This study is an attempt to provide a comprehensive review of humanitarian supply chain risks in a case study of Tehran Red Crescent Societies. For this purpose, Best-Worst method (BWM) has been used for analyzing the risks of the humanitarian supply chain. 22 risks of the humanitarian supply chain were identified based on the literature and interviews with four experts. According to BWM method, the importance of each risk was calculated. The findings showed that culture contexts, little awareness of people, and poor education system are the most important humanitarian supply chain risks. This research provides a useful guideline for managers so that they can benefit from the results to prioritize their solutions.

Keywords: Best worst method, humanitarian logistics, humanitarian supply chain, risk management.

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Authors: Erik Delarue, David Bekaert, Ronnie Belmans, William D'haeseleer

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This paper presents the development of an electricity simulation model taking into account electrical network constraints, applied on the Belgian power system. The base of the model is optimizing an extensive Unit Commitment (UC) problem through the use of Mixed Integer Linear Programming (MILP). Electrical constraints are incorporated through the implementation of a DC load flow. The model encloses the Belgian power system in a 220 – 380 kV high voltage network (i.e., 93 power plants and 106 nodes). The model features the use of pumping storage facilities as well as the inclusion of spinning reserves in a single optimization process. Solution times of the model stay below reasonable values.

Keywords: Electricity generation modeling, Unit Commitment(UC), Mixed Integer Linear Programming (MILP), DC load flow.

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Authors: M. Al-Saedi, A. Chegenizadeh, H. Nikraz

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Experimental investigations are conducted to assess a layered structure of glass (G) - rock (R) blends under the impact of repeated loading. Laboratory tests included sieve analyses, modified compaction test and repeated load triaxial test (RLTT) is conducted on different structures of stratified GR samples to reach the objectives of this study. Waste materials are such essential components in the climate system, and also commonly used in minimising the need for natural materials in many countries. Glass is one of the most widely used groups of waste materials which have been extensively using in road applications. Full range particle size and colours of glass are collected and mixed at different ratios with natural rock material trying to use the blends in pavement layers. Whole subsurface specimen sequentially consists of a single layer of R and a layer of G-R blend. 12G/88R and 45G/55R mix ratios are employed in this research, the thickness of G-R layer was changed, and the results were compared between the pure rock and the layered specimens. The relations between resilient module (Mr) and permanent deformation with sequence number are presented. During the earlier stages of RLTT, the results indicated that the 45G/55R specimen shows higher moduli than R specimen.

Keywords: Rock base course, layered structure, glass, resilient modulus.

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Authors: Amir Amiri, Naghmeh Morakabati

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During the recent years the six-fold growth of cancer in Iran has led the production of healthy products to become a challenge in the food industry. Due to the young population in the country, the consumption of fast foods is growing. The chemical cancer-causing preservatives are used to produce these products more than the standard; so using an appropriate alternative seems to be important. On the one hand, the plant essential oils show the high antimicrobial potential against pathogenic and spoilage microorganisms and on the other hand they are highly volatile and decomposed under the processing conditions. The study aims to produce the loaded chitosan nanoparticles with different concentrations of savory essential oil to improve the anti-microbial property and increase the resistance of essential oil to oxygen and heat. The encapsulation efficiency was obtained in the range of 32.07% to 39.93% and the particle size distribution of the samples was observed in the range of 159 to 210 nm. The range of Zeta potential was obtained between -11.9 to -23.1 mV. The essential oil loaded in chitosan showed stronger antifungal activity against Rhizopus stolonifer. The results showed that the antioxidant property is directly related to the concentration of loaded essential oil so that the antioxidant property increases by increasing the concentration of essential oil. In general, it seems that the savory essential oil loaded in chitosan particles can be used as a food processor.

Keywords: Chitosan, encapsulation, essential oil, nanogel.

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Authors: Mingyu Xie, Mietek Brdys

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The paper develops a Non-Linear Model Predictive Control (NMPC) of water quality in Drinking Water Distribution Systems (DWDS) based on the advanced non-linear quality dynamics model including disinfections by-products (DBPs). A special attention is paid to the analysis of an impact of the flow trajectories prescribed by an upper control level of the recently developed two-time scale architecture of an integrated quality and quantity control in DWDS. The new quality controller is to operate within this architecture in the fast time scale as the lower level quality controller. The controller performance is validated by a comprehensive simulation study based on an example case study DWDS.

Keywords: Model predictive control, hierarchical control structure, genetic algorithm, water quality with DBPs objectives.

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Authors: Eduardo N. Velloso, Fernando M. N. Dantas, Luciano S. Barros

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A common complaint from power system analysis students lies in the overly complex tools they need to learn and use just to simulate very basic systems or just to check the answers to power system calculations. The most basic power system studies are power-flow solutions and short-circuit calculations. This paper presents a simple tool with an intuitive interface to perform both these studies and assess its performance in comparison with existent commercial solutions. With this in mind, Elegant is a pure Python software tool for learning power system analysis developed for undergraduate and graduate students. It solves the power-flow problem by iterative numerical methods and calculates bolted short-circuit fault currents by modeling the network in the domain of symmetrical components. Elegant can be used with a user-friendly Graphical User Interface (GUI) and automatically generates human-readable reports of the simulation results. The tool is exemplified using a typical Brazilian regional system with 18 buses. This study performs a comparative experiment with 1 undergraduate and 4 graduate students who attempted the same problem using both Elegant and a commercial tool. It was found that Elegant significantly reduces the time and labor involved in basic power system simulations while still providing some insights into real power system designs.

Keywords: Free- and open-source software, power-flow, power system analysis, Python, short-circuit.

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Authors: R. Nayak, T. Panwar, R. Padhye

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Protective textiles get soiled, stained and even worn during their use, which may not be usable after a certain period due to the loss of protective performance. They need regular cleaning and maintenance, which helps to extend the durability of the clothing, retains their useful properties and ensures that fresh clothing is ready to wear when needed. Generally, the cleaning processes used for various protective clothing include dry-cleaning (using solvents) or wet cleaning (using water). These cleaning processes can alter the fabric surface properties, dimensions, and physical, mechanical and performance properties. The technology of laundering and dry-cleaning has undergone several changes. Sustainable methods and products are available for faster, safer and improved cleaning of protective textiles. We performed a comprehensive and systematic review of green technologies and eco-friendly products for sustainable cleaning of protective textiles. Special emphasis is given on the care and maintenance procedures of protective textiles for protection from fire, bullets, chemical and other types of protective clothing.

Keywords: Sustainable cleaning, protective textiles, eco-friendly cleaning, ozone laundering, ultrasonic cleaning.

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Authors: Odenigbo Veronica Ngozi, Lorreta Chika Ukwuaba

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This study focuses on how the strengthening adult literacy programs can help accelerate transformative strategies to end Female Genital Mutilation (FGM) in Nigeria, specifically in Nsukka Local Government Area of Enugu State. The research delved into the definition of FGM, adult literacy programs, and how to achieve ending FGM in order to attain Sustainable Development Goals (SDGs) in 2030. It further discussed the practice of FGM in Nigeria and emphasized the statement of the problem. Main purpose of the study was to investigate how strengthening adult literacy programs can help accelerate transformative strategies to end FGM in Nigeria and achieve SDGs in 2030. A survey research design was used to conduct the study in Nsukka L.G.A. The population was composed of 26 facilitators and adult learners in five adult learning centres in the area. The entire population was used as a sample. Structured questionnaires were employed to elicit information from the respondents. The items on the questionnaire were face-validated by three experts while the reliability of the instrument was verified using Cronbach Alpha Reliability Technique. The research questions were analysed using means and standard deviation while the hypothesis was tested at 0.05 level of degree of significance using a t-test statistics. The result of the findings shows that the practices of FGM can end through strengthening adult literacy programs. Strengthening adult literacy programs is a good channel to end or stop FGM through the knowledge and skill acquired from the learning centres. The theoretical importance of the study lies in the fact that it highlights the role of adult literacy programs in accelerating transformative strategies to combat harmful cultural practices such as FGM. It further supports the importance of education and knowledge in achieving SDGs by 2030. The study addressed the question of how strengthening adult literacy programs can help accelerate transformative strategies which can end FGM in Nigeria and achieve SDGs by 2030. In conclusion, the study revealed that adult literacy is a good tool to end FGM in Nigeria. The recommendation was that (NGOs), community-based organizations (CBOs), and individuals should support the funding and establishment of adult literacy centres in communities so as to reach all illiterate parents or individuals so that they can acquire the knowledge and skill needed to understand the negative effect of FGM in the life of a girl child.

Keywords: Adult literacy, female genital mutilation, learning centres, Sustainable Development Goals.

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Authors: Zhijun Ren, Zhang Lin, Zhao Ye, Zuo Xiangyu, Mei Dongxing

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As a pretreatment process of ballast water treatment, the performance of high gradient magnetic separation (HGMS) technology for the removal of particulates and microorganisms was studied. The results showed that HGMS process could effectively remove suspended particles larger than 5 µm and had ability to resist impact load. Microorganism could also be effectively removed by HGMS process, and the removal effect increased with increasing magnetic field strength. The maximum removal rates for Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) were 4016.1% and 9675.3% higher, respectively, than without the magnetic field. In addition, the superoxide dismutase (SOD) activity of the microbes decreased by 32.2% when the magnetic field strength was 15.4 mT for 72 min. The microstructure of the stainless steel wool was investigated, and the results showed that particle removal by HGMS has common function by the magnetic force of the high-strength, high-gradient magnetic field on weakly magnetic particles in the water, and on the stainless steel wool.

Keywords: HGMS, particulates, superoxide dismutase activity, steel wool magnetic medium.

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Authors: Zdenek Krnoul

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This article investigates a contribution of synthesized visual speech. Synthesis of visual speech expressed by a computer consists in an animation in particular movements of lips. Visual speech is also necessary part of the non-manual component of a sign language. Appropriate methodology is proposed to determine the quality and the accuracy of synthesized visual speech. Proposed methodology is inspected on Czech speech. Hence, this article presents a procedure of recording of speech data in order to set a synthesis system as well as to evaluate synthesized speech. Furthermore, one option of the evaluation process is elaborated in the form of a perceptual test. This test procedure is verified on the measured data with two settings of the synthesis system. The results of the perceptual test are presented as a statistically significant increase of intelligibility evoked by real and synthesized visual speech. Now, the aim is to show one part of evaluation process which leads to more comprehensive evaluation of the sign speech synthesis system.

Keywords: Perception test, Sign speech synthesis, Talking head, Visual speech.

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Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

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The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: Data management, digitization, Industry 4.0, knowledge engineering, metamodel.

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Authors: Michael W. Markowitz

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A central element of higher education today is the “core” or “general education” curriculum: that configuration of courses that often encompasses the essence of liberal arts education. Ensuring that such offerings reflect the mission and values of the institution is a challenge faced by most college and universities, often more than once. This paper presents an action model of program planning designed to structure the processes of developing, implementing and revising core curricula in a manner consistent with key institutional goals and objectives. Through presentation of a case study from a university in the United States, the elements of needs assessment, stakeholder investment and collaborative compromise are shown as key components of a planning strategy that can produce a general education program that is comprehensive, academically rigorous, assessable, and mission consistent. The paper concludes with recommendations for both the implementation and evaluation of such programs in practice.

Keywords: Academic assessment, academic program planning, curriculum development, general education reform.

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Authors: Peter Ndichu Muriuki

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The 9/11 suicide attacks in New York, Washington, D.C., and Pennsylvania, triggered a number of security responses both in the United States of America and other Countries in the World. Kenya, which is an ally and a close partner to North America and Europe, was not left behind. While many states had been parties to numerous terrorism conventions, their response in implementing them had been slow and needed this catalyst. This special case offered a window of opportunity for many “security conscious" regimes in cementing their legal-criminological and political security apparatus. At the international level, the 9/11 case led to the hasty adoption of Security Council resolution 1373 in 2001, which called upon states to adopt wide-ranging and comprehensive steps and strategies to combat international terrorism and to become parties to the relevant international conventions and protocols relating to terrorism. Since then, Kenya has responded with speed in devising social-legal-criminological-political actions.

Keywords: Justice, Policing, Security, Terrorism

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Authors: Li Jie, Zhang Wei

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In this paper, the problem of posture stabilization for a kinematic model of differential drive robots is studied. A more complex model of the kinematics of differential drive robots is used for the design of stabilizing control. This model is formulated in terms of the physical parameters of the system such as the radius of the wheels, and velocity of the wheels are the control inputs of it. In this paper, the framework of Lyapunov-based control design has been used to solve posture stabilization problem for the comprehensive model of differential drive robots. The results of the simulations show that the devised controller successfully solves the posture regulation problem. Finally, robustness and performance of the controller have been studied under system parameter uncertainty.

Keywords: Differential drive robots, nonlinear control, Lyapunov-based control design, posture regulation.

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Authors: Efat Lali Dastjerdi, Hassan Sadeghi Naeini, Hadi Sanjari

Abstract:

One of the important steps in a safety and risk management system is the economical evaluation of occupational accident and diseases costs in order to decrease accidents from reoccurring in the workplace. This study proposed a plausible method for calculating occupational accident costs and illnesses in work place. This method design for cost estimation takes into account both the personnel, organizational level as well as the community level especially intended for an Iranian work place. The research indicates that a using systematic method for calculating costs which also provides risk evaluation can help managers to plan correctly the investment in health and safety measures. Using this method is that not only is it comprehensive, easy and practical and could be applied in practice by a manager within a short period of time but it also shows the importance of accident costs as well as calculates the real cost of an accident and illnesses.

Keywords: ost calculating model, Economics of health and Safety.

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Authors: Norazah Mohd Suki, T Ramayah

Abstract:

e-Government structures permits the government to operate in a more transparent and accountable manner of which it increases the power of the individual in relation to that of the government. This paper identifies the factors that determine customer-s attitude towards e-Government services using a theoretical model based on the Technology Acceptance Model. Data relating to the constructs were collected from 200 respondents. The research model was tested using Structural Equation Modeling (SEM) techniques via the Analysis of Moment Structure (AMOS 16) computer software. SEM is a comprehensive approach to testing hypotheses about relations among observed and latent variables. The proposed model fits the data well. The results demonstrated that e- Government services acceptance can be explained in terms of compatibility and attitude towards e-Government services. The setup of the e-Government services will be compatible with the way users work and are more likely to adopt e-Government services owing to their familiarity with the Internet for various official, personal, and recreational uses. In addition, managerial implications for government policy makers, government agencies, and system developers are also discussed.

Keywords: E-government, structural equation modelling, attitude, service.

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Authors: S. A. Nta, M. J. Ayotamuno, I. J. Udom

Abstract:

The work presents result of laboratory analysis of the effects of landfill leachate on engineering properties of test soil. The soil used for the present study was a sandy loam soil and acidic in nature. It was collected at a depth of 0.9 m. The landfill leachate used was collected from a hole dug some meters away from dumped solid waste and analyzed to identify the pollutants and its effect on engineering properties of the test soil. The test soil applied with landfill leachate was collected at 0.25 and 0.50 m radial distances at a depth of 0.15, 0.30, 0.45 and 0.60 m from the point of application of leachate after 50 days were the application of the leachate end and 80 days from the start of the experiment for laboratory analysis. Engineering properties such as particle size distribution, specific gravity, optimum moisture content, maximum dry density, unconfined compressive strength, liquid limit, plastic limit and shrinkage limit were considered. The concentration of various chemicals at 0.25 and 0.50 radial distances and 0.15, 0.30, 0.45 and 0.6 m depth from the point of application of leachate were different. This study founds the effect of landfill leachate on the engineering properties of soil. It can be concluded that, the type of soil, chemical composition of the leachate, infiltration rate, aquifers, ground water table etc., will have a major role on the area of influence zone of the pollutants in a landfill.

Keywords: Engineering properties of test soil, landfill leachate, Municipal solid waste.

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Authors: H. Almohammadi, Sh. Nasiri Vatan, E. Esmaeilzadeh, A. Motezaker, A. Nokhosteen

Abstract:

In the present study, Convective heat transfer coefficient and pressure drop of Al2O3/water nanofluid in laminar flow regime under constant heat flux conditions inside a circular tube were experimentally investigated. Al2O3/water nanofluid with 0.5% and 1% volume concentrations with 15 nm diameter nanoparticles were used as working fluid. The effect of different volume concentrations on convective heat transfer coefficient and friction factor was studied. The results emphasize that increasing of particle volume concentration leads to enhance convective heat transfer coefficient. Measurements show the average heat transfer coefficient enhanced about 11-20% with 0.5% volume concentration and increased about 16-27% with 1% volume concentration compared to distilled water. In addition, the convective heat transfer coefficient of nanofluid enhances with increase in heat flux. From the results, the average ratio of (fnf/fbf) was about 1.10 for 0.5% volume concentration. Therefore, there is no significant increase in friction factor for nanofluids.

Keywords: Convective heat transfer, Laminar flow regime, Nanofluids, Pressure drop

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