Search results for: urban growth model

Authors: Kika Ioannou Kazamia

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This paper examines the action research cycle of the second phase of longitudinal research on sustainable interior design practices, between two groups of stakeholders, designers and clients. During this phase of the action research, the second step - the change stage - of Lewin’s change management model has been utilized to change values, approaches, and attitudes toward sustainable design practices among the participants. Affective domain learning theory is utilized to attach new values. Learning with the use of information technology, collaborative learning, and problem-based learning are the learning methods implemented toward the acquisition of the objectives. Learning methods, and aims, require the design of interventions with participants' involvement in activities that would lead to the acknowledgment of the benefits of sustainable practices. Interventions are steered to measure participants’ decisions for the worth and relevance of ideas, and experiences; accept or commit to a particular stance or action. The data collection methods used in this action research are observers’ reports, participants' questionnaires, and interviews. The data analyses use both quantitative and qualitative methods. The main beneficial aspect of the quantitative method was to provide the means to separate many factors that obscured the main qualitative findings. The qualitative method allowed data to be categorized, to adapt the deductive approach, and then examine for commonalities that could reflect relevant categories or themes. The results from the data indicate that during the second phase, designers and clients' participants altered their behaviours.

Keywords: design, change, sustainability, learning, practices

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Authors: Walter W. Loo

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China declared the “zero discharge rules which leave no toxics into our living environment and deliver blue sky, green land and clean water to many generations to come”. The achievement of ZWD will provide conservation of water, soil and energy and provide drastic increase in Gross Domestic Products (GDP). Our society’s engine needs a major tune up; it is sputtering. ZWD is achieved in world’s space stations – no toxic air emission and the water is totally recycled and solid wastes all come back to earth. This is all done with solar power. These are all achieved under extreme temperature, pressure and zero gravity in space. ZWD can be achieved on earth under much less fluctuations in temperature, pressure and normal gravity environment. ZWD systems are not expensive and will have multiple beneficial returns on investment which are both financially and environmentally acceptable. The paper will include successful case histories since the mid-1970s. ZWD discharge can be applied to the following types of projects: nuclear and coal fire power plants with a closed loop system that will eliminate thermal water discharge; residential communities with wastewater treatment sump and recycle the water use as a secondary water supply; waste water treatment Plants with complete water recycling including water distillation to produce distilled water by very economical 24-hours solar power plant. Landfill remediation is based on neutralization of landfilled gas odor and preventing anaerobic leachate formation. It is an aerobic condition which will render landfill gas emission explosion proof. Desert development is the development of recovering soil moisture from soil and completing a closed loop water cycle by solar energy within and underneath an enclosed greenhouse. Salt-alkali land development can be achieved by solar distillation of salty shallow water into distilled water. The distilled water can be used for soil washing and irrigation and complete a closed loop water cycle with energy and water conservation. Heavy metals remediation can be achieved by precipitation of dissolved toxic metals below the plant or vegetation root zone by solar electricity without pumping and treating. Soil and groundwater remediation - abandoned refineries, chemical and pesticide factories can be remediated by in-situ electrobiochemical and bioventing treatment method without pumping or excavation. Toxic organic chemicals are oxidized into carbon dioxide and heavy metals precipitated below plant and vegetation root zone. New water sources: low temperature distilled water can be recycled for repeated use within a greenhouse environment by solar distillation; nano bubble water can be made from the distilled water with nano bubbles of oxygen, nitrogen and carbon dioxide from air (fertilizer water) and also eliminate the use of pesticides because the nano oxygen will break the insect growth chain in the larvae state. Three dimensional high yield greenhouses can be constructed by complete water recycling using the vadose zone soil as a filter with no farming wastewater discharge.

Keywords: greenhouses, no discharge, remediation of soil and water, wastewater

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Authors: Isheanesu Hungwe, Munyaradzi Shumba, Tichaona Nharingo

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High levels of nitrates in drinking water present a potential risk to human health for it is responsible for methemoglobinemia in infants. It also gives rise to eutrophication of dams and rivers. It is, therefore, important to find ways of compating the increasing amount of nitrates in the environment. This study explored the bioremediation of nitrates from aqueous solution using Brachystegia spiciformis leaf powder (BSLP). The acid treated leaf powder was characterized using FTIR and SEM before and after nitrate biosorption and desorption experiments. Critical biosorption factors, pH, contact time and biomass dosage were optimized as 4, 30 minutes and 10 g/L respectively. The equilibrium data generated from the investigation of the effect of initial nitrate ion concentration fitted the isotherm models in the order Dudinin-Radushkevich < Halsey=Freundlich < Langmuir < Temkin model based on the correlation of determination (R2). The Freundlich’s adsorption intensity and Langmuir’s separation factors revealed the favorability of nitrate ion sorption onto BSLP biomass with maximum sorption capacity of 87.297 mg/g. About 95% of the adsorbed nitrate was removed from the biomass under alkaline conditions (pH 11) proving that the regeration of the biomass, critical in sorption-desorption cycles, was possible. It was concluded that the BSLP was a multifunctional group material characterised by both micropores and macropores that could be effectively utilised in nitrate ion removal from aqueous solutions.

Keywords: adsorption, brachystegia spiciformis, methemoglobinemia, nitrates

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Authors: Atefeh Heydari, Mohammadali Tavakoli, Naomie Salim

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In recent years, we have witnessed that online reviews are the most important source of customers’ opinion. They are progressively more used by individuals and organisations to make purchase and business decisions. Unfortunately, for the reason of profit or fame, frauds produce deceptive reviews to hoodwink potential customers. Their activities mislead not only potential customers to make appropriate purchasing decisions and organisations to reshape their business, but also opinion mining techniques by preventing them from reaching accurate results. Spam reviews could be divided into two main groups, i.e. multiple and singleton spam reviews. Detecting a singleton spam review that is the only review written by a user ID is extremely challenging due to lack of clue for detection purposes. Singleton spam reviews are very harmful and various features and proofs used in multiple spam reviews detection are not applicable in this case. Current research aims to propose a novel supervised technique to detect singleton spam reviews. To achieve this, various features are proposed in this study and are to be combined with the most appropriate features extracted from literature and employed in a classifier. In order to compare the performance of different classifiers, SVM and naive Bayes classification algorithms were used for model building. The results revealed that SVM was more accurate than naive Bayes and our proposed technique is capable to detect singleton spam reviews effectively.

Keywords: classification algorithms, Naïve Bayes, opinion review spam detection, singleton review spam detection, support vector machine

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Authors: Sarwat Jahan, Asker Rajin Rahman

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Management of offtake of any fluvial river is very sensitive in terms of long-term sustainability where the variation of water flow and sediment transport range are wide enough throughout a hydrological year. The Gorai River is a major distributary of the Ganges River in Bangladesh and is termed as a primary source of fresh water for the South-West part of the country. Every year, significant siltation of the Gorai offtake disconnects it from the Ganges during the dry season. As a result, the socio-economic and environmental condition of the downstream areas has been deteriorating for a few decades. To improve the overall situation of the Gorai offtake and its dependent areas, a study has been conducted by the Institute of Water Modelling, Bangladesh, in 2022. Using the mathematical morphological modeling tool MIKE 21C of DHI Water & Environment, Denmark, simulated results revealed the need for dredging/river training structures for offtake management at the Gorai offtake to ensure significant dry season flow towards the downstream. The dry season flow is found to increase significantly with the proposed river interventions, which also improves the environmental conditions in terms of salinity of the South-West zone of the country. This paper summarizes the primary findings of the analyzed results of the developed mathematical model for improving the existing condition of the Gorai River.

Keywords: Gorai river, mathematical modelling, offtake, siltation, salinity

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Authors: John M. Frimpong, Matilda K. Owusu-Bio, Caleb Annan

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Business today is highly competitive, and the automobile industry is no exception. Therefore, it is necessary to determine the customer value and service quality measures that lead to customer satisfaction which in turn lead to customer loyalty. However, in the automobile industry, the role of logistics service support in these relationships cannot be undermined. It could be inferred that logistics service supports and its management has a direct correlation with customer service and or service quality. But this is not always the same for all industries. Therefore, this study was to investigate how automobile companies implement the concept of customer service through logistics service supports. In order to ascertain this, two automobile companies in Ghana were selected, and these are Toyota Ghana Limited and Mechanical Lloyd Company Ltd. The study developed a conceptual model to depict the study’s objectives from which questionnaires were developed from for data collection. Respondents were made up of customers and staff of the two companies. The findings of the study revealed that the automobile industry partly attributes their customer satisfaction to the customer value, service quality or customer value. It shows a positive relationship between logistics service supports and service quality and customer value. However, the results indicate that customer satisfaction is not predicted by logistics services. This implies that in the automobile industry, it is not always the case that when customer service is implemented through logistics service supports, it leads to customer satisfaction. Therefore, there is the need for all players and stakeholders in the automobile industry investigate other factors which help to increase customer satisfaction in addition to logistics service supports. It is recommended that logistics service supports should be geared towards meeting customer expectations and not just based on the organization’s standards and procedures. It is necessary to listen to the voice of the customer to tailor the service package to suit the needs and expectations of the customer.

Keywords: customer loyalty, customer satisfaction, customer service, customer value, logistics service supports

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Authors: Mariel L. Alonzo, Patricia Mae T. Chi, Juliana Patrice P. Mayormita, Sanjana A. Sorio

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Compassion fade proposes an inverse relationship between the magnitude of stimuli to elicited compassion. This phenomenon is viewed within a framework that integrates a 3-Act Compassion structure with Latané and Darley’s Unresponsive Bystander Model and Prospect Theory of Decision-making under risk. Students (N=211) from Ateneo de Davao were sampled to examine the effects of mass perception (increasing number of needy persons) and intertemporal choice (soon versus later) on volunteering behavior. Collegiate classes in their natural setting were randomly assigned to five different treatment groups and were presented with audiovisual presentations featuring an increasing number of needy persons. The students were deceived to believe that two hypothetical feeding programs for Marawi refugees, taking place in 1 month and 6 months, were in need of volunteers for its preparatory phase. Results show a statistically significant (p=0.000; p=0.013) non-linear trend consistently for both feeding programs. There was a decrease in volunteered time means as identifiable victims increased from 0-47 and an increase as it progressed towards 267 non-identifiable victims. Highest interest was expressed for the 0 needy people shown and least for 47. The 0 hours volunteered was consistently the mode and median in all treatments. There was no statistically significant temporal discounting effect.

Keywords: compassion, group perception, identifiable victim, intertemporal choice, prosocial behavior, unresponsive bystander

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Authors: Viacheslav Shkuratskyy, Aminu Bello Usman, Michael O’Dea, 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 affect earthquakes of lower magnitude and shallow depth than earthquakes of magnitude 5.5 or larger with intermediate depth and deep depth.

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: Seyed Abdolreza Mosavi, Alireza Babakhan, Elham Sadat Hoseinifard

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Knowledge-based firms need to design mechanisms for continuous absorptive and creation of knowledge in order to ensure their survival in the competitive arena and to follow the path of development. Considering the project-oriented nature of product development activities in knowledge-based firms on the one hand and the importance of analyzing the factors affecting knowledge absorptive capacity in these firms on the other, the purpose of this study is to identify and classify the factors affecting project management practices on absorptive knowledge capacity. For this purpose, we have studied and reviewed the theoretical literature in the field of project management and absorptive knowledge capacity so as to clarify its dimensions and indexes. Then, using the ISM method, the relationship between them has been studied. To collect data, 21 questionnaires were distributed in project-oriented knowledge-based companies. The results of the ISM method analysis provide a model for the relationship between project management activities and knowledge absorptive capacity, which includes knowledge acquisition capacity, scope management, time management, cost management, quality management, human resource management, communications management, procurement management, risk management, stakeholders management and integration management. Having conducted the MICMAC analysis, we divided the variables into three groups of independent, relational and dependent variables and came up with no variables to be included in the group of autonomous variables.

Keywords: knowledge absorptive capacity, project management practices, knowledge-based firms, interpretive structural modeling

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Authors: C. A. Roberts, S. L. Mascaro, J. R. Gerrish, J. L. Horner

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Management-intensive Grazing (MiG) is a practice that rotates livestock through paddocks in a way that best matches the nutrient requirements of the animal to the yield and quality of the pasture. In the USA, MiG has been taught to livestock producers throughout the state of Missouri in 2- and 3-day workshops called “Missouri Grazing Schools.” The economic impact of these schools was quantified using IMPLAN software. The model included hectares of adoption, animal performance, carrying capacity, and input costs. To date, MiG, as taught in the Missouri Grazing Schools, has been implemented on more than 70,000 hectares in Missouri. The economic impact of these schools is presently $125 million USD per year added to the state economy. This magnitude of impact is the result not only of widespread adoption but also because of increased livestock carrying capacity; in Missouri, a capacity increase of 25 to 30% has been well documented. Additional impacts have been MiG improving forage quality and reducing the cost of feed and fertilizer. The environmental impact of MiG in the state of Missouri is currently being estimated. Environmental impact takes into account the reduction in the application of commercial fertilizers; in MiG systems, nitrogen is supplied by N fixation from legumes, and much of the P and K is recycled naturally by well-distributed manure. The environmental impact also estimates carbon sequestration and methane production; MiG can increase carbon sequestration and reduce methane production in comparison to default grazing practices and feedlot operations in the USA.

Keywords: agricultural education, forage quality, management-intensive grazing, nutrient cycling, stock density, sustainable agriculture

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Authors: Firas Mohamad Al-Sabek

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The Purpose of the paper is to examine the most critical and important factor which will affect the implementation of Total Quality Management (TQM) in the construction industry in the United Arab Emirates. It also examines the most effected Project outcome from implementing TQM. A framework was also proposed depending on the literature studies. The method used in this paper is a quantitative study. A survey with a sample of 60 respondents was created and distributed in a construction company in Abu Dhabi, which includes 15 questions to examine the most critical factor that will affect the implementation of TQM in addition to the most effected project outcome from implementing TQM. The survey showed that management commitment is the most important factor in implementing TQM in a construction company. Also it showed that Project cost is most effected outcome from the implementation of TQM. Management commitment is very important for implementing TQM in any company. If the management loose interest in quality then everyone in the organization will do so. The success of TQM will depend mostly on the top of the pyramid. Also cost is reduced and money is saved when the project team implement TQM. While if no quality measures are present within the team, the project will suffer a commercial failure. Based on literature, more factors can be examined and added to the model. In addition, more construction companies could be surveyed in order to obtain more accurate results. Also this study could be conducted outside the United Arab Emirates for further enchantment.

Keywords: construction project, total quality management, management commitment, cost, theoretical framework

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Authors: Babak Mirbaha, Mahmoud Saffarzadeh, Fatemeh Mohajeri

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Road traffic accidents lead to a higher rate of death and injury, especially in vulnerable road users such as pedestrians. Improving the safety of facilities for pedestrians is a major concern for policymakers because of the high number of pedestrian fatalities and direct and indirect costs which are imposed to the society. This study focuses on the idea of determining the willingness to pay of pedestrians for increasing their safety while crossing the street. In this study, three different scenarios including crossing the street with zebra crossing facilities, crossing the street with zebra crossing facilities and installing a pedestrian traffic light and constructing a pedestrian bridge with escalator are presented. The research was conducted based on stated preferences method. The required data were collected from a questionnaire that consisted of three parts: pedestrian’s demographic characteristics, travel characteristics and scenarios. Four different payment amounts are presented for each scenario and a logit model has been built for each proposed payment. The results show that sex, age, education, average household income and individual salary have significant effect on choosing a scenario. Among the policies that have been mentioned through the questionnaire scenarios, the scenario of crossing the street with zebra crossing facilities and installing a traffic lights is the most frequent, with willingness to pay 10,000 Rials and the scenario of crossing the street with a zebra crossing with a willingness to pay 100,000 Rials having the least frequency. For all scenarios, as the payment is increasing, the willingness to pay decreases.

Keywords: pedestrians, willingness to pay, safety, immunization

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Authors: Aniket S. Joshi, Aditya R. Mane, Arjun Tukaram

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In the 21st century, in the era of e-world, people are continuously getting updated by daily information such as weather conditions, news, stock exchange market updates, new projects, cricket updates, sports and other such applications. In the busy situation, they want this information on the little use of keyboard, time. Today in order to get such information user have to repeat same mouse and keyboard actions which includes time and inconvenience. In India due to rural background many people are not much familiar about the use of computer and internet also. Also in small clinics, small offices, and hotels and in the airport there should be a system which retrieves daily information with the minimum use of keyboard and mouse actions. We plan to design application based project that can easily retrieve information with minimum use of keyboard and mouse actions and make our task more convenient and easier. This can be possible with an image processing application which takes real time hand gestures which will get matched by system and retrieve information. Once selected the functions with hand gestures, the system will report action information to user. In this project we use real time hand gesture movements to select required option which is stored on the screen in the form of RSS Feeds. Gesture will select the required option and the information will be popped and we got the information. A real time hand gesture makes the application handier and easier to use.

Keywords: hand detection, hand tracking, hand gesture recognition, HSV color model, Blob detection

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Authors: Ali Shirazi, Robert A. Taylor, Stephen D. White, Graham L. Morrison

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In this paper, a detailed simulation model of a solar-powered triple-effect LiBr–H₂O absorption chiller is developed to supply both cooling and heating demand of a large-scale building, aiming to reduce the fossil fuel consumption and greenhouse gas emissions in building sector. TRNSYS 17 is used to simulate the performance of the system over a typical year. A combined energetic-economic-environmental analysis is conducted to determine the system annual primary energy consumption and the total cost, which are considered as two conflicting objectives. A multi-objective optimization of the system is performed using a genetic algorithm to minimize these objectives simultaneously. The optimization results show that the final optimal design of the proposed plant has a solar fraction of 72% and leads to an annual primary energy saving of 0.69 GWh and annual CO₂ emissions reduction of ~166 tonnes, as compared to a conventional HVAC system. The economics of this design, however, is not appealing without public funding, which is often the case for many renewable energy systems. The results show that a good funding policy is required in order for these technologies to achieve satisfactory payback periods within the lifetime of the plant.

Keywords: economic, environmental, multi-objective optimization, solar air-conditioning, triple-effect absorption chiller

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Authors: Hyemi Kim, Jay Kim, Kyunghoon Han, Ra-Yeong Choi, In-Woo Kim, Hyung Joo Suh, Ki-Bae Hong, Sung Hee Han

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Chitosan is used in various industries such as food and medical care because it is known to have various functions such as anti-obesity, anti-inflammatory and anti-cancer benefits. Most of the commercial chitosan is extracted from crustaceans. As the harvest rate of snow crabs and red snow crabs decreases and safety issues arise due to environmental pollution, research is underway to extract chitosan from insects. In this study, we used Response Surface Methodology (RSM) to predict the optimal conditions to produce chitosan oligosaccharides from mealworms (MCOS), which can be absorbed through the intestine as low-molecular-weight chitosan. The experimentally confirmed optimal conditions for MCOS production using chitosanase were found to be a substrate concentration of 2.5%, enzyme addition of 30 mg/g and a reaction time of 6 hours. The chemical structure and physicochemical properties of the produced MCOS were measured using MALDI-TOF mass spectra and FTIR spectra. The MALDI-TOF mass spectra revealed peaks corresponding to the dimer (375.045), trimer (525.214), tetramer (693.243), pentamer (826.296), and hexamer (987.360). In the FTIR spectra, commercial chitosan oligosaccharides exhibited a weak peak pattern at 3500-2500 cm-1, unlike chitosan or chitosan oligosaccharides. There was a difference in the peak at 3200~3500 cm-1, where different vibrations corresponding to OH and amine groups overlapped. Chitosan, chitosan oligosaccharide, and commercial chitosan oligosaccharide showed peaks at 2849, 2884, and 2885 cm-1, respectively, attributed to the absorption of the C-H stretching vibration of methyl or methine. The amide I, amide II, and amide III bands of chitosan, chitosan oligosaccharide, and commercial chitosan oligosaccharide exhibited peaks at 1620/1620/1602, 1553/1555/1505, and 1310/1309/1317 cm-1, respectively. Furthermore, the solubility of MCOS was 45.15±3.43, water binding capacity (WBC) was 299.25±4.57, and fat binding capacity (FBC) was 325.61±2.28 and the solubility of commercial chitosan oligosaccharides was 49.04±9.52, WBC was 280.55±0.50, and FBC was 157.22±18.15. Thus, the characteristics of MCOS and commercial chitosan oligosaccharides are similar. The results of investigating the impact of chitosan oligosaccharide on the proliferation of probiotics revealed increased growth in L. casei, L. acidophilus, and Bif. Bifidum. Therefore, the major short-chain fatty acids produced by gut microorganisms, such as acetic acid, propionic acid, and butyric acid, increased within 24 hours of adding 1% (p<0.01) and 2% (p<0.001) MCOS. The impact of MCOS on the overall gut microbiota was assessed, revealing that the Chao1 index did not show significant differences, but the Simpson index decreased in a concentration-dependent manner, indicating a higher species diversity. The addition of MCOS resulted in changes in the overall microbial composition, with an increase in Firmicutes and Verrucomicrobia (p<0.05) compared to the control group, while Proteobacteria and Actinobacteria (p<0.05) decreased. At the genus level, changes in microbiota due to MCOS supplementation showed an increase in beneficial bacteria like lactobacillus, Romboutsia, Turicibacter, and Akkermansia (p<0.0001) while harmful bacteria like Enterococcus, Morganella, Proterus, and Bacteroides (p<0.0001) decreased. In this study, chitosan oligosaccharides were successfully produced under established conditions from mealworms, and these chitosan oligosaccharides are expected to have prebiotic effects, similar to those obtained from crabs.

Keywords: mealworms, chitosan, chitosan oligosaccharide, prebiotics

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Authors: Umara Nissar Rafiqi, Irum Gul, Nazima Nasrullah, Monica Saifi, Malik Z. Abdin

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Background: Stevia rebaudiana, a member of Asteraceae family is an important medicinal plant and produces a commercially used non-caloric natural sweetener, which is also an alternate herbal cure for diabetes. Steviol glycosides are the main sweetening compounds present in these plants. Secondary metabolites are crucial to the adaption of plants to the environment and its overcoming stress conditions. In agricultural procedures, the abiotic stresses like salinity, high metal toxicity and drought, in particular, are responsible for the majority of the reduction that differentiates yield potential from harvestable yield. Salt stress and heavy metal toxicity lead to increased production of reactive oxygen species (ROS). To avoid oxidative damage due to ROS and osmotic stress, plants have a system of anti-oxidant enzymes along with several stress induced enzymes. This helps in scavenging the ROS and relieve the osmotic stress in different cell compartments. However, whether stress induced toxicity modulates the activity of these enzymes in Stevia rebaudiana is poorly understood. Aim: The present study focussed on the effect of salinity, heavy metal toxicity (lead and mercury) on physiological traits and transcriptional profiling of Stevia rebaudiana. Method: Stevia rebaudiana plants were collected from the Central Institute of Medicinal and Aromatic plants (CIMAP), Patnagar, India and maintained under controlled conditions in a greenhouse at Hamdard University, Delhi, India. The plants were subjected to different concentrations of salt (0, 25, 50 and 75 mM respectively) and heavy metals, lead and mercury (0, 100, 200 and 300 µM respectively). The physiological traits such as shoot length, root numbers, leaf growth were evaluated. The samples were collected at different developmental stages and analysed for transcription profiling by RT-PCR. Transcriptional studies in stevia rebaudiana involves important antioxidant enzymes: catalase (CAT), superoxide dismutase (SOD), cytochrome P450 monooxygenase (CYP) and stress induced aquaporin (AQU), auxin repressed protein (ARP-1), Ndhc gene. The data was analysed using GraphPad Prism and expressed as mean ± SD. Result: Low salinity and lower metal toxicity did not affect the fresh weight of the plant. However, this was substantially decreased by 55% at high salinity and heavy metal treatment. With increasing salinity and heavy metal toxicity, the values of all studied physiological traits were significantly decreased. Chlorosis in treated plants was also observed which could be due to changes in Fe:Zn ratio. At low concentrations (upto 25 mM) of NaCl and heavy metals, we did not observe any significant difference in the gene expressions of treated plants compared to control plants. Interestingly, at high salt concentration and high metal toxicity, a significant increase in the expression profile of stress induced genes was observed in treated plants compared to control (p < 0.005). Conclusion: Stevia rebaudiana is tolerant to lower salt and heavy metal concentration. This study also suggests that with the increase in concentrations of salt and heavy metals, harvest yield of S. rebaudiana was hampered.

Keywords: Stevia rebaudiana, natural sweetener, salinity, heavy metal toxicity

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Authors: Khairul Bariah Sulaiman, Tajul Aris Yang

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Fermentation is well known as an essential process in cocoa beans. Besides to develop the precursor of cocoa flavour, it also induce the colour changes in the beans.The fermentation process is reported to be influenced by duration of pod storage and fermentation. Therefore, this study was conducted to evaluate colour of Malaysian cocoa beans and how the pods storage and fermentation duration using shallow box technique will effect on it characteristics. There are two factors being studied ie duration of cocoa pod storage (0, 2, 4, and 6 days) and duration of cocoa fermentation (0, 1, 2, 3, 4 and 5 days). The experiment is arranged in 4 x 6 factorial design with 24 treatments and arrangement is in a Completely Randomised Design (CRD). The produced beans is inspected for colour changes under artificial light during cut test and divided into four groups of colour namely fully brown, purple brown, fully purple and slaty. Cut tests indicated that cocoa beans which are directly dried without undergone fermentation has the highest slaty percentage. However, application of pods storage before fermentation process is found to decrease the slaty percentage. In contrast, the percentages of fully brown beans start to dominate after two days of fermentation, especially from four and six days of pods storage batch. Whereas, almost all batch have percentage of fully purple less than 20%. Interestingly, the percentage of purple brown beans are scattered in the entire beans batch regardless any specific trend. Meanwhile, statistical analysis using General Linear Model showed that the pods storage has a significant effect on the colour characteristic of the Malaysian dried beans compared to fermentation duration.

Keywords: cocoa beans, colour, fermentation, shallow box

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Authors: Abeer Samy, Oliver C. Saavedra Valeriano, Abdelazim Negm

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The Blue Nile Basin is the most important tributary of the Nile River. Egypt and Sudan are almost dependent on water originated from the Blue Nile. This multi-dependency creates conflicts among the three countries Egypt, Sudan, and Ethiopia making the management of these conflicts as an international issue. Good assessment of the water resources of the Blue Nile is an important to help in managing such conflicts. Hydrological models are good tool for such assessment. This paper presents a critical review of the nature and variability of the climate and hydrology of the Blue Nile Basin as a first step of using hydrological modeling to assess the water resources of the Blue Nile. Many several attempts are done to develop basin-scale hydrological modeling on the Blue Nile. Lumped and semi distributed models used averages of meteorological inputs and watershed characteristics in hydrological simulation, to analyze runoff for flood control and water resource management. Distributed models include the temporal and spatial variability of catchment conditions and meteorological inputs to allow better representation of the hydrological process. The main challenge of all used models was to assess the water resources of the basin is the shortage of the data needed for models calibration and validation. It is recommended to use distributed model for their higher accuracy to cope with the great variability and complexity of the Blue Nile basin and to collect sufficient data to have more sophisticated and accurate hydrological modeling.

Keywords: Blue Nile Basin, climate change, hydrological modeling, watershed

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Authors: Isaac Mugume

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Since the beginning of the 21st century, climate change has been an issue due to the reported rise in global temperature and changes in the frequency as well as severity of extreme weather and climatic events. The changing climate has been attributed to rising concentrations of greenhouse gases, including environmental changes such as ecosystems and land-uses. Climatic projections have been carried out under the auspices of the intergovernmental panel on climate change where a couple of models have been run to inform us about the likelihood of future climates. Since one of the major forcings informing the changing climate is emission of greenhouse gases, different scenarios have been proposed and future climates for different periods presented. The global climate models project different areas to experience different impacts. While regional modeling is being carried out for high impact studies, bias correction is less documented. Yet, the regional climate models suffer bias which introduces uncertainty. This is addressed in this study by bias correcting the regional models. This study uses the Weather Research and Forecasting model under different representative concentration pathways and correcting the products of these models using observed climatic data. This study notes that bias correction (e.g., the running-mean bias correction; the best easy systematic estimator method; the simple linear regression method, nearest neighborhood, weighted mean) improves the climatic projection skill and therefore reduce the uncertainty inherent in the climatic projections.

Keywords: bias correction, climatic projections, numerical models, representative concentration pathways

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: factors, fuzzy cognitive map, group decision, integrated waste management system

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

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In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: T. Heiman, D. Olenik-Shemesh

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Over the past decade, with the rapid growth of electronic communication, the internet and, in particular, social networking has become an inseparable part of people's daily lives. Along with its benefits, a new type of online aggression has emerged, defined as cyber bullying, a form of interpersonal aggressive behavior that takes place through electronic means. Cyber-bullying is characterized by repetitive behavior over time of maladaptive authority and power usage using computers and cell phones via sending insulting messages and hurtful pictures. Preliminary findings suggest that the prevalence of involvement in cyber-bullying among higher education students varies between 10 and 35%. As to date, universities are facing an uphill effort in trying to restrain online misbehavior. As no studies examined the relationships between cyber-bullying involvement with personal aspects, and its impacts on academic achievement and work functioning, this present study examined the nature of cyber-bullying involvement among 1,052 undergraduate students (mean age = 27.25, S.D = 4.81; 66.2% female), coping with, as well as the effects of social support, perceived self-efficacy, well-being, and body-perception, in relation to cyber-victimization. We assume that students in higher education are a vulnerable population and at high risk of being cyber-victims. We hypothesize that social support might serve as a protective factor and will moderate the relationships between the socio-emotional variables and the occurrence of cyber- victimization. The findings of this study will present the relationships between cyber-victimization and the social-emotional aspects, which constitute risk and protective factors. After receiving approval from the Ethics Committee of the University, a Google Drive questionnaire was sent to a random sample of students, studying in the various University study centers. Students' participation was voluntary, and they completed the five questionnaires anonymously: Cyber-bullying, perceived self-efficacy, subjective well-being, social support and body perception. Results revealed that 11.6% of the students reported being cyber-victims during last year. Examining the emotional and behavioral reactions to cyber-victimization revealed that female emotional and behavioral reactions were significantly greater than the male reactions (p < .001). Moreover, females reported on a significant higher social support compared to men; male reported significantly on a lower social capability than female; and men's body perception was significantly more positive than women's scores. No gender differences were observed for subjective well-being scale. Significant positive correlations were found between cyber-victimization and fewer friends, lower grades, and work ineffectiveness (r = 0.37- .40, p < 0 .001). The results of the Hierarchical regression indicated significantly that cyber-victimization can be predicted by lower social support, lower body perception, and gender (female), that explained 5.6% of the variance (R2 = 0.056, F(5,1047) = 12.47, p < 0.001). The findings deepen our understanding of the students' involvement in cyber-bullying, and present the relationships of the social-emotional and academic aspects on cyber-victim students. In view of our findings, higher education policy could help facilitate coping with cyber-bullying incidents, and student support units could develop intervention programs aimed at reducing cyber-bullying and its impacts.

Keywords: academic and personal factors, cyber-victimization, social support, higher education

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Authors: Mei-Hui Liu

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This study examines the effectiveness of a blended professional development program on preservice EFL (English as a foreign language) teachers’ learning to teach speech acts with the advent of Information and Communication Technology, researchers and scholars underscore the significance of integrating online and face-to-face learning opportunities in the teacher education field. Yet, a paucity of evidence has been documented to investigate the extent to which such a blended professional learning model may impact real classroom practice and student learning outcome. This yearlong project involves various stakeholders, including 25 preservice teachers, 5 English professionals, and 45 secondary school students. Multiple data sources collected are surveys, interviews, reflection journals, online discussion messages, artifacts, and discourse completion tests. Relying on the theoretical lenses of Community of Inquiry, data analysis depicts the nature and process of preservice teachers’ professional development in this blended learning community, which triggers and fosters both face-to-face and synchronous/asynchronous online interactions among preservice teachers and English professionals (i.e., university faculty and in-service teachers). Also included is the student learning outcome after preservice teachers put what they learn from the support community into instructional practice. Pedagogical implications and research suggestions are further provided based on the research findings and limitations.

Keywords: blended professional development, preservice EFL teachers, speech act instruction, student learning outcome

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Authors: Changhan Ouyang, Zhonglin Xie

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In response to proatherosclerotic factors such as oxidized lipids, or to therapeutic interventions such as angioplasty, stents, or bypass surgery, vascular smooth muscle cells (VSMCs) migrate from the media to the intima, resulting in intimal hyperplasia, restenosis, graft failure, or atherosclerosis. These proatherosclerotic factors also activate autophagy in VSMCs. However, the functional role of autophagy in vascular health and disease remains poorly understood. In the present study, we determined the role of autophagy in the regulation of VSMC migration. Autophagy activity in cultured human aortic smooth muscle cells (HASMCs) and mouse carotid arteries was measured by Western blot analysis of microtubule-associated protein 1 light chain 3 B (LC3B) and P62. The VSMC migration was determined by scratch wound assay and transwell migration assay. Ex vivo smooth muscle cell migration was determined using aortic ring assay. The in vivo SMC migration was examined by staining the carotid artery sections with smooth muscle alpha actin (alpha SMA) after carotid artery ligation. To examine the relationship between autophagy and neointimal hyperplasia, C57BL/6J mice were subjected to carotid artery ligation. Seven days after injury, protein levels of Atg5, Atg7, Beclin1, and LC3B drastically increased and remained higher in the injured arteries three weeks after the injury. In parallel with the activation of autophagy, vascular injury-induced neointimal hyperplasia as estimated by increased intima/media ratio. The en face staining of carotid artery showed that vascular injury enhanced alpha SMA staining in the intimal cells as compared with the sham operation. Treatment of HASMCs with platelet-derived growth factor (PDGF), one of the major factors for vascular remodeling in response to vascular injury, increased Atg7 and LC3 II protein levels and enhanced autophagosome formation. In addition, aortic ring assay demonstrated that PDGF treated aortic rings displayed an increase in neovessel formation compared with control rings. Whole mount staining for CD31 and alpha SMA in PDGF treated neovessels revealed that the neovessel structures were stained by alpha SMA but not CD31. In contrast, pharmacological and genetic suppression of autophagy inhibits VSMC migration. Especially, gene silencing of Atg7 inhibited VSMC migration induced by PDGF. Furthermore, three weeks after ligation, markedly decreased neointimal formation was found in mice treated with chloroquine, an inhibitor of autophagy. Quantitative morphometric analysis of the injured vessels revealed a marked reduction in the intima/media ratio in the mice treated with chloroquine. Conclusion: Autophagy activation increases VSMC migration while autophagy suppression inhibits VSMC migration. These findings suggest that autophagy suppression may be an important therapeutic strategy for atherosclerosis and intimal hyperplasia.

Keywords: autophagy, vascular smooth muscle cell, migration, neointimal formation

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Authors: Delia Gabriela Moisa, Demos Parapanos, Tim Heap

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The tourism sector is mainly comprised of small and medium-sized tourism enterprises (SMEs), representing approximately 80% of global businesses in this field. These entities require focused attention and support to address challenges, ensuring their competitiveness and relevance in a dynamic industry characterized by continuously changing customer preferences. To address these challenges, it becomes imperative to consider not only socio-demographic factors but also delve into the intricate interplay of psychological elements influencing consumer behavior. This study investigates the impact of personality traits and travel motivations on visitor activities in Cumbria, United Kingdom, an iconic region marked by UNESCO World Heritage Sites, including The Lake District National Park and Hadrian's Wall. With a £4.1 billion tourism industry primarily driven by SMEs, Cumbria serves as an ideal setting for examining the relationship between tourist psychology and activities. Employing the Big Five personality model and the Travel Career Pattern motivation theory, this study aims to explain the relationship between psychological factors and tourist activities. The study further explores SME perspectives on personality-based market segmentation, providing strategic insights into addressing evolving tourist preferences.This pioneering mixed-methods study integrates quantitative data from 330 visitor surveys, subsequently complemented by qualitative insights from tourism SME representatives. The findings unveil that socio-demographic factors do not exhibit statistically significant variations in the activities pursued by visitors in Cumbria. However, significant correlations emerge between personality traits and motivations with preferred visitor activities. Open-minded tourists gravitate towards events and cultural activities, while Conscientious individuals favor cultural pursuits. Extraverted tourists lean towards adventurous, recreational, and wellness activities, while Agreeable personalities opt for lake cruises. Interestingly, a contrasting trend emerges as Extraversion increases, leading to a decrease in interest in cultural activities. Similarly, heightened Agreeableness corresponds to a decrease in interest in adventurous activities. Furthermore, travel motivations, including nostalgia and building relationships, drive event participation, while self-improvement and novelty-seeking lead to adventurous activities. Additionally, qualitative insights from tourism SME representatives underscore the value of targeted messaging aligned with visitor personalities for enhancing loyalty and experiences. This study contributes significantly to scholarship through its novel framework, integrating tourist psychology with activities and industry perspectives. The proposed conceptual model holds substantial practical implications for SMEs to formulate personalized offerings, optimize marketing, and strategically allocate resources tailored to tourist personalities. While the focus is on Cumbria, the methodology's universal applicability offers valuable insights for destinations globally seeking a competitive advantage. Future research addressing scale reliability and geographic specificity limitations can further advance knowledge on this critical relationship between visitor psychology, individual preferences, and industry imperatives. Moreover, by extending the investigation to other districts, future studies could draw comparisons and contrasts in the results, providing a more nuanced understanding of the factors influencing visitor psychology and preferences.

Keywords: personality trait, SME, tourist behaviour, tourist motivation, visitor activity

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Authors: Sarah Niklas, Lynne Chester, Mark Diesendorf

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Geopolitical tensions, climate change and recent movements favouring a transformative shift in institutional power structures have influenced the economics of conventional energy supply for decades. This study takes a multi-dimensional approach to illustrate the potential of renewable energy (RE) technology to provide a pathway to a low-carbon economy driven by ecologically sustainable, independent and socially just energy. This comparative analysis identifies economic, political and social drivers that shaped the adoption of RE policy in two significantly different economies, Germany and Australia, with strong and weak commitments to RE respectively. Two complementary political-economy theories frame the document-based analysis. Régulation Theory, inspired by Marxist ideas and strongly influenced by contemporary economic problems, provides the background to explore the social relationships contributing the adoption of RE within the macro-economy. Varieties of Capitalism theory, a more recently developed micro-economic approach, examines the nature of state-firm relationships. Together these approaches provide a comprehensive lens of analysis. Germany’s energy policy transformed substantially over the second half of the last century. The development is characterised by the coordination of societal, environmental and industrial demands throughout the advancement of capitalist regimes. In the Fordist regime, mass production based on coal drove Germany’s astounding economic recovery during the post-war period. Economic depression and the instability of institutional arrangements necessitated the impulsive seeking of national security and energy independence. During the postwar Flexi-Fordist period, quality-based production, innovation and technology-based competition schemes, particularly with regard to political power structures in and across Europe, favoured the adoption of RE. Innovation, knowledge and education were institutionalized, leading to the legislation of environmental concerns. Lastly the establishment of government-industry-based coordinative programs supported the phase out of nuclear power and the increased adoption of RE during the last decade. Australia’s energy policy is shaped by the country’s richness in mineral resources. Energy policy largely served coal mining, historically and currently one of the most capital-intense industry. Assisted by the macro-economic dimensions of institutional arrangements, social and financial capital is orientated towards the export-led and strongly demand-oriented economy. Here energy policy serves the maintenance of capital accumulation in the mining sector and the emerging Asian economies. The adoption of supportive renewable energy policy would challenge the distinct role of the mining industry within the (neo)-liberal market economy. The state’s protective role of the mining sector has resulted in weak commitment to RE policy and investment uncertainty in the energy sector. Recent developments, driven by strong public support for RE, emphasize the sense of community in urban and rural areas and the emergence of a bottom-up approach to adopt renewables. Thus, political economy frameworks on both the macro-economic (Regulation Theory) and micro-economic (Varieties of Capitalism theory) scales can together explain the strong commitment to RE in Germany vis-à-vis the weak commitment in Australia.

Keywords: political economy, regulation theory, renewable energy, social relationships, energy transitions

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Authors: Fella Lahmar

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This chapter investigates the educational reforms in Algeria, highlighting the challenges and complexities that arise in the context of globalization, equity, and decolonization. While Algeria’s education system historically had a socialist-economic model grounded in Islamic values, contemporary reforms reflect global influences and aspirations for cultural authenticity. The study employed a qualitative approach, utilizing semi-structured interviews with a diverse sample of 15 participants intimately involved in the Algerian education system. Analysis of the data reveals a discrepancy between the educational system’s pedagogical practices and students’ diverse learning needs, implying ramifications for educational equity and social justice. Furthermore, a critical tension was evident between global influences, local cultural authenticity, and the endeavor to decolonize education. In conclusion, the chapter advocates for reforms that prioritize the students’ holistic development and well-being while fostering intrinsic motivation and engagement. This entails re-evaluating curriculum frameworks, assessment strategies, and pedagogies in light of Algeria’s cultural and religious heritage. The chapter also calls for future research to explore methods for innovatively integrating cultural heritage into education in ways to cultivate learners who are both locally grounded and globally aware.

Keywords: impact of globalization on education, parental involvement in education, marketization of education, policy enactment and reform, curriculum overload, holistic approach, shadow education

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Authors: Jingting Luo, Yong Wang, Ying Wang

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Pedestrian detection in image or video data is a very important and challenging task in security surveillance. The difficulty of this task is to locate and detect pedestrians of different scales in complex scenes accurately. To solve these problems, a deep neural network (RT-YOLOv3) is proposed to realize real-time pedestrian detection at different scales in security monitoring. RT-YOLOv3 improves the traditional YOLOv3 algorithm. Firstly, the deep residual network is added to extract vehicle features. Then six convolutional neural networks with different scales are designed and fused with the corresponding scale feature maps in the residual network to form the final feature pyramid to perform pedestrian detection tasks. This method can better characterize pedestrians. In order to further improve the accuracy and generalization ability of the model, a hybrid pedestrian data set training method is used to extract pedestrian data from the VOC data set and train with the INRIA pedestrian data set. Experiments show that the proposed RT-YOLOv3 method achieves 93.57% accuracy of mAP (mean average precision) and 46.52f/s (number of frames per second). In terms of accuracy, RT-YOLOv3 performs better than Fast R-CNN, Faster R-CNN, YOLO, SSD, YOLOv2, and YOLOv3. This method reduces the missed detection rate and false detection rate, improves the positioning accuracy, and meets the requirements of real-time detection of pedestrian objects.

Keywords: pedestrian detection, feature detection, convolutional neural network, real-time detection, YOLOv3

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Authors: Mengping Cheng, John Everatt, Alison Arrow, Amanda Denston

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Based on the available evidence, Chinese heritage language learners have a basic level of Chinese language proficiency with lower capability in literacy compared to speaking. Low levels of literacy are likely related to the lack of reading activities in current textbook-based pedagogy used in Chinese community schools. The present study aims to use Reading to Learn pedagogy which is a top-down language learning model and test the effectiveness of Reading to Learn on Chinese heritage learners’ written vocabulary acquisition. A quasi-experiment with the pre-test/post-test non-equivalent group design was conducted. The experimental group received Reading to Learn instructions and the control group had traditional textbook-based instructions. Participants were given Chinese characters tasks (a recognize-and-read task and a listen-and-point task), vocabulary tasks (a receptive vocabulary task and a productive vocabulary task) and a sentence cloze test in pre-tests and post-tests. Data collection is in progress and results will be available shortly. If the results show more improvement of Chinese written vocabulary in the experimental group than in the control group, it will be recommended that Reading to Learn pedagogy is valuable to be used to maintain and develop Chinese heritage language literacy.

Keywords: Chinese heritage language, experimental research, Reading to Learn pedagogy, vocabulary acquisition

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Authors: Y. Ghiassi-Farrokhfal

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The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.

Keywords: solar energy, battery storage, electric vehicle, charging stations

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