Search results for: artificial artery

Authors: Lourdita Llanto

Abstract:

This study described and assessed the implementation of artificial insemination (AI) for cattle and carabaos in the Bicol Region, Philippines: Albay, Sorsogon and Camarines Sur. Three hundred respondents were interviewed. Results were analyzed using frequency counts, means, percentages and chi-square test. Semen samples from different stations were analyzed for motility, viability and morphology. T-test was used in semen quality evaluation. Provincial AI coordinators (PAIC) were male, averaging 59 years old, married, had college education, served in government service for 34 years, but as PAIC for 5.7 years. All had other designations. Mean AI operation was 11.33 years with annual support from the local government unit of Php76,666.67. AI technicians were males, married, with college education, and trained on AI. Problems were on mobility; inadequate knowledge of farmers in animal raising and AI; and lack of liquid nitrogen and frozen semen supply. There was 2.95 municipalities and breedable cattle/carabaos of 3,091.25 per AI technician. Mean number of artificially inseminated animals per AI technician for 2011 was 28.57 heads for carabaos and 8.64 heads for cattle. There was very low participation rate among farmers. Carabaos were 6.52 years with parity 1.53. Cattle were 5.61 years, with parity of 1.51. Semen quality significantly (p ≤ 0.05) deteriorated in normal and live sperm with storage and handling at the provincial and field stations. Breed, AI technicians practices and AI operation significantly affected conception rate. Mean conception rate was 57.62%.

Keywords: artificial insemination, carabao, parity, mother tanks, frozen semen

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Authors: Takuya Suzuki, Atsushi Shirai, Takashi Seki

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Acupuncture therapy is one of the treatments in traditional Chinese medicine. Recently, some reports have shown the effectiveness of acupuncture. However, its full acceptance has been hindered by the lack of understanding on mechanism of the therapy. Acupuncture applied to Zusanli (ST-36) enhances blood flow volume in superior mesenteric artery (SMA), yielding peripheral vascular resistance – regulated blood flow of SMA dominated by the parasympathetic system and inhibition of sympathetic system. In this study, a lumped-parameter approximation model of blood flow in the systemic arteries was developed. This model was extremely simple, consisting of the aorta, carotid arteries, arteries of the four limbs and SMA, and their peripheral vascular resistances. Here, the individual artery was simplified to a tapered tube and the resistances were modelled by a linear resistance. We numerically investigated contribution of the peripheral vascular resistance of SMA to the systemic blood distribution using this model. In addition to the upstream end of the model, which correlates with the left ventricle, two types of boundary condition were applied; mean left ventricular pressure which correlates with blood pressure (BP) and mean cardiac output which corresponds to cardiac index (CI). We examined it to reproduce the experimentally obtained hemodynamic change, in terms of the ratio of the aforementioned hemodynamic parameters from their initial values before the acupuncture, by regulating the peripheral vascular resistances and the upstream boundary condition. First, only the peripheral vascular resistance of SMA was changed to show contribution of the resistance to the change in blood flow volume in SMA, expecting reproduction of the experimentally obtained change. It was found, however, this was not enough to reproduce the experimental result. Then, we also changed the resistances of the other arteries together with the value given at upstream boundary. Here, the resistances of the other arteries were changed simultaneously in the same amount. Consequently, we successfully reproduced the hemodynamic change to find that regulation of the upstream boundary condition to the value experimentally obtained after the stimulation is necessary for the reproduction, though statistically significant changes in BP and CI were not observed in the experiment. It is generally known that sympathetic and parasympathetic tones take part in regulation of whole the systemic circulation including the cardiac function. The present result indicates that stimulation to ST-36 could induce vasodilation of peripheral circulation of SMA and vasoconstriction of that of other arteries. In addition, it implies that experimentally obtained small changes in BP and CI induced by the acupuncture may be involved in the therapeutic response.

Keywords: acupuncture, hemodynamics, lumped-parameter approximation, modeling, systemic vascular resistance

Procedia PDF Downloads 224

Authors: Sung Hyun Yoo, In Hwan Choi, Jun Ho Jung, Choon Ki Ahn, Myo Taeg Lim

Abstract:

Home energy management system (HEMS) has been issued to reduce the power consumption. The HEMS performs electric power control for the indoor electric device. However, HEMS commonly treats the smart devices. In this paper, we suggest the output estimation of home legacy device using the artificial neural fuzzy inference system (ANFIS). This paper discusses the overview and the architecture of the system. In addition, accurate performance of the output estimation using the ANFIS inference system is shown via a numerical example.

Keywords: artificial neural fuzzy inference system (ANFIS), home energy management system (HEMS), smart device, legacy device

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Authors: D. G. Badagha, C. D. Modhera, S. A. Vasanwala

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There is a great challenge for civil engineering field to contribute in environment prevention by finding out alternatives of cement and natural aggregates. There is a problem of global warming due to cement utilization in concrete, so it is necessary to give sustainable solution to produce concrete containing waste. It is very difficult to produce designated grade of concrete containing different ingredient and water cement ratio including waste to achieve desired fresh and harden properties of concrete as per requirement and specifications. To achieve the desired grade of concrete, a number of trials have to be taken, and then after evaluating the different parameters at long time performance, the concrete can be finalized to use for different purposes. This research work is carried out to solve the problem of time, cost and serviceability in the field of construction. In this research work, artificial neural network introduced to fix proportion of concrete ingredient with 50% waste replacement for M20, M25, M30, M35, M40, M45, M50, M55 and M60 grades of concrete. By using the neural network, mix design of high performance concrete was finalized, and the main basic mechanical properties were predicted at 3 days, 7 days and 28 days. The predicted strength was compared with the actual experimental mix design and concrete cube strength after 3 days, 7 days and 28 days. This experimentally and neural network based mix design can be used practically in field to give cost effective, time saving, feasible and sustainable high performance concrete for different types of structures.

Keywords: artificial neural network, high performance concrete, rebound hammer, strength prediction

Procedia PDF Downloads 155

Authors: Aya Idriss, Esraa Othman, Lujain Malak

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Artificial intelligence is the emulation of human intelligence processes by machines, particularly computer systems that act logically. Some of the specific applications of AI include natural language processing, speech recognition, and machine vision. Cortana is a virtual assistant and she’s an example of an AI Application. Microsoft made it possible for this app to be accessed not only on laptops and PCs but can be downloaded on mobile phones and used as a virtual assistant which was a huge success. Cortana can offer a lot apart from the basic orders such as setting alarms and marking the calendar. Its capabilities spread past that, for example, it provides us with listening to music and podcasts on the go, managing my to-do list and emails, connecting with my contacts hands-free by simply just telling the virtual assistant to call somebody, gives me instant answers and so on. A questionnaire was sent online to numerous friends and family members to perform the study, which is critical in evaluating Cortana's recognition capacity and the majority of the answers were in favor of Cortana’s capabilities. The results of the questionnaire assisted us in determining the level of Cortana's skills.

Keywords: artificial intelligence, Cortana, AI, abstract

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Authors: Nir Wittenberg, Moshe Farhi

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This mixed-methods study examines the integration of artificial intelligence (AI) tools in a first-year social work course to assess their potential for enhancing professional knowledge and skills. The incorporation of digital technologies, such as AI, in social work interventions, training, and research has increased, with the expectation that AI will become as commonplace as email and mobile phones. However, policies and ethical guidelines regarding AI, as well as empirical evaluations of its usefulness, are lacking. As AI is gradually being adopted in the field, it is prudent to explore AI thoughtfully in alignment with pedagogical goals. The outcomes assessed include professional identity, course satisfaction, and motivation. AI offers unique reflective learning opportunities through personalized simulations, feedback, and queries to complement face-to-face lessons. For instance, AI simulations provide low-risk practices for situations such as client interactions, enabling students to build skills with less stress. However, it is essential to recognize that AI alone cannot ensure real-world competence or cultural sensitivity. Outcomes related to student learning, experience, and perceptions will help to elucidate the best practices for AI integration, guiding faculty, and advancing pedagogical innovation. This strategic integration of selected AI technologies is expected to diversify course methodology, improve learning outcomes, and generate new evidence on AI’s educational utility. The findings will inform faculty seeking to thoughtfully incorporate AI into teaching and learning.

Keywords: artificial intelligence (AI), social work education, students, developing a professional identity, ethical considerations

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Authors: Samir Hessas

Abstract:

Modern medicine is witnessing a profound transformation as advanced technology reshapes surgical environments. Hybrid operating rooms, where state-of-the-art medical equipment, advanced imaging solutions, and Artificial Intelligence (AI) converge, are at the forefront of this revolution. In this comprehensive exploration, we scrutinize the multifaceted facets of AI and delve into an array of groundbreaking technologies. We also discuss visionary concepts that hold the potential to revolutionize hybrid operating rooms, making them more efficient and patient-centered. These innovations encompass real-time imaging, surgical simulation, IoT and remote monitoring, 3D printing, telemedicine, quantum computing, and nanotechnology. The outcome of this fusion of technology and imagination is a promising future of surgical precision, individualized patient care, and unprecedented medical advances in hybrid operating rooms.

Keywords: artificial intelligence, hybrid operating rooms, telemedicine, monitoring

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Junbeom Lee, Jaehyuck Cho, Wookyeong Jeong, Jonghan Won, Jungmin Hwang, Youngseok Song, Taikyeong Jeong

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This paper investigates and analyzes meta-learning technologies that use multiple-cameras to monitor and check abnormal behavior in people in real-time in the area of healthcare fields. Advances in artificial intelligence and computer vision technologies have confirmed that cameras can be useful for individual health monitoring and abnormal behavior detection. Through this, it is possible to establish a system that can respond early by automatically detecting abnormal behavior of the elderly, such as patients and the elderly. In this paper, we use a technique called meta-learning to analyze image data collected from cameras and develop a commercial product to determine abnormal behavior. Meta-learning applies machine learning algorithms to help systems learn and adapt quickly to new real data. Through this, the accuracy and reliability of the abnormal behavior discrimination system can be improved. In addition, this study proposes a meta-learning-based abnormal behavior detection system that includes steps such as data collection and preprocessing, feature extraction and selection, and classification model development. Various healthcare scenarios and experiments analyze the performance of the proposed system and demonstrate excellence compared to other existing methods. Through this study, we present the possibility that camera-based meta-learning technology can be useful for monitoring and testing abnormal behavior in the healthcare area.

Keywords: artificial intelligence, abnormal behavior, early detection, health monitoring

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Authors: Fadzil Ahmad, Noor Ashidi Mat Isa

Abstract:

This study introduces an improved genetic algorithm procedure that focuses search around near optimal solution corresponded to a group of elite chromosome. This is achieved through a novel crossover technique known as Segmented Multi Chromosome Crossover. It preserves the highly important information contained in a gene segment of elite chromosome and allows an offspring to carry information from gene segment of multiple chromosomes. In this way the algorithm has better possibility to effectively explore the solution space. The improved GA is applied for the automatic and simultaneous parameter optimization and feature selection of artificial neural network in pattern recognition of medical problem, the cancer and diabetes disease. The experimental result shows that the average classification accuracy of the cancer and diabetes dataset has improved by 0.1% and 0.3% respectively using the new algorithm.

Keywords: genetic algorithm, artificial neural network, pattern clasification, classification accuracy

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Authors: Chen Xi, LIU Xuebin, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Lao Xuerui

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature have led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using Yolov5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network, machine vision

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

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Authors: Dharshini Selvarajah, Nicula Lui, Karen Kong

Abstract:

Background: Uterine fibroids are a common benign gynaecologic neoplasm in reproductive-aged women. Fibroids may become symptomatic in a vast majority of nulliparous women. Their diagnosis and management is often coordinated between gyneacologists, radiologists and urologists depending on the anatomical location, growth, size and the fibroids sarcomatous evolvement. Some patients may develop obstructive uropathy symptoms, either uni or bilateral secondary urethral obstruction causing hydronephrosis. Uterine artery emoblisation (UAE) has previously shown to effectively resolve symptoms as well as relieve urethral obstruction and resolve the hydronephrosis. UAE has now established itself as an organ preserving and minimally invasive procedure in the management of symptomatic uterine fibroids. It is a safe and effective alternative to hysterectomy for resolving fibroid related pressure symptoms. The case presented examines the clinical manifestations and impact of uterine fibroids on the urinary tract system. The therapeutic options to relieve the urological symptoms as well as preserve fertility are explored and presented. Case: The case is a 29-year-old Nepalese female admitted to hospital with recurrent urosepsis with multiresistant organisms. This was on a background of an enlarged uterus (measuring 17cm x11cm) with multiple subserosal, intramural and exophytic fibroids- causing external ureteric compression. She had bilateral ureteric stents insitu and required bilateral right and left nephrostomies during repeated episodes of urosepsis and bilateral ureteric obstruction. The left nephrostomy was removed a month prior to admission and her most recent CT KUB demonstrated hypofunctioning ureteric stents with bilateral hydronephrosis. Options of hysterectomy versus uterine artery emoblisation (UAE) were extensively explored. The patient was keen to preserve fertility. Risks associated with UAE such as expulsion of the submucosal component of the fibroids and the possibilities of sepsis in the setting of ongoing ureteric colonisation were particularly high. The patient opted to trial UAE even though the risks of recurrent hospital admissions with urosepsis were going to be particularly high. In the event, the uterus fails to shrink adequately enough to relieve the obstructed ureters a hysterectomy would inevitably be required in future. Day 3 post UAE the patient developed fevers, was hypotensive and tachycardic post-receiving prophylactic meropenem and fluconazole pre emoblisation. She was noted to have a CRP of 293 with the most recent urine culture during this time growing Candida albicans. The patient was recommenced on oral fluconazole and IV meropenem, with good effect. Her repeat renal tract ultrasound post-UAE showed ongoing marked left hydronephrosis relatively unchanged from the scan one month prior to the procedure, however the right-sided hydronephrosis had resolved. The patient was discharged on a 2-week course of antibiotics. The patient will have a repeat renal tract ultrasound and MRI of the ureters to re-evaluate the degree of hydronephrosis and progress- this was unavailable at the time of abstract submission and will be presented at the conference. Conclusion: Fibroids are a common benign tumour of the uterus and can frequently impact the lower urinary system resulting in significant uropathy. They often enlarge and compress the urinary bladder, urethra and lower end of the ureters. The effectiveness of UAE as a fertility preserving option is described.

Keywords: Uterine leiomyomas and urological complications, uterine artery embolisation for fibroids, Uterine fibroids and complications, Management of uterine fibroids

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Authors: Mai Anh Tuan, Wenlong Liu, Meng Li

Abstract:

Despite warnings and concerns about the use of fast food that has health effects, the fast-food industry is actually a source of profit for the global food industry. Obviously, in the face of such huge economic benefits, investors will not hesitate to continuously add recipes, processing methods, menu diversity, etc., to improve and apply information technology in enhancing the diners' experience; the ultimate goal is still to attract diners to find their brand and give them the fastest, most convenient and enjoyable service. In China, as the achievements of the industrial revolution 4.0, big data and artificial intelligence are reaching new heights day by day, now fast-food diners can instantly pay the bills only by identifying the biometric signature available on the self-ordering kiosk, using their own face without any additional form of confirmation. In this study, the author will evaluate the acceptance level of customers with this new form of payment through a survey of customers who have used and witnessed the use of smart kiosks and biometric payments within the city of Nanjing, China. A total of 200 valid volunteers were collected in order to test the customers' intentions and feelings when choosing and experiencing payment through AI services. 55% think that it bothers them because of the need for personal information, but more than 70% think that smart kiosk brings out many benefits and convenience. According to the data analysis findings, perceived innovativeness has a positive influence on satisfaction which in turn affects behavioral intentions, including reuse and word-of-mouth intentions.

Keywords: artificial intelligence, catering industry, smart kiosks, technology acceptance

Procedia PDF Downloads 93

Authors: Dharshini Selvarajah, Karen Kong

Abstract:

Background: Uterine fibroids are a common benign gynaecologic neoplasm in reproductive-aged women. Fibroids may become symptomatic in a vast majority of nulliparous women. Their diagnosis and management are often coordinated between gyneacologists, radiologists and urologists depending on the anatomical location, growth, size and the fibroids' sarcomatous evolvement. Some patients may develop obstructive uropathy symptoms, either uni or bilateral secondary urethral obstruction causing hydronephrosis. Uterine artery embolization (UAE) has previously been shown to effectively resolve symptoms as well as relieve urethral obstruction and resolve hydronephrosis. UAE has now established itself as an organ-preserving and minimally invasive procedure in the management of symptomatic uterine fibroids. It is a safe and effective alternative to hysterectomy for resolving fibroid-related pressure symptoms. The case presented examines the clinical manifestations and impact of uterine fibroids on the urinary tract system. The therapeutic options to relieve the urological symptoms as well as preserve fertility are explored and presented. Case: The case is a 29-year-old Nepalese female admitted to the hospital with recurrent urosepsis with multiresistant organisms. This was on a background of an enlarged uterus (measuring 17cm x11cm) with multiple subserosal, intramural and exophytic fibroids- causing external ureteric compression. She had bilateral ureteric stents in situ and required bilateral right and left nephrostomies during repeated episodes of urosepsis and bilateral ureteric obstruction. The left nephrostomy was removed a month prior to admission, and her most recent CT KUB demonstrated hypofunctioning ureteric stents with bilateral hydronephrosis. Options of hysterectomy versus uterine artery embolization (UAE) were extensively explored. The patient was keen to preserve fertility. Risks associated with UAE, such as the expulsion of the submucosal component of the fibroids and the possibilities of sepsis in the setting of ongoing ureteric colonisation were particularly high. The patient opted to trial UAE even though the risks of recurrent hospital admissions with urosepsis were going to be particularly high. In the event, the uterus fails to shrink adequately enough to relieve the obstructed ureters, a hysterectomy would inevitably be required in the future. Day 3 post-UAE the patient developed fevers, was hypotensive and tachycardic post-receiving prophylactic meropenem and fluconazole pre emoblisation. She was noted to have a CRP of 293 with the most recent urine culture during this time growing Candida albicans. The patient was recommenced on oral fluconazole and IV meropenum, with good effect. Her repeat renal tract ultrasound post-UAE showed ongoing marked left hydronephrosis relatively unchanged from the scan one month prior to the procedure; however, the right-sided hydronephrosis had resolved. The patient was discharged on a 2-week course of antibiotics. The patient will have a repeat renal tract ultrasound and MRI of the ureters to re-evaluate the degree of hydronephrosis and progress- this was unavailable at the time of abstract submission and will be presented at the conference. Conclusion: Fibroids are a common benign tumor of the uterus and can frequently impact the lower urinary system resulting in significant uropathy. They often enlarge and compress the urinary bladder, urethra and lower end of the ureters. The effectiveness of the UAE as a fertility-preserving option is described.

Keywords: uterine artery embolisation for fibroids, urological complications from fibroids, uropathy of fibroids, obstructive fibroid management

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Authors: Deepika Bhalla, Raj Kumar Bansal, Hari Om Gupta

Abstract:

Dissolved Gas Analysis (DGA) has been widely used for fault diagnosis in a transformer. Artificial neural networks (ANN) have high accuracy but are regarded as black boxes that are difficult to interpret. For many problems it is desired to extract knowledge from trained neural networks (NN) so that the user can gain a better understanding of the solution arrived by the NN. This paper applies a pedagogical approach for rule extraction from function approximating neural networks (REFANN) with application to incipient fault diagnosis using the concentrations of the dissolved gases within the transformer oil, as the input to the NN. The input space is split into subregions and for each subregion there is a linear equation that is used to predict the type of fault developing within a transformer. The experiments on real data indicate that the approach used can extract simple and useful rules and give fault predictions that match the actual fault and are at times also better than those predicted by the IEC method.

Keywords: artificial neural networks, dissolved gas analysis, rules extraction, transformer

Procedia PDF Downloads 536

Authors: Iwan Cony Setiadi, Aulia M. T. Nasution

Abstract:

The multispectral imaging (MSI) technique has been used for skin analysis, especially for distant mapping of in-vivo skin chromophores by analyzing spectral data at each reflected image pixel. For ergonomic purpose, our multispectral imaging system is decomposed in two parts: a light source compartment based on LED with 11 different wavelenghts and a monochromatic 8-Bit CCD camera with C-Mount Objective Lens. The software based on GUI MATLAB to control the system was also developed. Our system provides 11 monoband images and is coupled with a software reconstructing hyperspectral cubes from these multispectral images. In this paper, we proposed a new method to build a hyperspectral reflectance cube based on artificial neural network algorithm. After preliminary corrections, a neural network is trained using the 32 natural color from X-Rite Color Checker Passport. The learning procedure involves acquisition, by a spectrophotometer. This neural network is then used to retrieve a megapixel multispectral cube between 380 and 880 nm with a 5 nm resolution from a low-spectral-resolution multispectral acquisition. As hyperspectral cubes contain spectra for each pixel; comparison should be done between the theoretical values from the spectrophotometer and the reconstructed spectrum. To evaluate the performance of reconstruction, we used the Goodness of Fit Coefficient (GFC) and Root Mean Squared Error (RMSE). To validate reconstruction, the set of 8 colour patches reconstructed by our MSI system and the one recorded by the spectrophotometer were compared. The average GFC was 0.9990 (standard deviation = 0.0010) and the average RMSE is 0.2167 (standard deviation = 0.064).

Keywords: multispectral imaging, reflectance cube, spectral reconstruction, artificial neural network

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Authors: Sandeep Mehmi, Harsh Verma, A. L. Sangal

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Ever since the idea of using computing services as commodity that can be delivered like other utilities e.g. electric and telephone has been floated, the scientific fraternity has diverted their research towards a new area called utility computing. New paradigms like cluster computing and grid computing came into existence while edging closer to utility computing. With the advent of internet the demand of anytime, anywhere access of the resources that could be provisioned dynamically as a service, gave rise to the next generation computing paradigm known as cloud computing. Today, cloud computing has become one of the most aggressively growing computer paradigm, resulting in growing rate of applications in area of IT outsourcing. Besides catering the computational and storage demands, cloud computing has economically benefitted almost all the fields, education, research, entertainment, medical, banking, military operations, weather forecasting, business and finance to name a few. Smart grid is another discipline that direly needs to be benefitted from the cloud computing advantages. Smart grid system is a new technology that has revolutionized the power sector by automating the transmission and distribution system and integration of smart devices. Cloud based smart grid can fulfill the storage requirement of unstructured and uncorrelated data generated by smart sensors as well as computational needs for self-healing, load balancing and demand response features. But, security issues such as confidentiality, integrity, availability, accountability and privacy need to be resolved for the development of smart grid cloud. In recent years, a number of intrusion prevention techniques have been proposed in the cloud, but hackers/intruders still manage to bypass the security of the cloud. Therefore, precise intrusion detection systems need to be developed in order to secure the critical information infrastructure like smart grid cloud. Considering the success of artificial neural networks in building robust intrusion detection, this research proposes an artificial neural network based model for detecting attacks in smart grid cloud.

Keywords: artificial neural networks, cloud computing, intrusion detection systems, security issues, smart grid

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Authors: Akshat Mathur, Sunil Kumar Khatri

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This paper presents brief about how the use of Artificial intelligence in respect to GUI testing can reduce workload by using DL-fueled method. This paper also discusses about how graphical user interface and event driven software testing can derive benefits from the use of AI techniques. The use of AI techniques not only reduces the task and work load but also helps in getting better output than manual testing. Although results are same, but the use of Artifical intelligence techniques for GUI testing has proven to provide ideal results. DL-fueled framework helped us to find imperfections of the entire webpage and provides test failure result in a score format between 0 and 1which signifies that are test meets it quality criteria or not. This paper proposes DL-fueled method which helps us to find the genuine GUI bugs and defects and also helped us to scale the existing labour-intensive and skill-intensive methodologies.

Keywords: graphical user interface, GUI, artificial intelligence, deep learning, ML technology

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Authors: Gurmeet Singh Cheema, Navjotinder Singh, Gurjinder Singh, Amardeep Singh

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Aluminium and its alloys play have excellent corrosion resistant properties, ease of fabrication and high specific strength to weight ratio. In this investigation an attempt has been made to study the effect of different post weld heat treatment methods on the mechanical and metallurgical properties of TIG welded joints of the commercial aluminium alloy. Three different methods of post weld heat treatments are, solution heat treatment, artificial aged and combination of solution heat treatment and artificial aging are given to TIG welded aluminium joints. Mechanical and metallurgical properties of as welded and post weld treated joints of the aluminium alloys was examined.

Keywords: aluminium alloys, TIG welding, post weld heat treatment

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Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Ashok Kumar Rastogi

Abstract:

Glass is a material commonly used for Glassdoor, glass bottles, cookware, and containers. It can be harmful, as it is a hard and blunt object. Glass has been associated with severe injury and is a common cause of injuries warranting hospital visits to the emergency department (ED). These injuries can be accidental or intentionally inflicted. Broken glass injuries can be severe, even deadly. If broken glass shards fall out on your arm, it may cause fatal injuries. Case history: A 20-year-old male dead body was found aside the road, police informed, and a video recording ceased during an investigation. In the video recording, the person was in a drunken state (unable to walk and disoriented), wandering in the residential area road. He saw a barber shop, the shop door made of Glass. Suddenly, he hit the Glassdoor with his right hand forcefully. The Glassdoor broke into multiple pieces, and multiple injuries were seen over the right hand. Observations: Multiple small and large lacerations were seen over the right anterior part of the elbow. The main injury looked like an incised wound caused by a hard and sharp object. The main injury was noted as a laceration of size 13 x 06 cm bone deep, placed obliquely over the anteromedial aspect of the right elbow joint, its medial end at medial end of elbow joint while its anterior end was 04 cm below the elbow joint with laceration of underline brachialis muscles and complete transaction of ulnar artery and vein, skin margins looking sharply cut with irregular margins with tiny cuts at the medial lower border of laceration. Injuries were antemortem and fresh in nature, caused by hard and blunt objects but looking like hard and sharp objects. All organs were found pale, and the cause of death was shock and hemorrhage because of ulnar vessel injury. Conclusion: The findings of this case report highlight the potentially lethal consequences of glass injuries, especially those involving Glassdoors. The study underscores the importance of accurate interpretation and identification of wounds caused by Glass, as they may resemble injuries caused by other objects. It emphasizes the challenges faced by autopsy surgeons when determining the cause and manner of death in cases where visual evidence of injury is absent or when the weapon is not recovered. Ultimately, this case report serves as a reminder of the potential dangers posed by Glass and the importance of comprehensive forensic examinations.

Keywords: glassdoor, incised, wound, laceration, autopsy

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Authors: Jae Ni Jang, Young Uk Kim

Abstract:

Background: Chat Generative Pre-training Transformer-3 (ChatGPT; San Francisco, California, Open Artificial Intelligence) is an artificial intelligence chatbot based on a large language model designed to generate human-like text. As the usage of ChatGPT is increasing among less knowledgeable patients, medical students, and anesthesia and pain medicine residents or trainees, we aimed to evaluate the accuracy of ChatGPT-3 responses to questions about the American Society of Anesthesiologists (ASA) classification based on patients’ underlying diseases and assess the quality of the generated responses. Methods: A total of 47 questions were submitted to ChatGPT using textual prompts. The questions were designed for ChatGPT-3 to provide answers regarding ASA classification in response to common underlying diseases frequently observed in adult patients. In addition, we created 18 questions regarding the ASA classification for pediatric patients and pregnant women. The accuracy of ChatGPT’s responses was evaluated by cross-referencing with Miller’s Anesthesia, Morgan & Mikhail’s Clinical Anesthesiology, and the American Society of Anesthesiologists’ ASA Physical Status Classification System (2020). Results: Out of the 47 questions pertaining to adults, ChatGPT -3 provided correct answers for only 23, resulting in an accuracy rate of 48.9%. Furthermore, the responses provided by ChatGPT-3 regarding children and pregnant women were mostly inaccurate, as indicated by a 28% accuracy rate (5 out of 18). Conclusions: ChatGPT provided correct responses to questions relevant to the daily clinical routine of anesthesiologists in approximately half of the cases, while the remaining responses contained errors. Therefore, caution is advised when using ChatGPT to retrieve anesthesia-related information. Although ChatGPT may not yet be suitable for clinical settings, we anticipate significant improvements in ChatGPT and other large language models in the near future. Regular assessments of ChatGPT's ASA classification accuracy are essential due to the evolving nature of ChatGPT as an artificial intelligence entity. This is especially important because ChatGPT has a clinically unacceptable rate of error and hallucination, particularly in pediatric patients and pregnant women. The methodology established in this study may be used to continue evaluating ChatGPT.

Keywords: American Society of Anesthesiologists, artificial intelligence, Chat Generative Pre-training Transformer-3, ChatGPT

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Authors: Selim M. Khan

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Indoor air quality is strongly influenced by the presence of radioactive radon (222Rn) gas. Indeed, exposure to high 222Rn concentrations is unequivocally linked to DNA damage and lung cancer and is a worsening issue in North American and European built environments, having increased over time within newer housing stocks as a function of as yet unclear variables. Indoor air radon concentration can be influenced by a wide range of environmental, structural, and behavioral factors. As some of these factors are quantitative while others are qualitative, no single statistical model can determine indoor radon level precisely while simultaneously considering all these variables across a complex and highly diverse dataset. The ability of AI- machine (deep) learning to simultaneously analyze multiple quantitative and qualitative features makes it suitable to predict radon with a high degree of precision. Using Canadian and Swedish long-term indoor air radon exposure data, we are using artificial deep neural network models with random weights and polynomial statistical models in MATLAB to assess and predict radon health risk to human as a function of geospatial, human behavioral, and built environmental metrics. Our initial artificial neural network with random weights model run by sigmoid activation tested different combinations of variables and showed the highest prediction accuracy (>96%) within the reasonable iterations. Here, we present details of these emerging methods and discuss strengths and weaknesses compared to the traditional artificial neural network and statistical methods commonly used to predict indoor air quality in different countries. We propose an artificial deep neural network with random weights as a highly effective method for assessing and predicting indoor radon.

Keywords: radon, radiation protection, lung cancer, aI-machine deep learnng, risk assessment, risk prediction, Europe, North America

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Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

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In this study, an artificial intelligence-based (ANN based) analytical method has been developed for analyzing earthquake performances of the reinforced concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code- 2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: artificial intelligence, earthquake, performance, reinforced concrete

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Authors: Justin Bin

Abstract:

Artificial intelligence (AI) has been rapidly rising in usage recently, already active in the daily lives of millions, from distinguished AIs like the popular ChatGPT or Siri to more obscure, inconspicuous AIs like those used in social media or internet search engines. As upcoming generations grow immersed in emerging technology, AI will play a vital role in their development. Namely, the education sector, an influential portion of a person’s early life as a student, faces a vast ocean of possibilities concerning the implementation of AI. The main purpose of this study is to analyze the effect that AI will have on the future of the educational field. More particularly, this study delves deeper into the following three categories: school admissions, the productivity of students, and ethical concerns (role of human teachers, purpose of schooling itself, and significance of diplomas). This study synthesizes research and data on the current effects of AI on education from various published literature sources and journals, as well as estimates on further AI potential, in order to determine the main, overarching effects it will have on the future of education. For this study, a systematic organization of data in terms of type (quantitative vs. qualitative), the magnitude of effect implicated, and other similar factors were implemented within each area of significance. The results of the study suggest that AI stands to change all the beforementioned subgroups. However, its specific effects vary in magnitude and favorability (beneficial or harmful) and will be further discussed. The results discussed will reveal to those affiliated with the education field, such as teachers, counselors, or even parents of students, valuable information on not just the projected possibilities of AI in education but the effects of those changes moving forward.

Keywords: artificial intelligence, education, schools, teachers

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Authors: Shen Xiaoyun

Abstract:

The AI-generated works must intersect with the right holder’s work, thus having a certain impact on the rights and interests of the right holder’s work. The law needs to explore and improve the regulation of the fair use of AI creations and build a compensation system to adapt to the development of the times. The development of AI technology has brought about problems such as the unclear relationship between fair use and infringement of copyright, the unclear general terms and conditions of application, and the incomplete criteria for judging at different stages. Through different theoretical methods, the legitimacy of the rational use of the system can be demonstrated. The compensation standard for fair use of copyright in AI creation can refer to the market pricing of the right holder's work, and the compensation can construct a formula for the amount of damages for AI copyright infringement, and construct the compensation standard based on the main factors affecting the market value of the work, so as to provide a reference for the construction of a compensation system for fair use of works generated by AI.

Keywords: artificial intelligence, creative acts, fair use of copyright, copyright compensation system

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Authors: Azidah Abu Ziden, Adu Ifedayo Emmanuel

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This study investigated the optical board as an artificial technology for peer teaching in a Nigerian university. A design and development research (DDR) design was adopted, which entailed the planning and testing of instructional design models adopted to produce the optical board. This research population involved twenty-five (25) peer-teaching students at a Nigerian university consisting of theatre arts, religion, and language education-related disciplines. Also, using a random sampling technique, this study selected eight (8) students to work on the optical board. Besides, this study introduced a research instrument titled lecturer assessment rubric containing 30-mark metrics for evaluating students’ teaching with the optical board. In this study, it was discovered that the optical board affords students acquisition of self-employment skills through their exposure to the peer teaching course, which is a teacher training module in Nigerian universities. It is evident in this study that students were able to coordinate their design and effectively develop the optical board without lecturer’s interference. This kind of achievement in this research shows that the Nigerian university curriculum had been designed with contents meant to spur students to create jobs after graduation, and effective implementation of the readily available curriculum contents is enough to imbue students with the needed entrepreneurial skills. It was recommended that the Federal Government of Nigeria (FGN) must discourage the poor implementation of Nigerian university curriculum and invest more in the betterment of the readily available curriculum instead of considering a synonymously acclaimed new curriculum for regurgitated teaching and learning process.

Keywords: optical board, artificial technology, peer teaching, educational technology, Nigeria, Malaysia, university, glass, wood, electrical, improvisation

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Authors: Mohammed Eltayeb Salih Elamin

Abstract:

This study discusses the concept of the artificial heart using engineering concepts, of the fluid mechanics and the characteristics of the non-Newtonian fluid. For the purpose to serve heart patients and improve aspects of their lives and since the Statistics review according to world health organization (WHO) says that heart disease and blood vessels are the first cause of death in the world. Statistics shows that 30% of the death cases in the world by the heart disease, so simply we can consider it as the number one leading cause of death in the entire world is heart failure. And since the heart implantation become a very difficult and not always available, the idea of the artificial heart become very essential. So it’s important that we participate in the developing this idea by searching and finding the weakness point in the earlier designs and hoping for improving it for the best of humanity. In this study a pump was designed in order to pump blood to the human body and taking into account all the factors that allows it to replace the human heart, in order to work at the same characteristics and the efficiency of the human heart. The pump was designed on the idea of the diaphragm pump. Three models of blood obtained from the blood real characteristics and all of these models were simulated in order to study the effect of the pumping work on the fluid. After that, we study the properties of this pump by using Ansys15 software to simulate blood flow inside the pump and the amount of stress that it will go under. The 3D geometries modeling was done using SOLID WORKS and the geometries then imported to Ansys design modeler which is used during the pre-processing procedure. The solver used throughout the study is Ansys FLUENT. This is a tool used to analysis the fluid flow troubles and the general well-known term used for this branch of science is known as Computational Fluid Dynamics (CFD). Basically, Design Modeler used during the pre-processing procedure which is a crucial step before the start of the fluid flow problem. Some of the key operations are the geometry creations which specify the domain of the fluid flow problem. Next is mesh generation which means discretization of the domain to solve governing equations at each cell and later, specify the boundary zones to apply boundary conditions for the problem. Finally, the pre–processed work will be saved at the Ansys workbench for future work continuation.

Keywords: Artificial heart, computational fluid dynamic heart chamber, design, pump

Procedia PDF Downloads 459

Authors: I. S. Gandhi, D. N. Patel, M. Johnson, A. R. Hirsch

Abstract:

Although distortion of taste perception following a cerebrovascular event may seem to be a frivolous consequence of a classic stroke presentation, altered taste perception places patients at an increased risk for malnutrition, weight loss, and depression, all of which negatively impact the quality of life. Impaired taste perception can result from a wide variety of cerebrovascular lesions to various locations, including pons, insular cortices, and ventral posteromedial nucleus of the thalamus. Wallenberg syndrome, also known as a lateral medullary syndrome, has been described to impact taste; however, specific sweet to bitter taste dysgeusia from a territory infarction is an infrequent event; as such, a case is presented. One year prior to presentation, this 64-year-old right-handed woman, suffered a right posterior inferior cerebellar artery aneurysm rupture with resultant infarction, culminating in a ventriculoperitoneal shunt placement. One and half months after this event, she noticed the gradual onset of lack of ability to taste sweet, to eventually all sweet food tasting bitter. Since the onset of her chemosensory problems, the patient has lost 60-pounds. Upon gustatory testing, the patient's taste threshold showed ageusia to sucrose and hydrochloric acid, while normogeusia to sodium chloride, urea, and phenylthiocarbamide. The gustatory cortex is made in part by the right insular cortex as well as the right anterior operculum, which are primarily involved in the sensory taste modalities. In this model, sweet is localized in the posterior-most along with the rostral aspect of the right insular cortex, notably adjacent to the region responsible for bitter taste. The sweet to bitter dysgeusia in our patient suggests the presence of a lesion in this localization. Although the primary lesion in this patient was located in the right medulla of the brainstem, neurodegeneration in the rostal and posterior-most aspect, of the right insular cortex may have occurred due to diaschisis. Diaschisis has been described as neurophysiological changes that occur in remote regions to a focal brain lesion. Although hydrocephalus and vasospasm due to aneurysmal rupture may explain the distal foci of impairment, the gradual onset of dysgeusia is more indicative of diaschisis. The perception of sweet, now tasting bitter, suggests that in the absence of sweet taste reception, the intrinsic bitter taste of food is now being stimulated rather than sweet. In the evaluation and treatment of taste parageusia secondary to cerebrovascular injury, prophylactic neuroprotective measures may be worthwhile. Further investigation is warranted.

Keywords: diaschisis, dysgeusia, stroke, taste

Procedia PDF Downloads 180