Search results for: artificial habitat mapping

Authors: Bouayachi Ali, Alikouss Saida, Baroudi Zouhir, Zerhouni Youssef, Zouhair Mohammed, El Idrissi Assia, Essalhi Mourad

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The world-class Imiter silver deposit is located on the northern flank of the Precambrian Imiter buttonhole. This deposit is formed by epithermal veins hosted in the sandstone-pelite formations of the lower complex and in the basic conglomerates of the upper complex, these veins are controlled by a regional scale fault cluster, oriented N70°E to N90°E. The present work on the contribution of remote sensing on the geological mapping of the Imiter buttonhole and application to the mineralized structures of the Principal Corps B3. Mapping on satellite images is a very important tool in mineral prospecting. It allows the localization of the zones of interest in order to orientate the field missions by helping the localization of the major structures which facilitates the interpretation, the programming and the orientation of the mining works. The predictive map also allows for the correction of field mapping work, especially the direction and dimensions of structures such as dykes, corridors or scrapings. The use of a series of processing such as SAM, PCA, MNF and unsupervised and supervised classification on a Landsat 8 satellite image of the study area allowed us to highlight the main facies of the Imite area. To improve the exploration research, we used another processing that allows to realize a spatial distribution of the alteration mineral indices, and the application of several filters on the different bands to have lineament maps.

Keywords: principal corps B3, teledetection, Landsat 8, Imiter II, silver mineralization, lineaments

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Authors: Aya Al Masri, Stefaan Carpentier, Fabrice Leroy, Thibault Julien, Safoin Aktaou, Malorie Martin, Fouad Maaloul

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Introduction: During an 'Interventional Radiology (IR)' procedure, the patient's skin-dose may become very high for a burn, necrosis and ulceration to appear. In order to prevent these deterministic effects, an accurate calculation of the patient skin-dose mapping is essential. For most machines, the 'Dose Area Product (DAP)' and fluoroscopy time are the only information available for the operator. These two parameters are a very poor indicator of the peak skin dose. We developed a mathematical model that reconstructs the magnitude (delivered dose), shape, and localization of each irradiation field on the patient skin. In case of critical dose exceeding, the system generates warning alerts. We present the results of its comparison with clinical studies. Materials and methods: Two series of comparison of the skin-dose mapping of our mathematical model with clinical studies were performed: 1. At a first time, clinical tests were performed on patient phantoms. Gafchromic films were placed on the table of the IR machine under of PMMA plates (thickness = 20 cm) that simulate the patient. After irradiation, the film darkening is proportional to the radiation dose received by the patient's back and reflects the shape of the X-ray field. After film scanning and analysis, the exact dose value can be obtained at each point of the mapping. Four experimentation were performed, constituting a total of 34 acquisition incidences including all possible exposure configurations. 2. At a second time, clinical trials were launched on real patients during real 'Chronic Total Occlusion (CTO)' procedures for a total of 80 cases. Gafchromic films were placed at the back of patients. We performed comparisons on the dose values, as well as the distribution, and the shape of irradiation fields between the skin dose mapping of our mathematical model and Gafchromic films. Results: The comparison between the dose values shows a difference less than 15%. Moreover, our model shows a very good geometric accuracy: all fields have the same shape, size and location (uncertainty < 5%). Conclusion: This study shows that our model is a reliable tool to warn physicians when a high radiation dose is reached. Thus, deterministic effects can be avoided.

Keywords: clinical experimentation, interventional radiology, mathematical model, patient's skin-dose mapping.

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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 infeasible and effective way.

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

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Authors: Morteza Naderi

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The Persian fallow deer was considered as a globally extinct species until 1956 when a small population was rediscovered from Dez Wildlife Refuge and Karkheh Wildlife Refuge in southwestern parts of Iran. After long species rehabilitation process, the species was transplanted to Dasht-e-Naz Wildlife Refuge in northern Iran, and from where, follow deer was introduced to the different selected habitats such as Ashk Island in Lake Uromiyeh National Park. During 12 years, (from 1978 to 1989) 58 individuals (25 males and 33 females) were transferred to Ask Island. The main threat to the established population was related to the freshwater shortage and existing just one single trough such as high mortality rate of adult males during rutting season, snake biting and dilutional hyponatremia. Desiccation of Lake Uromiyeh in recent years raised new challenges to the conservation process, as about 80 individuals, nearly one third of the population were died in 2011. Connection of Island to the mainland caused predators’ accessibility (such as wolf and Jackal) to the Ask Island and higher mortality because of follow deer attraction to the surrounding mainland farms. Conservation team faced such new challenges that may cause introduction plan to be probably failed. Investigations about habitat affinities and carrying capacity are the main basic researches in the management and conservation of the species. Logistic regression analysis showed that the presence of the different fresh water resources as well as Allium akaka and Pistacia atlantica are the main environmental variables affect Follow deer habitat selection. Habitat carrying capacity analysis both in summer and winter seasons indicated that Ashk Island can support 240±30 of Persian follow deer.

Keywords: carrying capacity, follow deer, lake Uromiyeh, microhabitat affinities, population oscillation, predation, sex ratio

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Authors: Ahmed Emad Ahmed

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This paper aims to address the concept of human resources information systems (HRIS) and how to link it to new technologies such as artificial intelligence (AI) to be implemented in two human resources processes. A literature view has been collected to cover the main points related to HRIS, AI, and BC. A study case has been presented by generating a random HRIS to apply some AI operations to it. Then, an algorithm was applied to the database to complete some human resources processes, including training and performance appraisal, using a pre-trained AI model. After that, outputs and results have been presented and discussed briefly. Finally, a conclusion has been introduced to show the ability of new technologies such as AI and ML to be applied to the human resources management processes.

Keywords: human resources new technologies, HR artificial intelligence, HRIS AI models, construction AI HRIS

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Authors: Elabed Saud

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This paper introduces the new ability of Artificial Neural Networks (ANNs) in estimating speed and controlling the separately excited DC motor. The neural control scheme consists of two parts. One is the neural estimator which is used to estimate the motor speed. The other is the neural controller which is used to generate a control signal for a converter. These two neutrals are training by Levenberg-Marquardt back-propagation algorithm. ANNs are the standard three layers feed-forward neural network with sigmoid activation functions in the input and hidden layers and purelin in the output layer. Simulation results are presented to demonstrate the effectiveness of this neural and advantage of the control system DC motor with ANNs in comparison with the conventional scheme without ANNs.

Keywords: Artificial Neural Network (ANNs), excited DC motor, convenional controller, speed Controller

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Authors: Juan Bojórquez, Henry E. Reyes, Edén Bojórquez, Alfredo Reyes-Salazar

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This paper addressed the use of Artificial Intelligence to obtain the structural reliability of reinforced concrete buildings. For this purpose, artificial neuronal networks (ANN) are developed to predict seismic demand hazard curves. In order to have enough input-output data to train the ANN, a set of reinforced concrete buildings (low, mid, and high rise) are designed, then a probabilistic seismic hazard analysis is made to obtain the seismic demand hazard curves. The results are then used as input-output data to train the ANN in a feedforward backpropagation model. The predicted values of the seismic demand hazard curves found by the ANN are then compared. Finally, it is concluded that the computer time analysis is significantly lower and the predictions obtained from the ANN were accurate in comparison to the values obtained from the conventional methods.

Keywords: structural reliability, seismic design, machine learning, artificial neural network, probabilistic seismic hazard analysis, seismic demand hazard curves

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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

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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

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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

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Authors: Luma Vaz, Marcio Port-Carvalho

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The main objective of this research was to study the basics aspects of the ecology of a group of capuchin monkeys (Cebus spp.), evaluating the risks that habit and food that is given by the visitors may cause to the people's health and animals welfare, also how to make proposals for mitigation and management guidelines. In order to do that, some aspects of the animal's ecology (such as diet, habitat range and habitat use) and activity patterns were studied. It was also measured the frequency of contact with visitors at the park using protocols for data collection. The behavioral categories of displacement and resting represent more than 80% of total activities, followed by feeding (13%) and others (6%). When compared to the studies in natural environment, the Cebus group studied has a small living area (1.7ha) occupying mostly the PEAL public area. The diversity of items offered by the visitors and the high frequency of contact closer than one meter suggests that using information and education campaigns must be a priority in the public program in PEAL in order to avoid future accidents and diseases transmissions.

Keywords: capuchin monkeys, Cebus, environmental education, public health, wildlife management

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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

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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: A. Ngunga, M. K. Soviti, S. Nakin

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South Africa is one of the developing countries rich in estuary ecosystem. Previous studies have identified many impacts of land use activities on the pollution status of the estuaries. These land use activity and related practices are often blamed for the many pollution problems affecting the estuaries. For example, the estuarine ecosystems on a global scale are experiencing vast transformations from anthropogenic influences; Buffalo River Estuary is one of the influenced estuaries whereby the sources of pollution are unknown. These problems consequently lead to the degradation of the estuaries. The aim of the research was to establish the factors that have the potential to impact pollution status of Buffalo river estuary. Study focuses on Identifying and mapping land use activities along Buffalo River Estuary. Questionnaire survey, structured interviews, direct observation, GPS survey and ArcGIS mapping were the methods used for data collection in the area, and results were analyzed and presented by ANOVA and Microsoft Excel statistical methods. The results showed that harbour is the main source of pollution, in Buffalo River Estuary, through Ballast water discharge. Therefore that requires more concern for protecting and cleaning the estuary.

Keywords: estuary, land-use activities, pollution, mapping, water pollution

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Authors: Wi-Sun Ryu, Eun-Kee Bae

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Prior studies have shown that patients with right hemispheric stroke are likely to seek medical service compared with those with left hemispheric stroke. However, the underlying mechanism for this phenomenon is unknown. In the present study, we generated lesion probability maps in a patient with right and left middle cerebral artery infarct and statistically compared. We found that precentral gyrus-Brodmann area 44, a language area in the left hemisphere - involvement was significantly higher in patients with left hemispheric stroke. This finding suggests that a language dysfunction was more noticeable, thereby taking more patients to hospitals.

Keywords: cerebral infarct, brain MRI, statistical parametric mapping, middle cerebral infarct

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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

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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

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Authors: Rakesh Kumar Meena, Tanushree Chatterjee

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Okra (Abelmoschus esculentas L. Moench) or lady’s finger is an important vegetable crop belonging to the Malvaceae family. Unfortunately, production and productivity of Okra are majorly affected by Yellow Vein mosaic virus (YVMV). The AO: 189 (resistant parent) X AO: 191(susceptible parent) used for the development of mapping population. The mapping population has 143 individuals (F₂:F₃). Population was characterized by physiological and pathological observations. Screening of 360 DNA markers was performed to survey for parental polymorphism between the contrasting parents’, i.e., AO: 189 and AO: 191. Out of 360; 84 polymorphic markers were used for genotyping of the mapping population. Total markers were distributed into four linkage groups (LG1, LG2, LG3, and LG4). LG3 covered the longest span (106.8cM) with maximum number of markers (27) while LG1 represented the smallest linkage group in terms of length (71.2cM). QTL identification using the composite interval mapping approach detected two prominent QTLs, QTL1 and QTL2 for resistance against YVMV disease. These QTLs were placed between the marker intervals of NBS-LRR72-Path02 and NBS-LRR06- NBS-LRR65 on linkage group 02 and linkage group 04 respectively. The LOD values of QTL1 and QTL2 were 5.7 and 6.8 which accounted for 19% and 27% of the total phenotypic variation, respectively. The findings of this study provide two linked markers which can be used as efficient diagnostic tools to distinguish between YVMV resistant and susceptible Okra cultivars/genotypes. Lines identified as highly resistant against YVMV infection can be used as donor lines for this trait. This will be instrumental in accelerating the trait improvement program in Okra and will substantially reduce the yield losses due to this viral disease.

Keywords: Okra, yellow vein mosaic virus, resistant, linkage map, QTLs

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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

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Authors: Anjana Rajput, Sandeep Chouksey, Bhaskar Bhandari, Shimpi Chourasia

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Ecologically, grassland is any plant community dominated by grasses, whether they exist naturally or because of management practices. Most forest grasslands are anthropogenic and established plant communities planted for forage production, though some are established for soil and water conservation and wildlife habitat. In Satpura Tiger Reserve, Madhya Pradesh, India, most of the grasslands have been established on evacuated village sites. Total of 42 villages evacuated, and study was carried out in 23 sites to evaluate habitat improvement. Grasslands were classified into three categories, i.e., evacuated sites, established sites, and controlled sites. During the present study impact of various management interventions on grassland health was assessed. Grasslands assessment was done for its composition, status of palatable and non-palatable grasses, the status of herbs and legumes, status of weeds species, and carrying capacity of particular grassland. Presence of wild herbivore species in the grasslands with their abundance, availability of water resources was also assessed. Grassland productivity is dependent mainly on the biotic and abiotic components of the area, but management interventions may also play an important role in grassland composition and productivity. Variation in the status of palatable and non-palatable grasses, legumes, and weeds was recorded and found effected by management intervention practices. Overall in all the studied grasslands, the most dominant grasses recorded are Themeda quadrivalvis, Dichanthium annulatum, Ischaemum indicum, Oplismenus burmanii, Setaria pumilla, Cynodon dactylon, Heteropogon contortus, and Eragrostis tenella. Presence of wild herbivores, i.e., Chital, Sambar, Bison, Bluebull, Chinkara, Barking deer in the grassland area has been recorded through the installation of camera traps and estimated their abundance. Assessment of developed grasslands was done in terms of habitat suitability for Chital (Axis axis) and Sambar (Rusa unicolor). The parameters considered for suitability modeling are biotic and abiotic life requisite components existing in the area, i.e., density of grasses, density of legumes, availability of water, site elevation, site distance from human habitation. Findings of the present study would be useful for further grassland management and animal translocation programmes.

Keywords: carrying capacity, dominant grasses, grassland, habitat suitability, management intervention, wild herbivore

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Authors: Hongbo Zhang, Xinlu Tang, Jiangwei Li, Chi Yan

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Home zone parking pilot (HPP) is a fast-growing segment in low-speed autonomous driving applications. It requires the car automatically cruise around a parking lot and park itself in a range of up to 100 meters inside a recurrent home/office parking lot, which requires precise parking lot mapping and localization solution. Although Lidar is ideal for SLAM, the car OEMs favor a low-cost fish-eye camera based visual SLAM approach. Recent approaches have employed segmentation models to extract semantic features and improve mapping accuracy, but these AI models are memory unfriendly and computationally expensive, making deploying on embedded ADAS systems difficult. To address this issue, we proposed a new method that utilizes object detection models to extract robust and accurate parking lot features. The proposed method could reduce computational costs while maintaining high accuracy. Once combined with vehicles’ wheel-pulse information, the system could construct maps and locate the vehicle in real-time. This article will discuss in detail (1) the fish-eye based Around View Monitoring (AVM) with transparent chassis images as the inputs, (2) an Object Detection (OD) based feature point extraction algorithm to generate point cloud, (3) a low computational parking lot mapping algorithm and (4) the real-time localization algorithm. At last, we will demonstrate the experiment results with an embedded ADAS system installed on a real car in the underground parking lot.

Keywords: ADAS, home zone parking pilot, object detection, visual SLAM

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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

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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: Abishek Poudel

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Human-tiger conflicts are serious issues of conflicts between local people and park authority and the conflicting situation potentially play negative role in park management. The study aimed (1) To determine the trend and nature of human-tiger conflicts (2) To understand people's perception and mitigation measures towards tiger conservation. Both primary and secondary information were used to determine human- tiger conflicts in Chitwan National Park. Systematic random sampling with 5% intensity was done to collect the perception of the villagers regarding human-tiger conflicts. The study sites were selected based on frequencies of incidences of human attacks and livestock depredation viz. Rajahar and Ayodhyapuri VDCs respectively. The trend of human casualties by tiger has increased in last five year whereas the trend of livestock has decreased. Reportedly, between 2008 and 2012, tigers killed 22 people, injured 10 and killed at least 213 livestock. Conflict was less common in the park and more intense in the sub-optimal habitats of Buffer Zone. Goat was the most vulnerable livestock followed by cattle. The livestock grazing and human intrusion into tiger habitat were the causes of conflicts. Developing local stewardship and support for tiger conservation, livestock insurance, and compensation policy simplification may help reduce human-tiger conflicts.

Keywords: livestock depredation, sub optimal habitat, human-tiger, local stewardship

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Authors: Hassan Masoumi, Ahad Salimi, Nazanin Barhemmat, Babak Gholami

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Artificial neural networks have gained a lot of interest as empirical models for their powerful representational capacity, multi input and output mapping characteristics. In fact, most feed-forward networks with nonlinear nodal functions have been proved to be universal approximates. In this paper, we propose a new supervised method for color image classification based on self organizing feature maps (SOFM). This algorithm is based on competitive learning. The method partitions the input space using self-organizing feature maps to introduce the concept of local neighborhoods. Our image classification system entered into RGB image. Experiments with simulated data showed that separability of classes increased when increasing training time. In additional, the result shows proposed algorithms are effective for color image classification.

Keywords: classification, SOFM algorithm, neural network, neighborhood, RGB image

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Authors: Yusuf Turan

Abstract:

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: Abdulrahman S. Shryan Aldossary

Abstract:

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

Procedia PDF Downloads 159