Search results for: artificial treatment

Authors: Alanod Alqasim, Yasmine Iskandarani, Sita Algethami, Jawaher alzughaiby

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This study focuses on the usage of AI (Artificial Intelligence) systems and features on the Instagram application and how it influences user experience and satisfaction. The aim is to evaluate the techniques and current capabilities, restrictions, and potential future directions of AI in an Instagram application. Following a concise explanation of the core concepts underlying AI usage on Instagram. To answer this question, 19 randomly selected users were asked to complete a 9-question survey on their experience and satisfaction with the app's features (Filters, user preferences, translation tool) and authenticity. The results revealed that there were three prevalent allegations. These declarations include that Instagram has an extremely attractive user interface; secondly, Instagram creates a strong sense of community; and lastly, Instagram has an important influence on mental health.

Keywords: AI (Artificial Intelligence), instagram, features, satisfaction, experience

Procedia PDF Downloads 81

Authors: Hamed Zolfaghari, Mojtaba Kord

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After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

Procedia PDF Downloads 92

Authors: Djoudi Ali

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In this article, we shall expose some of the more interesting interactions of philosophy and cybernetics, some philosophical issues arising in cybernetic systems, and some questions in philosophy of our daily life related to the artificial intelligence. Many of these are fruitfully explored in the article..This article will shed light also on the importance of science and technology in our life and what are the main problems of misusing the latest technologies known under artificial intelligence and cybernatics acoording to Bertrand Russell’s point of view; then to analyse his project of reforms inculding science progress risks , the article show also the whole aspect of the impact of technology on peace , nature and on individual daily behavior, we shall discuss all issues and defies imposing by this new era , The article will invest in showing what Russell will suggest to eliminate or to slow down the dangers of these changes and what are the main solutions to protect the indiviual’s rights and responsiblities In this article, We followed a different methodology, like analysis method and sometimes the historical or descriptive method, without forgetting criticizing some conclusions when it is logically needed In the end, we mentioned what is supposed to be solutions suggested by Bertrand Russell that should be taken into considerations during the next decades and how to protect our ennvironement and the human being of any risk of disappearing

Keywords: artificial intelligence, technology, cybernetics, sience

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Authors: S. M. Anowarul Haque, Md. Asiful Islam

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Electrical load forecasting is considered to be one of the most indispensable parts of a modern-day electrical power system. To ensure a reliable and efficient supply of electric energy, special emphasis should have been put on the predictive feature of electricity supply. Artificial Neural Network-based approaches have emerged to be a significant area of interest for electric load forecasting research. This paper proposed an Artificial Neural Network model based on the particle swarm optimization algorithm for improved electric load forecasting for Mymensingh, Bangladesh. The forecasting model is developed and simulated on the MATLAB environment with a large number of training datasets. The model is trained based on eight input parameters including historical load and weather data. The predicted load data are then compared with an available dataset for validation. The proposed neural network model is proved to be more reliable in terms of day-wise load forecasting for Mymensingh, Bangladesh.

Keywords: load forecasting, artificial neural network, particle swarm optimization

Procedia PDF Downloads 167

Authors: Supriyadi, Andi Intan Purnamasari, Aminuddin Kasim, Sulbadana, Mohammad Reza

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The development of the Industrial Revolution Era 4.0 brought a significant influence in the administration of countries in all parts of the world, including Indonesia, not only in the administration and economic sectors but the ways and methods of forming laws should also be adjusted. Until now, the process of making laws carried out by the Parliament with the Government still uses the classical method. The law-making process still uses manual methods, such as typing harmonization of regulations, so that it is not uncommon for errors to occur, such as writing errors, copying articles and so on, things that require a high level of accuracy and relying on inventory and harmonization carried out manually by humans. However, this method often creates several problems due to errors and inaccuracies on the part of officers who harmonize laws after discussion and approval; this has a very serious impact on the system of law formation in Indonesia. The use of artificial intelligence in the process of forming laws seems to be justified and becomes the answer in order to minimize the disharmony of various laws and regulations. This research is normative research using the Legislative Approach and the Conceptual Approach. This research focuses on the question of how to use Artificial Intelligence for Harmonization in the Lawmaking Process.

Keywords: artificial intelligence, harmonization, laws, intelligence

Procedia PDF Downloads 151

Authors: Kiraz Esmeli, Alper Ozkan

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In this study, firstly, the effect of ultrasonic treatment on the stability of celestite suspension was investigated. In this context, the variations of the suspension stability with ultrasonic power, treatment time, immersion depth of ultrasonic probe, and treatment regime (batch and continuous) were determined. The experimental results showed that the suspension stability and zeta potential of celestite decreased with ultrasonic treatment. Also, the treatment time, immersion depth of probe, and treatment regime affected the stability of celestite suspension. Secondly, the effect of pre-treatment of the suspension with the ultrasonic process on the shear flocculation of celestite using sodium dodecyl sulfate (SDS) was studied and the variations of the flocculation, zeta potential, and contact angle of the mineral with SDS concentration were presented. It was found that the ultrasonic pre-treatment slightly improved the shear flocculation of celestite particles in accordance with the increase in the contact angles. In addition, the ultrasonic process again relatively reduced the magnitude of the negative potential of celestite particles in the presence of SDS.

Keywords: celestite, contact angle, suspension stability, ultrasonic treatment, zeta potential

Procedia PDF Downloads 223

Authors: Manal Bouasria, Mohammed-Hichem Benzaama, Valérie Pralong, Yassine El Mendili

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Reducing the quantity of cement in cementitious composites can help to reduce the environmental effect of construction materials. By-products such as ferronickel slags (FNS), fly ash (FA), and Crepidula fornicata (CR) are promising options for cement replacement. In this work, we investigated the relevance of substituting cement with FNS-CR and FA-CR on the mechanical properties of mortar and on the thermal properties of concrete. Foraging intervals ranging from 2 to 28 days, the mechanical properties are obtained by 3-point bending and compression tests. The chosen mix is used to construct a prototype in order to study the material’s hygrothermal performance. The data collected by the sensors placed on the prototype was utilized to build an artificial neural network.

Keywords: artificial neural network, cement, circular economy, concrete, by products

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Authors: I. Sterbova, E. Oberhofnerova, M. Panek, M. Pavelek

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With growing popularity, wood of European larch (Larix decidua, Mill.) is being more often applied into the exterior, usually as facade elements, also without surface treatment. The aim of this work was to compare two laboratory tests of artificial accelerated weathering of wood with two ways of natural weathering in the exterior. To assess changes in selected surface characteristics of larch wood, accelerated weathering methods in the Xenotest and UV chamber were used, both in combination with temperature cycling, for 6 weeks. They were compared with natural weathering results at exposition under 45° and 90° in the exterior for 12 months. The changes of colour, gloss, contact angle of water and also changes in visual characteristics were evaluated. The results of wood surfaces changes after 6 weeks of accelerated weathering in Xenotest are closer to 12 months of natural weathering in the exterior at an angle of 90° compared to the UV chamber testing. The results, especially the colour changes, of the samples exposed at an angle of 45° in the exterior were significantly different. Testing in Xenotest more closely simulates the weathering of façade elements in the exterior compared to the UV chamber testing.

Keywords: larch wood, wooden facade, wood accelerated weathering, weathering methods

Procedia PDF Downloads 138

Authors: Parisa Mansour

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Introduction: Early diagnosis of coronavirus disease (COVID-19) is extremely important to isolate and treat patients in time, thus preventing the spread of the disease, improving prognosis and reducing mortality. High-resolution computed tomography (HRCT) chest imaging and artificial intelligence (AI)-based analysis of HRCT chest images can play a central role in the treatment of patients with COVID-19. Objective: To investigate different chest HRCT findings in different stages of COVID-19 pneumonia and to evaluate the potential role of artificial intelligence in the quantitative assessment of lung parenchymal involvement in COVID-19 pneumonia. Materials and Methods: This retrospective observational study was conducted between May 1, 2020 and August 13, 2020. The study included 2169 patients with COVID-19 who underwent chest HRCT. HRCT images showed the presence and distribution of lesions such as: ground glass opacity (GGO), compaction, and any special patterns such as septal thickening, inverted halo, mark, etc. HRCT findings of the breast at different stages of the disease (early: andlt) 5 days, intermediate: 6-10 days and late stage: >10 days). A CT severity score (CTSS) was calculated based on the extent of lung involvement on HRCT, which was then correlated with clinical disease severity. Use of artificial intelligence; Analysis of CT pneumonia and quot; An algorithm was used to quantify the extent of pulmonary involvement by calculating the percentage of pulmonary opacity (PO) and gross opacity (PHO). Depending on the type of variables, statistically significant tests such as chi-square, analysis of variance (ANOVA) and post hoc tests were applied when appropriate. Results: Radiological findings were observed in HRCT chest in 1438 patients. A typical pattern of COVID-19 pneumonia, i.e., bilateral peripheral GGO with or without consolidation, was observed in 846 patients. About 294 asymptomatic patients were radiologically positive. Chest HRCT in the early stages of the disease mostly showed GGO. The late stage was indicated by such features as retinal enlargement, thickening and the presence of fibrous bands. Approximately 91.3% of cases with a CTSS = 7 were asymptomatic or clinically mild, while 81.2% of cases with a score = 15 were clinically severe. Mean PO and PHO (30.1 ± 28.0 and 8.4 ± 10.4, respectively) were significantly higher in the clinically severe categories. Conclusion: Because COVID-19 pneumonia progresses rapidly, radiologists and physicians should become familiar with typical TC chest findings to treat patients early, ultimately improving prognosis and reducing mortality. Artificial intelligence can be a valuable tool in treating patients with COVID-19.

Keywords: chest, HRCT, covid-19, artificial intelligence, chest HRCT

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Authors: Hossain A., Chowdhury S. I.

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Introduction: The use of a gamma camera is a standard procedure in nuclear medicine facilities or hospitals to diagnose chronic kidney disease (CKD), but the gamma camera does not precisely stage the disease. The authors sought to determine whether they could use an artificial neural network to determine whether CKD was in normal or abnormal stages based on GFR values (ANN). Method: The 250 kidney patients (Training 188, Testing 62) who underwent an ultrasonography test to diagnose a renal test in our nuclear medical center were scanned using a gamma camera. Before the scanning procedure, the patients received an injection of ⁹⁹ᵐTc-DTPA. The gamma camera computes the pre- and post-syringe radioactive counts after the injection has been pushed into the patient's vein. The artificial neural network uses the softmax function with cross-entropy loss to determine whether CKD is normal or abnormal based on the GFR value in the output layer. Results: The proposed ANN model had a 99.20 % accuracy according to K-fold cross-validation. The sensitivity and specificity were 99.10 and 99.20 %, respectively. AUC was 0.994. Conclusion: The proposed model can distinguish between normal and abnormal stages of CKD by using an artificial neural network. The gamma camera could be upgraded to diagnose normal or abnormal stages of CKD with an appropriate GFR value following the clinical application of the proposed model.

Keywords: artificial neural network, glomerular filtration rate, stages of the kidney, gamma camera

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Authors: Rupan Preet Kaur

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This article reviewed the potential of artificial intelligence in the field of identity and access management (IAM) and identity governance and administration (IGA), the most critical pillars of any organization. The power of leveraging AI in the most complex and huge user base environment was outlined by simplifying and streamlining the user access approvals and re-certifications without any impact on the user productivity and at the same time strengthening the overall compliance of IAM landscape. Certain challenges encountered in the current state were detailed where majority of organizations are still lacking maturity in the data integrity aspect. Finally, this paper concluded that within the realm of possibility, users and application owners can reap the benefits of unified approach provided by AI to improve the user experience, improve overall efficiency, and strengthen the risk posture.

Keywords: artificial intelligence, machine learning, user access review, access approval

Procedia PDF Downloads 89

Authors: Á. L. Bendes

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By the end of the second decade of the 21st century, artificial intelligence (AI) has become an unavoidable part of everyday life and has necessarily aroused the interest of researchers in almost every field of science. This is no different in the case of jurisprudence, whose main task is not only to create its own theoretical paradigm related to AI. Perhaps the biggest impact on digital crime is artificial intelligence. In addition, the need to create legal frameworks suitable for the future application of the law has a similar importance. The prognosis according to which AI can reshape the practical application of law and, ultimately, the entire legal life is also of considerable importance. In the past, criminal law was basically created to sanction the criminal acts of a person, so the application of its concepts with original content to AI-related violations is not expected to be sufficient in the future. Taking this into account, it is necessary to rethink the basic elements of criminal law, such as the act and factuality, but also, in connection with criminality barriers and criminal sanctions, several new aspects have appeared that challenge both the criminal law researcher and the legislator. It is recommended to continuously monitor technological changes in the field of criminal law as well since it will be timely to re-create both the legal and scientific frameworks to correctly assess the events related to them, which may require a criminal law response. Artificial intelligence has completely reformed the world of digital crime. New crimes have appeared, which the legal systems of many countries do not or do not adequately regulate. It is considered important to investigate and sanction these digital crimes. The primary goal is prevention, for which we need a comprehensive picture of the intertwining of artificial intelligence and digital crimes. The goal is to explore these problems, present them, and create comprehensive proposals that support legal certainty.

Keywords: artificial intelligence, chat forums, defamation, international criminal cooperation, social networking, virtual sites

Procedia PDF Downloads 80

Authors: Masoumeh Mofarrah, Amir NahanMoghadam

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Higher oil prices and increasing oil demand are main reasons for great attention to Enhanced Oil Recovery (EOR). Comprehensive researches have been accomplished to develop, appraise and improve EOR methods and their application. Recently Artificial Intelligence (AI) gained popularity in petroleum industry that can help petroleum engineers to solve some fundamental petroleum engineering problems such as reservoir simulation, EOR project risk analysis, well log interpretation and well test model selection. This study presents a historical overview of most popular AI tools including neural networks, genetic algorithms, fuzzy logic and expert systems in petroleum industry and discusses two case studies to represent the application of two mentioned AI methods for selecting an appropriate EOR method based on reservoir characterization in feasible and effective way.

Keywords: artificial intelligence, EOR, neural networks, expert systems

Procedia PDF Downloads 406

Authors: Eliska Oberhofnerova, Milos Panek, Stepan Hysek, Martin Lexa

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Nowadays the use of wood, both indoors and outdoors, is constantly increasing. However wood is a natural organic material and in the exterior is subjected to a degradation process caused by abiotic factors (solar radiation, rain, moisture, wind, dust etc.). This process affects only surface layers of wood but neglecting some of the basic rules of wood protection leads to increased possibility of biological agents attack and thereby influences a function of the wood element. The process of wood degradation can be decreased by proper surface treatment, especially in the case of less naturally durable wood species, as spruce. Modern coating systems are subjected to many requirements such as colour stability, hydrophobicity, low volatile organic compound (VOC) content, long service life or easy maintenance. The aim of this study is to evaluate the colour stability of spruce wood (Picea abies), as the basic parameter indicating the coating durability, treated with two layers of transparent natural oil wood stain and exposed to outdoor conditions. The test specimens were exposed for 2 years to natural weathering and 2000 hours to artificial weathering in UV-chamber. The colour parameters were measured before and during exposure to weathering by the spectrophotometer according to CIELab colour space. The comparison between untreated and treated wood and both testing procedures was carried out. The results showed a significant effect of coating on the colour stability of wood, as expected. Nevertheless, increasing colour changes of wood observed during the exposure to weathering differed according to applied testing procedure - natural and artificial.

Keywords: colour stability, natural and artificial weathering, spruce wood, transparent coating

Procedia PDF Downloads 214

Authors: Javed Mohammed

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Robotics is the fastest growing industry in the world, poised to become the largest in the next decade. The use of robots requires design, application and implementation of the appropriate safety controls in order to avoid creating hazards to production personnel, programmers, maintenance specialists and systems engineers. The increasing use of artificial intelligence (AI) and related technologies in the workplace are dramatically changing the employment landscape. The impact of robotics technology on workplace policy is dramatic and complex. The robotics revolution calls for a comprehensive approach to job training, and retraining, to mitigate worker displacement and enable workers to benefit from the new jobs that the technology will generate. It calls for a thoughtful, forward-thinking approach by lawmakers, regulators and employers to prepare for the oncoming transformation of the workplace and workforce.

Keywords: design, artificial intelligence, programmers, system engineers, robotics, transformation

Procedia PDF Downloads 466

Authors: Wei Hu, Wenguang Chen, Chong Dong

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In order to improve the efficiency and safety of photovoltaic power generation devices, this photovoltaic power generation system combines Artificial Intelligence (AI) and the Internet of Things (IoT) to control the chasing photovoltaic power generation device to track the sun to improve power generation efficiency and then convert energy management. The system uses artificial intelligence as the control terminal, the power generation device executive end uses the Linux system, and Exynos4412 is the CPU. The power generating device collects the sun image information through Sony CCD. After several power generating devices feedback the data to the CPU for processing, several CPUs send the data to the artificial intelligence control terminal through the Internet. The control terminal integrates the executive terminal information, time information, and environmental information to decide whether to generate electricity normally and then whether to convert the converted electrical energy into the grid or store it in the battery pack. When the power generation environment is abnormal, the control terminal authorizes the protection strategy, the power generation device executive terminal stops power generation and enters a self-protection posture, and at the same time, the control terminal synchronizes the data with the cloud. At the same time, the system is more intelligent, more adaptive, and longer life.

Keywords: photo-voltaic power generation, the pursuit of light, artificial intelligence, internet of things, photovoltaic array, power management

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Authors: S. Neelima, P. S. Subramanyam

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The major tool for distribution planning is load forecasting, which is the anticipation of the load in advance. Artificial neural networks have found wide applications in load forecasting to obtain an efficient strategy for planning and management. In this paper, the application of neural networks to study the design of short term load forecasting (STLF) Systems was explored. Our work presents a pragmatic methodology for short term load forecasting (STLF) using proposed two-stage model of wavelet transform (WT) and artificial neural network (ANN). It is a two-stage prediction system which involves wavelet decomposition of input data at the first stage and the decomposed data with another input is trained using a separate neural network to forecast the load. The forecasted load is obtained by reconstruction of the decomposed data. The hybrid model has been trained and validated using load data from Telangana State Electricity Board.

Keywords: electrical distribution systems, wavelet transform (WT), short term load forecasting (STLF), artificial neural network (ANN)

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Authors: Yusuf Turan

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Definition of Intellectual Property Rights according to the World Intellectual Property Organization: " Intellectual property (IP) refers to creations of the mind, such as inventions; literary and artistic works; designs; and symbols, names and images used in commerce." It states as follows. There are 2 important points in the definition; we can say that it is the result of intellectual activities that occur by one or more than one PERSON and as INNOVATION. When the history and development of the relevant definitions are briefly examined, it is realized that these two points have remained constant and Intellectual Property law and rights have been shaped around these two points. With the expansion of the scope of the term Intellectual Property as a result of the development of technology, especially in the field of artificial intelligence, questions such as "Can "Artificial Intelligence" be an inventor?" need to be resolved within the expanding scope. In the past years, it was ruled that the artificial intelligence named DABUS seen in the USA did not meet the definition of "individual" and therefore would be an inventor/inventor. With the developing technology, it is obvious that we will encounter such situations much more frequently in the field of intellectual property. While expanding the scope, we should definitely determine the boundaries of how we should decide who performs the mental activity or creativity that we call indispensable on the inventor/inventor according to these problems. As a result of all these problems and innovative situations, it is clearly realized that not only Intellectual Property Law and Rights but also their definitions need to be updated and improved. Ignoring the situations that are outside the scope of the current Intellectual Property Term is not enough to solve the problem and brings uncertainty. The fact that laws and definitions that have been operating on the same theories for years exclude today's innovative technologies from the scope contradicts intellectual property, which is expressed as a new and innovative field. Today, as a result of the innovative creation of poetry, painting, animation, music and even theater works with artificial intelligence, it must be recognized that the definition of Intellectual Property must be revised.

Keywords: artificial intelligence, innovation, the term of intellectual property, right

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Authors: Tse-An Pan, Sheng-Long Lee

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The effect of non-isothermal aging on the mechanical properties and corrosion resistance of Al-9Zn-2.3Mg-1.9Cu (AA7056) alloys was investigated. The results revealed that thick materials were limited to retrogression and re-aging treatment (RRA). It could not reach the retrogression temperature in the RRA treatment. Compared with the RRA treatment, the non-isothermal aging (NIA) treatment produced discontinuous precipitates at grain boundaries, while the intragranular precipitates were fine and dense. The strength was similar to that of the RRA treatment; the corrosion resistance of the alloy was significantly improved by NIA aging. NIA treatment was less affected by the thickness of the alloy. The difference between the actual temperature and the setting temperature of the alloy is minimal during the aging process. The combination of properties could overcome the fact that RRA treatment cannot handle thick materials.

Keywords: Al-Zn-Mg-Cu alloy, corrosion, retrogression, re-aging, non-isothermal aging

Procedia PDF Downloads 174

Authors: Abdulrahman S. Shryan Aldossary

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Globally, artificial intelligence (AI) is already performing legitimate tasks on behalf of humans. In Saudi Arabia, large-scale national projects, primarily based on AI technologies and receiving billions of dollars of funding, are projected for completion by 2030. However, the legal aspect of these projects is seriously vulnerable, given AI’s unprecedented ability to self-learn and act independently. This paper, therefore, identifies the critical legal aspects of AI that authorities and policymakers should be aware of, specifically whether AI can possess identity and be liable for the risk of public harm. The article begins by identifying the problematic characteristics of AI and what should be considered by legal experts when dealing with it. Also discussed are the possible competent institutions that could regulate AI in Saudi Arabia. Finally, a procedural proposal is presented for controlling AI, focused on Saudi Arabia but potentially of interest to other jurisdictions facing similar concerns about AI safety.

Keywords: regulation, artificial intelligence, tech law, automated systems

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Authors: Matthew Holland, Jason Everett, Martin Cox, Iain Suthers

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High spatial-resolution distribution of planktivorous reef fish can reveal behavioural adaptations to optimise the balance between feeding success and predator avoidance. We used a multi-beam echosounder to record bathymetry and the three-dimensional distribution of fish schools associated with natural and artificial reefs. We utilised generalised linear models to assess the distribution, orientation, and aggregation of fish schools relative to the structure, vertical relief, and currents. At artificial reefs, fish schooled more closely to the structure and demonstrated a preference for the windward side, particularly when exposed to strong currents. Similarly, at natural reefs fish demonstrated a preference for windward aspects of bathymetry, particularly when associated with high vertical relief. Our findings suggest that under conditions with stronger current velocity, fish can exercise their preference to remain close to structure for predator avoidance, while still receiving an adequate supply of zooplankton delivered by the current. Similarly, when current velocity is low, fish tend to disperse for better access to zooplankton. As artificial reefs are generally deployed with the goal of creating productivity rather than simply attracting fish from elsewhere, we advise that future artificial reefs be designed as semi-linear arrays perpendicular to the prevailing current, with multiple tall towers. This will facilitate the conversion of dispersed zooplankton into energy for higher trophic levels, enhancing reef productivity and fisheries.

Keywords: artificial reef, current, forage fish, multi-beam, planktivorous fish, reef fish, schooling

Procedia PDF Downloads 154

Authors: Reda Abdel Azim, Tariq Shehab

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The main objective of this study is to develop a subsurface fracture map of naturally fractured reservoirs by overcoming the limitations associated with different data sources in characterising fracture properties. Some of these limitations are overcome by employing a nested neuro-stochastic technique to establish inter-relationship between different data, as conventional well logs, borehole images (FMI), core description, seismic attributes, and etc. and then characterise fracture properties in terms of fracture density and fractal dimension for each data source. Fracture density is an important property of a system of fracture network as it is a measure of the cumulative area of all the fractures in a unit volume of a fracture network system and Fractal dimension is also used to characterize self-similar objects such as fractures. At the wellbore locations, fracture density and fractal dimension can only be estimated for limited sections where FMI data are available. Therefore, artificial intelligence technique is applied to approximate the quantities at locations along the wellbore, where the hard data is not available. It should be noted that Artificial intelligence techniques have proven their effectiveness in this domain of applications.

Keywords: naturally fractured reservoirs, artificial intelligence, fracture intensity, fractal dimension

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Authors: Jim S. Meng, Mammo H. Yewondwossen

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As a part of routine oesophageal HDR brachytherapy procedure, treatment planning takes about 45 minutes while patients are under light sedation. Some patients may suffer gagging and/or spasms, and the treatment may need to be aborted. A pre-prepared plan generated before the patient’s sedation may reduce the brachytherapy procedure time by forty minutes. This paper reports the rationality and evidence of pre-prepared treatment plans. A retrospective study of 28 patients confirm that all of the pre-prepared plans would be acceptable. The rationality of pre-prepared HDR brachytherapy plans is further confirmed by a systemic study with a wide range of applicator curvature and treatment volume. Detailed comparison between CT based treatment plans and pre-prepared plans are discussed. This argument holds also for endobronchial HDR brachytherapy. With the above evidence, pre-prepared plans have been used for all oesophagus and bronchus HDR brachytherapy cases in our clinic.

Keywords: HDR brachytherapy, treatment planning, oesophageal carcinoma, pre-planning

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Authors: Royan Dawud Aldian, Endah Purwanti, Soegianto Soelistiono

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In this research we have been developed an automatic investigation to classify normal children voice or autistic by using modern computation technology that is computation based on artificial neural network. The superiority of this computation technology is its capability on processing and saving data. In this research, digital voice features are gotten from the coefficient of linear-predictive coding with auto-correlation method and have been transformed in frequency domain using fast fourier transform, which used as input of artificial neural network in back-propagation method so that will make the difference between normal children and autistic automatically. The result of back-propagation method shows that successful classification capability for normal children voice experiment data is 100% whereas, for autistic children voice experiment data is 100%. The success rate using back-propagation classification system for the entire test data is 100%.

Keywords: autism, artificial neural network, backpropagation, linier predictive coding, fast fourier transform

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Authors: Kudzanayi Chiteka, Wellington Makondo

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The whole world is on the drive to go green owing to the negative effects of burning fossil fuels. Therefore, there is immediate need to identify and utilise alternative renewable energy sources. Among these energy sources solar energy is one of the most dominant in Zimbabwe. Solar power plants used to generate electricity are entirely dependent on solar radiation. For planning purposes, solar radiation values should be known in advance to make necessary arrangements to minimise the negative effects of the absence of solar radiation due to cloud cover and other naturally occurring phenomena. This research focused on the prediction of Global Horizontal Irradiation values for the sixth day given values for the past five days. Artificial intelligence techniques were used in this research. Three models were developed based on Support Vector Machines, Radial Basis Function, and Feed Forward Back-Propagation Artificial neural network. Results revealed that Support Vector Machines gives the best results compared to the other two with a mean absolute percentage error (MAPE) of 2%, Mean Absolute Error (MAE) of 0.05kWh/m²/day root mean square (RMS) error of 0.15kWh/m²/day and a coefficient of determination of 0.990. The other predictive models had prediction accuracies of MAPEs of 4.5% and 6% respectively for Radial Basis Function and Feed Forward Back-propagation Artificial neural network. These two models also had coefficients of determination of 0.975 and 0.970 respectively. It was found that prediction of GHI values for the future days is possible using artificial intelligence-based predictive models.

Keywords: solar energy, global horizontal irradiation, artificial intelligence, predictive models

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Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

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Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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Authors: Prashant Dhiman, Viranshu Kumar, Pradeep Joshi

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Lot of research is going on to study the effect of cryogenic treatment on materials. Cryogenic treatment is a heat treatment process which is used widely to enhance the mechanical and metallurgical properties of various materials whether the material is ferrous or non ferrous. In almost all ferrous metals, it is found that retained austenite is converted into martensite. Generally deep cryogenic treatment is done using liquid nitrogen having temperature of -195 ℃. The austenite is unstable at this stage and converts into martensite. In non ferrous materials there presents a microcavity and under the action of stress it becomes crack. When this crack propagates, fracture takes place. As the metal contract under low temperature, by doing cryogenic treatment these microcavities will be filled hence increases the soundness of the material. Properties which are enhanced by cryogenic treatment of both ferrous and non ferrous materials are hardness, tensile strength, wear rate, electrical and thermal conductivity, and others. Also there is decrease in residual stress. A large number of manufacturing process (EDM, CNC etc.) are using cryogenic treatment on different tools or workpiece to reduce their wear. In this Review paper the use of cryogenic heat treatment in different manufacturing has been shown along with their advantages.

Keywords: cyrogenic treatment, EDM (Electrical Discharge Machining), CNC (Computer Numeric Control), Mechanical and Metallurgical Properties

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Authors: Angeliki Peponi, Paulo Morgado, Jorge Trindade

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Artificial Neural Networks (ANNs) and Geographic Information Systems (GIS) are applied as a robust tool for modeling and forecasting the erosion changes in Costa Caparica, Lisbon, Portugal, for 2021. ANNs present noteworthy advantages compared with other methods used for prediction and decision making in urban coastal areas. Multilayer perceptron type of ANNs was used. Sensitivity analysis was conducted on natural and social forces and dynamic relations in the dune-beach system of the study area. Variations in network’s parameters were performed in order to select the optimum topology of the network. The developed methodology appears fitted to reality; however further steps would make it better suited.

Keywords: artificial neural networks, backpropagation, coastal urban zones, erosion prediction

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Authors: D. S. Zhuravkova, A. G. Temnikov, O. S. Belova, L. L. Chernensky, T. K. Gerastenok, I. Y. Kalugina, N. Y. Lysov, A.V. Orlov

Abstract:

Investigation of the discharges from the artificial charged water aerosol clouds in presence of the arrays of the model hydrometeors could help to receive the new data about the peculiarities of the return stroke formation between the thundercloud and the ground when the large volumes of the hail particles participate in the lightning discharge initiation and propagation stimulation. Artificial charged water aerosol clouds of the negative or positive polarity with the potential up to one million volts have been used. Hail has been simulated by the group of the conductive model hydrometeors of the different form. Parameters of the impulse current of the main stage of the discharge between the artificial positively and negatively charged water aerosol clouds and the ground in presence of the model hydrometeors array and of its corresponding electromagnetic radiation have been determined. It was established that the parameters of the array of the model hydrometeors influence on the parameters of the main stage of the discharge between the artificial thundercloud cell and the ground. The maximal values of the main stage current impulse parameters and the electromagnetic radiation registered by the plate antennas have been found for the array of the model hydrometeors of the cylinder revolution form for the negatively charged aerosol cloud and for the array of the hydrometeors of the plate rhombus form for the positively charged aerosol cloud, correspondingly. It was found that parameters of the main stage of the discharge between the artificial charged water aerosol cloud and the ground in presence of the model hydrometeor array of the different considered forms depend on the polarity of the artificial charged aerosol cloud. In average, for all forms of the investigated model hydrometeors arrays, the values of the amplitude and the current rise of the main stage impulse current and the amplitude of the corresponding electromagnetic radiation for the artificial charged aerosol cloud of the positive polarity were in 1.1-1.9 times higher than for the charged aerosol cloud of the negative polarity. Thus, the received results could indicate to the possible more important role of the big volumes of the large hail arrays in the thundercloud on the parameters of the return stroke for the positive lightning.

Keywords: main stage of discharge, hydrometeor form, lightning parameters, negative and positive artificial charged aerosol cloud

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Authors: Oleg Sapelnikov, Ruslan Latypov, Darina Ardus, Samvel Aivazian, Andrey Shiryaev, Renat Akchurin

Abstract:

OBJECTIVE: MAZE procedure is one of the most effective surgical methods in atrial fibrillation (AF) treatment. Nowadays we are all aware of its modifications. In our study we conducted clinical analysis of “Box lesion+” approach during MAZE procedure in two-year follow-up. METHODS: We studied the results of the open-heart on-pump procedures performed in our hospital from 2017 to 2018 years. Thirty-two (32) patients with atrial fibrillation (AF) were included in this study. Fifteen (15) patients had concomitant coronary bypass grafting and seventeen (17) patients had mitral valve repair. Mean age was 62.3±8.7 years; prevalence of men was admitted (56.1%). Mean duration of AF was 4.75±5.44 and 7.07±8.14 years. In all cases, we performed endocardial Cryo-MAZE procedure with one-time myocardium revascularization or mitral-valve surgery. All patients of this study underwent pulmonary vein (PV) isolation and ablation of mitral isthmus with additional isolation of LA posterior wall (Box-lesion+ procedure). Mean follow-up was 2 years. RESULTS: All cases were performed without any complications. Additional isolation of posterior wall did not prolong the operative time and artificial circulation significantly. Cryo-MAZE procedure directly lasted 20±2.1 min, the whole operation time was 192±24 min and artificial circulation time was 103±12 min. According to design of the study, we performed clinical investigation of the patients in 12 months and in 2 years from the initial procedure. In 12 months, the number of AF free patients 81.8% and 75.8% in two years of follow-up. CONCLUSIONS: Isolation of the left atrial posterior wall and perimitral area may considerably improve the efficacy of surgical treatment, which was demonstrated in significant decrease of AF recurrences during the whole period of follow-up.

Keywords: atrial fibrillation, cryoablation, left atrium isolation, open heart procedure

Procedia PDF Downloads 123