Search results for: artificial recharge site

Authors: Ngo the Bach

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Information technology and communications are growing strongly and penetrated almost the entire Vietnamese economy and society. The article presents an overview of information technology and application communications in the management the Central Sector of the Imperial Citadel of Thang Long (Hanoi, Vietnam) - A World Heritage Site. The author also points out the opportunities and challenges of the information technology and communications in the sectors of culture and heritage; the use of information technology as an effective tool to develop mass and interactive communications. The article emphasizes on the advantage of information technology and communications in supporting effectively the management reform with respect to the Imperial Citadel of Thang Long in particular and the management of world heritage sites in Vietnam in general.

Keywords: information technology, communications, management, culture, heritage

Procedia PDF Downloads 325

Authors: Alò Roberta, Bottiglione Francesco, Mantriota Giacomo

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The efficiency of the actuation system of lower limb exoskeletons and of active orthoses is a significant aspect of the design of such devices because it affects their efficacy. F-IVT is an innovative actuation system to power artificial knee joint with energy recovery capabilities. Its key and non-conventional elements are a flywheel, that acts as a mechanical energy storage system, and an Infinitely Variable Transmission (IVT). The design of the F-IVT can be optimized for a certain walking condition, resulting in a heavy reduction of both the electric energy consumption and of the electric peak power. In this work, by means of simulations of level ground walking at different speeds, it is demonstrated how F-IVT is still an advantageous actuator, even when it does not work in nominal conditions.

Keywords: active orthoses, actuators, lower extremity exoskeletons, knee joint

Procedia PDF Downloads 596

Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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Authors: Hayder H. Kareem, Shunqi Pan

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Groundwater is a vital water resource in many areas in the world, particularly in the Middle-East region where the water resources become scarce and depleting. Sustainable management and planning of the groundwater resources become essential and urgent given the impact of the global climate change. In the recent years, numerical models have been widely used to predict the flow pattern and assess the water resources security, as well as the groundwater quality affected by the contaminants transported. In this study, MODFLOW is used to study the current status of groundwater resources and the risk of water resource security in the region centred at Al-Najaf City, which is located in the mid-west of Iraq and adjacent to the Euphrates River. In this study, a conceptual model is built using the geologic and hydrogeologic collected for the region, together with the Digital Elevation Model (DEM) data obtained from the "Global Land Cover Facility" (GLCF) and "United State Geological Survey" (USGS) for the study area. The computer model is also implemented with the distributions of 69 wells in the area with the steady pro-defined hydraulic head along its boundaries. The model is then applied with the recharge rate (from precipitation) of 7.55 mm/year, given from the analysis of the field data in the study area for the period of 1980-2014. The hydraulic conductivity from the measurements at the locations of wells is interpolated for model use. The model is calibrated with the measured hydraulic heads at the locations of 50 of 69 wells in the domain and results show a good agreement. The standard-error-of-estimate (SEE), root-mean-square errors (RMSE), Normalized RMSE and correlation coefficient are 0.297 m, 2.087 m, 6.899% and 0.971 respectively. Sensitivity analysis is also carried out, and it is found that the model is sensitive to recharge, particularly when the rate is greater than (15mm/year). Hydraulic conductivity is found to be another parameter which can affect the results significantly, therefore it requires high quality field data. The results show that there is a general flow pattern from the west to east of the study area, which agrees well with the observations and the gradient of the ground surface. It is found that with the current operational pumping rates of the wells in the area, a dry area is resulted in Al-Najaf City due to the large quantity of groundwater withdrawn. The computed water balance with the current operational pumping quantity shows that the Euphrates River supplies water into the groundwater of approximately 11759 m3/day, instead of gaining water of 11178 m3/day from the groundwater if no pumping from the wells. It is expected that the results obtained from the study can provide important information for the sustainable and effective planning and management of the regional groundwater resources for Al-Najaf City.

Keywords: Al-Najaf city, conceptual modelling, groundwater, unconfined aquifer, visual MODFLOW

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Authors: Thomas Schalow

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This paper posits the need to take a cross-cultural approach to communication with non-human cultures and intelligences in order to meet the following three imminent contingencies: communicating with sentient biological intelligences, communicating with extraterrestrial intelligences, and communicating with artificial super-intelligences. The paper begins with a discussion of how intelligence emerges. It disputes some common assumptions we maintain about consciousness, intention, and language. The paper next explores cross-cultural communication among humans, including non-sapiens species. The next argument made is that we need to become much more serious about communicating with the non-human, intelligent life forms that already exist around us here on Earth. There is an urgent need to broaden our definition of communication and reach out to the other sentient life forms that inhabit our world. The paper next examines the science and philosophy behind CETI (communication with extraterrestrial intelligences) and how it has proven useful, even in the absence of contact with alien life. However, CETI’s assumptions and methodology need to be revised and based on the cross-cultural approach to communication proposed in this paper if we are truly serious about finding and communicating with life beyond Earth. The final theme explored in this paper is communication with non-biological super-intelligences using a cross-cultural communication approach. This will present a serious challenge for humanity, as we have never been truly compelled to converse with other species, and our failure to seriously consider such intercourse has left us largely unprepared to deal with communication in a future that will be mediated and controlled by computer algorithms. Fortunately, our experience dealing with other human cultures can provide us with a framework for this communication. The basic assumptions behind intercultural communication can be applied to the many types of communication envisioned in this paper if we are willing to recognize that we are in fact dealing with other cultures when we interact with other species, alien life, and artificial super-intelligence. The ideas considered in this paper will require a new mindset for humanity, but a new disposition will prepare us to face the challenges posed by a future dominated by artificial intelligence.

Keywords: artificial intelligence, CETI, communication, culture, language

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Authors: Yung-Chung Chuang

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Current situation and accumulated development of archaeological sites have very high impacts on the preservation value of the site. This research set 3 archaeological sites in Taiwan as study areas. Assessment of the degree of destruction of cultural layers due to land use change and geomorphological change were conducted with aerial photographs (1976-1978; 2016-2017) and digital aerial survey technology on 2D and 3D geographic information system platforms. The results showed that the archaeological sites were all seriously influenced due to the high land use intensity between 1976-2017. Geomorphological changes caused by human cultivation and engineering construction were main causes of site destruction, especially in private lands. Therefore, urban planning methods for land acquisition or land regulation are necessary.

Keywords: archaeological sites, accumulated development, destruction of cultural layers, geomorphological changes

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Authors: Jen Wang, Wei-Chia Hsu, Zih-Sin Wang, Ching-Ping Chu, Bo-Shiou Guo

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In the late 19th century, the Jinguashi ore deposit in northern Taiwan was discovered, and accompanied with flourishing mining activities. However, tons of contaminants including heavy metals, sulfur dioxide, and total petroleum hydrocarbons (TPH) were released to surroundings and caused environmental problems. Site T was one of copper smelter located on the coastal hill near Jinguashi ore deposit. In over ten years of operation, variety contaminants were emitted that it polluted the surrounding soil and groundwater quality. In order to exhaust fumes produced from smelting process, three stacks were built along the hill behind the factory. The sediment inside the stacks contains high concentration of heavy metals such as arsenic, lead, copper, etc. Moreover, soil around the discarded stacks suffered a serious contamination when deposition leached from the ruptures of stacks. Consequently, Site T (including the factory and its surroundings) was declared as a pollution remediation site that visiting the site and land-use activities on it are forbidden. However, the natural landscape and cultural attractions of Site T are spectacular that it attracts a lot of visitors annually. Moreover, land resources are extremely precious in Taiwan. In addition, Taiwan Environmental Protection Administration (EPA) is actively promoting the contaminated land revitalization policy. Therefore, this study took Site T as case study for brownfield revitalization planning to the limits of activate and remediate the natural resources. Land-use suitability analysis and risk mapping were applied in this study to make appropriate risk management measures and redevelopment plan for the site. In land-use suitability analysis, surrounding factors into consideration such as environmentally sensitive areas, biological resources, land use, contamination, culture, and landscapes were collected to assess the development of each area; health risk mapping was introduced to show the image of risk assessments results based on the site contamination investigation. According to land-use suitability analysis, the site was divided into four zones: priority area (for high-efficiency development), secondary area (for co-development with priority area), conditional area (for reusing existing building) and limited area (for Eco-tourism and education). According to the investigation, polychlorinated biphenyls (PCB), heavy metals and TPH were considered as target contaminants while oral, inhalation and dermal would be the major exposure pathways in health risk assessment. In accordance with health risk map, the highest risk was found in the southwest and eastern side. Based on the results, the development plan focused on zoning and land use. Site T was recommended be divides to public facility zone, public architectonic art zone, viewing zone, existing building preservation zone, historic building zone, and cultural landscape zone for various purpose. In addition, risk management measures including sustained remediation, extinguish exposure and administration management are applied to ensure particular places are suitable for visiting and protect the visitors’ health. The consolidated results are corroborated available by analyzing aspects of law, land acquired method, maintenance and management and public participation. Therefore, this study has a certain reference value to promote the contaminated land revitalization policy in Taiwan.

Keywords: brownfield revitalization, land-use suitability analysis, health risk map, risk management

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Authors: Jeferson Brito Fernades, Breno Padovezi Rocha, Roger Augusto Rodrigues, Heraldo Luiz Giacheti

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The geotechnical projects demand the appropriate knowledge of soil characteristics and parameters. The determination of geotechnical soil parameters can be done by means of laboratory or in situ tests. In countries with tropical weather, like Brazil, unsaturated soils are very usual. In these soils, the soil suction has been recognized as an important stress state variable, which commands the geo-mechanical behavior. Triaxial and direct shear tests on saturated soils samples allow determine only the minimal soil shear strength, in other words, no suction contribution. This paper briefly describes the triaxial test with controlled suction as well as discusses the influence of suction on the shear strength parameters of a lateritic tropical sandy soil from a Brazilian research site. In this site, a sample pit was excavated to retrieve disturbed and undisturbed soil blocks. The samples extracted from these blocks were tested in laboratory to represent the soil from 1.5, 3.0 and 5.0 m depth. The stress curves and shear strength envelopes determined by triaxial tests varying suction and confining pressure are presented and discussed. The water retention characteristics on this soil complement this analysis. In situ CPT tests were also carried out at this site in different seasons of the year. In this case, the soil suction profile was determined by means of the soil water retention. This extra information allowed assessing how soil suction also affected the CPT data and the shear strength parameters estimative via correlation. The major conclusions of this paper are: the undisturbed soil samples contracted before shearing and the soil shear strength increased hyperbolically with suction; and it was possible to assess how soil suction also influenced CPT test data based on the water content soil profile as well as the water retention curve. This study contributed with a better understanding of the shear strength parameters and the soil variability of a typical unsaturated tropical soil.

Keywords: site characterization, triaxial test, CPT, suction, variability

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Authors: Nabilah Filzah Mohd Radzuan, Andi Putra, Zalinda Othman, Azuraliza Abu Bakar, Abdul Razak Hamdan

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Precipitation forecast is important to avoid natural disaster incident which can cause losses in the involved area. This paper reviews three techniques logistic regression, decision tree, and random forest which are used in making precipitation forecast. These combination techniques through the vector auto-regression (VAR) model help in finding the advantages and strengths of each technique in the forecast process. The data-set contains variables of the rain’s domain. Adaptation of artificial intelligence techniques involved in rain domain enables the forecast process to be easier and systematic for precipitation forecast.

Keywords: logistic regression, decisions tree, random forest, VAR model

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Authors: Balamurali Gunji, B. B. V. L. Deepak, B. B. Biswal, Amrutha Rout, Golak Bihari Mohanta

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Robots play an important role in the operations like pick and place, assembly, spot welding and much more in manufacturing industries. Out of those, assembly is a very important process in manufacturing, where 20% of manufacturing cost is wholly occupied by the assembly process. To do the assembly task effectively, Assembly Sequences Planning (ASP) is required. ASP is one of the multi-objective non-deterministic optimization problems, achieving the optimal assembly sequence involves huge search space and highly complex in nature. Many researchers have followed different algorithms to solve ASP problem, which they have several limitations like the local optimal solution, huge search space, and execution time is more, complexity in applying the algorithm, etc. By keeping the above limitations in mind, in this paper, a new automated optimal robotic assembly sequence planning using Artificial Bee Colony (ABC) Algorithm is proposed. In this algorithm, automatic extraction of assembly predicates is done using Computer Aided Design (CAD) interface instead of extracting the assembly predicates manually. Due to this, the time of extraction of assembly predicates to obtain the feasible assembly sequence is reduced. The fitness evaluation of the obtained feasible sequence is carried out using ABC algorithm to generate the optimal assembly sequence. The proposed methodology is applied to different industrial products and compared the results with past literature.

Keywords: assembly sequence planning, CAD, artificial Bee colony algorithm, assembly predicates

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Authors: Shalini Tripathi, Pardeep Kumar

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The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

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Authors: Zhengkun Yi

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Surface texture discrimination using artificial tactile sensors has attracted increasing attentions in the past decade as it can endow technical and robot systems with a key missing ability. However, as a major component of texture, roughness has rarely been explored. This paper presents an approach for tactile surface roughness discrimination, which includes two parts: (1) design and fabrication of a bioinspired artificial fingertip, and (2) tactile signal processing for tactile surface roughness discrimination. The bioinspired fingertip is comprised of two polydimethylsiloxane (PDMS) layers, a polymethyl methacrylate (PMMA) bar, and two perpendicular polyvinylidene difluoride (PVDF) film sensors. This artificial fingertip mimics human fingertips in three aspects: (1) Elastic properties of epidermis and dermis in human skin are replicated by the two PDMS layers with different stiffness, (2) The PMMA bar serves the role analogous to that of a bone, and (3) PVDF film sensors emulate Meissner’s corpuscles in terms of both location and response to the vibratory stimuli. Various extracted features and classification algorithms including support vector machines (SVM) and k-nearest neighbors (kNN) are examined for tactile surface roughness discrimination. Eight standard rough surfaces with roughness values (Ra) of 50 μm, 25 μm, 12.5 μm, 6.3 μm 3.2 μm, 1.6 μm, 0.8 μm, and 0.4 μm are explored. The highest classification accuracy of (82.6 ± 10.8) % can be achieved using solely one PVDF film sensor with kNN (k = 9) classifier and the standard deviation feature.

Keywords: bioinspired fingertip, classifier, feature extraction, roughness discrimination

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Authors: Leila Najeh Bel'Kiry

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Artificial intelligence (AI) brought about many language robots, with ChatGPT being the most sophisticated thanks to its human-like linguistic capabilities. This aspect raises the idea of using ChatGPT in learning foreign languages. Starting from the premise that positions ChatGPT as a mediator between the language and the leaner, functioning as a “ghost teacher" offering a peaceful and secure learning space, this study aims to explore the attitudes of Tunisian students of English towards ChatGPT as a “Foreign Language Teacher” . Forty-five students, in their third year of fundamental English at Tunisian universities and high institutes, completed a Likert scale questionnaire consisting of thirty-two items and covering various aspects of language (phonology, morphology, syntax, semantics, and pragmatics). A scale ranging from 'Strongly Disagree,' 'Disagree,' 'Undecided,' 'Agree,' to 'Strongly Agree.' is used to assess the attitudes of the participants towards the integration of ChaGPTin learning a foreign language. Results indicate generally positive attitudes towards the reliance on ChatGPT in learning foreign languages, particularly some compounds of language like syntax, phonology, and morphology. However, learners show insecurity towards ChatGPT when it comes to pragmatics and semantics, where the artificial model may fail when dealing with deeper contextual and nuanced language levels.

Keywords: artificial language model, attitudes, foreign language learning, ChatGPT, linguistic capabilities, Tunisian English language learners

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Authors: Meng-Hui Chen, Chen-Yu Kao, Chia-Yu Hsu, Pei-Chann Chang

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The main idea in this paper is using sequential pattern mining to find the information which is helpful for finding high performance solutions. By combining this information, it is defined as blocks. Using the blocks to generate artificial chromosomes (ACs) could improve the structure of solutions. Estimation of Distribution Algorithms (EDAs) is adapted to solve the combinatorial problems. Nevertheless many of these approaches are advantageous for this application, but only some of them are used to enhance the efficiency of application. Generating ACs uses patterns and EDAs could increase the diversity. According to the experimental result, the algorithm which we proposed has a better performance to solve the permutation flow-shop problems.

Keywords: combinatorial problems, sequential pattern mining, estimationof distribution algorithms, artificial chromosomes

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Authors: Dirk Briskorn, Michael Dienstknecht

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Cranes are a key element in construction projects as they are the primary lifting equipment and among the most expensive construction equipment. Thus, selecting cranes and locating them on-site is an important factor for a project's profitability. We focus on a site with supply and demand areas that have to be connected by tower cranes. There are several types of tower cranes differing in certain specifications such as costs or operating radius. The objective is to select cranes and determine their locations such that each demand area is connected to its supply area at minimum cost. We detail the problem setting and show how to obtain a discrete set of candidate locations for each crane type without losing optimality. This discretization allows us to reduce our problem to the classic set cover problem. Despite its NP-hardness, we achieve good results employing a standard solver and a greedy heuristic, respectively.

Keywords: positioning, selection, standard solver, tower cranes

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Authors: Mohammad Heidari

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In this paper a method for high strength steel is proposed of residual stresses in autofrettaged tubes by combination of artificial neural networks is presented. Many different thick walled cylinders that were subjected to different conditions were studied. At first, the residual stress is calculated by analytical solution. Then by changing of the parameters that influenced in residual stresses such as percentage of autofrettage, internal pressure, wall ratio of cylinder, material property of cylinder, bauschinger and hardening effect factor, a neural network is created. These parameters are the input of network. The output of network is residual stress. Numerical data, employed for training the network and capabilities of the model in predicting the residual stress has been verified. The output obtained from neural network model is compared with numerical results, and the amount of relative error has been calculated. Based on this verification error, it is shown that the radial basis function of neural network has the average error of 2.75% in predicting residual stress of thick wall cylinder. Further analysis of residual stress of thick wall cylinder under different input conditions has been investigated and comparison results of modeling with numerical considerations shows a good agreement, which also proves the feasibility and effectiveness of the adopted approach.

Keywords: thick walled cylinder, residual stress, radial basis, artificial neural network

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Authors: Tewelde Gebreslassie Gebreanenia, Frie Ayalew Yimam, Seada Hussen Adem

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Patient safety and quality of care are essential goals of health care delivery, but they are often compromised by human errors, system failures, or resource constraints. In a variety of healthcare contexts, artificial intelligence (AI), a quickly developing field, can provide fresh approaches to enhancing patient safety and treatment quality. Artificial Intelligence (AI) has the potential to decrease errors and enhance patient outcomes by carrying out tasks that would typically require human intelligence. These tasks include the detection and prevention of adverse events, monitoring and warning patients and clinicians about changes in vital signs, symptoms, or risks, offering individualized and evidence-based recommendations for diagnosis, treatment, or prevention, and assessing and enhancing the effectiveness of health care systems and services. This study examines the state-of-the-art and potential future applications of AI-based technologies for enhancing patient safety and care quality, as well as the opportunities and problems they present for patients, policymakers, researchers, and healthcare providers. In order to ensure the safe, efficient, and responsible application of AI in healthcare, the paper also addresses the ethical, legal, social, and technical challenges that must be addressed and regulated.

Keywords: artificial intelligence, health care, human intelligence, patient safty, quality of care

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Authors: Mehrdad Taghipour, Mina Rostami, Mahdi Eskandarlou

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Partial-thickness skin graft is the cornerstone for scalp defect repair. Given the potential side effects following harvesting from these sites, this study aimed to compare the outcomes of graft harvesting from scalp and lower limb. This clinical trial was conducted among a sample number of 40 partial thickness graft candidates (20 case and 20 control group) with scalp defect presenting to Plastic Surgery Clinic at Besat Hospital, Hamadan, Iran during 2018-2019. Sampling was done by simple randomization using random digit table. The donor site in case group and control group was scalp and lower limb respectively. Overall, 28 patients (70%) were male and 12 (30%) were female. Basal cell carcinoma (BCC) and trauma were the most common etiology for the defects. There was a statistically meaningful relationship between two groups regarding the etiology of defect (P=0.02). The mean diameter of defect was 24.28±45.37 mm for all of the patients. The difference between diameters of defect in both groups were statistically meaningful while no such difference between graft diameters was seen. The graft “Take” was completely successful in both groups according to evaluations. The level of postoperative pain was lower in the case group compared to the control according to VAS scale and the satisfaction was higher in them per Likert scale. Scalp can safely be used as donor site for skin graft to be used for scalp defects associated with better results and lower complication rates compared to other donor sites.

Keywords: donor site, graft, scalp, partial thickness

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Authors: Hsien-Tsen Wang

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Business Intelligence (BI) has long helped organizations make informed decisions based on data-driven insights and gain competitive advantages in the marketplace. In the past two decades, businesses witnessed not only the dramatically increasing volume and heterogeneity of business data but also the emergence of new technologies, such as Artificial Intelligence (AI), Semantic Web (SW), Cloud Computing, and Big Data. It is plausible that the convergence of these technologies would bring more value out of business data by establishing linked data frameworks and connecting in ways that enable advanced analytics and improved data utilization. In this paper, we first review and summarize current BI applications and methodology. Emerging technologies that can be integrated into BI applications are then discussed. Finally, we conclude with a proposed synergy framework that aims at achieving a more flexible, scalable, and intelligent BI solution.

Keywords: business intelligence, artificial intelligence, semantic web, big data, cloud computing

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Authors: Sayor Ajfar Aaron, Mushfiqur Rahman, Sajjat Hossain Abir, Ashif Newaz

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This study delves into the development of an artificial intelligence application designed for real-time emotion recognition from human vocal patterns. Utilizing advanced machine learning algorithms, including deep learning and neural networks, the paper highlights both the technical challenges and potential opportunities in accurately interpreting emotional cues from speech. Key findings demonstrate the critical role of diverse training datasets and the impact of ambient noise on recognition accuracy, offering insights into future directions for improving robustness and applicability in real-world scenarios.

Keywords: artificial intelligence, convolutional neural network, emotion recognition, vocal patterns

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Authors: Eleni Maistrou, D. Kosmopoulos, Carolina Moretti, Amalia Konidi, Katerina Boulougoura

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InterArch is an ongoing research project that has been running since September 2020. It aims to propose the design of a site-based digital application for archaeological sites and outdoor guided tours, supporting virtual and augmented reality technology. The research project is co‐financed by the European Union and Greek national funds, through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH - CREATE – INNOVATE (project code: Τ2ΕΔΚ-01659). It involves mutual collaboration between academic and cultural institutions and the contribution of an IT applications development company. The research will be completed by July 2023 and will run as a pilot project for the city of Ancient Messene, a place of outstanding natural beauty in the west of Peloponnese, which is considered one of the most important archaeological sites in Greece. The applied research project integrates an interactive approach to the natural environment, aiming at a manifold sensory experience. It combines the physical space of the archaeological site with the digital space of archaeological and cultural data while at the same time, it embraces storytelling processes by engaging an interdisciplinary approach that familiarizes the user with multiple semantic interpretations. The mingling of the real-world environment with its digital and cultural components by using augmented reality techniques could potentially transform the visit on-site into an immersive multimodal sensory experience. To this purpose, an extensive spatial analysis along with a detailed evaluation of the existing digital and non-digital archives is proposed in our project, intending to correlate natural landscape morphology (including archaeological material remains and environmental characteristics) with the extensive historical records and cultural digital data. On-site research was carried out, during which visitors’ itineraries were monitored and tracked throughout the archaeological visit using GPS locators. The results provide our project with useful insight concerning the way visitors engage and interact with their surroundings, depending on the sequence of their itineraries and the duration of stay at each location. InterArch aims to propose the design of a site-based digital application for archaeological sites and outdoor guided tours, supporting virtual and augmented reality technology. Extensive spatial analysis, along with a detailed evaluation of the existing digital and non-digital archives, is used in our project, intending to correlate natural landscape morphology with the extensive historical records and cultural digital data. The results of the on-site research provide our project with useful insight concerning the way visitors engage and interact with their surroundings, depending on the sequence of their itineraries and the duration of stay at each location.

Keywords: archaeological site, digital space, semantic interpretations, cultural heritage

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Authors: Hamed Sadeghi, Pouya A. Panahi, Hamed Nasiri, Mohammad Sadeghi

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Collapsible soils like loess comprise an important category of problematic soils for construction purposes and sustainable development. As a result, research on both geological and geotechnical aspects of this type of soil have been in progress for decades. However, considerable natural variability in physical properties of in-situ loess strata even in a single block sample challenges the fundamental laboratory investigations. The reason behind this is that it is somehow impossible to remove the effect of a specific factor like void ratio from fair comparisons to come with a reliable conclusion. In order to cope with this limitation, two types of artificially made dispersive and calcareous loess are introduced which can be easily reproduced in any soil mechanics laboratory provided that all its compositions are known and controlled. The collapse potential is explored for a variety of soil water salinity and lime content and comparisons are made against the natural soil behavior. Trends are reported for the influence of pore water salinity on collapse potential under different osmotic flow conditions. The most important advantage of artificial loess is the ease of controlling cementing agent content like calcite or dispersive potential for studying their influence on mechanical soil behavior.

Keywords: artificial loess, unsaturated soils, collapse potential, dispersive clays, laboratory tests

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Authors: Waleed Basuliman

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Anthropometric dimensions are considered one of the important factors when designing human-machine systems. In this study, the estimation of anthropometric dimensions has been improved by using Artificial Neural Network (ANN) model that is able to predict the anthropometric measurements of Saudi males in Riyadh City. A total of 1427 Saudi males aged 6 to 60 years participated in measuring 20 anthropometric dimensions. These anthropometric measurements are considered important for designing the work and life applications in Saudi Arabia. The data were collected during eight months from different locations in Riyadh City. Five of these dimensions were used as predictors variables (inputs) of the model, and the remaining 15 dimensions were set to be the measured variables (Model’s outcomes). The hidden layers varied during the structuring stage, and the best performance was achieved with the network structure 6-25-15. The results showed that the developed Neural Network model was able to estimate the body dimensions of Saudi male population in Riyadh City. The network's mean absolute percentage error (MAPE) and the root mean squared error (RMSE) were found to be 0.0348 and 3.225, respectively. These results were found less, and then better, than the errors found in the literature. Finally, the accuracy of the developed neural network was evaluated by comparing the predicted outcomes with regression model. The ANN model showed higher coefficient of determination (R2) between the predicted and actual dimensions than the regression model.

Keywords: artificial neural network, anthropometric measurements, back-propagation

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Authors: M. Unis, S. Turky, A. Elalem, A. Meshrghi

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The Esterification kinetics of acetic acid with isopropnol in the presence of sulfuric acid as a homogenous catalyst was studied with isothermal batch experiments at 60,70 and 80°C and at a different molar ratio of isopropnol to acetic acid. Investigation of kinetics of the reaction indicated that the low of molar ratio is favored for esterification reaction, this is due to the reaction is catalyzed by acid. The maximum conversion, approximately 60.6% was obtained at 80°C for molar ratio of 1:3 acid : alcohol. It was found that increasing temperature of the reaction, increases the rate constant and conversion at a certain mole ratio, that is due to the esterification is exothermic. The homogenous reaction has been described with simple power-law model. The chemical equilibrium combustion calculated from the kinetic model in agreement with the measured chemical equilibrium.

Keywords: artificial flavors, esterification, chemical equilibria, isothermal

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Authors: R. Sharma, J. K. Bhatnagar, Poonam, R. C. Sharma

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Metal–air batteries have been designed and developed as an essential source of electric power to propel automobiles, make electronic equipment functional, and use them as the source of power in remote areas and space. High energy and power density, lightweight, easy recharge capabilities, and low cost are essential features of these batteries. Both primary and rechargeable magnesium air batteries are highly promising. Our focus will be on the basics of electrode reaction kinetics of Mg–air cell in this paper. Design and development of Mg or Mg alloys as anode materials, design and composition of air cathode, and promising electrolytes for Mg–air batteries have been reviewed. A brief note on the possible and proposed improvements in design and functionality is also incorporated. This article may serve as the primary and premier document in the critical research area of Mg-air battery systems.

Keywords: air cathode, battery design, magnesium air battery, magnesium anode, rechargeable magnesium air battery

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Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

Abstract:

Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

Procedia PDF Downloads 123

Authors: Xiaochen Mu

Abstract:

Whether in common law countries that adhere to the "commercial copyright theory" or in civil law countries that center around "author's rights," the standards for judging originality have undergone continuous adjustments in response to the development of information technology. The adherence to originality standards does not arbitrarily dictate that all types of works be judged according to a single standard of originality, nor does it rigidly ignore the changes in creative methods and dissemination models brought about by technology. Adjustments and interpretations should be allowed based on the different forms of expression of works. Appropriate adjustments and interpretations are our response to technological advancements. However, what should be upheld are the principles and bottom lines of these adjustments and interpretations, namely the legislative intent and purpose of copyright law, which are to encourage the creation and dissemination of outstanding cultural works and to promote the flourishing of culture.

Keywords: generative artificial intelligence, originality, works, copyright

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Authors: Leonard Kabeya Mukeba Yakasham

Abstract:

The theoretical machinery from singularity theory introduced by Glolubitsky, Stewart, and Schaeffer, to study equivariant bifurcation problem is completed and expanded wile generalized to the multiparameter context. In this setting the finite deterinancy theorem or normal forms, the stability of equivariant bifurcation problem, and the structural stability of universal unfolding are discussed. With Yakam Matrix the solutions are limited for some partial differential equations stochastic nonlinear of the open questions in singularity artificial intelligence for future.

Keywords: equivariant bifurcation, symmetry singularity, equivariant jets and transversality; normal forms, universal unfolding instability, structural stability, artificial intelligence, pdens, yakam matrix

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Authors: Yudhitya Kusumawati, Yuki Mitsuya, Tomooki Shiba, Mitsuru Uesaka

Abstract:

After the Fukushima Daiichi nuclear power reactor incident, there are a lot of unaccountable nuclear fuel debris in the reactor core area, which is subject to safeguard and criticality safety. Before the actual precise analysis is performed, preliminary on-site screening and mapping of nuclear debris activity need to be performed to provide a reliable data on the nuclear debris mass-extraction planning. Through a collaboration project with Japan Atomic Energy Agency, an on-site nuclear debris screening system by using dual energy X-Ray inspection and neutron energy resonance analysis has been established. By using the compact and mobile pulsed neutron source constructed from 3.95 MeV X-Band electron linac, coupled with Tungsten as electron-to-photon converter and Beryllium as a photon-to-neutron converter, short-distance neutron Time of Flight measurement can be performed. Experiment result shows this system can measure neutron energy spectrum up to 100 eV range with only 2.5 meters Time of Flightpath in regards to the X-Band accelerator’s short pulse. With this, on-site neutron Time of Flight measurement can be used to identify the nuclear debris isotope contents through Neutron Resonance Transmission Analysis (NRTA). Some preliminary NRTA experiments have been done with Tungsten sample as dummy nuclear debris material, which isotopes Tungsten-186 has close energy absorption value with Uranium-238 (15 eV). The results obtained shows that this system can detect energy absorption in the resonance neutron area within 1-100 eV. It can also detect multiple elements in a material at once with the experiment using a combined sample of Indium, Tantalum, and silver makes it feasible to identify debris containing mixed material. This compact neutron Time of Flight measurement system is a great complementary for dual energy X-Ray Computed Tomography (CT) method that can identify atomic number quantitatively but with 1-mm spatial resolution and high error bar. The combination of these two measurement methods will able to perform on-site nuclear debris screening at Fukushima Daiichi reactor core area, providing the data for nuclear debris activity mapping.

Keywords: neutron source, neutron resonance, nuclear debris, time of flight

Procedia PDF Downloads 232

Authors: Ismail Abubakar, Hamid Mehrabi, Reg Morton

Abstract:

Currently, extensive signal analysis is performed in order to evaluate structural health of turbomachinery blades. This approach is affected by constraints of time and the availability of qualified personnel. Thus, new approaches to blade dynamics identification that provide faster and more accurate results are sought after. Generally, modal analysis is employed in acquiring dynamic properties of a vibrating turbomachinery blade and is widely adopted in condition monitoring of blades. The analysis provides useful information on the different modes of vibration and natural frequencies by exploring different shapes that can be taken up during vibration since all mode shapes have their corresponding natural frequencies. Experimental modal testing and finite element analysis are the traditional methods used to evaluate mode shapes with limited application to real live scenario to facilitate a robust condition monitoring scheme. For a real time mode shape evaluation, rapid evaluation and low computational cost is required and traditional techniques are unsuitable. In this study, artificial neural network is developed to evaluate the mode shape of a lab scale rotating blade assembly by using result from finite element modal analysis as training data. The network performance evaluation shows that artificial neural network (ANN) is capable of mapping the correlation between natural frequencies and mode shapes. This is achieved without the need of extensive signal analysis. The approach offers advantage from the perspective that the network is able to classify mode shapes and can be employed in real time including simplicity in implementation and accuracy of the prediction. The work paves the way for further development of robust condition monitoring system that incorporates real time mode shape evaluation.

Keywords: modal analysis, artificial neural network, mode shape, natural frequencies, pattern recognition

Procedia PDF Downloads 153