Search results for: fire scenario

Authors: Sifat Rahman Ahona, Rifat Tasnim, Naima Hassan

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Data aggregation is a helpful technique for reducing the data communication overhead in wireless sensor network. One of the important tasks of data aggregation is positioning of the aggregator points. There are a lot of works done on data aggregation. But, efficient positioning of the aggregators points is not focused so much. In this paper, authors are focusing on the positioning or the placement of the aggregation points in wireless sensor network. Authors proposed an algorithm to select the aggregators positions for a scenario where aggregator nodes are more powerful than sensor nodes.

Keywords: aggregation point, data communication, data aggregation, wireless sensor network

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Authors: Najah Kalifah Almazmomi

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In the time of artificial intelligence (AI), there is a need to know the determinants of success in business management, which are taking on a new dimension. This research purports to scrutinize the Critical Success Factors (CSFs) that drive and ignite the fire of success to help uncover the subtle and profound dynamics that might be operative in organizations. By means of a systematic literature review and a number of empirical methods, the paper is aimed at determining and assessing the key aspects of CSFs, putting emphasis on their role and meaning in the context of AI technology adoption. Some central features such as leadership ways, innovation models, strategic thinking methodologies, organizational culture transformations, and human resource management approaches are compared and contrasted with the AI-driven revolution. Additionally, this research will explore the interactive effects of these factors and their joint impact on the success, survival, and flexibility of a business in the current environment, which is changing due to AI development. Through the use of different qualitative and quantitative methodologies, the research concludes that the findings are significant in understanding the relative roles of individual CSFs and in studying the interactions between them in such an AI-enabled business environment.

Keywords: critical success factors, business and management, artificial intelligence, leadership strategies

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Authors: Surajo Ladan

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English has been in existence in Nigeria since colonial period. The advent of English in Nigeria has caused a lot of linguistic changes in Nigerian languages especially among the educated elites and to some extent, even the ordinary people were not spared from this phenomenon. This scenario has generated a linguistic situation which culminated into the creation of Nigerian Pidgin that are conglomeration of English and other Nigerian languages. English has infiltrated the Nigerian languages to a point that a typical Nigerian can hardly talk without code-switching or using one English word or the other. The existence of English loanwords in Nigerian languages has taken another dimension in this scientific and technological age. Most of scientific and technological inventions are products of English language which are virtually adopted into the languages with phonological, morphological, and sometimes semantic variations. This paper is of the view that there should be a re-think and agitation from Nigerians to protect their languages from the linguistic genocide of English which are invariably facing extinction.

Keywords: linguistic change, loanword, phenomenon, pidgin

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Authors: Nursah Kutuk, Sevil Cetinkaya

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Geopolymers are becoming new concrete materials to use alongside cement, which are formed due to reaction between alumino-silicates and oxides with alkaline media. Silicates obtained from natural minerals or industrial wastes are used for geopolymer synthesis. Geopolymers have recently received wide attention because of their advantages over other cementitious material like Portland cement. Some of the advantages are high compressive strength, low environmental impact, chemical and fire resistance and thermal stability. In this study, geopolymers were prepared by using inorganic materials such as kaolinite and calcite. The experiments were carried out by varying the concentration of NaOH as 5, 10, 15 and 20 M, and at cure temperature of 22, 45 and 65 °C. Compressive strengths for each mixes at each cure temperature were measured. Results of the analyses indicated that the compressive strength of geopolymers did not increase steadily with increasing concentration of NaOH, but did increase steadily with increasing cure temperature. We examined the effect Na2SiO3/NaOH weight ratio on the properties of the geopolymers, too. It was seen that Na2SiO3/NaOH weight ratio was also important to prepare geopolymers that can be applied to construction industry.

Keywords: geopolymers, compressive strength, kaolinite, calcite

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Authors: S. M. Hashemy Shahdany

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Equitable water delivery becomes one of the main concerns for water authorities in arid regions. Due to water scarcity, providing reliable amount of water is not possible for most of the irrigation districts in arid regions. In this paper, water level difference control is applied to keep the water level errors equal in adjacent reaches. Distant downstream decentralized configurations of the control method are designed and tested under a realistic scenario shows canal operation under water shortage. The simulation results show that the difference controllers share the water level error among all of the users in a fair way. Therefore, water deficit has a similar influence on downstream as well as upstream and water offtakes.

Keywords: equitable water distribution, precise agriculture, sustainable agriculture, water shortage

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Authors: Gopinath Rathod, Vinod Puranik

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Sustainability is regarded as a key concept for survival in the competitive scenario. Industrial risk and diversification of risk type’s increases with industrial developments. In the context of sustainable manufacturing, the evaluation of risk is difficult because of the incomplete information and multiple indicators. Fuzzy Multiple Attribute Decision Method (FMADM) has been used with a three level hierarchical decision making model to evaluate aggregate risk for sustainable manufacturing projects. A case study has been presented to reflect the risk characteristics in sustainable manufacturing projects.

Keywords: sustainable manufacturing, decision making, aggregate risk, fuzzy logic, fuzzy multiple attribute decision method

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Authors: Mohammed Taleb

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Morocco is characterized by an important genetic diversity represented by a rich and varied flora with 5211 species and subspecies and many natural ecosystems. Biodiversity and natural ecosystems provide the local population with highly diversified services represented by aromatic and medicinal plants, forage plants, melliferous plants, firewood, lumber, mushrooms, etc. Ecosystem services are currently subject to many pressures: overgrazing and deforestation, climate change, including increased drought, urbanization and forest fire. Conscious of the risks that weigh on biodiversity and ecosystem services, Morocco had made an important effort to reverse the tendencies by developing a consistent biodiversity conservation strategy focused on in-situ and ex-situ conservation. This presentation will be focused on the current state of biodiversity and ecosystem services and their role for the human development and their decline under the action of different pressures (grazing, timber harvest, harvesting of medicinal and aromatic plants, charcoal making...) while emphasizing efforts constructed by Morocco to conserve and sustainably manage biodiversity and ecosystem services.

Keywords: morocco, biodiversity, ecosystem services, local population

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Authors: Donghun Jeong, Somyoung Shin, Yeoil Yun

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A large-scale traffic accident refers to an accident in which more than three people die or more than thirty people are dead or injured. In order to prevent a large-scale traffic accident from causing a big loss of lives or establish effective improvement measures, it is important to analyze accident situations in-depth and understand the effects of major accident variables on an accident. This study aims to analyze the contribution of individual accident variables to accident results, based on the accurate reconstruction of traffic accidents using PC-Crash’s Multi-Body, which is an accident reconstruction program, and simulation of each scenario. Multi-Body system of PC-Crash accident reconstruction program is used for multi-body accident reconstruction that shows motions in diverse directions that were not approached previously. MB System is to design and reproduce a form of body, which shows realistic motions, using several bodies. Targeting the 'freight truck cargo drop accident around the Changwon Tunnel' that happened in November 2017, this study conducted a simulation of the freight truck cargo drop accident and analyzed the contribution of individual accident majors. Then on the basis of the driving speed, cargo load, and stacking method, six scenarios were devised. The simulation analysis result displayed that the freight car was driven at a speed of 118km/h(speed limit: 70km/h) right before the accident, carried 196 oil containers with a weight of 7,880kg (maximum load: 4,600kg) and was not fully equipped with anchoring equipment that could prevent a drop of cargo. The vehicle speed, cargo load, and cargo anchoring equipment were major accident variables, and the accident contribution analysis results of individual variables are as follows. When the freight car only obeyed the speed limit, the scattering distance of oil containers decreased by 15%, and the number of dropped oil containers decreased by 39%. When the freight car only obeyed the cargo load, the scattering distance of oil containers decreased by 5%, and the number of dropped oil containers decreased by 34%. When the freight car obeyed both the speed limit and cargo load, the scattering distance of oil containers fell by 38%, and the number of dropped oil containers fell by 64%. The analysis result of each scenario revealed that the overspeed and excessive cargo load of the freight car contributed to the dispersion of accident damage; in the case of a truck, which did not allow a fall of cargo, there was a different type of accident when driven too fast and carrying excessive cargo load, and when the freight car obeyed the speed limit and cargo load, there was the lowest possibility of causing an accident.

Keywords: accident reconstruction, large-scale traffic accident, PC-Crash, MB system

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Authors: Abirham Simeneh Ayalew, Seada Hussen Adem, Frie Ayalew Yimam

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Battery energy storage has a great role on storing energy harnessed from different alternative resources and greatly benefit the power sector by supply energy back to the system during outage and regular operation in power sectors. Most of the study shows that there is an exponential increase in the quantity of lithium - ion battery energy storage system due to their power density, economical aspects and its performance. But this lithium ion battery failures resulted in fire and explosion due to its having flammable electrolytes (chemicals) which can create those hazards. Hazards happen in these energy storage system lead to minimize battery life spans or efficiency. Identifying the real cause of these hazards and its mitigation techniques can be the solution to improve the efficiency of battery technologies and the electrode materials should have high electrical conductivity, large surface area, stable structure and low resistance. This paper asses the real causes of chemical hazards, its impact on efficiency, proposed solution for mitigating those hazards associated with efficiency improvement and summery of researchers new finding related to the field.

Keywords: battery energy storage, battery energy storage efficiency, chemical hazards, lithium ion battery

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Authors: Stepan Kuchar, Martin Golasowski, Radim Vavrik, Michal Podhoranyi, Boris Sir, Jan Martinovic

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The main goal of this article is to describe the online flood monitoring and prediction system Floreon+ primarily developed for the Moravian-Silesian region in the Czech Republic and the basic process it uses for running automatic rainfall-runoff and hydrodynamic simulations along with their calibration and uncertainty modeling. It takes a long time to execute such process sequentially, which is not acceptable in the online scenario, so the use of high-performance computing environment is proposed for all parts of the process to shorten their duration. Finally, a case study on the Ostravice river catchment is presented that shows actual durations and their gain from the parallel implementation.

Keywords: flood prediction process, high performance computing, online flood prediction system, parallelization

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Authors: Nafisa Mahbub, Hajo Ribberink

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Electrification of long-haul trucks has been in discussion as a potential strategy to decarbonization. These trucks will require large batteries because of their weight and long daily driving distances. Around 245 million battery electric vehicles are predicted to be on the road by the year 2035. This huge increase in the number of electric vehicles (EVs) will require intensive mining operations for metals and other materials to manufacture millions of batteries for the EVs. These operations will add significant environmental burdens and there is a significant risk that the mining sector will not be able to meet the demand for battery materials, leading to higher prices. Since the battery is the most expensive component in the EVs, technologies that can enable electrification with smaller batteries sizes have substantial potential to reduce the material usage and associated environmental and cost burdens. One of these technologies is an ‘electrified road’ (eroad), where vehicles receive power while they are driving, for instance through an overhead catenary (OC) wire (like trolleybuses and electric trains), through wireless (inductive) chargers embedded in the road, or by connecting to an electrified rail in or on the road surface. This study assessed the total material use and associated life cycle GHG emissions of two types of eroads (overhead catenary and in-road wireless charging) for long-haul trucks in Canada and compared them to electrification using stationary plug-in fast charging. As different electrification technologies require different amounts of materials for charging infrastructure and for the truck batteries, the study included the contributions of both for the total material use. The study developed a bottom-up approach model comparing the three different charging scenarios – plug in fast chargers, overhead catenary and in-road wireless charging. The investigated materials for charging technology and batteries were copper (Cu), steel (Fe), aluminium (Al), and lithium (Li). For the plug-in fast charging technology, different charging scenarios ranging from overnight charging (350 kW) to megawatt (MW) charging (2 MW) were investigated. A 500 km of highway (1 lane of in-road charging per direction) was considered to estimate the material use for the overhead catenary and inductive charging technologies. The study considered trucks needing an 800 kWh battery under the plug-in charger scenario but only a 200 kWh battery for the OC and inductive charging scenarios. Results showed that overall the inductive charging scenario has the lowest material use followed by OC and plug-in charger scenarios respectively. The materials use for the OC and plug-in charger scenarios were 50-70% higher than for the inductive charging scenarios for the overall system including the charging infrastructure and battery. The life cycle GHG emissions from the construction and installation of the charging technology material were also investigated.

Keywords: charging technology, eroad, GHG emissions, material use, overhead catenary, plug in charger

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Authors: J. I. Santos, A. E. Cesarin, C. A. R. Sales, M. B. B. Triano, P. F. R. B. Martins, A. F. Braga, N. J. Neto, A., A. M. Barroso, P. L. C. A. Alves, C. A. M. Huaman

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Climate change projections based on the emission of greenhouse effect gases suggest an increase in the concentration of atmospheric carbon dioxide, in up to 750 ppm. In this scenario, we have significant changes in plant development, and consequently, in agricultural systems. This study aims to evaluate the interaction between culture (Glycine max) and weed (Amaranthus viridis and Euphorbia heterophylla) in two conditions of CO₂, 400 and 800 ppm. The results showed that the coexistence of culture with both weed species resulted in a mutual loss, with decrease in dry mass productivity of culture + weeds, in both conditions of CO₂. However, when the culture is grown in association with E. heterophylla, total dry mass of culture + weed was smaller at 800 ppm. Soybean was more aggressive in comparison to the A. viridis in both the concentrations of CO₂, but not in relation to the E. heterophylla.

Keywords: plants interaction, increase of [CO₂], plants of metabolismo C3, glycine max

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Authors: Lorenzo Petrucci

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This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

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Authors: Loris Franchi, Daniele Calvi, Sabrina Corpino

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This paper presents a design methodology in which stakeholders are assisted with the exploration of a so-called negotiation space, aiming to the maximization of both group social welfare and single stakeholder’s perceived utility. The outcome results in less design iterations needed for design convergence while obtaining a higher solution effectiveness. During the early stage of a space project, not only the knowledge about the system but also the decision outcomes often are unknown. The scenario is exacerbated by the fact that decisions taken in this stage imply delayed costs associated with them. Hence, it is necessary to have a clear definition of the problem under analysis, especially in the initial definition. This can be obtained thanks to a robust generation and exploration of design alternatives. This process must consider that design usually involves various individuals, who take decisions affecting one another. An effective coordination among these decision-makers is critical. Finding mutual agreement solution will reduce the iterations involved in the design process. To handle this scenario, the paper proposes a design methodology which, aims to speed-up the process of pushing the mission’s concept maturity level. This push up is obtained thanks to a guided negotiation space exploration, which involves autonomously exploration and optimization of trade opportunities among stakeholders via Artificial Intelligence algorithms. The negotiation space is generated via a multidisciplinary collaborative optimization method, infused by game theory and multi-attribute utility theory. In particular, game theory is able to model the negotiation process to reach the equilibria among stakeholder needs. Because of the huge dimension of the negotiation space, a collaborative optimization framework with evolutionary algorithm has been integrated in order to guide the game process to efficiently and rapidly searching for the Pareto equilibria among stakeholders. At last, the concept of utility constituted the mechanism to bridge the language barrier between experts of different backgrounds and differing needs, using the elicited and modeled needs to evaluate a multitude of alternatives. To highlight the benefits of the proposed methodology, the paper presents the design of a CubeSat mission for the observation of lunar radiation environment. The derived solution results able to balance all stakeholders needs and guaranteeing the effectiveness of the selection mission concept thanks to its robustness in valuable changeability. The benefits provided by the proposed design methodology are highlighted, and further development proposed.

Keywords: concurrent engineering, artificial intelligence, negotiation in engineering design, multidisciplinary optimization

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Authors: Linda D. F. Bambara, Marie Sawadogo

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Jatropha curcas (jatropha) is the plant that has been the most studied for biofuel production in West Africa. There exist however other plants such as Balanites aegyptiaca (balanites) that have been targeted as a potential feedstock for biofuel production. This biomass could be an alternative feedstock for the production of straight vegetable oil (SVO) at costs lower than jatropha-based SVO production costs. This study aims firstly to determine, through an MILP model, the optimal organization that minimizes the costs of the oilseeds supply of two biomass conversion units (BCU) exploiting respectively jatropha seeds and the balanitès seeds. Secondly, the study aims to carry out a comparative study of these costs obtained for each BCU. The model was then implemented on two theoretical cases studies built on the basis of the common practices in Burkina Faso and two scenarios were carried out for each case study. In Scenario 1, 3 pre-processing locations ("at the harvesting area", "at the gathering points", "at the BCU") are possible. In scenario 2, only one location ("at the BCU") is possible. For each biomass, the system studied is the upstream supply chain (harvesting, transport and pre-processing (drying, dehulling, depulping)), including cultivation (for jatropha). The model optimizes the area of land to be exploited based on the productivity of the studied plants and material losses that may occur during the harvesting and the supply of the BCU. It then defines the configuration of the logistics network allowing an optimal supply of the BCU taking into account the most common means of transport in West African rural areas. For the two scenarios, the results of the implementation showed that the total area exploited for balanites (1807 ha) is 4.7 times greater than the total area exploited for Jatropha (381 ha). In both case studies, the location of pre-processing “at the harvesting area” was always chosen for scenario1. As the balanites trees were not planted and because the first harvest of the jatropha seeds took place 4 years after planting, the cost price of the seeds at the BCU without the pre-processing costs was about 430 XOF/kg. This cost is 3 times higher than the balanites's one, which is 140 XOF/kg. After the first year of harvest, i.e. 5 years after planting, and assuming that the yield remains constant, the same cost price is about 200 XOF/kg for Jatropha. This cost is still 1.4 times greater than the balanites's one. The transport cost of the balanites seeds is about 120 XOF/kg. This cost is similar for the jatropha seeds. However, when the pre-processing is located at the BCU, i.e. for scenario2, the transport costs of the balanites seeds is 1200 XOF/kg. These costs are 6 times greater than the transport costs of jatropha which is 200 XOF/kg. These results show that the cost price of the balanites seeds at the BCU can be competitive compared to the jatropha's one if the pre-processing is located at the harvesting area.

Keywords: Balanites aegyptiaca, biomass conversion, Jatropha curcas, optimization, post-harvest operations

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Authors: Iqbal Felani

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A Coal-Fired Power Plant has some integrated facilities to handle coal from three separated coal yards to eight units power plant’s bunker. But nowadays the facilities are not reliable enough for supporting the system. Management planned to invest some facilities to increase the reliability. They also had a plan to make single spesification of coal used all of the units, called Single Quality Coal (SQC). This simulation would compare before and after improvement with two scenarios i.e First In First Out (FIFO) and Last In First Out (LIFO). Some parameters like stay time, reorder point and safety stock is determined by the simulation. Discrete event simulation based software, Flexsim 5.0, is used to help the simulation. Based on the simulation, Single Quality Coal with FIFO scenario has the shortest staytime with 8.38 days.

Keywords: Coal Yard Management, Discrete event simulation First In First Out, Last In First Out.

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Authors: Alok Saini, Rajkumar Ghosh

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Water is nature's important resource for survival of all living things, but freshwater scarcity exists in some parts of world. This study has predicted that Gomti Nagar area (49.2 sq. km.) will harvest about 91110 ML of rainwater till 2051 (assuming constant and present annual rainfall). But 17.71 ML of rainwater was harvested from only 53 buildings in Gomti Nagar area in the year 2021. Water level will be increased (rise) by 13 cm in Gomti Nagar from such groundwater recharge. The total annual groundwater abstraction from Gomti Nagar area was 35332 ML (in 2021). Due to hydrogeological constraints and lower annual rainfall, groundwater recharge is less than groundwater abstraction. The recent scenario is only 0.07% of rainwater recharges by RTRWHs in Gomti Nagar. But if RTRWHs would be installed in all buildings then 12.39% of rainwater could recharge groundwater table in Gomti Nagar area. But if RTRWHs would be installed in all buildings then 12.39% of rainwater could recharge groundwater table in Gomti Nagar area. Gomti Nagar is situated in 'Zone–A' (water distribution area) and groundwater is the primary source of freshwater supply. Current scenario indicates only 0.07% of rainwater recharges by RTRWHs in Gomti Nagar. In Gomti Nagar, the difference between groundwater abstraction and recharge will be 735570 ML in 30 yrs. Statistically, all buildings at Gomti Nagar (new and renovated) could harvest 3037 ML of rainwater through RTRWHs annually. The most recent monsoonal recharge in Gomti Nagar was 10813 ML/yr. Harvested rainwater collected from RTRWHs can be used for rooftop irrigation, and residential kitchen and gardens (home grown fruit and vegetables). According to bylaws, RTRWH installations are required in both newly constructed and existing buildings plot areas of 300 sq. m or above. Harvested rainwater is of higher quality than contaminated groundwater. Harvested rainwater from RTRWHs can be considered water self-sufficient. Rooftop Rainwater Harvesting Systems (RTRWHs) are least expensive, eco-friendly, most sustainable, and alternative water resource for artificial recharge. This study also predicts about 3.9 m of water level rise in Gomti Nagar area till 2051, only when all buildings will install RTRWHs and harvest for groundwater recharging. As a result, this current study responds to an impact assessment study of RTRWHs implementation for the water scarcity problem in the Gomti Nagar area (1.36 sq.km.). This study suggests that common storage tanks (recharge wells) should be built for a group of at least ten (10) households and optimal amount of harvested rainwater will be stored annually. Artificial recharge from alternative water sources will be required to improve the declining water level trend and balance the groundwater table in this area. This over-exploitation of groundwater may lead to land subsidence, and development of vertical cracks.

Keywords: aquifer, aquitard, artificial recharge, bylaws, groundwater, monsoon, rainfall, rooftop rainwater harvesting system, RTRWHs water table, water level

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Authors: Dana Alghool, Tarek ElMekkawy, Mohamed Haouari, Adel Elomari

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District cooling systems have captured the attentions of many researchers recently due to the enormous benefits offered by such system in comparison with traditional cooling technologies. It is considered a major component of urban cities due to the significant reduction of energy consumption. This paper aims to find the optimal design and operation of district cooling systems by developing a mixed integer linear programming model to minimize the annual total system cost and satisfy the end-user cooling demand. The proposed model is experimented with different cooling demand scenarios. The results of the very high cooling demand scenario are only presented in this paper. A sensitivity analysis on different parameters of the model was performed.

Keywords: Annual Cooling Demand, Compression Chiller, Mathematical Modeling, District Cooling Systems, Optimization

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Authors: Alexander Vandesompele, Joni Dambre

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The diversity in dendritic arborization, as first illustrated by Santiago Ramon y Cajal, has always suggested a role for dendrites in the functionality of neurons. In the past decades, thanks to new recording techniques and optical stimulation methods, it has become clear that dendrites are not merely passive electrical components. They are observed to integrate inputs in a non-linear fashion and actively participate in computations. Regardless, in simulations of neural networks dendritic structure and functionality are often overlooked. Especially in a machine learning context, when designing artificial neural networks, point neuron models such as the leaky-integrate-and-fire (LIF) model are dominant. These models mimic the integration of inputs at the neuron soma, and ignore the existence of dendrites. In this work, the LIF point neuron model is extended with a simple form of dendritic computation. This gives the LIF neuron increased capacity to discriminate spatiotemporal input sequences, a dendritic functionality as observed in another study. Simulations of the spiking neurons are performed using the Bindsnet framework. In the common LIF model, incoming synapses are independent. Here, we introduce a dependency between incoming synapses such that the post-synaptic impact of a spike is not only determined by the weight of the synapse, but also by the activity of other synapses. This is a form of short term plasticity where synapses are potentiated or depressed by the preceding activity of neighbouring synapses. This is a straightforward way to prevent inputs from simply summing linearly at the soma. To implement this, each pair of synapses on a neuron is assigned a variable,representing the synaptic relation. This variable determines the magnitude ofthe short term plasticity. These variables can be chosen randomly or, more interestingly, can be learned using a form of Hebbian learning. We use Spike-Time-Dependent-Plasticity (STDP), commonly used to learn synaptic strength magnitudes. If all neurons in a layer receive the same input, they tend to learn the same through STDP. Adding inhibitory connections between the neurons creates a winner-take-all (WTA) network. This causes the different neurons to learn different input sequences. To illustrate the impact of the proposed dendritic mechanism, even without learning, we attach five input neurons to two output neurons. One output neuron isa regular LIF neuron, the other output neuron is a LIF neuron with dendritic relationships. Then, the five input neurons are allowed to fire in a particular order. The membrane potentials are reset and subsequently the five input neurons are fired in the reversed order. As the regular LIF neuron linearly integrates its inputs at the soma, the membrane potential response to both sequences is similar in magnitude. In the other output neuron, due to the dendritic mechanism, the membrane potential response is different for both sequences. Hence, the dendritic mechanism improves the neuron’s capacity for discriminating spa-tiotemporal sequences. Dendritic computations improve LIF neurons even if the relationships between synapses are established randomly. Ideally however, a learning rule is used to improve the dendritic relationships based on input data. It is possible to learn synaptic strength with STDP, to make a neuron more sensitive to its input. Similarly, it is possible to learn dendritic relationships with STDP, to make the neuron more sensitive to spatiotemporal input sequences. Feeding structured data to a WTA network with dendritic computation leads to a significantly higher number of discriminated input patterns. Without the dendritic computation, output neurons are less specific and may, for instance, be activated by a sequence in reverse order.

Keywords: dendritic computation, spiking neural networks, point neuron model

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Authors: Azeez Shaik, Yagnik Kalariya, Amit Salvi

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High-performance requirements and emission norms were forcing the automobile industry to opt for lightweight materials which improve the fuel efficiency and absorb energy during crash applications. In such scenario, the woven fabric composites are providing better energy absorption compared to metals. Woven fabric composites have a repetitive unit cell (RUC) and the mechanical properties of these materials are highly dependent on RUC. This work investigates the importance of detailed modelling of the RUC, the size effects associated and the mitigation techniques to avoid them using Finite element analysis approach.

Keywords: repetitive unit cell, representative volume element, size effects, cohesive zone, finite element analysis

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Authors: Mamatha M. N.

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Traffic problems, congested traffic, and flow management were recognized as major problems mostly in all the areas, which have caused a problem for the ambulance which carries the emergency patient. The proposed paper aims in the development of ambulance which reaches the nearby hospital faster even in heavy traffic scenario. This process is activated by implementing hardware in an ambulance as well as in traffic post thus allowing a smooth flow to the ambulance to reach the hospital in time. 1) The design of the vehicle to have a communication between ambulance and traffic post. 2)Electronic Health Record with Data-acquisition system 3)Telemetry of acquired biological parameters to the nearest hospital. Thus interfacing all these three different modules and integrating them on the ambulance could reach the hospital earlier than the present ambulance. The system is accurate and efficient of 99.8%.

Keywords: bio-telemetry, data acquisition, patient database, automatic traffic control

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Authors: Hamid Ahmadi, Neda Azari-Dodaran

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A total of 270 nonlinear steady-state finite element (FE) analyses were performed on 54 FE models of two-planar circular hollow section (CHS) KK-joints subjected to axial loading at five different temperatures (20 ºC, 200 ºC, 400 ºC, 550 ºC, and 700 ºC). The primary goal was to investigate the effects of temperature and geometrical characteristics on the ultimate strength, modes of failure, and initial stiffness of the KK-joints. Results indicated that on an average basis, the ultimate load of a two-planar tubular KK-joint at 200 ºC, 400 ºC, 550 ºC, and 700 ºC is 90%, 75%, 45%, and 16% of the joint’s ultimate load at ambient temperature, respectively. Outcomes of the parametric study showed that replacing the yield stress at ambient temperature with the corresponding value at elevated temperature to apply the EN 1993-1-8 equations for the calculation of the joint’s ultimate load at elevated temperatures may lead to highly unconservative results that might endanger the safety of the structure. Results of the parametric study were then used to develop a set of design formulas, through nonlinear regression analyses, to calculate the ultimate load of two-planar tubular KK-joints subjected to axial loading at elevated temperatures.

Keywords: ultimate load, two-planar tubular KK-joint, axial loading, elevated temperature, parametric equation

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Authors: I. Inuaeyen, L. Phil, O. Eni

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Fossil fuels have been the main source of global energy for many decades, accounting for about 80% of global energy need. This is beginning to change however with increasing concern about greenhouse gas emissions which comes mostly from fossil fuel combustion. Greenhouse gases such as carbon dioxide are responsible for stimulating climate change. As a result, there has been shift towards more clean and renewable energy sources of energy as a strategy for stemming greenhouse gas emission into the atmosphere. The production of bio-products such as bio-fuel, bio-electricity, bio-chemicals, and bio-heat etc. using biomass materials in accordance with the bio-refinery concept holds a great potential for reducing high dependence on fossil fuel and their resources. The bio-refinery concept promotes efficient utilisation of biomass material for the simultaneous production of a variety of products in order to minimize or eliminate waste materials. This will ultimately reduce greenhouse gas emissions into the environment. In Nigeria, cassava solid waste from cassava processing facilities has been identified as a vital feedstock for bio-refinery process. Cassava is generally a staple food in Nigeria and one of the most widely cultivated foodstuff by farmers across Nigeria. As a result, there is an abundant supply of cassava waste in Nigeria. In this study, the aim is to explore opportunities for converting cassava waste to a range of bio-products such as butanol, ethanol, electricity, heat, methanol, furfural etc. using a combination of biochemical, thermochemical and chemical conversion routes. . The best process scenario will be identified through the evaluation of economic analysis, energy efficiency, life cycle analysis and social impact. The study will be carried out by developing a model representing different process options for cassava waste conversion to useful products. The model will be developed using Aspen Plus process simulation software. Process economic analysis will be done using Aspen Icarus software. So far, comprehensive survey of literature has been conducted. This includes studies on conversion of cassava solid waste to a variety of bio-products using different conversion techniques, cassava waste production in Nigeria, modelling and simulation of waste conversion to useful products among others. Also, statistical distribution of cassava solid waste production in Nigeria has been established and key literatures with useful parameters for developing different cassava waste conversion process has been identified. In the future work, detailed modelling of the different process scenarios will be carried out and the models validated using data from literature and demonstration plants. A techno-economic comparison of the various process scenarios will be carried out to identify the best scenario using process economics, life cycle analysis, energy efficiency and social impact as the performance indexes.

Keywords: bio-refinery, cassava waste, energy, process modelling

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Authors: Camila Lima, Murilo Andrade Valle, Patrícia Teixeira Leite Asano

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The growth in demand for electricity, caused by human development, depletion and environmental impacts caused by traditional sources of electricity generation have made new energy sources are increasingly encouraged and necessary for companies in the electricity sector. Based on this scenario, this paper assesses the negative environmental impacts associated with thermoelectric power plants in Brazil, pointing out the importance of using renewable energy sources, reducing environmental aggression. This article points out the existence of an energy alternative, wind energy, of the municipalities of São Paulo, represented by georeferenced maps with the help of GIS, using as a premise the indicators of sustainability and multicriteria analysis in the decision-making process.

Keywords: GIS (geographic information systems), multicriteria analysis, sustainability, wind energy

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Authors: Martin Pellon Consunji

Abstract:

Due to the rise in popularity of Bitcoin and other crypto assets as a store of wealth and speculative investment, there is an ever-growing demand for automated trading tools, such as bots, in order to gain an advantage over the market. Traditionally, trading in the stock market was done by professionals with years of training who understood patterns and exploited market opportunities in order to gain a profit. However, nowadays a larger portion of market participants are at minimum aided by market-data processing bots, which can generally generate more stable signals than the average human trader. The rise in trading bot usage can be accredited to the inherent advantages that bots have over humans in terms of processing large amounts of data, lack of emotions of fear or greed, and predicting market prices using past data and artificial intelligence, hence a growing number of approaches have been brought forward to tackle this task. However, the general limitation of these approaches can still be broken down to the fact that limited historical data doesn’t always determine the future, and that a lot of market participants are still human emotion-driven traders. Moreover, developing markets such as those of the cryptocurrency space have even less historical data to interpret than most other well-established markets. Due to this, some human traders have gone back to the tried-and-tested traditional technical analysis tools for exploiting market patterns and simplifying the broader spectrum of data that is involved in making market predictions. This paper proposes a method which uses neuro evolution techniques on both sentimental data and, the more traditionally human-consumed, technical analysis data in order to gain a more accurate forecast of future market behavior and account for the way both automated bots and human traders affect the market prices of Bitcoin and other cryptocurrencies. This study’s approach uses evolutionary algorithms to automatically develop increasingly improved populations of bots which, by using the latest inflows of market analysis and sentimental data, evolve to efficiently predict future market price movements. The effectiveness of the approach is validated by testing the system in a simulated historical trading scenario, a real Bitcoin market live trading scenario, and testing its robustness in other cryptocurrency and stock market scenarios. Experimental results during a 30-day period show that this method outperformed the buy and hold strategy by over 260% in terms of net profits, even when taking into consideration standard trading fees.

Keywords: neuro-evolution, Bitcoin, trading bots, artificial neural networks, technical analysis, evolutionary algorithms

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Authors: R. Conde

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The Brazilian economic projections and social indicators show a future of crisis for the country. Solutions to avoid this crisis scenario are necessary. Several developed countries implement initiatives linked to sustainability, mainly related to the circular economy, to solve their crises quickly - green recovery. This article aims to assess social gains if Brazil followed the same recovery strategy. Furthermore, with the use of data presented and recognized in the international academic society, the number of jobs that can be created, if Brazil took the first steps towards a more circular economy, was found. Moreover, in addition to the gross value in the number of jobs created, this article also detailed the number of these jobs by type of activity (collection, processing, and manufacturing) and by type of material.

Keywords: circular economy, green recovery, job creation, social gains

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Authors: M. Prasanth, V. Nithin, R. Keerthana, S.Kalyani

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In the current scenario, the steering system in automobiles is such that the motion from the steering wheel is transferred to driving wheel by mechanical linkages. In this paper, we propose a method to design a steering mechanism using servomotors to turn the wheels instead of linkages. In this method, a steering angle sensor senses the turn angle of the steering wheel and its output is processed by an electronical control module. Then the ECM compares the angle value to that of a standard value from a look-up database. Then it gives the appropriate input power and the turning duration to the motors. Correspondingly, the motors turn the wheels by means of bevel gears welded to both the motor output shafts and the wheel hubs. Thus, the wheels are turned without the complicated framework of linkages, reducing the driver’s effort and fatigue considerably.

Keywords: electronic control unit, linkage-less steering, servomotors, E-Mo Steer

Procedia PDF Downloads 245

Authors: V. V. Singh, Yusuf Ibrahim Gwanda, Rajesh Prasad

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In this paper, we focus on the reliability and performance analysis of Computer Centre (CC) at Yobe State University, Damaturu, Nigeria. The CC consists of three servers: one database mail server, one redundant and one for sharing with the client computers in the CC (called as a local server). Observing the different possibilities of the functioning of the CC, the analysis has been done to evaluate the various popular measures of reliability such as availability, reliability, mean time to failure (MTTF), profit analysis due to the operation of the system. The system can ultimately fail due to the failure of router, redundant server before repairing the mail server and switch failure. The system can also partially fail when a local server fails. The failed devices have restored according to Least Recently Used (LRU) techniques. The system can also fail entirely due to a cooling failure of the server, electricity failure or some natural calamity like earthquake, fire tsunami, etc. All the failure rates are assumed to be constant and follow exponential time distribution, while the repair follows two types of distributions: i.e. general and Gumbel-Hougaard family copula distribution.

Keywords: reliability, availability Gumbel-Hougaard family copula, MTTF, internet data centre

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Authors: Johannes Gantner, Michael Held, Rafael Horn, Matthias Fischer

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At the United Nations Climate Change Conference 2015 a global agreement on the reduction of climate change was achieved stating CO₂ reduction targets for all countries. For instance, the EU targets a reduction of 40 percent in emissions by 2030 compared to 1990. In order to achieve this ambitious goal, the environmental performance of the different European electricity grid mixes is crucial. First, the electricity directly needed for everyone’s daily life (e.g. heating, plug load, mobility) and therefore a reduction of the environmental impacts of the electricity grid mix reduces the overall environmental impacts of a country. Secondly, the manufacturing of every product depends on electricity. Thereby a reduction of the environmental impacts of the electricity mix results in a further decrease of environmental impacts of every product. As a result, the implementation of the two-degree goal highly depends on the decarbonization of the European electricity mixes. Currently the production of electricity in the EU27 is based on fossil fuels and therefore bears a high GWP impact per kWh. Due to the importance of the environmental impacts of the electricity mix, not only today but also in future, within the European research projects, CommONEnergy and Senskin, time-dynamic Life Cycle Assessment models for all EU27 countries were set up. As a methodology, a combination of scenario modeling and life cycle assessment according to ISO14040 and ISO14044 was conducted. Based on EU27 trends regarding energy, transport, and buildings, the different national electricity mixes were investigated taking into account future changes such as amount of electricity generated in the country, change in electricity carriers, COP of the power plants and distribution losses, imports and exports. As results, time-dynamic environmental profiles for the electricity mixes of each country and for Europe overall were set up. Thereby for each European country, the decarbonization strategies of the electricity mix are critically investigated in order to identify decisions, that can lead to negative environmental effects, for instance on the reduction of the global warming of the electricity mix. For example, the withdrawal of the nuclear energy program in Germany and at the same time compensation of the missing energy by non-renewable energy carriers like lignite and natural gas is resulting in an increase in global warming potential of electricity grid mix. Just after two years this increase countervailed by the higher share of renewable energy carriers such as wind power and photovoltaic. Finally, as an outlook a first qualitative picture is provided, illustrating from environmental perspective, which country has the highest potential for low-carbon electricity production and therefore how investments in a connected European electricity grid could decrease the environmental impacts of the electricity mix in Europe.

Keywords: electricity grid mixes, EU27 countries, environmental impacts, future trends, life cycle assessment, scenario analysis

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Authors: Meenakshi Pappu

Abstract:

The term, 'urban ecology' has often been misconstrued by the educational practitioners as well as the researchers as a study under a single discipline i.e., the environmental sciences. One who has done research extensively in this study would always argue that urban ecology is not a study under a single discipline, but it is a study across disciplines such as social sciences and other sciences like architecture, engineering, planning, ecology, geography, biology, economics, sociology, anthropology, psychology and health sciences. The aim of this paper is to discuss at length the scope of Urban Ecology as an interdisciplinary study. The paper highlights the nuances of urban ecology as a study across disciplines and the challenges and the implications it holds for future research by conducting a qualitative survey in the particular areas.

Keywords: educational practitioners, interdisciplinary, researchers, urban ecology

Procedia PDF Downloads 400