Search results for: artificial recharge

Authors: Md. Kumruzzaman, Anutosh Das, Md. Mosharraf Hossain

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Historically, rapid urban growth activities are considered one of the main culprits behind urban floods or waterlogging. The increased unplanned urbanization of many areas of Dhaka has resulted in waterlogging, urban floods, and increasing groundwater depth. To determine potential groundwater recharge from precipitation, the study is being conducted to examine the changes in land use/land cover (LULC) and urban runoff extent based on the NRCS-CN from 2005–2021. Four kinds of land use are used to examine the LULC change: built-up, bare land, vegetation, and water body. These categories are used for the years 2005, 2010, 2015, and 2021. The built-up area is growing at a relatively fast rate: 7.43%, 17.4%, and 5.21%, respectively, between the years 2005 and 2010, 2010 and 2015, and 2015 and 2021. As the amount of impervious surface rose in Dhaka city, stormwater discharge increased from 2005 to 2021. In 2005, 2010, 2015, and 2021, heavy stormwater runoff regions made up around 24.873%, 32.616%, 49.118%, and 55.986% of the entire Dhaka city. Stormwater runoff accounted for around 53.738%, 55.092%, 63.472%, and 67.061% of the total rainfall in 2005, 2010, 2015, and 2021, respectively. Between 2005 and 2021, a significant portion of the natural land cover was altered because of the expanding impervious surface, which also harmed the natural drainage system. Due to careless growth, the potential for stormwater runoff and groundwater recharge in Dhaka city worsens every year. Concerning this situation, a sustainable urban drainage system (SUDS) can be the best possible solution for minimizing the stormwater runoff and groundwater recharge problem.

Keywords: LULC, impervious surface, stormwater runoff, groundwater recharge, SUDS

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Authors: Meshandren Naidoo, Amy Gooden

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The concept of personhood extending from the moral status of an artificial intelligence system has been explored – but predominantly from a Western conception of personhood. African personhood, however, is distinctly different from Western personhood in that communitarianism is central rather than individualism. Given the decolonization projects happening in Africa, it’s paramount to consider these views. This research demonstrates that the African notion of personhood may extend for an artificial intelligent system where the pre-conditions are met.

Keywords: artificial intelligence, ethics, law, personhood, policy

Procedia PDF Downloads 87

Authors: Mehrnoosh Abouzari

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Artificial intelligence has covered all areas of human life and has helped or replaced many jobs. One of the areas of application of artificial intelligence in the police is to detect crime, identify the accused or victim and prove the crime. It will play an effective role in implementing preventive justice and creating security in the community, and improving judicial decisions. This will help improve the performance of the police, increase the accuracy of criminal investigations, and play an effective role in preventing crime and high-risk behaviors in society. This article presents and analyzes the capabilities and capacities of artificial intelligence in police and similar examples used worldwide to prove the necessity of using artificial intelligence in the police. The main topics discussed include the performance of artificial intelligence in crime detection and prediction, the risk capacity of criminals and the ability to apply arbitray institutions, and the introduction of artificial intelligence programs implemented worldwide in the field of criminal investigation for police.

Keywords: police, artificial intelligence, forecasting, prevention, software

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Authors: Nejmeddine Ouhichi, Fethi Lachaal, Radhouane Hamdi, Olivier Grunberger

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Located in Cap Bon peninsula (Tunisia), the Lebna dam was built in 1987 to balance local water salt intrusion taking place in the coastal aquifer of Korba. The first intention was to reduce coastal groundwater over-pumping by supplying surface water to a large irrigation system. The unpredicted beneficial effect was recorded with the occurrence of a direct localized recharge to the coastal aquifer by leakage through the geological material of the southern bank of the lake. The hydrological balance of the reservoir dam gave an estimation of the annual leakage volume, but dynamic processes and sound quantification of recharge inputs are still required to understand the localized effect of the recharge in terms of piezometry and quality. Present work focused on simulating the recharge process to confirm the hypothesis, and established a sound quantification of the water supply to the coastal aquifer and extend it to multi-annual effects. A spatial frame of 30km² was used for modeling. Intensive outcrops and geophysical surveys based on 68 electrical resistivity soundings were used to characterize the aquifer 3D geometry and the limit of the Plio-quaternary geological material concerned by the underground flow paths. Permeabilities were determined using 17 pumping tests on wells and piezometers. Six seasonal piezometric surveys on 71 wells around southern reservoir dam banks were performed during the 2019-2021 period. Eight monitoring boreholes of high frequency (15min) piezometric data were used to examine dynamical aspects. Model boundary conditions were specified using the geophysics interpretations coupled with the piezometric maps. The dam-groundwater flow model was performed using Visual MODFLOW software. Firstly, permanent state calibration based on the first piezometric map of February 2019 was established to estimate the permanent flow related to the different reservoir levels. Secondly, piezometric data for the 2019-2021 period were used for transient state calibration and to confirm the robustness of the model. Preliminary results confirmed the temporal link between the reservoir level and the localized recharge flow with a strong threshold effect for levels below 16 m.a.s.l. The good agreement of computed flow through recharge cells on the southern banks and hydrological budget of the reservoir open the path to future simulation scenarios of the dilution plume imposed by the localized recharge. The dam reservoir-groundwater flow-model simulation results approve a potential for storage of up to 17mm/year in existing wells, under gravity-feed conditions during level increases on the reservoir into the three years of operation. The Lebna dam groundwater flow model characterized a spatiotemporal relation between groundwater and surface water.

Keywords: leakage, MODFLOW, saltwater intrusion, surface water-groundwater interaction

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Authors: Naci Büyükkaracığan

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Artificial neural networks (ANN) is an electrical model based on the human brain nervous system and working principle. Artificial neural networks have been the subject of an active field of research that has matured greatly over the past 55 years. ANN now is used in many fields. But, it has been viewed that artificial neural networks give better results in particular optimization and control systems. There are requirements of optimization and control system in many of the area forming the subject of civil engineering applications. In this study, the first artificial intelligence systems are widely used in the solution of civil engineering systems were examined with the basic principles and technical aspects. Finally, the literature reviews for applications in the field of civil engineering were conducted and also artificial intelligence techniques were informed about the study and its results.

Keywords: artificial neural networks, civil engineering, Fuzzy logic, statistics

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Authors: Pandurang Balwant, Ashutosh Mishra, Jyothi V., Abhay Soni, Padmakar C., Rafat Quamar, Ramesh J.

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The sea water intrusion in the coastal aquifers has become one of the major environmental concerns. Although, it is a natural phenomenon but, it can be induced with anthropogenic activities like excessive exploitation of groundwater, seacoast mining, etc. The geological and hydrogeological conditions including groundwater heads and groundwater pumping pattern in the coastal areas also influence the magnitude of seawater intrusion. However, this problem can be remediated by taking some preventive measures like rainwater harvesting and artificial recharge. The present study is an attempt to identify suitable sites for rainwater harvesting in salt intrusion affected area near coastal aquifer of Jafrabad town, Amreli district, Gujrat, India. The physico-chemical water quality results show that out of 25 groundwater samples collected from the study area most of samples were found to contain high concentration of Total Dissolved Solids (TDS) with major fractions of Na and Cl ions. The Cl/HCO3 ratio was also found greater than 1 which indicates the salt water contamination in the study area. The geophysical survey was conducted at nine sites within the study area to explore the extent of contamination of sea water. From the inverted resistivity sections, low resistivity zone (<3 Ohm m) associated with seawater contamination were demarcated in North block pit and south block pit of NCJW mines, Mitiyala village Lotpur and Lunsapur village at the depth of 33 m, 12 m, 40 m, 37 m, 24 m respectively. Geospatial techniques in combination of Analytical Hierarchy Process (AHP) considering hydrogeological factors, geographical features, drainage pattern, water quality and geophysical results for the study area were exploited to identify potential zones for the Rainwater Harvesting. Rainwater harvesting suitability model was developed in ArcGIS 10.1 software and Rainwater harvesting suitability map for the study area was generated. AHP in combination of the weighted overlay analysis is an appropriate method to identify rainwater harvesting potential zones. The suitability map can be further utilized as a guidance map for the development of rainwater harvesting infrastructures in the study area for either artificial groundwater recharge facilities or for direct use of harvested rainwater.

Keywords: analytical hierarchy process, groundwater quality, rainwater harvesting, seawater intrusion

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Authors: Leen Sulaimani, Maryam Hafiz, Naba Ali, Roba Alsharif

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One of Amazon’s most crucial online systems is artificial intelligence. Amazon would not have a worldwide successful online store, an easy and secure way of payment, and other services if it weren’t for artificial intelligence and machine learning. Amazon uses AI to expand its operations and enhance them by upgrading the website daily; having a strong base of artificial intelligence in a worldwide successful business can improve marketing, decision-making, feedback, and more qualities. Aiming to have a rational AI system in one’s business should be the start of any process; that is why Amazon is fortunate that they keep taking care of the base of their business by using modern artificial intelligence, making sure that it is stable, reaching their organizational goals, and will continue to thrive more each and every day. Artificial intelligence is used daily in our current world and is still being amplified more each day to reach consumer satisfaction and company short and long-term goals.

Keywords: artificial intelligence, Amazon, business, customer, decision making

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Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

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Authors: Vahid Bayrami Rad

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Ever since humans developed a collective way of life to the development of urbanization, the concern of security has always been considered one of the most important challenges of life. To protect property, locks have always been a practical tool. With the advancement of technology, the form of locks has changed from mechanical to electric. One of the most widely used fields of using artificial intelligence is its application in the technology of surveillance security systems. Currently, the technologies used in smart anti-theft door handles are one of the most potential fields for using artificial intelligence. Artificial intelligence has the possibility to learn, calculate, interpret and process by analyzing data with the help of algorithms and mathematical models and make smart decisions. We will use Arduino board to process data.

Keywords: arduino board, artificial intelligence, image processing, solenoid lock

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Authors: Ajit Kumar Behera, Saranya P., Sudhir Kumar, Krishnakumar A

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The stable isotope (δ¹⁸ O and δ²H) composition of groundwater of the coastal areas of Periyar and Mahanadi basins falling along East and West coast of India during North-East (NE) monsoon season have been studied. The east and west coast regions are surrounded by the Bay of Bengal and the Arabian Sea respectively, which are considered to be the primary sources for precipitation over India. The major difference between the Bay of Bengal and the Arabian Sea is that a number of large rivers feed the Bay of Bengal, whereas the Arabian Sea is fed by very few small rivers, resulting in enriched stable isotopic composition of the Arabian Sea than the Bay of Bengal. Previous studies have reported depleted ratios of stable isotopes during Northeast monsoon along East and West coasts due to the influence of the Bay of Bengal moisture source. The isotopic composition of groundwater of the Mahanadi delta in the east coast region varies from -6.87 ‰ to -3.40 ‰ for δ¹⁸ O and -45.42 ‰ to -22.43‰ for δ²H. However, the groundwater of the Periyar basin in the west coast has enriched stable isotope value varying from -4.3‰ to -2.5 ‰ for δ¹⁸ O and for δ²H from -23.7 to -6.4 ‰ which is a characteristic of South-West monsoon season. This suggests the groundwater system of the Mahanadi delta and the Periyar basins are influenced by dissimilar moisture sources. The δ¹⁸ O and δ² H relationship (δ²H= 6.513 δ¹⁸ O - 1.39) and d-excess value (< 10) in the east coast region indicates the influence of NE monsoon implying the quick groundwater recharge after precipitation with significant amount of evaporation. In contrast, the δ¹⁸ O and δ²H regression line (δ²H= 8.408 δ¹⁸ O + 11.71) with high d-excess value (>10) in the west coast region implies delayed recharge due to SW monsoon. The observed isotopic enrichment in west coast suggests that NE winter monsoon rainfall does not replenish groundwater quick enough to produce isotopic depletion during the season.

Keywords: Arabian sea, bay of Bengal, groundwater, monsoon, stable isotope

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Authors: Ali Ashraf Hamedi Oghul Beyk

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This research is aimed in order to demonstrate the factors affecting on effectiveness of animal artificial insemination training courses in Zanjan province. The research method is descriptive and correlation. Research tools a questionnaire and research sample are 104 persons who participated in animal artificial insemination training courses. The data resulted from this procedure was analysed by using SPSS software under windows system.independent variables include :individual, sociological, technical, and organizational, dependent variable is: affecting factors on effectiveness of animal artificial insemination training courses the finding of this study indicates that there is a significant correlation(99/0) between individual variables such as motivation and interest and experiment and effectiveness of animal artificial insemination training courses. There is significant correlation (95/0) between sociological variables such as job and education and effectiveness of animal artificial insemination training course. There is significant correlation (99/0) between techn ical variables such as training quality media and instructional materials. Moreover, effectiveness of animal artificial insemination training course there is significant correlation(0/95) between organizational variables such as trainers combination,place conditions.

Keywords: animal artificial insemination, effect, effectiveness, training courses, Zanjan

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Authors: Yu Luan

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The bone-conducted objective occlusion effect (OE) is characterized by a discomforting sensation of fullness experienced in an occluded ear. This phenomenon arises from various external stimuli, such as human speech, chewing, and walking, which generate vibrations transmitted through the body to the ear canal walls. The bone-conducted OE occurs due to the pressure build-up inside the occluded ear caused by sound radiating into the ear canal cavity from its walls. In the hearing aid industry, artificial ears are utilized as a tool for developing hearing aids. However, the currently available commercial artificial ears primarily focus on pure acoustics measurements, neglecting the bone-conducted vibration aspect. This research endeavors to develop an artificial ear specifically designed for bone-conducted occlusion measurements. Finite element analysis (FEA) modeling has been employed to gain insights into the behavior of the artificial ear.

Keywords: artificial ear, bone conducted vibration, occlusion measurement, finite element modeling

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Authors: S. M. Islam, Wasi Uddin, Nazmun Nahar

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Dhaka, the capital of Bangladesh, faces two contrasting problems; excess of water during monsoon season and scarcity of water during dry season. The first problem occurs due to rapid urbanization and mismanagement of rainwater whereas the second problem is related to climate change and increasing urban population. Inadequate drainage system also worsens the overall water management scenario in Dhaka city. Dhaka has a population density of 115,000 people per square miles. This results in a 2.5 billion liter water demand every day, 87% of which is fulfilled by groundwater. Over dependency on groundwater has resulted in more than 200 feet drop in the last 50 years and continues to decline at a rate of 9 feet per year. Considering the gravity of the problem, it is high time that practitioners, academicians and policymakers consider different water management practices and look into their cumulative impacts at different scales. The present study assesses different rainwater management options for North South University of Bangladesh and recommends the most feasible and sustainable rainwater management measure. North South University currently accommodates over 20,000 students, faculty members, and administrative staffs. To fulfill the water demand, there are two deep tube wells, which bring up approximately 150,000 liter of water every hour. The annual water demand is approximately 103 million liters. Dhaka receives approximately 1800 mm of rainfall every year. For the current study, two academic buildings and one administrative building consist of 4924 square meters of rooftop area was selected as catchment area. Both rainwater harvesting and groundwater recharge options were analyzed separately. It was estimated that by rainwater harvesting, annually a total of 7.2 million liters of water can be reused which is approximately 7% of the total annual water usage. In the monsoon, rainwater harvesting fulfills 12.2% of the monthly water demand. The approximate cost of the rainwater harvesting system is estimated to be 940975 bdt (USD 11500). For direct groundwater recharge, a system comprises of one de-siltation tank, two recharge tanks and one siltation tank were designed that requires approximately 532788 bdt (USD 6500). The payback period is approximately 7 years and 4 months for the groundwater recharge system whereas the payback period for rainwater harvesting option is approximately 12 years and 4 months. Based on the cost-benefit analysis, the present study finds the groundwater recharge system to be most suitable for North South University. The present study also demonstrates that if only one institution like North South University can add up a substantial amount of water to the aquifer, bringing other institutions in the network has the potential to create significant cumulative impact on replenishing the declining groundwater level of Dhaka city. As an additional benefit, it also prevents large amount of water being discharged into the storm sewers which results in severe flooding in Dhaka city during monsoon.

Keywords: Dhaka, groundwater, harvesting, rainwater, recharge

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Authors: Benjamin Mauck, Kevin Winter

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The city of Cape Town in South Africa, has shown consistent economic and population growth in the last few decades and that growth is expected to continue to increase into the future. These projected economic and population growth rates are set to place additional pressure on the city’s already strained water supply system. Thus, given Cape Town’s water scarcity, increasing water demands and stressed water supply system, coupled with global awareness around the issues of sustainable development, environmental protection and climate change, alternative water management strategies are required to ensure water is sustainably managed. Water Sensitive Urban Design (WSUD) is an approach to sustainable urban water management that attempts to assign a resource value to all forms of water in the urban context, viz. stormwater, wastewater, potable water and groundwater. WSUD employs a wide range of strategies to improve the sustainable management of urban water such as the water reuse, developing alternative available supply sources, sustainable stormwater management and enhancing the aesthetic and recreational value of urban water. Managed Aquifer Recharge (MAR) is one WSUD strategy which has proven to be a successful reuse strategy in a number of places around the world. MAR is the process where an aquifer is intentionally or artificially recharged, which provides a valuable means of water storage while enhancing the aquifers supply potential. This paper investigates the feasibility of implementing MAR in the sandy, unconfined Cape Flats Aquifer (CFA) in Cape Town. The main objective of the study is to assess if MAR is a viable strategy for stormwater management on the Cape Flats, aiding the prevention or mitigation of the seasonal flooding that occurs on the Cape Flats, while also improving the supply potential of the aquifer. This involves the infiltration of stormwater into the CFA during the wet winter months and in turn, abstracting from the CFA during the dry summer months for fit-for-purpose uses in order to optimise the recharge and storage capacity of the CFA. The fully-integrated MIKE SHE model is used in this study to simulate both surface water and groundwater hydrology. This modelling approach enables the testing of various potential recharge and abstraction scenarios required for implementation of MAR on the Cape Flats. Further MIKE SHE scenario analysis under projected future climate scenarios provides insight into the performance of MAR as a stormwater management strategy under climate change conditions. The scenario analysis using an integrated model such as MIKE SHE is a valuable tool for evaluating the feasibility of the MAR as a stormwater management strategy and its potential to contribute towards improving Cape Town’s water security into the future.

Keywords: managed aquifer recharge, stormwater management, cape flats aquifer, MIKE SHE

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Authors: Antoni Grau, Yolanda Bolea, Alberto Sanfeliu

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Mobile robots can be used in many different applications, including mapping, search, rescue, reconnaissance, hazard detection, and carpet cleaning, exploration, etc. However, they are limited due to their reliance on traditional energy sources such as electricity and oil which cannot always provide a convenient energy source in all situations. In an ever more eco-conscious world, solar energy offers the most environmentally clean option of all energy sources. Electricity presents threats of pollution resulting from its production process, and oil poses a huge threat to the environment. Not only does it pose harm by the toxic emissions (for instance CO2 emissions), it produces the combustion process necessary to produce energy, but there is the ever present risk of oil spillages and damages to ecosystems. Solar energy can help to mitigate carbon emissions by replacing more carbon intensive sources of heat and power. The challenge of this work is to propose the design and the implementation of electric battery recharge stations. Those recharge docks are based on the use of renewable energy such as solar energy (with photovoltaic panels) with the object to reduce the CO2 emissions. In this paper, a comparative study of the CO2 emission productions (from the use of different energy sources: natural gas, gas oil, fuel and solar panels) in the charging process of the Segway PT batteries is carried out. To make the study with solar energy, a photovoltaic panel, and a Buck-Boost DC/DC block has been used. Specifically, the STP005S-12/Db solar panel has been used to carry out our experiments. This module is a 5Wp-photovoltaic (PV) module, configured with 36 monocrystalline cells serially connected. With those elements, a battery recharge station is made to recharge the robot batteries. For the energy storage DC/DC block, a series of ultracapacitors have been used. Due to the variation of the PV panel with the temperature and irradiation, and the non-integer behavior of the ultracapacitors as well as the non-linearities of the whole system, authors have been used a fractional control method to achieve that solar panels supply the maximum allowed power to recharge the robots in the lesser time. Greenhouse gas emissions for production of electricity vary due to regional differences in source fuel. The impact of an energy technology on the climate can be characterised by its carbon emission intensity, a measure of the amount of CO2, or CO2 equivalent emitted by unit of energy generated. In our work, the coal is the fossil energy more hazardous, providing a 53% more of gas emissions than natural gas and a 30% more than fuel. Moreover, it is remarkable that existing fossil fuel technologies produce high carbon emission intensity through the combustion of carbon-rich fuels, whilst renewable technologies such as solar produce little or no emissions during operation, but may incur emissions during manufacture. The solar energy thus can help to mitigate carbon emissions.

Keywords: autonomous robots, CO2 emissions, DC/DC buck-boost, solar energy

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Authors: Young Kwon Yang, Bo Rang Park, Hyo Eun Lee, Tea Won Kim, Eun Ji Choi, Jin Chul Park

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To develop an artificial intelligence based automatic ventilation system, recent research trends were analyzed and analyzed. This research method is as follows. In the field of architecture and window technology, the use of artificial intelligence, the existing study of machine learning model and the theoretical review of the literature were carried out. This paper collected journals such as Journal of Energy and Buildings, Journal of Renewable and Sustainable Energy Reviews, and articles published on Web-sites. The following keywords were searched for articles from 2000 to 2016. We searched for the above keywords mainly in the title, keyword, and abstract. As a result, the global artificial intelligence market is expected to grow at a CAGR of 14.0% from USD127bn in 2015 to USD165bn in 2017. Start-up investments in artificial intelligence increased from the US $ 45 million in 2010 to the US $ 310 million in 2015, and the number of investments increased from 6 to 54. Although AI is making efforts to advance to advanced countries, the level of technology is still in its infant stage. Especially in the field of architecture, artificial intelligence (AI) is very rare. Based on the data of this study, it is expected that the application of artificial intelligence and the application of architectural field will be revitalized through the activation of artificial intelligence in the field of architecture and window.

Keywords: artificial intelligence, window, fine dust, thermal comfort, ventilation system

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Authors: Buruk Kitachew Wossenyeleh

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Groundwater is the largest freshwater reservoir in the world. Like the other reservoirs of the hydrologic cycle, it is a finite resource. This study focused on the groundwater modeling of the Ter Kamerenbos well field to understand the groundwater flow system and the impact of different scenarios. The study area covers 68.9Km2 in the Brussels Capital Region and is situated in two river catchments, i.e., Zenne River and Woluwe Stream. The aquifer system has three layers, but in the modeling, they are considered as one layer due to their hydrogeological properties. The catchment aquifer system is replenished by direct recharge from rainfall. The groundwater recharge of the catchment is determined using the spatially distributed water balance model called WetSpass, and it varies annually from zero to 340mm. This groundwater recharge is used as the top boundary condition for the groundwater modeling of the study area. During the groundwater modeling using Processing MODFLOW, constant head boundary conditions are used in the north and south boundaries of the study area. For the east and west boundaries of the study area, head-dependent flow boundary conditions are used. The groundwater model is calibrated manually and automatically using observed hydraulic heads in 12 observation wells. The model performance evaluation showed that the root means the square error is 1.89m and that the NSE is 0.98. The head contour map of the simulated hydraulic heads indicates the flow direction in the catchment, mainly from the Woluwe to Zenne catchment. The simulated head in the study area varies from 13m to 78m. The higher hydraulic heads are found in the southwest of the study area, which has the forest as a land-use type. This calibrated model was run for the climate change scenario and well operation scenario. Climate change may cause the groundwater recharge to increase by 43% and decrease by 30% in 2100 from current conditions for the high and low climate change scenario, respectively. The groundwater head varies for a high climate change scenario from 13m to 82m, whereas for a low climate change scenario, it varies from 13m to 76m. If doubling of the pumping discharge assumed, the groundwater head varies from 13m to 76.5m. However, if the shutdown of the pumps is assumed, the head varies in the range of 13m to 79m. It is concluded that the groundwater model is done in a satisfactory way with some limitations, and the model output can be used to understand the aquifer system under steady-state conditions. Finally, some recommendations are made for the future use and improvement of the model.

Keywords: Ter Kamerenbos, groundwater modelling, WetSpass, climate change, well operation

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Authors: Paula C. Latorre Arroyo, Andrea C. Latorre Arroyo

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In the present society, children are exposed to and impacted by technology from very early on in various ways. Artificial intelligence (AI), in particular, directly affects them, be it positively or negatively. The concept of artificial intelligence is commonly defined as the technological programming of computers or robotic mechanisms with humanlike capabilities and characteristics. These technologies are often designed as helpful machines or disguised as handy tools that could ultimately steal private information for illicit purposes. Children, being one of the most vulnerable groups due to their lack of experience and knowledge, do not have the ability to recognize or have the malice to distinguish if an apparatus with artificial intelligence is good or bad for them. For this reason, as a society, there must be a sense of responsibility to regulate and monitor different types of uses for artificial intelligence to protect children from potential risks that might arise. This article aims to investigate the many implications that artificial intelligence has in the lives of children, starting from a home setting, within the classroom, and, ultimately, in online spaces. Irrefutably, there are numerous beneficial aspects to the use of artificial intelligence. However, due to its limitless potential and lack of specific and substantial regulations to prevent the illicit use of this technology, safety and privacy concerns surface, specifically regarding the youth. This written work aims to provide an in-depth analysis of how artificial intelligence can both help children and jeopardize their safety. Concluding with resources and data supporting the aforementioned statement.

Keywords: artificial intelligence, children, privacy, rights, safety

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Authors: Salah Ghamari

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In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.

Keywords: artificial neural networks, clustering, self organizing map, wheat variety

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Authors: Ilker Ali Ozkan

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In this study, an artificial neural network model has been developed to estimate chronic kidney failure which is a common disease. The patients’ age, their blood and biochemical values, and 24 input data which consists of various chronic diseases are used for the estimation process. The input data have been subjected to preprocessing because they contain both missing values and nominal values. 147 patient data which was obtained from the preprocessing have been divided into as 70% training and 30% testing data. As a result of the study, artificial neural network model with 25 neurons in the hidden layer has been found as the model with the lowest error value. Chronic kidney failure disease has been able to be estimated accurately at the rate of 99.3% using this artificial neural network model. The developed artificial neural network has been found successful for the estimation of chronic kidney failure disease using clinical data.

Keywords: estimation, artificial neural network, chronic kidney failure disease, disease diagnosis

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Authors: Amad Nasseef, Layan Zugail, Joud Musalli, Layan Shaikan

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Technology has become an essential part of our lives. We have also witnessed the significant emergence of artificial intelligence in so many areas. Throughout this research paper, the following will be discussed: an introduction on AI and Socratic application, we also did an overview on the application’s background and other similar applications, as for the methodology, we conducted a survey to collect results on users experience in using the Socratic application. The results of the survey strongly supported the usefulness and interest of users in the Socratic application. Finally, we concluded that Socratic is a meaningful tool for learning purposes due to it being supported by artificial intelligence, which made the application easy to use and familiar to users to deal with through a click of a button.

Keywords: Socratic, artificial intelligence, application, features

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Authors: Kylie Leonard

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Investment in artificial intelligence (AI) can be an attractive opportunity for business leaders as there are many easy-to-see benefits. These benefits include task completion rates, overall cost, and better forecasting. Business leaders are often unaware of the challenges that can accompany AI, such as data center costs, access to data, employee acceptance, and privacy concerns. In addition to the benefits and challenges of AI, it is important to practice AI ethics to ensure the safe creation of AI. AI ethics include aspects of algorithm bias, limits in transparency, and surveillance. To be a good business leader, it is critical to address all the considerations involving the challenges of AI and AI ethics.

Keywords: artificial intelligence, artificial intelligence ethics, business leaders, business concerns

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Authors: Priyanka Bhatnagar, Malkeshkumar Patel, Joondong Kim, Joonpyo Hong

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Artificial skin and sensory memory platforms are produced using a flexible, transparent photovoltaic (TPV) device. The TPV device is composed of a metal oxide heterojunction (nZnO/p-NiO) and transmits visible light (> 50%) while producing substantial electric power (0.5 V and 200 μA cm-2 ). This TPV device is a transparent energy interface that can be used to detect signals and propagate information without an external energy supply. The TPV artificial skin offers a temperature detection range (0 C75 C) that is wider than that of natural skin (5 C48 °C) due to the temperature-sensitive pyrocurrent from the ZnO layer. Moreover, the TPV thermoreceptor offers sensory memory of extreme thermal stimuli. Much like natural skin, artificial skin uses the nociceptor mechanism to protect tissue from harmful damage via signal amplification (hyperalgesia) and early adaption (allodynia). This demonstrates the many features of TPV artificial skin, which can sense and transmit signals and memorize information under self-operation mode. This transparent photovoltaic skin can provide sustainable energy for use in human electronics.

Keywords: transparent, photovoltaics, thermal memory, artificial skin, thermoreceptor

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Authors: Chukwuma Mgboji

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Since the advent of Artificial Intelligence, robots have become a major stay in developing societies. Robots are deployed in Education, Health, Food and in other spheres of life. Nigeria a country in West Africa has a very low profile in the advancement of Artificial Intelligence especially in the grass roots. The benefits of Artificial intelligence are not fully maximised and harnessed. Advances in artificial intelligence are perceived as impossible or observed as irrelevant. This study seeks to ascertain the needed skills for the development of artificialintelligence amongst secondary schools in Nigeria. The study focused on South East Nigeria with Five states namely Imo, Abia, Ebonyi, Anambra and Enugu. The sample size is 1000 students drawn from Five Government owned Universities offering Computer Science, Computer Education, Electronics Engineering across the Five South East states. Survey method was used to solicit responses from respondents. The findings from the study identified mathematical skills, analytical skills, problem solving skills, computing skills, programming skills, algorithm skills amongst others. The result of this study to the best of the author’s knowledge will be highly beneficial to all stakeholders involved in the advancements and development of artificial intelligence.

Keywords: artificial intelligence, secondary school, robotics, skills

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Authors: Yiqiao Yin

Abstract:

Many scholars and educators have dedicated their lives in K12 education system and there has been an exploding amount of attention to implement technical foundations for Artificial Intelligence Education for high school and precollege level students. This paper focuses on the development and use of resources to support K-12 education in Artificial Intelligence (AI). The author and his team have more than three years of experience coaching students from pre-college level age from 15 to 18. This paper is a culmination of the experience and proposed online tools, software demos, and structured activities for high school students. The paper also addresses a portfolio of AI concepts as well as the expected learning outcomes. All resources are provided with online videos and Github repositories for immediate use.

Keywords: K12 education, AI4ALL, pre-college education, pre-college AI

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Authors: Artur Matuck, Guilherme F. Nobre

Abstract:

Machines can be either tool, media, or social agents. Advances in technology have been delivering machines capable of autonomous expression, both through communication and art. This paper deals with models (theoretical approach) and experiments (applied approach) related to artificial agents. On one hand it traces how social sciences' scholars have worked with topics such as text automatization, man-machine writing cooperation, and communication. On the other hand it covers how computer sciences' scholars have built communicative and artistic machines, including the programming of creativity. The aim is to present a brief survey on artificially intelligent communicators and artificially creative writers, and provide the basis to understand the meta-authorship and also to new and further man-machine co-authorship.

Keywords: artificial communication, artificial creativity, artificial writers, meta-authorship, robotic art

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Authors: Lipeng Zhang, Limei Li, Yanming Pearl Zhang

Abstract:

This paper takes a philosophical view as axiom, and reveals the relationship between information theory and Natural Intelligence and Artificial Intelligence under real world conditions. This paper also derives the relationship between natural intelligence and nature. According to communication principle of information theory, Natural Intelligence can be divided into real part and virtual part. Based on information theory principle that Information does not increase, the restriction mechanism of Natural Intelligence creativity is conducted. The restriction mechanism of creativity reveals the limit of natural intelligence and artificial intelligence. The paper provides a new angle to observe natural intelligence and artificial intelligence.

Keywords: natural intelligence, artificial intelligence, creativity, information theory, restriction of creativity

Procedia PDF Downloads 346

Authors: G. Venkata Rao, R. Srinivasa Rao, B. Neelima Sri Priya

Abstract:

The over extraction of groundwater from the coastal aquifers, result in reduction of groundwater resource and lowering of water level. In general, the depletion of groundwater level enhances the landward migration of saltwater wedge. Now a days the ground water extraction increases by year to year because increased population and industrialization. The ground water is the only source of irrigation, domestic and Industrial purposes at Pydibhimavaram industrial area, which is located in the coastal belt of Srikakulam district, India of Latitudes 18.145N 83.627E and Longitudes 18.099N 83.674E. The present study has been attempted to calculate amount of water getting recharged into this aquifer, status of rainfall pattern for the past two decades and the runoff is calculated by using Khosla’s formula with available rainfall and temperature in the study area. A decision support model has been developed on the basis of Monthly Extractions of the water from the ground through bore wells and the Net Recharge of the aquifer. It is concluded that the amount of extractions is exceeding the amount of recharge from May to October in a given year which will in turn damage the water balance in the subsurface layers.

Keywords: aquifer, decision support model, groundwater extraction, run off estimation and rainfall

Procedia PDF Downloads 268

Authors: Rajkumar Ghosh

Abstract:

Rapid urbanization, rising population, changing lifestyles and in-migration, Lucknow is groundwater over-exploited area, with an abstract rate of 1968 m3/day/km2 in Gomti Nagar. The groundwater situation in Gomti Nagar is deteriorating day-by-day. According to the work, the calculated annual water deficiency in Gomti Nagar area will be 28061 Million Litre (ML) in 2022. Within 30 yrs., the water deficiency will be 735570 ML (till 2051). The calculated groundwater recharge in Gomti Nagar was 10813 ML/y (in 2022). The annual groundwater abstraction from Gomti Nagar area was 35332 ML/yr. (in 2022). Bye-laws (≥ 300 sq.m) existing RTRWHs can recharge 17.71 ML/yr. in Gomti Nagar area. The existing RTRWHs are contributing 0.07% for recharging groundwater table. In Gomti Nagar, the water level is dropping at a rate of 1.0 metre per year, and the depth of the water table is less than 30 metre below ground level (mbgl). Natural groundwater recharge is affected by the geomorphological conditions of the surrounding area. Gomti Nagar is located on the erosional terrace (Te) and depositional terrace (d) of the Gomti River. The flood plain in Lucknow city is less active due to the embankments on the both sides of the Gomti River. The alluvium is composed of clay sandy up to a depth of 30m, and the alignment of the Gomti River reveals the presence of sandy soil at shallow depths. Aquifer depth 120 metre. Recharge as in Gomti Nagar (it may vary) 0 – 150 metre. Infiltration rates in alluvial floodplains range from 0.8 to 74 cm/hr. Geologically and Geomorphologically support rapid percolation of rainwater through alluvium in Gomti Nagar, Lucknow city, Uttar Pradesh. Over-exploitation of groundwater causes natural hazards viz. land subsidence, development of cracks on roads and buildings, development of vacuum and compactness of soil/clay which leads towards land subsidence, devastating effects on natural stream flow. Gomti River already transitioning phase from ‘effluent’ to ‘influent’, and saline intrusion in Aquifer –II (among Five aquifers in Lucknow city). A 250 m long crack developed in 2007 due to groundwater depletion in Dullu Khera and Vader Khera village of Kakori, Uttar Pradesh. The groundwater table of Lucknow is declining and water table imbalance occurs due to 17 times less recharge than groundwater exploitation. Uttar Pradesh along with four states have extracted 49% of groundwater in the entire country. In Gomti Nagar area, 27305 no of houses are present and available build up area 3.8 sq. km (60% of plot area) based on Lucknow Development Authority (LDA) Master plan 2031. If RTRWHs would install in all the houses, then 12% harvested rainwater contribute to the water table in Gomti Nagar area. Till 2051, Gomti Nagar area will harvest 91110 ML of rainwater. There are minimalistic chances that any incidence of flood can occur due to RTRWH. Thus, it can conclud that RTRWH is not related to flood happening in urban areas viz. Gomti Nagar.

Keywords: RTRWH, aquifer, groundwater table, rainwater, infiltration

Procedia PDF Downloads 47

Authors: O. P. Oladipo, O. A. Falode

Abstract:

The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

Procedia PDF Downloads 408