Search results for: physical model tests

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: Bhakti Chitale

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Mumbai city, which is the business capital of India and one of the most crowded cities in the world, holds the biggest slum in Asia. The Mumbai Metropolitan Region (MMR) occupies an area of 4035 sq.km. with a population of 22.8 million people. This population is mostly urban with 91% of this population living in areas of Municipal Corporations and Councils. Another 3% live in Census Towns. The region has 9 Municipal Corporations, 8 Municipal councils, and around 1000 villages. On the one hand MMR reflects the highest contribution to the Nations overall economy and on the other hand it shows the horrible and intolerable picture of about 2 million people, who are living in slums/without even slum with totally unhygienic conditions and with total loss of hope. The generations are about to get affected adversely if the solution is not worked out. This study is an attempt towards working out the solution. Mumbai Metropolitan Region Development Authority (MMRDA) is state government's authority, specially formed to govern the development of MMR. MMRDA is engaged in long term planning, promotion of new growth centres, implementation of strategic projects and financing infrastructure development. While preparing the master plan for MMR for next 20 years MMRDA conducted a detail study regarding Housing scenario in MMR and possible options for improvement. The author was the in charge officer for the said assignment. This paper puts light on the interesting outcomes of the research study, which ranges from the adverse effects of government policies, automatic responses of housing market, effects on planning processes, and overall changing needs of housing patterns in the world due to changes in the social mechanism. It alarms the urban planners who usually focus on smart infrastructure development, about allied future dangers. This housing study will explain the complexities, realities and needs of innovations in the housing policies all over the world. The paper will explain further few success stories and failure stories of government initiatives with reasons. It gives the clear idea about the differences in needs of housing for people from different economic groups and direct and indirect market pressures on low cost housing. Magical phenomenon came in front like a large percentage of vacant houses is present in spite of the huge need. Housing market gets affected by the developments or any other physical and financial changes taking place in the nearby areas or cities, also by changes in cities which are located far from the region and also by the international investments or policy changes. Instead of just depending on governments actions in case of generation of affordable housing, it becomes equally important to make the housing markets automatically generate such stock and still make them sustainable is the aim of all the movement. In summary, we may say that the paper will sequentially elaborate the complete dynamics of housing in one of the most crowded urban area in the world that is Mumbai Metropolitan Region, with a lot of data, analysis, case studies, and recommendations.

Keywords: Mumbai India, slum housing, region planning, market recommendations

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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: Neha Joshi, Srikanth Jois, Hector J. Peughero, Poornima Jayakrishna, Moulya R., Purnima Madivanan, Kiran Kumar K. Salagame

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Transgenders are a marginalized section of the community, who are at high risk of mental health problems due to their stigmatization, abandonment by family, prejudice, discrimination by society at large, and the physical, emotional, and sexual abuse from both within and outside their community. Their mental healthcare needs remain largely unaddressed due to lack of access, discrimination by healthcare professions, and lack of resources, including time and money, to seek conventional medical and psychotherapeutic treatments. Meditation is increasingly receiving acceptance as a tool for managing stress and anxiety by the patients as well as mental healthcare professionals. “Meditation on Twin Hearts” is a no cost, self-administered intervention that a person can practice anywhere and at any time of the day. This pilot study evaluates the need for alternate traditional and ingenious interventions like “Meditation of Twin Hearts” to address the mental healthcare needs of the transgender community and acceptance of such an intervention by the community. Thirteen individuals identifying themselves as transgender were invited to participate in one (Hunsur Taluk) of the five scheduled free meditation camps in Mysore. After obtaining informed consent for participation in the study, their mental health status is captured using an anonymous survey using standard, validated, self-reported questionnaires Generalised Anxiety Disorders (GAD)-7 for anxiety, Patient Health Questionnaire (PHQ-9) for depression, and Suicidal Behavior Questionnaire-Revised for suicidality. Then, they were requested to attend a session on “Meditation on Twin Hearts.” After the session, their feedback on willingness to further explore the meditation technique for managing their mental healthcare need was assessed through another survey form. Out of the 13 participants, 92% scored for anxiety (4 mild, and 8 moderate anxiety). In the depression scale, 5 scored for mild and 5 for moderate depression, with a total of 77% (10/13) scoring positively on depression scale. Nearly 70% of participants (9/13), scored greater than the clinical cutoff for the need for clinical intervention. The proportion of individuals at risk for suicide was particularly high in this group, with 8/ 13 (61.5%) participants scoring the clinical cutoff score of ≥ 7. Surprisingly, none of the participants had ever consulted a mental healthcare professional. All the participants (13/13; 100%) responded in affirmative to the question, “Will you be willing to continue meditation for management of your anxiety?” Six out of 13 participants described their experience of meditation as “happy” and 3 described it as “peaceful”. None of the participants reported any negative beliefs or experience regarding the meditation. The study provides evidence for the urgent yet unmet mental healthcare need of the transgender community. The findings of the study also supports the rationale of conducting future systematic research to evaluate and explore ingenious and traditional practices, such as meditation, to meet the healthcare needs, especially in marginalized populations in a low income setting such as Lower and Middle Income countries. Based on these preliminary findings, the Principal Investigator (PI) is planning to cover 4 more areas of Mysore district.

Keywords: anxiety, depression, meditation on twin heart, suicidality, transgender

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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: 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: Suneet Jagdev, Hrishabh Amrodia, Siddharth Menon, Abhishek Singh, Mansi Shivhare

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Delhi, the National Capital, has undergone a surge in development rate, consequently engendering an unprecedented increase in population. Over the years the city has transformed into a car-centric infrastructure with high-speed corridors, flyovers and fast lanes. A considerable section of the population is hankering to rehabilitate to the good old cycling days, in order to contribute towards a green environment as well as to maintain their physical well-being. Furthermore, an extant section of Delhi’s population relies on cycles as their primary means of commuting in the city. Delhi has the highest number of cyclists and second highest number of pedestrians in the country. However, the tumultuous problems of unregulated traffic, inadequate space on roads, adverse weather conditions stifle them to opt for cycling. Lately, the city has been facing a conglomeration of problems such as haphazard traffic movement, clogged roads, congestion, pollution, accidents, safety issues, etc. In 1957, Delhi’s cyclists accounted for 36 per cent of trips which dropped down to a mere 4 per cent in 2008. The declining rate is due to unsafe roads and lack of proper cycle lanes. Now as the 10 percent of the city has cycle tracks. There is also a lack of public recreational activities in the city. These conundrums incite the need of a covered elevated cycling bridge track to facilitate the safe and smooth cycle commutation in the city which would also serve the purpose of an alternate urban public space over the cycle bridge reducing the cost as well as the space requirement for the same, developing a user–friendly transportation and public interaction system for urban areas in the city. Based on the archival research methodologies, the following research draws information and extracts records from the data accounts of the Delhi Metro Rail Corporation Ltd. as well as the Centre for Science and Environment, India. This research will predominantly focus on developing a prototype design for high speed elevated bicycle lanes based on different road typologies, which can be replicated with minor variations in similar situations, all across the major cities of our country including the proposed smart cities. Furthermore, how these cycling lanes could be utilized for the place making process accommodating cycle parking and renting spaces, public recreational spaces, food courts as well as convenient shopping facilities with appropriate optimization. How to preserve and increase the share of smooth and safe cycling commute cycling for the routine transportation of the urban community of the polluted capital which has been on a steady decline over the past few decades.

Keywords: bicycle track, prototype, road safety, urban spaces

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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: Ashish Thakur

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This technical paper was written in view of focusing the biomaterials and its various applications in modern industries. Author tires to elaborate not only the medical, infect plenty of application in other industries. The scope of the research area covers the wide range of physical, biological and chemical sciences that underpin the design of biomaterials and the clinical disciplines in which they are used. A biomaterial is now defined as a substance that has been engineered to take a form which, alone or as part of a complex system, is used to direct, by control of interactions with components of living systems, the course of any therapeutic or diagnostic procedure. Biomaterials are invariably in contact with living tissues. Thus, interactions between the surface of a synthetic material and biological environment must be well understood. This paper reviews the benefits and challenges associated with surface modification of the metals in biomedical applications. The paper also elaborates how the surface characteristics of metallic biomaterials, such as surface chemistry, topography, surface charge, and wettability, influence the protein adsorption and subsequent cell behavior in terms of adhesion, proliferation, and differentiation at the biomaterial–tissue interface. The chapter also highlights various techniques required for surface modification and coating of metallic biomaterials, including physicochemical and biochemical surface treatments and calcium phosphate and oxide coatings. In this review, the attention is focused on the biomaterial-associated infections, from which the need for anti-infective biomaterials originates. Biomaterial-associated infections differ markedly for epidemiology, aetiology and severity, depending mainly on the anatomic site, on the time of biomaterial application, and on the depth of the tissues harbouring the prosthesis. Here, the diversity and complexity of the different scenarios where medical devices are currently utilised are explored, providing an overview of the emblematic applicative fields and of the requirements for anti-infective biomaterials. In addition to this, chapter introduces nanomedicine and the use of both natural and synthetic polymeric biomaterials, focuses on specific current polymeric nanomedicine applications and research, and concludes with the challenges of nanomedicine research. Infection is currently regarded as the most severe and devastating complication associated to the use of biomaterials. Osteoporosis is a worldwide disease with a very high prevalence in humans older than 50. The main clinical consequences are bone fractures, which often lead to patient disability or even death. A number of commercial biomaterials are currently used to treat osteoporotic bone fractures, but most of these have not been specifically designed for that purpose. Many drug- or cell-loaded biomaterials have been proposed in research laboratories, but very few have received approval for commercial use. Polymeric nanomaterial-based therapeutics plays a key role in the field of medicine in treatment areas such as drug delivery, tissue engineering, cancer, diabetes, and neurodegenerative diseases. Advantages in the use of polymers over other materials for nanomedicine include increased functionality, design flexibility, improved processability, and, in some cases, biocompatibility.

Keywords: nanomedicine, tissue, infections, biomaterials

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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: 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: 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: 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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Authors: Deepa Shokeen, Bani Tamber Aeri

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Food choice is a complex process influenced by the interplay of multiple factors, including physical, socio-cultural and economic factors comprising macro or micro level food environments. While a clear understanding of the relationship between what we eat and the environmental context in which these food choices are made is still needed; it has however now been shown that food environments do play a significant role in the obesity epidemic and increasing cardio-metabolic risk factors. Evidence in other countries indicates that the food environment may strongly influence the prevalence of obesity and cardio-metabolic risk factors among young adults. Although in the Indian context, data does indicate the associations between sedentary lifestyle, stress, faulty diets but very little evidence supports the role of food environment in influencing cardio-metabolic health among employed adults. Thus, this research is required to establish how different environments affect different individuals as individuals interact with the environment on a number of levels. Methodology: The objective of the present study is to assess the effect of selected food and nutrition environments with emphasis on worksite environment and to analyse its impact on the food choices and dietary behaviour of the employees (25-45 years of age) of the organizations under study. In the proposed study an attempt will be made to randomly select various worksite environments from Delhi and NCR. The study will be conducted in two phases. In phase I, Information will be obtained on their socio-demographic profile and various factors influencing their food choices including most commonly consumed foods and most frequently visited eating outlets in and around the work place. Data will also be gathered on anthropometry (height, weight, waist circumference), biochemical parameters (lipid profile and fasting glucose), blood pressure and dietary intake. Based on the findings of phase I, a list of the most frequently visited eating outlets in and around the workplace will be prepared in Phase II. These outlets will then be subjected to nutrition environment assessment survey (NEMS). On the basis of the information gathered from phase I and phase II, influence of selected food and nutrition environments on food choice, dietary behaviour and prevalence of cardio-metabolic risk factors among employed adults will be assessed. Expected outcomes: The proposed study will try to ascertain the impact of selected food and nutrition environments on food choice and dietary intake of the working adults as it is important to learn how these food environments influence the eating perceptions and health behavior of the adults. In addition to this, anthropometry blood pressure and biochemical assessment of the subjects will be done to assess the prevalence of cardio-metabolic risk factors. If the findings indicate that the work environment, where most of these young adults spend their productive hours of the day, influence their health, than perhaps steps maybe needed to make these environments more conducive to health.

Keywords: food and nutrition environment, cardio-metabolic risk factors, India, worksite environment

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

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The development, operation and maintenance of Integrated Waste Management Systems (IWMS) affects essentially the sustainable concern of every region. The features of such systems have great influence on all of the components of sustainability. In order to reach the optimal way of processes, a comprehensive mapping of the variables affecting the future efficiency of the system is needed such as analysis of the interconnections among the components and modelling of their interactions. The planning of a IWMS is based fundamentally on technical and economical opportunities and the legal framework. Modelling the sustainability and operation effectiveness of a certain IWMS is not in the scope of the present research. The complexity of the systems and the large number of the variables require the utilization of a complex approach to model the outcomes and future risks. This complex method should be able to evaluate the logical framework of the factors composing the system and the interconnections between them. The authors of this paper studied the usability of the Fuzzy Cognitive Map (FCM) approach modelling the future operation of IWMS’s. The approach requires two input data set. One is the connection matrix containing all the factors affecting the system in focus with all the interconnections. The other input data set is the time series, a retrospective reconstruction of the weights and roles of the factors. This paper introduces a novel method to develop time series by content analysis.

Keywords: content analysis, factors, integrated waste management system, time series

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Authors: Maryam Solgi, Behzad Shahmohammadi, Morteza Raissi Dehkordi

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One of the main steps for seismic retrofitting of buildings is to determine the vulnerability of structures. While current procedures for evaluating existing buildings are complicated, and there is no limitation between short, middle-high, and tall buildings. This research utilizes a simplified method for assessing structures, which is adequate for existing reinforced concrete buildings. To approach this aim, Simple Lateral Mechanisms Analysis (SLaMA) procedure proposed by NZSEE (New Zealand Society for Earthquake Engineering) has been carried out. In this study, three RC moment-resisting frame buildings are determined. First, these buildings have been evaluated by inelastic static procedure (Pushover) based on acceptance criteria. Then, Park-Ang Damage Index is determined for the whole members of each building by Inelastic Time History Analysis. Next, the Simple Lateral Mechanisms Analysis procedure, a hand method, is carried out to define the capacity of structures. Ultimately, existing procedures are compared with Peak Ground Acceleration caused to fail (PGAfail). The results of this comparison emphasize that the Pushover procedure and SLaMA method define a greater value of PGAfail than the Park-Ang Damage model.

Keywords: peak ground acceleration caused to fail, reinforced concrete moment-frame buildings, seismic vulnerability analysis, simple lateral mechanisms analysis

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Authors: Pubudu K. Hitigala Kaluarachchilage, Champike Attanayake, Sasith Rajasooriya, Chris P. Tsokos

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Operating system (OS) security is a key component of computer security. Assessing and improving OSs strength to resist against vulnerabilities and attacks is a mandatory requirement given the rate of new vulnerabilities discovered and attacks occurring. Frequency and the number of different kinds of vulnerabilities found in an OS can be considered an index of its information security level. In the present study five mostly used OSs, Microsoft Windows (windows 7, windows 8 and windows 10), Apple’s Mac and Linux are assessed for their discovered vulnerabilities and the risk associated with each. Each discovered and reported vulnerability has an exploitability score assigned in CVSS score of the national vulnerability database. In this study the risk from vulnerabilities in each of the five Operating Systems is compared. Risk Indexes used are developed based on the Markov model to evaluate the risk of each vulnerability. Statistical methodology and underlying mathematical approach is described. Initially, parametric procedures are conducted and measured. There were, however, violations of some statistical assumptions observed. Therefore the need for non-parametric approaches was recognized. 6838 vulnerabilities recorded were considered in the analysis. According to the risk associated with all the vulnerabilities considered, it was found that there is a statistically significant difference among average risk levels for some operating systems, indicating that according to our method some operating systems have been more risk vulnerable than others given the assumptions and limitations. Relevant test results revealing a statistically significant difference in the Risk levels of different OSs are presented.

Keywords: cybersecurity, Markov chain, non-parametric analysis, vulnerability, operating system

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Authors: Bessaha Hassiba, Bouraada Mohamed

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

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

Procedia PDF Downloads 214

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

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

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

Procedia PDF Downloads 89