Search results for: automated diagnoses

Authors: Tatipamula Samiksha Goud, .A.Naveena, M.sresta

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Traffic congestion is a major issue in many cities throughout the world, particularly in urban areas, and it is past time to switch from a fixed timer mode to an automated system. The current traffic signalling system is a fixed-time system that is inefficient if one lane is more functional than the others. A structure for an intelligent traffic control system is being designed to address this issue. When traffic density is higher on one side of a junction, the signal's green time is extended in comparison to the regular time. This study suggests a technique in which the signal's time duration is assigned based on the amount of traffic present at the time. Infrared sensors can be used to do this.

Keywords: infrared sensors, micro-controllers, LEDs, oscillators

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Authors: Anusha Jain, Santosh Vishwanathan, Praveen K. Gupta, Shwetha S., Kavitha S. N.

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Agriculture has a major impact on the Indian economy, with the highest employment ratio than any sector of the country. Currently, most of the traditional agricultural practices and farming methods are manual, which results in farmers not realizing their maximum productivity often due to increasing in labour cost, inefficient use of water sources leading to wastage of water, inadequate soil moisture content, subsequently leading to food insecurity of the country. This research paper aims to solve this problem by developing a full-fledged web application-based platform that has the capacity to associate itself with a Microcontroller-based Automated Irrigation System which schedules the irrigation of crops based on real-time soil moisture content employing soil moisture sensors centric to the crop’s requirements using WSN (Wireless Sensor Networks) and M2M (Machine To Machine Communication) concepts, thus optimizing the use of the available limited water resource, thereby maximizing the crop yield. This robust automated irrigation system provides end-to-end automation of Irrigation of crops at any circumstances such as droughts, irregular rainfall patterns, extreme weather conditions, etc. This platform will also be capable of achieving a nationwide united farming community and ensuring the welfare of farmers. This platform is designed to equip farmers with prerequisite knowledge on tech and the latest farming practices in general. In order to achieve this, the MailChimp mailing service is used through which interested farmers/individuals' email id will be recorded and curated articles on innovations in the world of agriculture will be provided to the farmers via e-mail. In this proposed system, service is enabled on the platform where nearby crop vendors will be able to enter their pickup locations, accepted prices and other relevant information. This will enable farmers to choose their vendors wisely. Along with this, we have created a blogging service that will enable farmers and agricultural enthusiasts to share experiences, helpful knowledge, hardships, etc., with the entire farming community. These are some of the many features that the platform has to offer.

Keywords: WSN (wireless sensor networks), M2M (M/C to M/C communication), automation, irrigation system, sustainability, SAAS (software as a service), soil moisture sensor

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Authors: Hammad Khalid

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In this paper, a strategy for computerized arranging of Fiber to the Home (FTTH) get to systems is proposed. We presented an efficient methodology for arranging access organize framework. The GIS information and a lot of calculations were utilized to make the arranging procedure increasingly programmed. The technique clarifies various strides of the arranging process. Considering various situations, various designs can be produced by utilizing the technique. It was likewise conceivable to produce the designs in an extremely brief temporal contrast with the conventional arranging. A contextual investigation is considered to delineate the utilization and abilities of the arranging technique. The technique, be that as it may, doesn't completely robotize the arranging however, make the arranging procedure fundamentally quick. The outcomes and dialog are displayed and end is given at last.

Keywords: FTTH, GIS, robotize, plan

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Authors: Ivanka Valova

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This paper is aimed at using a multi-agent approach to monitor and diagnose a biotechnological system in order to validate certain control actions depending on the process development and the operating conditions. A multi-agent system is defined as a network of interacting software modules that collectively solve complex tasks. Remote monitoring and control of biotechnological processes is a necessity when automated and reliable systems operating with no interruption of certain activities are required. The advantage of our approach is in its flexibility, modularity and the possibility of improving by acquiring functionalities through the integration of artificial intelligence.

Keywords: multi-agent approach, artificial intelligence, biotechnological processes, anaerobic biodegradation

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Authors: Igor Belykh

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Anti-scatter grids used in radiographic imaging for the contrast enhancement leave specific artifacts. Those artifacts may be visible or may cause Moiré effect when a digital image is resized on a diagnostic monitor. In this paper, we propose an automated grid artifacts detection and suppression algorithm which is still an actual problem. Grid artifacts detection is based on statistical approach in spatial domain. Grid artifacts suppression is based on Kaiser bandstop filter transfer function design and application avoiding ringing artifacts. Experimental results are discussed and concluded with description of advantages over existing approaches.

Keywords: grid, computed radiography, pattern recognition, image processing, filtering

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Authors: Mayssa Bensalah, Atef Boujelben, Mouna Baklouti, Mohamed Abid

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Image segmentation has a fundamental role in analysis and interpretation for many applications. The automated segmentation of organs and tissues throughout the body using computed imaging has been rapidly increasing. Indeed, it represents one of the most important parts of clinical diagnostic tools. In this paper, we discuss a thorough literature review of recent methods of tumour segmentation from medical images which are briefly explained with the recent contribution of various researchers. This study was followed by comparing these methods in order to define new directions to develop and improve the performance of the segmentation of the tumour area from medical images.

Keywords: features extraction, image segmentation, medical images, tumor detection

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Authors: Robin Singh, Jing-Chiou Liou

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The Internet of Things (IoT) devices are being used heavily as part of our everyday routines. Through improved communication and automated procedures, its popularity has assisted users in raising the quality of work. These devices are used in healthcare in order to better collect the patient’s data for their treatment. They are generally considered safe and secure. However, there is some possibility that some loopholes do exist which manufacturers do need to identify before some hacker takes advantage of them. For this study, we focused on two medical IoT devices which are pacemakers and hearing aids. The aim of this paper is to identify if there is any likelihood of these medical devices being hijacked and used as a botnet in Distributed Denial-Of Service attacks. Moreover, some mitigation strategies are being proposed to better secure

Keywords: cybersecurity, DDoS, IoT, medical devices

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Authors: Joel Vilca Tarazona, Igor Aguilar-Alonso

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The problem of this research related to business intelligence is the lack of a tool that supports automated and efficient financial analysis for decision-making and allows an evaluation of the financial statements, which is why the availability of the information is difficult. Relevant information to managers and users as an instrument in decision making financial, and administrative. For them, a business intelligence solution is proposed that will reduce information access time, personnel costs, and process automation, proposing a 4-layer architecture based on what was reviewed by the research methodology.

Keywords: decision making, business intelligence, Google Cloud, Microsoft Power BI

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Authors: Erekle Magradze, Davit Soselia, Levan Shughliashvili, Irakli Koberidze, Shota Tsiskaridze, Victor Kakhniashvili, Tamar Chaghiashvili

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Since the beginning of active publishing activity in Georgia, voluminous printed material has been accumulated, the digitization of which is an important task. Digitized materials will be available to the audience, and it will be possible to find text in them and conduct various factual research. Digitizing scanned documents means scanning documents, extracting text from the scanned documents, and processing the text into a corresponding language model to detect inaccuracies and grammatical errors. Implementing these stages requires a unified, scalable, and automated platform, where the digital service developed for each stage will perform the task assigned to it; at the same time, it will be possible to develop these services dynamically so that there is no interruption in the work of the platform.

Keywords: NLP, OCR, BERT, Kubernetes, transformers

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Authors: Qurat-ul-Ain, Humaira Mehmood

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Background: HIV infection (a global pandemic) in pregnant women has turn out to be an emerging aspect of public health because of its role in the spread of HIV infection, predominantly among children. Aim: The aim was to analyze the trends of diagnosis with respect to gestational age and an overview of the mode of delivery over ten years. Methods: A retrospective data collection from clinical records of diagnosed HIV infected pregnant females attended at HIV antenatal clinic (special clinic), at Pakistan Institute of Medical Sciences, Islamabad, for various complaints during the period of 10 years from February 2007 to December 2016 was done. Results: A total of 113 pregnancies were reported with HIV infection in 10 years. Cases diagnosed at the 1st trimester (1-12 weeks) of pregnancy were (50.4%, 57/113), at the 2nd trimester (13-26 weeks) were (24.8%, 28/113), at the 3rd trimester (27-40+ weeks) were (24.7%, 28/113). Most deliveries were by caesarean section (53.1%, 60/113), elective caesarean sections were (58.3%, 35/60) and emergency caesarean sections were (41.6%,25/60). Vaginal deliveries were (26.5%, 30/113). Reported miscarriages were (17.7%, 20/113). Conclusion: At 1st trimester, 50% of the females were diagnosed with HIV infection, and 50% remained undiagnosed at their 1st trimester. Routine antenatal HIV testing throughout the country is vastly needed for timely diagnoses and prompt treatment(antiretroviral therapy), to suppress the virus, to reduce the risk of spread of HIV infection, to plan elective caesarean section delivery and to prevent mother-to-child transmission.

Keywords: gestational age, HIV infection, mode of delivery, pregnancy

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Authors: Osama Shakeel

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The objective of the paper is to study the clinic-pathological factors, survival analyses, recurrence rate, metastatic rate, risk factors and the management of cutaneous malignant melanoma at Shaukat Khanum Memorial Cancer Hospital and Research Center. Methodology: From 2014 to 2017, all patients with a diagnosis of cutaneous malignant melanoma (CMM) were included in the study. Demographic variables were collected. Short and long term oncological outcomes were recorded. All data were entered and analyzed in SPSS version 21. Results: A total of 28 patients were included in the study. Median age was 46.5 +/-15.9 years. There were 16 male and 12 female patients. The family history of melanoma was present in 7.1% (n=2) of the patients. All patients had a mean survival of 13.43+/- 9.09 months. Lower limb was the commonest site among all which constitutes 46.4%(n=13). On histopathological analyses, ulceration was seen in 53.6% (n=15) patients. Unclassified tumor type was present in 75%(n=21) of the patients followed by nodular 21.4% (n=6) and superficial spreading 3.5%(n=1). Clark level IV was the commonest presentation constituting 46.4%(n=13). Metastases were seen in 50%(n=14) of the patients. Local recurrence was observed in 60.7%(n=17). 64.3%(n=18) lived after one year of treatment. Conclusion: CMM is a fatal disease. Although its disease of fair skin individuals, however, the incidence of CMM is also rising in this part of the world. Management includes early diagnoses and prompt management. However, mortality associated with this disease is still not favorable.

Keywords: malignant cancer of skin, cutaneous malignant melanoma, skin cancer, survival analyses

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Authors: Ali Fuad Ashour

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Introduction: Contrary to the common belief that physical training for multiple sclerosis (MS) patients might exacerbate fatigue and provoke other symptoms of the illness, it is now widely accepted that exercise can be actually beneficial in terms of activities of daily living, reduced fatigue, and improved quality of life. The aim of this study was to assess the attitude of MS patients toward exercise. Methodology: 112 MS patients who were recruited from the local community participated in this study. We utilised a self-developed questionnaire targeting attitudes and perceptions of MS patients towards physical exercise. The questionnaire was piloted and tested for validity and reliability. Results: Before being diagnosed with MS, 49.9% of our MS patients’ respondents used to engage in different types of physical activities and sports, namely aerobics/walking (35.3%), stretching exercise (18.7%), and strengthening exercise (11.4%). After being diagnosed with MS, 40.8% of our sample showed determination to remain physically active. The interest in sports activities was consistent after the diagnoses with MS and included aerobics/walking (33.8%), stretching exercise (22.6%), and strengthening exercise (19.7%). Discussion: The Kuwaiti respondents thought that lack of encouragement was the main reason for them not exercise. Aptly put, if they try to exercise, they will be discouraged by the loved ones lest the worse happens. On the other side, British patients are generally aware of the benefits of physical and mental health-promoting activities; they can seek help from a wide range of professionals and are more actively involved in the management of their condition. It is therefore important that the benefits of physical activity are promoted among MS patients, and that attitude towards MS and MS patients is changed through education.

Keywords: perception, multiple sclerosis, exercise, physical training

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Authors: Frantisek Kopriva, Kamila Michalkova, Radim Dudek, Jana Volejnikova

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Rationale: Diagnostic criteria of asthma–COPD overlap syndrome (ACOS) are controversial in pediatrics. Emphysema is characteristic of COPD and usually does not occur in typical asthma; its presence in patients with asthma suggests the concurrence with COPD. Low-dose chest computed tomography (CT) allows a non-invasive assessment of the lung tissue structure. Here we present CT findings of emphysematous changes in a child with ACOS. Patient and Methods: In a 6-year-old boy, atopy was confirmed by a skin prick test using common allergen extracts (grass and tree pollen, house dust mite, molds, cat, dog; manufacturer Stallergenes Greer, London, UK), where reactions over 3 mm were considered positive. Treatment with corticosteroids was started during the course of severe asthma. At 12 years of age, his spirometric parameters deteriorated despite treatment adjustment (VC 1.76 L=85%, FEV1 1.13 L=67%, TI%VCmax 64%, MEF25 19%, TLC 144%) and the bronchodilator test became negative. Results: Low-dose chest CT displayed irregular regions with increased radiolucency of pulmonary parenchyma (typical for hyperinflation in emphysematous changes) in both lungs. This was in accordance with the results of spirometric examination. Conclusions: ACOS is infrequent in children. However, low-dose chest CT scan can be considered to confirm this diagnosis or eliminate other diagnoses when the clinical condition is deteriorating and treatment response is poor.

Keywords: child, asthma, low-dose chest CT, ACOS

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Authors: Alexander Street, Nina Wollersberger, Paul Fernie, Leonardo Muller, Ming Hung HSU, Helen Odell-Miller, Jorg Fachner, Patrizia Di Campli San Vito, Stephen Brewster, Hari Shaji, Satvik Venkatesh, Paolo Itaborai, Nicolas Farina, Alexis Kirke, Sube Banerjee, Eduardo Reck Miranda

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Escalating neuropsychiatric symptoms (NPS) in people with dementia may lead to earlier care home admission. Music listening has been reported to stimulate cognitive function, potentially reducing agitation in this population. We present a scoping review, reporting on current developments and discussing the potential for music listening with related technology in managing agitation in dementia care. Of two searches for music listening studies, one focused on older people or people living with dementia where music listening interventions, including technology, were delivered in participants’ homes or in institutions to address neuropsychiatric symptoms, quality of life and independence. The second included any population focusing on the use of music technology for health and wellbeing. In search one 70/251 full texts were included. The majority reported either statistical significance (6, 8.5%), significance (17, 24.2%) or improvements (26, 37.1%). Agitation was specifically reported in 36 (51.4%). The second search included 51/99 full texts, reporting improvement (28, 54.9%), significance (11, 21.5%), statistical significance (1, 1.9%) and no difference compared to the control (6, 11.7%). The majority in the first focused on mood and agitation, and the second on mood and psychophysiological responses. Five studies used AI or machine learning systems to select music, all involving healthy controls and reporting benefits. Most studies in both reviews were not conducted in a home environment (review 1 = 12; 17.1%; review 2 = 11; 21.5%). Preferred music listening may help manage NPS in the care home settings. Based on these and other data extracted in the review, a reasonable progression would be to co-design and test music listening systems and protocols for NPS in all settings, including people’s homes. Machine learning and automated technology for music selection and arousal adjustment, driven by live biodata, have not been explored in dementia care. Such approaches may help deliver the right music at the appropriate time in the required dosage, reducing the use of medication and improving quality of life.

Keywords: music listening, dementia, agitation, scoping review, technology

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Authors: Abdullah H. Özcan, Dilara Hisar, Yetkin Sayar, Cem Ünsalan

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In this study, an automated building and tree detection method is proposed using DSM data and true orthophoto image. A multiscale matched filtering is used on DSM data. Therefore, first watershed transform is applied. Then, Otsu’s thresholding method is used as an adaptive threshold to segment each watershed region. Detected objects are masked with NDVI to separate buildings and trees. The proposed method is able to detect buildings and trees without entering any elevation threshold. We tested our method on ISPRS semantic labeling dataset and obtained promising results.

Keywords: building detection, local maximum filtering, matched filtering, multiscale

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Ayodele James Akinola

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This study examines how social and linguistic variables influenced communication between neurologists and patients in selected university teaching hospitals (UTHs) in southwestern Nigeria. Jacob Mey’s Pragmatic Acts, complemented by Emanuel and Emanuel’s model of doctor-patient relationship, served as the theoretical framework. Data comprising 22 audio-recorded neurologist-patient interactions were collected from two UTHs in the southwestern region of Nigeria. Data revealed that educational attainment of patients has insignificant influence on the interaction where the linguistic prowess of the patient has been impaired for consultative communication. However, the status influenced the degree of attention paid to patients by neurologists and determines the amount of time 'trying to help patients to communicate'. Patients with lower educational status and who could not communicate in English spent more time narrating their ailment to neurologists. Patients with higher educational status and could communicate in English saves consultation time as they express themselves briefly unlike those who were of little or no education in the clinics. Through this, diagnoses and therapeutic processes took eight to 12 minutes. 20 minutes was the longest duration recorded. Neurologist-patient interaction in the observed hospitals is shaped by neurologists’ experience, patients’ social variables and language.

Keywords: medical pragmatics, neurologist-patient interaction, nigeria, socio-linguistic influence

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Authors: Marianne Paimre

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Estonia is heralded as the most successful digital country in the world with the highly acclaimed eHealth system. Yet 40% of the 65–74-year-olds do not use the Internet at all, and digital divide between young and elderly people's use of ICT is larger than in many advanced countries. Poor access to ICT resource and insufficient digital skills can lead to detachment from digital health resources, delayed diagnoses, and increased rates of hospitalization. To reveal digital divide within the elderly population itself, the presentation focuses on the health information behavior of Estonian seniors who either continue or have stopped working after retirement to use digital health applications. The author's main interest is on access, trust, and skills to use the Internet for medical purposes. Fifteen in-depth interviews with 65+ working persons, as well as 15 interviews with full-time retirees, were conducted. Also, six think-aloud protocols were conducted. The results indicate that older adults, who due to the nature of their work, have regular access to computers, often search for health-related information online. They exposed high source criticism and were successful in solving the given tasks. Conversely, most of the fully retired older adults claimed not using computers or other digital devices and cited lack of skills as the main reason for their inactivity. Thus, when developing health applications, it should be borne in mind that the ability and willingness of older adults to use e-solutions are very different.

Keywords: digital divide, digital healthcare, health information behavior, older adults

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Authors: Mohammad Abu-Shaira, Weishi Shi

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Adaptive learning, a commonly employed solution to drift, involves updating predictive models online during their operation to react to concept drifts, thereby serving as a critical component and natural extension for online learning systems that learn incrementally from each example. This paper introduces LSTM-SCCM “Long Short-Term Memory Stream Cruise Control Method”, a drift adaptation-as-a-service framework for online learning. LSTM-SCCM automates drift adaptation through prompt detection, drift magnitude quantification, dynamic hyperparameter tuning, performing shortterm optimization and model recalibration for immediate adjustments, and, when necessary, conducting long-term model recalibration to ensure deeper enhancements in model performance. LSTM-SCCM is incorporated into a suite of cutting-edge online regression models, assessing their performance across various types of concept drift using diverse datasets with varying characteristics. The findings demonstrate that LSTM-SCCM represents a notable advancement in both model performance and efficacy in handling concept drift occurrences. LSTM-SCCM stands out as the sole framework adept at effectively tackling concept drifts within regression scenarios. Its proactive approach to drift adaptation distinguishes it from conventional reactive methods, which typically rely on retraining after significant degradation to model performance caused by drifts. Additionally, LSTM-SCCM employs an in-memory approach combined with the Self-Adjusting Memory (SAM) architecture to enhance real-time processing and adaptability. The framework incorporates variable thresholding techniques and does not assume any particular data distribution, making it an ideal choice for managing high-dimensional datasets and efficiently handling large-scale data. Our experiments, which include abrupt, incremental, and gradual drifts across both low- and high-dimensional datasets with varying noise levels, and applied to four state-of-the-art online regression models, demonstrate that LSTM-SCCM is versatile and effective, rendering it a valuable solution for online regression models to address concept drift.

Keywords: automated drift detection and adaptation, concept drift, hyperparameters optimization, online and adaptive learning, regression

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Authors: Radul Shishkov, Orlin Davchev

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The digital era has revolutionized architectural practices, with building information modeling (BIM) emerging as a pivotal tool for architects, engineers, and construction professionals. However, the transition from traditional methods to BIM-centric approaches poses significant challenges, particularly in the context of existing structures. This research introduces a technical approach to bridge this gap through the development of algorithms that facilitate the automated transformation of 3D point cloud data into detailed BIM models. The core of this research lies in the application of algorithmic modeling and computational design methods to interpret and reconstruct point cloud data -a collection of data points in space, typically produced by 3D scanners- into comprehensive BIM models. This process involves complex stages of data cleaning, feature extraction, and geometric reconstruction, which are traditionally time-consuming and prone to human error. By automating these stages, our approach significantly enhances the efficiency and accuracy of creating BIM models for existing buildings. The proposed algorithms are designed to identify key architectural elements within point clouds, such as walls, windows, doors, and other structural components, and to translate these elements into their corresponding BIM representations. This includes the integration of parametric modeling techniques to ensure that the generated BIM models are not only geometrically accurate but also embedded with essential architectural and structural information. Our methodology has been tested on several real-world case studies, demonstrating its capability to handle diverse architectural styles and complexities. The results showcase a substantial reduction in time and resources required for BIM model generation while maintaining high levels of accuracy and detail. This research contributes significantly to the field of architectural technology by providing a scalable and efficient solution for the integration of existing structures into the BIM framework. It paves the way for more seamless and integrated workflows in renovation and heritage conservation projects, where the accuracy of existing conditions plays a critical role. The implications of this study extend beyond architectural practices, offering potential benefits in urban planning, facility management, and historic preservation.

Keywords: BIM, 3D point cloud, algorithmic modeling, computational design, architectural reconstruction

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Authors: Magda Olesiuk-Okomska

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Although international criminal law has grown significantly in the last decades, it still remains fragmented and lacks doctrinal cohesiveness. Its concept is described in the doctrine as highly disputable. There is no concrete definition of the term. In the domestic doctrine, the problem of criminal law issues that arise in the international setting, and international issues that arise within the national criminal law, is underdeveloped both theoretically and practically. To the best of author’s knowledge, there are no studies describing international aspects of criminal law in a comprehensive manner, taking a more expansive view of the subject. This paper presents results of a part of the doctoral research, undertaking a theoretical framework of the international criminal law. It aims at sorting out the existing terminology on international aspects of criminal law. It demonstrates differences between the notions of international criminal law, criminal law international and law international criminal. It confronts the notion of criminal law with related disciplines and shows their interplay. It specifies the scope of international criminal law. It diagnoses the current legal framework of international aspects of criminal law, referring to both criminal law issues that arise in the international setting, and international issues that arise in the context of national criminal law. Finally, de lege lata postulates were formulated and direction of changes in international criminal law was proposed. The adopted research hypothesis assumed that the notion of international criminal law was inconsistent, not understood uniformly, and there was no conformity as to its place within the system of law, objective and subjective scopes, while the domestic doctrine did not correspond with international standards and differed from the worldwide doctrine. Implemented research methods included inter alia a dogmatic and legal method, an analytical method, a comparative method, as well as desk research.

Keywords: criminal law, international crimes, international criminal law, international law

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Authors: Metehan Mutlu, Meltem Elitas

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This study aims to provide an automated method for placing the balloon uterine stents after hysteroscopy adhesiolysis. Currently, there are no automatized tools to place the balloon uterine stent; therefore, surgeons into the endometrial cavity manually fit it. However, it is very hard to pass the balloon stent through the cervical canal, which is roughly 10mm after the surgery. Our method aims to provide an effective and practical way of placing the stent, by automating the procedure through our designed device. Furthermore, our device does the required tasks fast compared to traditional methods, reduces the narcosis time, and decreases the bacterial contamination risks.

Keywords: balloon uterine stent, endometrial cavity, hysteroscopy, motorized-tool

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Authors: Ayat E. Ali, Christeen R. Aziz, Merna A. Helmy, Mohammed M. Malek, Sherif H. El-Gohary

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Goal: Purpose of the project was to make a plastic surgery prediction by using pre-operative images for the plastic surgeries’ patients and to show this prediction on a screen to compare between the current case and the appearance after the surgery. Methods: To this aim, we implemented a software which used data from the internet for facial skin diseases, skin burns, pre-and post-images for plastic surgeries then the post- surgical prediction is done by using K-nearest neighbor (KNN). So we designed and fabricated a smart mirror divided into two parts a screen and a reflective mirror so patient's pre- and post-appearance will be showed at the same time. Results: We worked on some skin diseases like vitiligo, skin burns and wrinkles. We classified the three degrees of burns using KNN classifier with accuracy 60%. We also succeeded in segmenting the area of vitiligo. Our future work will include working on more skin diseases, classify them and give a prediction for the look after the surgery. Also we will go deeper into facial deformities and plastic surgeries like nose reshaping and face slim down. Conclusion: Our project will give a prediction relates strongly to the real look after surgery and decrease different diagnoses among doctors. Significance: The mirror may have broad societal appeal as it will make the distance between patient's satisfaction and the medical standards smaller.

Keywords: k-nearest neighbor (knn), face detection, vitiligo, bone deformity

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Authors: Dahi Ghareab Abdelsalam Ibrahim, R. H. Bakr

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Ionizing radiation, such as gamma radiation and X-rays, has many applications in medical diagnoses and cancer treatment. In this paper, we used the windowed Fourier transform to extract the complex image of the deformed red blood cells. The real values of the complex image are used to extract the best fitting of the deformed cell boundary. Male albino rats are irradiated by γ-rays from ⁶⁰Co. The male albino rats are anesthetized with ether, and then blood samples are collected from the eye vein by heparinized capillary tubes for studying the radiation-damaging effect in-vivo by the proposed windowed Fourier transform. The peripheral blood films are prepared according to the Brown method. The peripheral blood film is photographed by using an Automatic Image Contour Analysis system (SAMICA) from ELBEK-Bildanalyse GmbH, Siegen, Germany. The SAMICA system is provided with an electronic camera connected to a computer through a built-in interface card, and the image can be magnified up to 1200 times and displayed by the computer. The images of the peripheral blood films are then analyzed by the windowed Fourier transform method to extract the precise deformation from the best fitting. Based on accurate deformation evaluation of the red blood cells, diseases can be diagnosed in their primary stages.

Keywords: windowed Fourier transform, red blood cells, phase wrapping, Image processing

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Authors: Amin Nazerzadeh, Afsaneh Nouri Houshyar , Azadeh Noori Hoshyar

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With the rapid growing of information technology, the industry and manufacturing systems are becoming more automated. Therefore, achieving the highly accurate automatic systems with reliable security is becoming more critical. Biometrics that refers to identifying individual based on physiological or behavioral traits are unique identifiers provide high reliability and security in different industrial systems. As biometric cannot easily be transferred between individuals or copied, it has been receiving extensive attention. Due to the importance of security applications, this paper provides an overview on biometrics and discuss about background, types and applications of biometric as an effective tool for the industrial applications.

Keywords: Industial and manufacturing applications, intelligence and security, information technology, recognition; security technology; biometrics

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Authors: Pavel H. Llamocca, Victoria Lopez

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The main objective of our work is the comparative analysis of environmental data from Open Data bases, belonging to different governments. This means that you have to integrate data from various different sources. Nowadays, many governments have the intention of publishing thousands of data sets for people and organizations to use them. In this way, the quantity of applications based on Open Data is increasing. However each government has its own procedures to publish its data, and it causes a variety of formats of data sets because there are no international standards to specify the formats of the data sets from Open Data bases. Due to this variety of formats, we must build a data integration process that is able to put together all kind of formats. There are some software tools developed in order to give support to the integration process, e.g. Data Tamer, Data Wrangler. The problem with these tools is that they need data scientist interaction to take part in the integration process as a final step. In our case we don’t want to depend on a data scientist, because environmental data are usually similar and these processes can be automated by programming. The main idea of our tool is to build Hadoop procedures adapted to data sources per each government in order to achieve an automated integration. Our work focus in environment data like temperature, energy consumption, air quality, solar radiation, speeds of wind, etc. Since 2 years, the government of Madrid is publishing its Open Data bases relative to environment indicators in real time. In the same way, other governments have published Open Data sets relative to the environment (like Andalucia or Bilbao). But all of those data sets have different formats and our solution is able to integrate all of them, furthermore it allows the user to make and visualize some analysis over the real-time data. Once the integration task is done, all the data from any government has the same format and the analysis process can be initiated in a computational better way. So the tool presented in this work has two goals: 1. Integration process; and 2. Graphic and analytic interface. As a first approach, the integration process was developed using Java and Oracle and the graphic and analytic interface with Java (jsp). However, in order to open our software tool, as second approach, we also developed an implementation with R language as mature open source technology. R is a really powerful open source programming language that allows us to process and analyze a huge amount of data with high performance. There are also some R libraries for the building of a graphic interface like shiny. A performance comparison between both implementations was made and no significant differences were found. In addition, our work provides with an Official Real-Time Integrated Data Set about Environment Data in Spain to any developer in order that they can build their own applications.

Keywords: open data, R language, data integration, environmental data

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Authors: Reza Karimpour

Abstract:

Ports play a decisive role in the EU's external and internal trade, as about 74% of imports and exports and 37% of exchanges go through ports. Although ports, especially Deep Sea Shipping (DSS) ports, are integral nodes within multimodal logistic flows, Short Sea Shipping (SSS) and inland waterways are not so well integrated. The automated vessels and supply chain optimisations for sustainable shortsea shipping (MOSES) project aims to enhance the short sea shipping component of the European supply chain by addressing the vulnerabilities and strains related to the operation of large containerships. The MOSES concept can be shortly described as a large containership (mother-vessel) approaching a DSS port (or a large container terminal). Upon her arrival, a combined intelligent mega-system consisting of the MOSES Autonomous tugboat swarm for manoeuvring and the MOSES adapted AutoMoor system. Then, container handling processes are ready to start moving containers to their destination via hinterland connections (trucks and/or rail) or to be shipped to destinations near small ports (on the mainland or island). For the first case, containers are stored in a dedicated port area (Storage area), waiting to be moved via trucks and/or rail. For the second case, containers are stacked by existing port equipment near-dedicated berths of the DSS port. They then are loaded on the MOSES Innovative Feeder Vessel, equipped with the MOSES Robotic Container-Handling System that provides (semi-) autonomous (un) feeding of the feeder. The Robotic Container-Handling System is remotely monitored through a Shore Control Centre. When the MOSES innovative Feeder vessel approaches the small port, where her docking is achieved without tugboats, she automatically unloads the containers using the Robotic Container-Handling System on the quay or directly on trucks. As a result, ports with minimal or no available infrastructure may be effectively integrated with the container supply chain. Then, the MOSES innovative feeder vessel continues her voyage to the next small port, or she returns to the DSS port. MOSES exploitation activity mainly aims to exploit research outcomes beyond the project, facilitate utilisation of the pilot results by others, and continue the pilot service after the project ends. By the mid-lifetime of the project, the exploitation plan introduces the reader to the MOSES project and its key exploitable results. It provides a plan for delivering the MOSES innovations to the market as part of the overall exploitation plan.

Keywords: automated vessels, exploitation, shortsea shipping, supply chain

Procedia PDF Downloads 112

Authors: M. A. Okezue, K. L. Clase, S. R. Byrn

Abstract:

The requirement for maintaining data integrity in laboratory operations is critical for regulatory compliance. Automation of procedures reduces incidence of human errors. Quality control laboratories located in low-income economies may face some barriers in attempts to automate their processes. Since data from quality control tests on pharmaceutical products are used in making regulatory decisions, it is important that laboratory reports are accurate and reliable. Zinc Sulphate (ZnSO₄) tablets is used in treatment of diarrhea in pediatric population, and as an adjunct therapy for COVID-19 regimen. Unfortunately, zinc content in these formulations is determined titrimetrically; a manual analytical procedure. The assay for ZnSO4 tablets involves time-consuming steps that contain mathematical formulae prone to calculation errors. To achieve consistency, save costs, and improve data integrity, validated spreadsheets were developed to simplify the two critical steps in the analysis of ZnSO4 tablets: standardization of 0.1M Sodium Edetate (EDTA) solution, and the complexometric titration assay procedure. The assay method in the United States Pharmacopoeia was used to create a process flow for ZnSO₄ tablets. For each step in the process, different formulae were input into two spreadsheets to automate calculations. Further checks were created within the automated system to ensure validity of replicate analysis in titrimetric procedures. Validations were conducted using five data sets of manually computed assay results. The acceptance criteria set for the protocol were met. Significant p-values (p < 0.05, α = 0.05, at 95% Confidence Interval) were obtained from students’ t-test evaluation of the mean values for manual-calculated and spreadsheet results at all levels of the analysis flow. Right-first-time analysis and principles of data integrity were enhanced by use of the validated spreadsheet calculators in titrimetric evaluations of ZnSO₄ tablets. Human errors were minimized in calculations when procedures were automated in quality control laboratories. The assay procedure for the formulation was achieved in a time-efficient manner with greater level of accuracy. This project is expected to promote cost savings for laboratory business models.

Keywords: data integrity, spreadsheets, titrimetry, validation, zinc sulphate tablets

Procedia PDF Downloads 170

Authors: I. Caldas, T. Duarte

Abstract:

Avoidant Restrictive Food Intake Disorder (ARFID) was included for the first time in DSM-5, replacing the old diagnosis of DSM-4 'Early Childhood Eating Disorder'. An ARFID is characterized by a restrictive/avoidant eating pattern that can lead to severe nutritional deficiency, weight loss, nutritional supplementation dependence, and poor psychosocial functioning. This eating pattern is associated with decreased interest in food, worries about food characteristics or the act of ingestion, and lack of concern with weight or body image. This paper aims to understand the impact of this new diagnosis in other Eating Disorders (ED) prevalence, as well as to compare their therapeutic approaches. Methodology: Literature reviewed by PubMed with the following keywords: 'ARFID', 'Prevalence', and 'Eating Disorders'. We selected articles related to this theme, written since 2016. Results: In a population of children hospitalized with ED, 5% to 14% was diagnosed with ARFID, and, as outpatient treatment, the prevalence was 22%. People diagnosed with ARFID have more prevalence of other comorbidities, especially autism spectrum, are younger, and are more often male. Regarding the treatment of ARFID, it most often required nasogastric feeding, and with less suffering associated with this procedure, compared to AN. Despite these differences, 12% of patients diagnosed with ARFID transited to AN during treatment, suggesting that the first pathology may be a risk factor for the development of AN. Conclusions: The differences identified between ARFID and the other EDs are important when analyzed as differential diagnostic hypotheses and therapeutic approaches. Further study is necessary regarding its prevalence, risk factors, and treatment.

Keywords: avoidant restrictive food intake disorder, ARFID, differential diagnoses, eating disorders, prevalence

Procedia PDF Downloads 111

Authors: Jun Hong Lee

Abstract:

Background: Alzheimer`s disease (AD) I: creases with age and is characterized by the premature progressive loss of neuronal cell. In contrast, cancer cells have inappropriate cell proliferation and resistance to cell death. Objective: We evaluated the association between cancer and AD and also examined the specific types of cancer. Patients and Methods/Material and Methods: This retrospective, nationwide, longitudinal study used National Health Insurance Service – Senior cohort (NHIS-Senior) 2002-2013, which was released by the KNHIS in 2016, comprising 550,000 random subjects who were selected from over than 60. The study included a cohort of 4,408 patients who were first diagnoses as AD between 2003 and 2005. To match each dementia patient, 19,150 subjects were selected from the database by Propensity Score Matching. Results: We enrolled 4,790 patients for analysis in this cohort and the prevalence of AD was higher in female (19.29%) than in male (17.71%). A higher prevalence of AD was observed in the 70-84 year age group and in the higher income status group. A total of 540 cancers occurred within the observation interval. Overall cancer was less frequent in those with AD (12.25%) than in the control (18.46%), with HR 0.704 (95% Confidence Intervals (CIs)=0.0.64-0.775, p-Value < 0.0001). Conclusion: Our data showed a decreased incidence of overall cancers in patients with AD similar to previous studies. Patients with AD had a significantly decreased risk of colon & rectum, lung and stomach cancer. This finding lower than but consistent with Western countries. We need further investigation of genetic evidence linking AD to cancer.

Keywords: Alzheimer, cancer, nationwide, longitudinal study

Procedia PDF Downloads 181