Search results for: artificial artery

Authors: Sule Yucelbas, Gulay Tezel, Cuneyt Yucelbas, Seral Ozsen

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In this study, it was tried to identify some heart rhythm disorders by electrocardiography (ECG) data that is taken from MIT-BIH arrhythmia database by subtracting the required features, presenting to artificial neural networks (ANN), artificial immune systems (AIS), artificial neural network based on artificial immune system (AIS-ANN) and particle swarm optimization based artificial neural network (PSO-NN) classifier systems. The main purpose of this study is to evaluate the performance of hybrid AIS-ANN and PSO-ANN classifiers with regard to the ANN and AIS. For this purpose, the normal sinus rhythm (NSR), atrial premature contraction (APC), sinus arrhythmia (SA), ventricular trigeminy (VTI), ventricular tachycardia (VTK) and atrial fibrillation (AF) data for each of the RR intervals were found. Then these data in the form of pairs (NSR-APC, NSR-SA, NSR-VTI, NSR-VTK and NSR-AF) is created by combining discrete wavelet transform which is applied to each of these two groups of data and two different data sets with 9 and 27 features were obtained from each of them after data reduction. Afterwards, the data randomly was firstly mixed within themselves, and then 4-fold cross validation method was applied to create the training and testing data. The training and testing accuracy rates and training time are compared with each other. As a result, performances of the hybrid classification systems, AIS-ANN and PSO-ANN were seen to be close to the performance of the ANN system. Also, the results of the hybrid systems were much better than AIS, too. However, ANN had much shorter period of training time than other systems. In terms of training times, ANN was followed by PSO-ANN, AIS-ANN and AIS systems respectively. Also, the features that extracted from the data affected the classification results significantly.

Keywords: AIS, ANN, ECG, hybrid classifiers, PSO

Procedia PDF Downloads 442

Authors: Eman Alhajjar, Albatool Jamjoom, Fatmah Bugshan

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This research aims to investigate the artificial intelligence (AI) application Jung GPT and how helpful it is, as a therapy AI, to users. Jung GPT has the potential to make mental health care more accessible and cheaper while also providing tailored support and advice. However, it is not intended to be a substitute for human therapists. Jung GPT is instructed to understand a wide range of concepts, including emojis, sensitive subjects, and various languages. Furthermore, participants were asked to fill out a survey based on their experience with Jung GPT. Additionally, analysis of the responses indicated that Jung GPT was helpful in identifying and exploring challenges, and the use of Jung GPT by participants in the future is highly possible. The results demonstrate that Jung GPT does help in recognizing challenges or problems within the users. On this basis, it is recommended that individuals use Jung GPT to explore their thoughts, feelings, and challenges. Moreover, further research is needed to better evaluate the effectiveness of Jung GPT.

Keywords: Jung GPT, artificial intelligence, therapy, mental health, AI application

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Authors: Hadi Rouhi Belvirdi, Davoud Beheshtizadeh

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The increasing demand for sustainable construction materials has led to a growing interest in high-strength recycled concrete (HSRC). Utilizing recycled materials not only reduces waste but also minimizes the depletion of natural resources. This study explores the application of artificial intelligence (AI) techniques to model and predict the properties of HSRC. In the past two decades, the production levels in various industries and, consequently, the amount of waste have increased significantly. Continuing this trend will undoubtedly cause irreparable damage to the environment. For this reason, engineers have been constantly seeking practical solutions for recycling industrial waste in recent years. This research utilized the results of the compressive strength of 90-day high-strength recycled concrete. The method for creating recycled concrete involved replacing sand with crushed glass and using glass powder instead of cement. Subsequently, a feedforward artificial neural network was employed to model the compressive strength results for 90 days. The regression and error values obtained indicate that this network is suitable for modeling the compressive strength data.

Keywords: high-strength recycled concrete, feedforward artificial neural network, regression, construction materials

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Authors: Anna Demian, Levi Howard, L. Ng, Leslie Simon, Mark Dragon, A. Desai, Timothy Devlantes, W. David Freeman

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Introduction: Out-of-hospital cardiac arrest (OHCA) can carry a high mortality. For survivors, the most common complication is hypoxic-ischemic brain injury (HIBI). Rarely, lumbosacral spinal cord and/or other spinal cord artery ischemia can occur due to anatomic variation and variable mean arterial pressure after the return of spontaneous circulation. We present a case of an OHCA survivor who later woke up with bilateral leg weakness with preserved sensation (ASIA grade B, L2 level). Methods: We describe a clinical, radiographic, and laboratory presentation, as well as a National Library of Medicine (NLM) search engine methodology, characterizing incidence/prevalence of this entity is discussed. A 70-year-old male, a longtime smoker, and alcohol user, suddenly collapsed at a bar surrounded by friends. He had complained of chest pain before collapsing. 911 was called. EMS arrived, and the patient was in pulseless electrical activity (PEA), cardiopulmonary resuscitation (CPR) was initiated, and the patient was intubated, and a LUCAS device was applied for continuous, high-quality CPR in the field by EMS. In the ED, central lines were placed, and thrombolysis was administered for a suspected Pulmonary Embolism (PE). It was a prolonged code that lasted 90 minutes. The code continued with the eventual return of spontaneous circulation. The patient was placed on an epinephrine and norepinephrine drip to maintain blood pressure. ECHO was performed and showed a “D-shaped” ventricle worrisome for PE as well as an ejection fraction around 30%. A CT with PE protocol was performed and confirmed bilateral PE. Results: The patient woke up 24 hours later, following commands, and was extubated. He was found paraplegic below L2 with preserved sensation, with hypotonia and areflexia consistent with “spinal shock” or anterior spinal cord syndrome. MRI thoracic and lumbar spine showed a conus medullaris level spinal cord infarction. The patient was given IV steroids upon initial discovery of cord infarct. NLM search using “cardiac arrest” and “spinal cord infarction” revealed 57 results, with only 8 review articles. Risk factors include age, atherosclerotic disease, and intraaortic balloon pump placement. AoA (Artery of Adamkiewicz) anatomic variation along with existing atherosclerotic factors and low perfusion were also known risk factors. Conclusion: Acute paraplegia from anterior spinal cord infarction of the AoA territory after cardiac arrest is rare. Larger prospective, multicenter trials are needed to examine potential interventions of hypothermia, lumbar drains, which are sometimes used in aortic surgery to reduce ischemia and/or other neuroprotectants.

Keywords: cardiac arrest, spinal cord infarction, artery of Adamkiewicz, paraplegia

Procedia PDF Downloads 189

Authors: F. Ece Cetin, H. Nezih Ozdemir, Emre Kumral

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Ischemic stroke of the precuneal cortex (PC) alone is extremely rare. This study aims to evaluate the clinical, neurocognitive, and behavioural characteristics of isolated PC infarcts. We assessed neuropsychological and behavioral findings in 12 patients with isolated PC infarct among 3800 patients with ischemic stroke. To determine the most frequently affected brain locus in patients, we first overlapped the ischemic area of patients with specific cognitive disorders and patients without specific cognitive disorders. Secondly, we compared both overlap maps using the 'subtraction plot' function of MRIcroGL. Patients showed various types of cognitive disorders. All patients experienced more than one category of cognitive disorder, except for two patients with only one cognitive disorder. Lesion topographical analysis showed that damage within the anterior precuneal region might lead to consciousness disorders (25%), self-processing impairment (42%), visuospatial disorders (58%), and lesions in the posterior precuneal region caused episodic and semantic memory impairment (33%). The whole precuneus is involved in at least one body awareness disorder. The cause of the stroke was cardioembolism in 5 patients (42%), large artery disease in 3 (25%), and unknown in 4 (33%). This study showed a wide variety of neuropsychological and behavioural disorders in patients with precuneal infarct. Future studies are needed to achieve a proper definition of the function of the precuneus in relation to the extended cortical areas. Precuneal cortex region infarcts have been found to predict a source of embolism from the large arteries or heart.

Keywords: cognition, pericallosal artery, precuneal cortex, ischemic stroke

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Authors: Von Jerick Tenorio, Jonald Lucero, Marivic Vestal, Edwin Tiempo

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In patients with hostile aortic neck anatomy, the risks of proximal seal complications and stent migration remain with EVAR despite improved endograft technology. This case report discusses how the technical challenges of the hostile neck anatomy, proximal penetrating atherosclerotic ulcer (PAU) and tortuous femoral access were addressed. The CT aortogram of a 63-year-old hypertensive and diabetic man with recurring abdominal discomfort revealed a fusiform infra-renal aneurysm measuring 8.8 cm in length and 5.7 cm in diameter. The proximal landing zone only has a 3 mm healthy neck with a conicity of > 10% and a thrombus of 4 mm thick. Proximal to the aneurysm is a PAU with a circumferential mural thrombus. The right femoral artery is tortuous with > 90o angulation. A 20% oversized Endurant II endograft and Aptus Heli-FX EndoAnchors were deployed as prophylaxis for type I endoleaks and endograft migration consequent to the conical neck and proximal aneurysm extension consequent to the PAU. A stiff Backup Meier guide wire facilitated the deployment of the endograft. Coil embolization of the right internal iliac artery was performed as prophylaxis for type II endoleaks. EndoAnchors can be used as an adjunct to EVAR as prophylaxis for proximal seal complications and stent migration in patients with hostile aortic aneurysm neck anatomy and concomitant proximal PAU.

Keywords: endoAnchors, endoleaks, EVAR, hostile neck

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Authors: Djermani Farouk, Sri Rahayu Hijrah Hati, Fenitra Maminirin, Permata Wulandari

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This study investigates the implications of Artificial Intelligence Marketing (AIM) marketing mix (PRD) Product, (PRC) Price, (PRM), Promotion and (PLC) Place on consumption patterns of halal food (CPHF). A quantitative approach was adopted in this study and responses were obtained from 350 Indonesian consumers. Using Partial Least Squares-Structural Equation Modeling (PLS-SEM), the results show that there is a direct support of marketing mix (PRD, PRC, PLC) to AIM and CPHF, while PRM does not play a significant role in CPHF. In addition, the findings reveal that AIM mediates significantly the relationship between PLC, PRC and PRM and CPHF, while AIM indicates no mediation between PRD and CPHF. Indonesian consumer’s exhibit serious concerns with consumption patterns of halal food. it is recommended that managers focus their attention on marketing strategies to predict consumer behavior in terms of consumption patterns of halal food through the integration of AIM.

Keywords: marketing mix, consumption patterns, artificial intelligence marketing, Halal food

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Authors: Rezvan Ravanfar Haghighi, S. Chatterjee, Pratik Kumar, V. C. Vani, Priya Jagia, Sanjiv Sharma, Susama Rani Mandal, R. Lakshmy

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The dual energy computed tomography (DECT) aims at noting the HU(V) values for the sample at two different voltages V=V1, V2 and thus obtain the electron densities (ρe) and effective atomic number (Zeff) of the substance. In the present paper, we aim to obtain a numerical algorithm by which (ρe, Zeff) can be obtained from the HU(100) and HU(140) data, where V=100, 140 kVp. The idea is to use this inversion method to characterize and distinguish between the lipid and fibrous coronary artery plaques.With the idea to develop the inversion algorithm for low Zeff materials, as is the case with non calcified coronary artery plaque, we prepare aqueous samples whose calculated values of (ρe, Zeff) lie in the range (2.65×1023≤ ρe≤ 3.64×1023 per cc ) and (6.80≤ Zeff ≤ 8.90). We fill the phantom with these known samples and experimentally determine HU(100) and HU(140) for the same pixels. Knowing that the HU(V) values are related to the attenuation coefficient of the system, we present an algorithm by which the (ρe, Zeff) is calibrated with respect to (HU(100), HU(140)). The calibration is done with a known set of 20 samples; its accuracy is checked with a different set of 23 known samples. We find that the calibration gives the ρe with an accuracy of ± 4% while Zeff is found within ±1% of the actual value, the confidence being 95%.In this inversion method (ρe, Zeff) of the scanned sample can be found by eliminating the effects of the CT machine and also by ensuring that the determination of the two unknowns (ρe, Zeff) does not interfere with each other. It is found that this algorithm can be used for prediction of chemical characteristic (ρe, Zeff) of unknown scanned materials with 95% confidence level, by inversion of the DECT data.

Keywords: chemical composition, dual-energy computed tomography, inversion algorithm

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Authors: Mohammadjavad Sotoudeheian, Navid Farahmandian

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Kawasaki disease (KD) is the primary cause of acquired pediatric heart disease as an acute vasculitis. In children with prolonged fever, rash, and inflammation of the mucosa KD must be considered as a clinical diagnosis. There is a persuasive suggestion of immune-mediated damage as the pathophysiologic cascade of KD. For example, the invasion of cytotoxic T-cells supports a viral etiology and the inflammasome of the innate immune system is a critical component in the vasculitis formation in KD. Animal models of KD propose the cytokine profiles, such as increased IL-1 and GM-CSF, which cause vascular damage. CRP and IFN-γ elevated expression and the upregulation of IL-6, and IL-10 production are also described in previous studies. Untreated KD is a critical risk factor for coronary artery diseases and myocardial infarction. Vascular damage may encompass amplified T-cell activity. SMAD3 is an essential molecule in down-regulating T-cells and increasing expression of FoxP3. It has a critical effect in the differentiation of regulatory T-cells. The discrepancy of regulatory T-cells and pro-inflammatory Th17 has been studied in acute coronary syndrome during KD. However in the coronary artery damaged lymphocytes and IgA plasma cells are seen at the lesion locations, the major immune cells in the coronary lesions are monocytes/macrophages and neutrophils. These cells secrete TNF-α, and activates matrix metalloprotease (MMP)-9, reducing the integrity of vessels and prompting patients to arise aneurysm. MMPs can break down the components of the extracellular matrix and assist immune cell movement. IVIG as an effective form of treatment clarified the role of the immune system, which may target pathogenic antigens and regulate cytokine production. Several reports have revealed that in the coronary arteries, high expression of MMP-9 in monocyte/macrophage results in pathologic cascades. Curcumin is a potent antioxidant and anti-inflammatory molecule. Curcumin decreases the production of reactive oxygen and nitrogen species and inhibits transcription factors like AP-1 and NF-κB. Curcumin also contains the characteristics of inhibitory effects on MMPs, especially MMP-9. The upregulation of MMP-9 is an important cellular response. Curcumin treatment caused a reverse effect and down-regulates MMP-9 gene expression which may fund the anti-inflammatory effect. Curcumin inhibits MMP-9 expression via PKC and AMPK-dependent pathways in Human monocytes cells. Elevated expression and activity of MMP-9 are correlated with advanced vascular lesions. AMPK controls lipid metabolism and oxidation, and protein synthesis. AMPK is also necessary for the MMP-9 activity and THP-1 cell adhesion to endothelial cells. Curcumin was shown to inhibit the activation of AMPKα. Compound C (AMPK inhibitor) inhibits MMP-9 expression level. Therefore, through inactivating AMPKs and PKC, curcumin decreases the MMP-9 level, which results in inhibiting monocyte/macrophage differentiation. Compound C also suppress the phosphorylation of three major classes of MAP kinase signaling, suggesting that curcumin may suppress MMP-9 level by inactivation of MAPK pathways. MAPK cascades are activated to induce the expression of MMP-9. Curcumin inhibits MAPKs phosphorylation, which contributes to the down-regulation of MMP-9. This study demonstrated that the potential inhibitory properties of curcumin over MMP-9 lead to a therapeutic strategy to reduce the risk of coronary artery involvement during KD.

Keywords: MMP-9, coronary artery aneurysm, Kawasaki’s disease, curcumin, AMPK, immune system, NF-κB, MAPK

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Authors: A. Elmajdoub, A. El-Mahmoudy

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The present study was designed to investigate the neurotransmitters that mediate the excitatory response of the circular muscle of final branches of mesenteric artery in bovine calves. Mesentery was dissected and the iliac branches were separated and used. The final mesenteric branches of diameter 400 micrometers and less responded strongly to norepinephrine and moderately to ATP. However, the mesenteric branches of wider diameters were gradually less responsive to norepinephrine and those of diameter 700 micrometers were exclusively nonresponsive. These arteries were strongly responsive to ATP (100 µM). Norepinephrine response was sensitive to phentolamine (3 µM) and prazosin (5 µM) indicating that it is mediated by α1 receptor; while ATP response was sensitive to suramin (200 µM), PPADS (50 µM), but not to cibacron blue (100 µM) indicating that it is mediated via P2X receptor. Further confirmatory experiments were performed including application of α1 and P2X receptor specific agonists which are methoxamine and α,β-methylene ATP. Methoxamine (1 µM) showed effects similar to norepinephrine in final branches and was without effect in wider branches. α,β-methylene ATP (1 µM), exhibited more pronounced effects on both wide and narrow branches but in parallel manner to that of ATP. Agonists for α2 and P2Y receptors as clonidine (10 µM) and 2-meThio ATP (10 µM), respectively, were without effect indicating that involvement of these receptors is unlikely. The neuropeptide-Y (200 nM) did not have any effects on either the narrow or the wide rings. Conclusion: These data may imply that in the most peripheral mesenteric arteries a strong vasopressor power represented by norepinephrine and ATP integration is needed for maintaining peripheral resistance; on the other hand a mild vasopressor power mediated only by ATP is enough to maintain the vascular tone in the relatively central mesenteric branches.

Keywords: ATP, calves, mesenteric artery, norepinephrine

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Authors: Dereje Ferede, Solomon Negash

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Artificial Intelligence (AI) is a key enabler and driver to transform and revolutionize the healthcare industries. However, utilizing AI and achieving these benefits is challenging for different sectors in wide-ranging, more difficult for developing economy healthcare. Due to this, real-world clinical execution and implementation of AI have not yet aged. We believe that examining the determinants is key to addressing these challenges. Furthermore, the literature does not yet particularize determinants of AI capabilities and ways of empowering the healthcare ecosystem to develop AI capabilities in a developing economy. Thus, this study aims to position AI as a digital transformation weapon for the healthcare ecosystem by examining AI capability determinants and providing insights on better empowering the healthcare industry to develop AI capabilities. To do so, we base on the technology-organization-environment (TOE) model and will apply a mixed research approach. We will conclude with recommendations based on findings for future practitioners and researchers.

Keywords: artificial intelligence, capability, digital transformation, developing economies, healthcare

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Authors: Anuradha Gupta, Neelam Bansal, Varinder Uppal

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The present investigation was made on 35 Indian buffalo fetuses ranging from 0.9 cm to 104 cm curved crown rump length (CVRL). The gross anatomical study revealed that all structures were developed at 13 cm CVRL (87 days) in group I. At 0.9 cm CVRL (32 days) the heart was unseptated and tubular and was clearly divided into common atrial chamber dorsally and primitive ventricle in 1.2 cm CVRL fetus (34 days). Septum primum appeared at 1.9 cm CVRL (37 days), truncal ridges at 2.5 cm CVRL (39 days) and foramen ovale in 3.0 cm CVRL (42 days) buffalo foetuses. At 7.6 cm CVRL (62 days) endocardial cushions fused to form left and right atrioventricular openings and four chambered heart was formed in 8.7 cm CVRL (66 days). Endocardium and epicardium was thicker in atria as compared to ventricles in all the age groups. Myocardium of atria was thin as compared to ventricles in all the age groups and was loosely arranged. Immature hyaline cartilage was first appeared at base of aorta in 62 cm CVRL (213 days) fetuses. Intercalated discs were seen in group III and aorta, pulmonary artery, coronary artery were well appreciated in 3.2 cm CVRL (43 days). Neutral and acid mucopolysaccharides were comparatively more in atria than ventricles. Basic proteins showed strong reaction in atrium and ventricle, and intense in conduction system. Lipids and phospholipids were more in myocardium and conduction system than endocardium and epicardium. All the histochemical moieties were comparatively more in tunica intima than media and adventitia of all the great vessels of heart.

Keywords: buffalo, fetal development, histochemistry, heart

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Authors: Sawsan Eissa, Momen Gharib, Omnia Kabbany

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A flushing numerical study has been performed for intended artificial islands on the Persian Gulf coast in Abu Dhabi, UAE. The island masterplan was tested for flushing using the DELFT 3D hydrodynamic model, and it was found that its residence time exceeds the acceptable PIANC flushing Criteria. Therefore, a number of mitigation measures were applied and tested one by one using the flushing model. Namely, changing the location of the entrance opening, dredging, removing part of the mangrove existing in the near vicinity to create a channel, removing the mangrove altogether, using culverts of different numbers and locations, and pumping at selected points. The pumping option gave the best solution, but it was disregarded due to high capital and running costs. Therefore, it opted for a combination of other solutions, including removing mangroves, introducing culverts, and adjusting island boundaries and types of protection.

Keywords: hydrodynamics, flushing, delft 3d, Persian Gulf, artificial islands.

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Authors: Mernoosh Abouzari, Shahrokh Sahraei

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Electronic government is a way for governments to use new technology that provides people with the necessary facilities for proper access to government information and services, improving the quality of services and providing broad opportunities to participate in democratic processes and institutions. That leads to providing the possibility of easy use of information technology in order to distribute government services to the customer without holidays, which increases people's satisfaction and participation in political and economic activities. The expansion of e-government services and its movement towards intelligentization has the ability to re-establish the relationship between the government and citizens and the elements and components of the government. Electronic government is the result of the use of information and communication technology (ICT), which by implementing it at the government level, in terms of the efficiency and effectiveness of government systems and the way of providing services, tremendous commercial changes are created, which brings people's satisfaction at the wide level will follow. The main level of electronic government services has become objectified today with the presence of artificial intelligence systems, which recent advances in artificial intelligence represent a revolution in the use of machines to support predictive decision-making and Classification of data. With the use of deep learning tools, artificial intelligence can mean a significant improvement in the delivery of services to citizens and uplift the work of public service professionals while also inspiring a new generation of technocrats to enter government. This smart revolution may put aside some functions of the government, change its components, and concepts such as governance, policymaking or democracy will change in front of artificial intelligence technology, and the top-down position in governance may face serious changes, and If governments delay in using artificial intelligence, the balance of power will change and private companies will monopolize everything with their pioneering in this field, and the world order will also depend on rich multinational companies and in fact, Algorithmic systems will become the ruling systems of the world. It can be said that currently, the revolution in information technology and biotechnology has been started by engineers, large economic companies, and scientists who are rarely aware of the political complexities of their decisions and certainly do not represent anyone. Therefore, it seems that if liberalism, nationalism, or any other religion wants to organize the world of 2050, it should not only rationalize the concept of artificial intelligence and complex data algorithm but also mix them in a new and meaningful narrative. Therefore, the changes caused by artificial intelligence in the political and economic order will lead to a major change in the way all countries deal with the phenomenon of digital globalization. In this paper, while debating the role and performance of e-government, we will discuss the efficiency and application of artificial intelligence in e-government, and we will consider the developments resulting from it in the new world and the concepts of governance.

Keywords: electronic government, artificial intelligence, information and communication technology., system

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Authors: Sushil Kumar Singh, Vivek Tewarson, Sarvesh Kumar, Shobhit Kumar

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Objective: ‘Beating Heart coronary artery bypass grafting on Intermittent Pump Support’ is a more reliable method of coronary revascularization that takes advantage of off and on-pump CABG while eliminating the disadvantage of both techniques. Methods: From January 2015 to December 2021, a new technique, “Intermittent On pump beating heart CABG” using a suction stabilizer was used by putting aortic and venous cannulas electively in all the patients. Patients were supported by a pump intermittently, as and when required (Group 1, n=254). Retrospective data were collected from our record of the patients who underwent off-pump CABG electively by the same surgeon and team (Group 2, n=254). Results: Significant advantage was noted in Group 1 patients in terms of the number of grafts (3.31 ± 1.16 vs. 2.30 ±0.66), grafting of lateral vessels (316 vs.202), mean operating time (1.37 ± 0.23 hrs vs. 2.22 ± 0.45 hrs) and postoperative blood loss (406.30 ± 257.90 ml vs. 567.41 ± 265.20 ml).CPB support time was less than 15 minutes in the majority of patients (n=179, 70.37 %), with a mean of 16.81 minutes. It was required, particularly during the grafting of lateral vessels. A rise in enzymes level (CRP, CKMB, Trop I, and NTPro BNP) was noted in Group 1 patients. But, these did not affect the postoperative course in patients. There was no mortality in Group 1 patients, while four patients in Group 2 died. Coclusions: Intermittent on-pump CABG technique is a promising method of surgical revascularization for all patients requiring CABG. It has shown its superiority in terms of safety, the number of grafts, operating time, and better perioperative course.

Keywords: cardiopulmonary bypass, CABG, beating heart CABG, on-pump CABG

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Authors: Yulin Rao, Zhixuan Li, Burra Venkata Durga Kumar

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Intrusion detection refers to monitoring the actions of internal and external intruders on the system and detecting the behaviours that violate security policies in real-time. In intrusion detection, there has been much discussion about the application of neural network technology and artificial immune system (AIS). However, many solutions use static methods (signature-based and stateful protocol analysis) or centralized intrusion detection systems (CIDS), which are unsuitable for real-time intrusion detection systems that need to process large amounts of data and detect unknown intrusions. This article proposes a framework for a distributed intrusion detection system (DIDS) with multi-agents based on the concept of AIS and neural network technology to detect anomalies and intrusions. In this framework, multiple agents are assigned to each host and work together, improving the system's detection efficiency and robustness. The trainer agent in the central server of the framework uses the artificial neural network (ANN) rather than the negative selection algorithm of AIS to generate mature detectors. Mature detectors can distinguish between self-files and non-self-files after learning. Our analyzer agents use genetic algorithms to generate memory cell detectors. This kind of detector will effectively reduce false positive and false negative errors and act quickly on known intrusions.

Keywords: artificial immune system, distributed artificial intelligence, multi-agent, intrusion detection system, neural network

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Authors: Rachid Dehini, Brahim Berbaoui

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The main objectives of shunt active power filter (SAPF) is to preserve the power system from unwanted harmonic currents produced by nonlinear loads, as well as to compensate the reactive power. The aim of this paper is to present a (PAPF) supplied by the Photovoltaic cells ,in such a way that the (PAPF) feeds the linear and nonlinear loads by harmonics currents and the excess of the energy is injected into the power system. In order to improve the performances of conventional (PAPF) This paper also proposes artificial neural networks (ANN) for harmonics identification and DC link voltage control. The simulation study results of the new (SAPF) identification technique are found quite satisfactory by assuring good filtering characteristics and high system stability.

Keywords: SAPF, harmonics current, photovoltaic cells, MPPT, artificial neural networks (ANN)

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Authors: Guangyuan Zhao, Nan Huang, Xuesong Han, Xu Huang

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In order to solve the problem of sample dilution in the traditional particle filter algorithm and achieve accurate state estimation in a nonlinear system, a particle filter method based on an improved artificial bee colony (ABC) algorithm was proposed. The algorithm simulated the process of bee foraging and optimization and made the high likelihood region of the backward probability of particles moving to improve the rationality of particle distribution. The opposition-based learning (OBL) strategy is introduced to optimize the initial population of the artificial bee colony algorithm. The convergence factor is introduced into the neighborhood search strategy to limit the search range and improve the convergence speed. Finally, the crossover and mutation operations of the genetic algorithm are introduced into the search mechanism of the following bee, which makes the algorithm jump out of the local extreme value quickly and continue to search the global extreme value to improve its optimization ability. The simulation results show that the improved method can improve the estimation accuracy of particle filters, ensure the diversity of particles, and improve the rationality of particle distribution.

Keywords: particle filter, impoverishment, state estimation, artificial bee colony algorithm

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Authors: Savjot Kaur, Mridula Mahajan, AJS Bhanwer, Santokh Singh, Kawaljit Matharoo

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Background: Disorders of lipid metabolism and genetic predisposition are CAD risk factors. ApoA1 is the apolipoprotein component of anti-atherogenic high density lipoprotein (HDL) particles. The protective action of HDL and ApoA1 is attributed to their central role in reverse cholesterol transport (RCT). Aim: This study was aimed at identifying sequence variations in ApoA1 (-75G>A) and its association with serum ApoA1 levels. Methods: A total of 300 CAD patients and 300 Normal individuals (controls) were analyzed. PCR-RFLP method was used to determine the DNA polymorphism in the ApoA1 gene, PCR products digested with restriction enzyme MspI, followed by Agarose Gel Electrophoresis. Serum apolipoprotein A1 concentration was estimated with immunoturbidimetric method. Results: Deviation from Hardy- Weinberg Equilibrium (HWE) was observed for this gene variant. The A- allele frequency was higher among Coronary Artery disease patients (53.8) compared to controls (45.5), p= 0.004, O.R= 1.38(1.11-1.75). Under recessive model analysis (AA vs. GG+GA) AA genotype of ApoA1 G>A substitution conferred ~1 fold increased risk towards CAD susceptibility (p= 0.002, OR= 1.72(1.2-2.43). With serum ApoA1 levels < 107 A allele frequency was higher among CAD cases (50) as compared to controls (43.4) [p=0.23, OR= 1.2(0.84-2)] and there was zero % occurrence of A allele frequency in individuals with ApoA1 levels > 177. Conclusion: Serum ApoA1 levels were associated with ApoA1 promoter region variation and influence CAD risk. The individuals with the APOA1 -75 A allele confer excess hazard of developing CAD as a result of its effect on low serum concentrations of ApoA1.

Keywords: apolipoprotein A1 (G>A) gene polymorphism, coronary artery disease (CAD), reverse cholesterol transport (RCT)

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Authors: M. H. Hussain, I. Musirin, A. F. Abidin, S. R. A. Rahim

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This paper presents the implementation of Artificial Bees Colony (ABC) algorithm in solving Directional OverCurrent Relays (DOCRs) coordination problem for near-end faults occurring in fixed network topology. The coordination optimization of DOCRs is formulated as linear programming (LP) problem. The objective function is introduced to minimize the operating time of the associated relay which depends on the time multiplier setting. The proposed technique is to taken as a technique for comparison purpose in order to highlight its superiority. The proposed algorithms have been tested successfully on 8 bus test system. The simulation results demonstrated that the ABC algorithm which has been proved to have good search ability is capable in dealing with constraint optimization problems.

Keywords: artificial bees colony, directional overcurrent relay coordination problem, relay settings, time multiplier setting

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Authors: Tugce Talay, Kadir Erkan

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In this study, the necessary steps for the design of axial flow permanent magnet motors are shown. The design and analysis of the engine were carried out based on ANSYS Maxwell program. The design parameters of the ANSYS Maxwell program and the artificial neural network system were established in MATLAB and the most efficient design parameters were found with the trained neural network. The results of the Maxwell program and the results of the artificial neural networks are compared and optimal working design parameters are found. The most efficient design parameters were submitted to the ANSYS Maxwell 3D design and the cogging torque was examined and design studies were carried out to reduce the cogging torque.

Keywords: AFPM, ANSYS Maxwell, cogging torque, design optimisation, efficiency, NNTOOL

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Xi Gu, Guan Heng Yeoh, Victoria Timchenko

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In the current work, a three-dimensional geometry of a 75% stenosed blood vessel is analysed. Large eddy simulation (LES) with the help of a dynamic subgrid scale Smagorinsky model is applied to model the turbulent pulsatile flow. The geometry, the transmural pressure and the properties of the blood and the elastic boundary were based on clinical measurement data. For the flexible wall model, a thin solid region is constructed around the 75% stenosed blood vessel. The deformation of this solid region was modelled as a deforming boundary to reduce the computational cost of the solid model. Fluid-structure interaction is realised via a two-way coupling between the blood flow modelled via LES and the deforming vessel. The information of the flow pressure and the wall motion was exchanged continually during the cycle by an arbitrary lagrangian-eulerian method. The boundary condition of current time step depended on previous solutions. The fluctuation of the velocity in the post-stenotic region was analysed in the study. The axial velocity at normalised position Z=0.5 shows a negative value near the vessel wall. The displacement of the elastic boundary was concerned in this study. In particular, the wall displacement at the systole and the diastole were compared. The negative displacement at the stenosis indicates a collapse at the maximum velocity and the deceleration phase.

Keywords: Large Eddy Simulation, Fluid Structural Interaction, constricted artery, Computational Fluid Dynamics

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Authors: Jamerson Felipe Pereira Lima, Jeane Cecília Bezerra de Melo

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The difficulty and cost related to obtaining of protein tertiary structure information through experimental methods, such as X-ray crystallography or NMR spectroscopy, helped raising the development of computational methods to do so. An approach used in these last is prediction of tridimensional structure based in the residue chain, however, this has been proved an NP-hard problem, due to the complexity of this process, explained by the Levinthal paradox. An alternative solution is the prediction of intermediary structures, such as the secondary structure of the protein. Artificial Intelligence methods, such as Bayesian statistics, artificial neural networks (ANN), support vector machines (SVM), among others, were used to predict protein secondary structure. Due to its good results, artificial neural networks have been used as a standard method to predict protein secondary structure. Recent published methods that use this technique, in general, achieved a Q3 accuracy between 75% and 83%, whereas the theoretical accuracy limit for protein prediction is 88%. Alternatively, to achieve better results, support vector machines prediction methods have been developed. The statistical evaluation of methods that use different AI techniques, such as ANNs and SVMs, for example, is not a trivial problem, since different training sets, validation techniques, as well as other variables can influence the behavior of a prediction method. In this study, we propose a prediction method based on artificial neural networks, which is then compared with a selected SVM method. The chosen SVM protein secondary structure prediction method is the one proposed by Huang in his work Extracting Physico chemical Features to Predict Protein Secondary Structure (2013). The developed ANN method has the same training and testing process that was used by Huang to validate his method, which comprises the use of the CB513 protein data set and three-fold cross-validation, so that the comparative analysis of the results can be made comparing directly the statistical results of each method.

Keywords: artificial neural networks, protein secondary structure, protein structure prediction, support vector machines

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Authors: Badr M. Alshammari, T. Guesmi

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This study presents a modified version of the artificial bee colony (ABC) algorithm by including a local search technique for solving the non-convex economic power dispatch problem. The local search step is incorporated at the end of each iteration. Total system losses, valve-point loading effects and prohibited operating zones have been incorporated in the problem formulation. Thus, the problem becomes highly nonlinear and with discontinuous objective function. The proposed technique is validated using an IEEE benchmark system with ten thermal units. Simulation results demonstrate that the proposed optimization algorithm has better convergence characteristics in comparison with the original ABC algorithm.

Keywords: economic power dispatch, artificial bee colony, valve-point loading effects, prohibited operating zones

Procedia PDF Downloads 257

Authors: P. Siriarchawatana, K. Leungchavaphongse, N. Covavisaruch, K. Rojananuangnit, P. Boondaeng, N. Panyayingyong

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Glaucoma is a disease that causes visual loss in adults. Glaucoma causes damage to the optic nerve and its overall pathophysiology is still not fully understood. Vasculopathy may be one of the possible causes of nerve damage. Photographic imaging of retinal vessels by fundus camera during eye examination may complement clinical management. This paper presents an innovation for measuring central light reflex width-to-retinal vessel diameter ratio (CRR) from digital retinal photographs. Using our edge detection technique, CRRs from glaucoma and normal eyes were compared to examine differences and associations. CRRs were evaluated on fundus photographs of participants from Mettapracharak (Wat Raikhing) Hospital in Nakhon Pathom, Thailand. Fifty-five photographs from normal eyes and twenty-one photographs from glaucoma eyes were included. Participants with hypertension were excluded. In each photograph, CRRs from four retinal vessels, including arteries and veins in the inferotemporal and superotemporal regions, were quantified using edge detection technique. From our finding, mean CRRs of all four retinal arteries and veins were significantly higher in persons with glaucoma than in those without glaucoma (0.34 vs. 0.32, p < 0.05 for inferotemporal vein, 0.33 vs. 0.30, p < 0.01 for inferotemporal artery, 0.34 vs. 0.31, p < 0.01 for superotemporal vein, and 0.33 vs. 0.30, p < 0.05 for superotemporal artery). From these results, an increase in CRRs of retinal vessels, as quantitatively measured from fundus photographs, could be associated with glaucoma.

Keywords: glaucoma, retinal vessel, central light reflex, image processing, fundus photograph, edge detection

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Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir

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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.

Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.

Procedia PDF Downloads 385

Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

Procedia PDF Downloads 145

Authors: Daifeng Hao, Guang Feng, Jingfeng Zhao, Tao Li, Xiaoye Tuo

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Objective: To retrospectively analyze the clinical characteristics of incision infection with sternal osteomyelitis sinus tract after cardiac surgery and the operation method and therapeutic effect of filling and repairing with activated PRP gel. Methods: From March 2011 to October 2022, 142 cases of incision infection after cardiac surgery with sternal osteomyelitis sinus were retrospectively analyzed, and the causes of poor wound healing after surgery, wound characteristics, perioperative wound management were summarized. Treatment during operation, collection and storage process of autologous PRP before debridement surgery, PRP filling repair and activation method after debridement surgery, effect of anticoagulant drugs on surgery, postoperative complications and average wound healing time, etc.. Results: Among the cases in this group, 53.3% underwent coronary artery bypass grafting, 36.8% underwent artificial heart valve replacement, 8.2% underwent aortic artificial vessel replacement, and 1.7% underwent allogeneic heart transplantation. The main causes of poor incision healing were suture reaction, fat liquefaction, osteoporosis, diabetes, and metal allergy in sequence. The wound is characterized by an infected sinus tract. Before the operation, 100-150ml of PRP with 4 times the physiological concentration was collected separately with a blood component separation device. After sinus debridement, PRP was perfused to fill the bony defect in the middle of the sternum, activated with thrombin freeze-dried powder and calcium gluconate injection to form a gel, and the outer skin and subcutaneous tissue were sutured freely. 62.9% of patients discontinued warfarin during the perioperative period, and 37.1% of patients maintained warfarin treatment. There was no significant difference in the incidence of postoperative wound hematoma. The average postoperative wound healing time was 12.9±4.7 days, and there was no obvious postoperative complication. Conclusions: Application of activated PRP gel to fill incision infection with sternal osteomyelitis sinus after cardiac surgery has a less surgical injury and satisfactory and stable curative effect. It can completely replace the previously used pectoralis major muscle flap transplantation operation scheme.

Keywords: platelet-rich plasma, negative-pressure wound therapy, sternal osteomyelitis, cardiac surgery

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Authors: Vladimir Sharapaev

Abstract:

This paper seeks to address the question of the authorship of copyrighted works created solely by the artificial intelligence or with the use thereof, and proposes possible interpretational or legislative solutions to the problems arising from the plurality of the persons potentially involved in the ultimate creation of the work and division of tasks among such persons. Being based on the commonly accepted assumption that a copyrighted work can only be created by a natural person, the paper does not deal with the issues regarding the creativity of the artificial intelligence per se (or the lack thereof), and instead focuses on the distribution of the intellectual property rights potentially belonging to the creators of the artificial intelligence and/or the creators of the content used for the formation of the copyrighted work. Moreover, the technical development and rapid improvement of the AI-based programmes, which tend to be reaching even greater independence on a human being, give rise to the question whether the initial creators of the artificial intelligence can be entitled to the intellectual property rights to the works created by such AI at all. As the juridical practice of some European courts and legal doctrine tends to incline to the latter opinion, indicating that the works created by the AI may not at all enjoy copyright protection, the questions of authorships appear to be causing great concerns among the investors in the development of the relevant technology. Although the technology companies dispose with further instruments of protection of their investments, the risk of the works in question not being copyrighted caused by the inconsistency of the case law and a certain research gap constitutes a highly important issue. In order to assess the possible interpretations, the author adopted a doctrinal and analytical approach to the research, systematically analysing the European and Czech copyright laws and case law in some EU jurisdictions. This study aims to contribute to greater legal certainty regarding the issues of the authorship of the AI-created works and define possible clues for further research.

Keywords: artificial intelligence, copyright, authorship, copyrighted work, intellectual property

Procedia PDF Downloads 122