Damascus University Journal of Scientific Conferences
A scientific Journal concerned with publishing research and topics presented at conferences held at the University of Damascus
Development of an intelligent device for monitoring the performance of athletes
This work demonstrates the design, development and prototyping of a comprehensive monitoring system for football players in real time. Utilizing the ESP8266 microcontroller, GPS module, and pulse sensor, we have created a robust and reliable solution for tracking and analyzing player metrics such as heart rate, oxygen level, speed, and positional data. The integration of a user-friendly app further enhances the system's functionality, allowing trainers to monitor player performance, receive instant feedback, and make informed decisions to improve overall game play. Despite encountering challenges with sensor accuracy and power stability, iterative testing and optimization led to the selection of the most reliable components, such as the Neo-8M GPS module. The final prototype not only meets the initial project objectives but also provides a scalable platform for future enhancements, including more advanced analytics and additional sensor integration. Looking ahead, there are several ways to enhance and expand the capabilities of the system. One key improvement could be increasing the frequency of data transmission from the GPS module to the mobile app, providing even more precise and timely performance insights. Additionally, further development of the mobile app could include features such as the ability to download detailed reports of each match, allowing for comprehensive analysis and record-keeping. In general, this project exemplifies the successful application of mechatronics engineering principles to solve real-world problems, providing valuable tools for athletic performance monitoring and contributing to the advancement of sports technology. With the proposed improvements, the system can become an even more powerful asset for trainers and athletes alike, promoting continuous improvement and excellence in sports performance.
Copyright (c) 2025 Damascus University Journal of Scientific Conferences
Using Machine Learning and Deep Learning Techniques for Predicting Melanoma Risks
This study investigates the use of machine learning and deep learning techniques to predict the progression of melanoma, a highly aggressive form of skin cancer known for its rapid spread to vital organs. The research reviews various studies that have employed diverse datasets, including clinical and serological data, whole slide images, and lymphocytes, to enhance the accuracy of predictive models. The models utilized in these studies show promising potential for improving early diagnosis and aiding treatment decision-making, ultimately leading to better survival rates and reduced melanoma-related mortality. The study emphasizes the need for further research to validate these findings across larger datasets and diverse clinical settings.
Using Machine Learning to Build a Model or Early Prediction of Alzheimer's Disease
Alzheimer's disease is a neurodegenerative disease and a common factor of dementia in the elderly, and based on the fact that the appearance of its apparent clinical symptoms is late and there is no treatment for it, work was done in this study on the early prediction of Alzheimer's disease by detecting the stage of mild cognitive impairment experienced by most Alzheimer's patients. This study was used the ADNI database. After preprocessing, preparation, balancing and division into 80% as a training set and 20% as a test set, Two models were Hyperparameters tuned, trained and tested. Two models of Machine Learning were worked on in this study: the first model KNN (K-Nearest Neighbors) and the second model AB (AdaBoost) to classify three cases: Normal Cognition (NL), Alzheimer's Disease (AD) and mild Cognitive improvement (MCI). The AB model showed higher efficiency than the KNN model, where it outperformed, the Accuracy value of the AB model was a ratio 92.86%, and the Sensitivity value was equal to 92.86%, and these are good results to help support the doctor's decision.
Detecting Differences in Gait Between Healthy individuals and Amputees Using Principal Component Analysis and Self-Organizing Maps
This study presents an approach for analyzing and detecting variations in gait between healthy individuals and above-knee amputees with lower-limb prosthetics using principal component analysis (PCA) and self-organizing maps (SOM). The methodology begins with the extraction of principal components from the angular movements of the hip, knee, and ankle joints to capture the most significant movement patterns observed during walking in the sagittal plane. The SOM network then uses these principal components, or principal movements, as inputs. The role of the SOM is to classify the data and automatically discern differences between healthy individuals and amputees based on the principal movement elements. Through the classification results of the SOM network for the principal components, the study demonstrates the potential of using SOM to detect differences due to prosthetic limbs, including distinctive movement patterns in the extension and flexion patterns of the three lower extremity joints (ankle, knee, and hip). The findings suggest that employing the principal component analysis of gait with SOM technology can aid in constructing a diagnostic system that supports medical decision-making and uses the variance in principal movement elements for rapid identification through neural networks. Furthermore, this method could improve lower limb prosthetic design and rehabilitation programs to restore natural gait mechanisms in amputees.
An Artificial Intelligence Model for Estimating theRadiation Dose for a Patient in the Cardiac Catheterization Room
This study aims to develop an intelligent model to estimate the radiation dose to patients during cardiac catheterization procedures[1] using X-rays. Data from 41 patients who underwent cardiac catheterization procedures were collected, and several machine learning models were built to predict the radiation dose, including linear regression, random forest, and stacked model. The results showed that the improved stacked model is the most accurate, providing an effective tool for estimating the expected radiation dose before the procedure begins, thus improving patient safety.
Real-Time Eye Movement-Controlled Wheelchair Using Image Processing and SSD Network for Enhanced Directional Classification
The war that passed through the country left many injuries, resulting in limb amputations or bilateral or quadriplegic paralysis. Consequently, there became an urgent need to use wheelchairs, which led us to address the problem of automating a motorized wheelchair and enhancing the mobility of people with special needs. This research focuses on utilizing eye movement to control and steer a wheelchair using advanced image processing techniques. In this work, image segmentation and the Hough Transform were employed to preprocess eye movement images, improving the precision of feature detection. These segmented images were then used to train a Single Shot Detector (SSD) neural network to classify eye positions into three categories: Right, Left, and Neutral. This classification helps control the wheelchair's movement by detecting the user's intent based on eye direction. The motorized wheelchair was converted into an electric wheelchair using two DC motors with carefully calculated power to withstand the weight of the chair and the expected user. Two specially designed control loops were used to manage the motors, while the Viola-Jones algorithm was adopted for initial face and eye detection. The image processing pipeline was then enhanced by combining Hough Transform for feature detection and segmentation, followed by training the SSD network for classification. A model and software interface were designed using the MATLAB environment. The system was tested on five individuals (three males and two females), aged between 30-45 years and weighing between 65-85 kg, under daylight conditions and on a level surface. Each participant performed the test at least three times. The success rate for detecting eye movement direction and steering the wheelchair was approximately 85% after incorporating the enhanced image processing techniques.
Application of Fuzzy Logic type 2 in Building a Numerical Index for Evaluating Surgical Intervention for Children with Spastic Cerebral Palsy
Gait analysis has many applications in the quantitative assessment of normal or pathological human gait. Many parameters are calculated in gait monitoring, including spatiotemporal, kinematic, and joint kinematic parameters to evaluate the patient's gait numerically or based on a scale. In this research, a Fuzzy logic type-2 system was used To design a smart index (FL2-AKHDI) that evaluates the deviations of the ankle, knee, and hip joints in CP patients before and after surgery compared to children with normal development. The proposed methodology starts by extracting the characteristic features from the angle diagrams of the hip, knee, and ankle joints during the gait cycle. Then it initializes the FL system based on the extracted features. Finally, the performance of the proposed index will be evaluated. The results concluded that it is possible to use Fuzzy logic type-2 to evaluate the effectiveness of surgical operations for patients with cerebral palsy The average value of the index for the patient group decreased by (25%), and this percentage corresponds to the percentage of decrease in the average value of the GPS index, which is equal to (21%). The importance of this research also lies in providing a prototype of a medical decision support system that can quantitatively evaluate disease conditions and evaluate the efficiency of treatment and medical intervention using FL.
The role of digitalization technologies in agricultural production, food industries, and ecommerce- a review
The Arab economy depends largely on agricultural production, related food industries, and electronic commerce, it is necessary to study the obstacles facing the application of modern technologies in economic growth and marketing of goods via the Internet. This review focused on identifying the most important obstacles facing the application of digitization technologies and their impact on agricultural economic growth indicators, as well as pointing out the advantages of these technologies in terms of use and application. It has become clear that the most important obstacles facing the application of digitization techniques are legal legislation, in addition to the lack of appropriate infrastructure for applying digitization in agricultural production and related industries. There is also the spread of digital illiteracy, especially in rural areas. It recommended that an appropriate strategy developed to apply digitalization techniques in agricultural production, food industries, and e-commerce, in addition to developing human capital, especially in rural areas, to provide an appropriate technical environment to achieve development in agricultural production and food industries to contribute to economic growth
Copyright (c) 2024 Damascus University Journal of Scientific Conferences
The role of digital transformation in developing the accounting and external auditing profession in Syria( Analytical study of factors and challenges )
This study aims to investigate the role played by digital blockchain technology (being one of the most important digital transformation tools) in developing the accounting and external auditing profession in Syria, by knowing the impact of using technology in the accounting and auditing profession, and the challenges facing its application in Syria. To achieve the objectives of the study, knowledge was collected from research related to the subject of the study, and analyzed in accordance with the Syrian business environment. A set of results were reached, the most important of which is that the use of digital blockchain technology in the accounting and external auditing profession contributes to preventing fraud and error, managing data and applications, and processing transactions through a decentralized structure from a single platform, and simplifies procedures and hides the complexities of operations. The results of the study also showed a low rate of implementation of Syrian projects related to the digital transformation process, the absence of a governmental strategic plan to provide the necessary infrastructure or to provide financial credits for the application of blockchain technology in government agencies and organizations, the lack of compatibility of current contract systems with the requirements of digital transformation in economic projects and services, and the lack of Provide sufficient flexibility for the current control mechanism to finance projects and economic services.
Digitization in Syrian Islamic Banks and its Role inEnhancing Financial Inclusion
The digital economy and its impact in enhancing economic growth in Syria: An econometric study for the period (2000-2021)
The shift towards the digital economy is a modern and effective variable in enhancing economic growth, as it contributes directly and indirectly to increasing the gross domestic product of various economic sectors. In this context, this study aims to examine the impact of the shift towards the digital economy in enhancing the economic growth process in Syria. To achieve this goal, the necessary data was collected to calculate the variables for the time period (2000-2021), and the results were tested using the econometric analysis model (the multiple linear regression equation based on a vector autoregression (VAR) model ) by the statistical program Eviews 13. The analytical results indicate that there is no a positive impact of the development in technological and digital economy in economic growth in Syria during the study period. The results highlight the importance of the need to increase investments in the infrastructure of the digital economy, and to enhance competitive capabilities in the field of information and communications technologies, in addition to enacting legislation to protect electronic transactions to attract local and foreign investments and enhance confidence in the digital business and economic environment in Syria.
The Impact of Digital Transformation on the Accounting and AuditingProfession in Syria) A Field Study)
This research aims to study the impact of digital transformation on the accounting and auditing profession in Syria, by explaining the theoretical framework of digital transformation and identifying the most important digital transformation technologies that can be used in the field of accounting and auditing, in addition to identifying the advantages and challenges of using each of these technologies. The researcher followed the descriptive-analytical approach in preparing this research. In the theoretical aspect, reliance was placed on Arab and foreign studies related to the subject of the research to define the concept of the research variables and describe them accurately. As for the practical aspect, the researcher relied on the questionnaire that was distributed to a sample of experts in the field of accounting. And auditing to investigate their opinions regarding the research variables, and the research hypotheses were tested using Excel and the statistical program SPSS, and the results showed the following: 1- There is an impact of digital transformation on the accounting profession in Syria, as there was agreement among members of the research sample with a relative weight of 83.93% on the importance of using digital transformation techniques when completing accounting work and in a way that serves the interest of the final beneficiaries. 2- There is an impact of digital transformation on the auditing profession in Syria, as there was agreement among the members of the research sample with a relative weight of 83.38% that digital transformation helps in carrying out the necessary auditing procedures, especially in light of the use of digital transformation techniques when completing accounting work, which calls for the necessity of providing The skills necessary for the auditor to provide reliable audit reports.
The role of digital transformation strategy in building the advantages of competitive superiority: the mediating role of knowledge leadership, an analytical study of the opinions of a sample of teachers at the Northern Technical University/ Iraq
The study aimed to investigate the role of digital transformation strategy, with its dimensions of managerial capabilities and operational capabilities, in building competitive superiority across its dimensions of sensing advantage, system advantage, social advantage, simulation advantage, and human resource advantage, through knowledge leadership represented by its dimensions of leadership skills, collaboration and trust, and knowledge integration and creativity, in the Iraqi higher education and scientific research context. The descriptive-analytical method was adopted through data collection, analysis, and scheduling using a primary data collection tool represented by a questionnaire. The Northern Technical University was chosen as the field of study, with the study population consisting of all faculty members at the Northern Technical University, totaling 1100 teaching staff. A sample of 285 teaching staff was drawn from this population using Steven Thompson's formula. The questionnaire was distributed to the sampled population, and 275 questionnaires were retrieved, with 5 of them being defective and thus invalid for analysis, resulting in a final valid sample of 270 questionnaires. The study found a fundamental result indicating that the digital transformation strategy, through its capabilities, influences the construction of competitive superiority, with an impact rate of 32%. This impact is magnified through the mediating role of the relationship between them through knowledge leadership by 61%, meaning that the overall impact is 93%. This underscores the imperative necessity for Iraqi universities to adopt a digital transformation strategy in all its facets, including the Northern Technical University. This is achieved by enhancing both managerial and operational capabilities related to digital transformation, as well as the necessity to establish relationships with external parties to acquire knowledge that complements internal knowledge. Furthermore, it is essential to incentivize creative behavior among employees to generate new ideas that enhance competitive advantages.
Predicting The Performance of Emerging Financial Markets Using NARX-NAR Neural Network
One of the biggest challenges facing investors at the international level is measuring the performance of their investment operations within the structure of an international investment portfolio by predicting the future performance of its standard index. In this research, we studied and analyzed the component prices of the MSCI Emerging International Index (Open-Max-Min-Close) as a time series based on testing several methods for modeling the closing price and comparing them with each other based on artificial neural networks for non-linear autoregressive NAR and NARX. In order to create a highly accurate neural model capable of responding quickly to price changes dynamically by predicting the future closing price of the general index, which represents the standard market portfolio, to support the process of making trading decisions in emerging markets. The study concluded that it is possible to build a model to predict the future price of the general index for emerging financial markets based on several variables related to its component prices as a time series using the NARX neural network, with more accurate results than the model that was built based on a single variable, which is the closing price, as a time series using a network. Neural NAR, where the models were built based on the Matlab program, and the models’ effectiveness and generalizability were confirmed based on the mean square error (MSE) between the actual and expected values of the closing price, as the MSE value for the NARX network model was 0.00012653 and the MSE value for the NAR network model was 0.00015258.
The role of the digital economy in supporting the sustainable development ofthe advancement of countries with special reference to Iraq
The digital economy with sustainable development constitutes an impressive and important economic duality in the economies of developed and developing countries. This was after the majority of co untries linked their economic progress to their ability to achieve sustainable development and it’s seventeen goals approved by the United Nations. The countries of the world committed to achieving these goals as economic, social and environmental goals un til 2030 . I found that one of the pillars of its ability to achieve that development and ensure its achievement was the digital economy. That the contemporary variable that has played and is still playing a role in mitigating or ensuring adaptation to the economic shocks, to which the economies of countries are exposed. This is able to play an active role in ensuring the achievement of sustainable development goals, as many contemporary studies indicate that the digital economy plays a very influential role in sustainable development. For this we find that most countries raced to enhance their retention of an integrated system The digital economy has hoped to achieve the UN goals that have set a path for sustainable development. The contemporary technologie s for communication and information have become the main role in the various economic sectors. This is done by contributing to increasing the level of efficiency through three elements of reducing cost, shortening time and quality. According to this persp ective, this research came with its four topics to study and analysis the role of the digital economy in supporting the sustainable development of the advancement of countries with a special reference to Iraq. The researchers relied on the analytical desc riptive deductive method, which is consistent with the nature and content of this research. In light of this, the research consisted of four sections, the first of which was devoted to the research methodology by formulating its problem. Defining its objec tives and indicating its importance, with a specific hypothesis, which is (that the digital economy is an entrance to support sustainable development for the advancement of countries that are engaged in this development, including Iraq economically, social ly and environmentally). The second topic dealt with the digital economy as a new system for the advancement of countries. While the third section focused on sustainable development and its goals according to the perspective of the international organization, while the fourth section analysed the role of the digital economy in sustainable development in Iraq and some other co untries. To end the research with conclusions and recommendations. The research has reached a package of conclusions, the most important of which are: 1 Sustainable development is a dynamic and renewable process, which brings together human needs (econo mic, social and environmental) and takes into account current needs without prejudice to the rights of subsequent generations. Indicating that countries must develop strategies for this, foremost of which are the contents of the digital economy. 2 Iraq is still characterized by weakness in the rules of the digital economy, as the Arab Digital Economy Index for the year 2022 , issued by the Arab Federation for Digital Economy, showed that Iraq is ranked 13 th out of 22 Arab countries with an index value of ( 3 3.6 ) points. This shows that Iraq is within the third and weaker group (countries that need to enhance capabilities). This This is due to the weakness of dealing with the mechanisms of the digital economy in general. Without developing effective strategies to p romote innovation, creativity and communications, which weakened the role of the digital economy in sustainable development in Iraq. 3 The spread of administrative and financial corruption in the institutions of the Iraqi state, especially the period bef ore 2023 , which clearly weakened the role of the digital economy in supporting sustainable development.
The barriers to digital transformation in Syrian BanksAn Empirical Study in Syrian Islamic Banks
This study aimed to identify the barriers that affect the digital transformation in Syrian Islamic Banks. Five barriers have been chosen, which are ا Individual barriers, organizational barriers, Technical Barriers, External barriers, and Missing skills barriers. To achieve this goal, a questionnaire was distributed to a random sample of 175 employees of Syrian Islamic banks in Damascus. 150 questionnaires were retrieved and analyzed using the statistical program SPSS. The concept of digital transformation has been found to exist and is well understood by employees of Islamic banks. It was also found that organizational barriers play the greatest impact on the digital transformation process in these banks, followed by external barriers, technical barriers, and missing skills barriers. The study also found that the impact of some of these barriers may vary depending on demographic variables such as age, educational level and number of years of experience.
Study stromal cell-derived factor-1 (SDF1-α) in patients infected Urinary tract infections and bacterial vaginosis
Background: Study stromal cell-derived factor-1 is produced soon after an infection, an interesting immunological response is triggered, allowing for quick and effective bacterial clearance. Urinary tract infections and bacterial vaginosis are two major hazards that have an impact on millions of women worldwide that are of reproductive age. The purpose of this study is to analyze the connection between the SDF1 gene in patients both urinary tract infections with bacterial vaginosis and healthy individuals as a control group. Methods: In order to study the distribution of the SDF1 gene the Gynecology Consultant at the Imam Al-Sadiq General Educational Hospital in Iraq-Babylon split the topics to four collections after collecting medical data from (240) entrants. the patients and the control group (UTI, BV, UTI with BV groups), while the population study in this area included age and education, During the period from September to December 2022, SDF1-α detection by Conventional amplified technique (PCR) - We reveal alleles with a single primer and distinguished the alleles by molecular weight. Results: The results revealed that patients and a control group who have G allele, and G/G genotyping in the SDF1-α gene, had no significance, therefore considered a protective factor to the development of disease, for urinary tract infection, particularly among women of childbearing age in college education. Also, women with bacterial vaginosis especially among women sexually active in Intermediate education, also women with both UTIs with BV especially among women sexually active studying in the institute. Conclusion: According to our research, SDF1-α/CXCL-12 gene polymorphism is not linked to BV-associated UTIs. To further explain these findings, a larger-scale and well planned case-control research should be carried out.
EXAMINE THE IMPACT OF TOTAL HIP REPLACEMENT ON SPINE MOBILITY VIA GAIT ANALYSIS
Total hip replacement (THR) is an elective surgical procedure with the primary indication being pain relief. Secondary to pain relief, but still very important, is a patient’s desire to improve his or her physical function and quality of life. The aim of this study was to assess the impaction of the THR on the mobility of the spine. a method has been proposed for assessing the geometry of spine, and study the spine kinematics and their association during walking pre and post THR. Nine healthy men (age 20.44 آ± SD 1.01 years, height: mean 178.44 آ± SD 6.34 cm, mass: mean 68.55 آ± SD 10.4 kg) were studied. The results of control cases were compared with 6 pre THR and 6 post - THR patients (Age: mean 40 آ± SD 13.08 years, height: mean 165.7 آ± SD 8.693 cm, mass: mean 81.2 آ± SD 18.042 kg), four of them before undergoing unilateral total hip replacement surgery, and four other patients after the operation, two of them were examined before and after surgery. The gait analysis was performed by two-dimensional (2D) motion analysis using two digital video cameras, one placed in the sagittal plane and the other on the frontal plane. Kinematics data were obtained from 2D trajectories of eight passive markers using SkillSpector software (version1.2.4). The digitizing points were exported as txt files that could be imported into Microsoft Excel. The sagittal vertical axes and spinal angles (thoracic kyphosis, lumbar lordosis, thoracic scoliosis, lumbar scoliosis, horizontal pelvic slop, and vertical spine slope) were measured; this was found to be more correlated with a corotation factor >0.65 and a p-value of 0.05. When comparing these angles for patients pre and post THR with control cases, these angles are near control cases post total hip replacement (p-value < 0.05). So, as a conclusion, functional improvement was found in spinal movement and balance after the operation. It is not uncommon for the mechanics of walking to still not be back to normal after months of recovery. This is because the muscles around the joint need time to heal.
Personalized Temperature Control System for Hypo and Hyper-thermic Patients
In the medical field, every health problem is defined by its own symptoms. Certain infections (bacterial or viral infections), endocrine disorders (thyroid or adrenal disorders), heart disease or heat-related disorders (heart stroke or heat exhaustion) can cause hyper-thermic condition, which confuses, agitates, and increase the person’s anxiety level [1]. An underactive thyroid function, a malnutrition, tachycardia or even neurological disorders can contribute to recurrent hypothermia which, in its turn, is related to an abnormal body temperature causing a high lack of coordination and confusion for the diagnosed person [2]. The proposed system acts like a temperature control device. Using a temperature sensor and heartrate sensor, it is able to capture any abnormalities in the individual’s body temperature and heartrate respectively. The main component is the Peltier element used for the achievement of a cooling process in case of hyperthermia or a heating process in case of hypothermia in order to decrease in a quick and effective way the side effects of the thermal irregularities on the person’s body. All these processes will be controlled by the user via a mobile application letting him activate his desired medical mode. As well as an automatic system activation in case of severe thermal shocks. It is a low cost, efficient and convenient product.
Segmentation of Brain Images for Medical Diagnostic Assistance
Segmentation of brain images plays a crucial role in medical diagnostics, aiding clinicians in the accurate detection and analysis of various neurological conditions. This paper presents an overview of recent advancements and methodologies in brain image segmentation techniques, focusing on their application in medical diagnostic assistance. Various image-processing methods, such as region-based, boundary-based, and clustering-based approaches, are discussed, along with their advantages and limitations. We have developed an innovative algorithm based in particular on the segmentation by the region-growing method, are explored for their effectiveness in brain image segmentation tasks. The paper highlights the challenges and future directions in this field, including the need for robust algorithms capable of handling diverse image modalities and anatomical variations, as well as the integration of segmentation results into clinical workflows for improved diagnostic accuracy and patient care.
Utilize ML for Abnormal Tooth Classification in Dental Radiography
This research explores the potential of deep learning for analyzing panoramic dental X-rays. Panoramic X-rays provide a wide-angle view of all the teeth in the upper and lower jaws, making them valuable tools for dentists. By analyzing these X-rays, dentists can identify various dental features, including Implants, Fillings, Impacted teeth, and Caries. The study proposes a new, three-stage method that combines image processing techniques and deep learning models for simultaneously recognizing these crucial features. The study compares its deep learning approach to existing, advanced algorithms. The high detection accuracy of 97% and overall recognition accuracy of 92% suggest that deep learning has great promise for more precise diagnoses and can optimize treatment planning. Overall, this research highlights the potential of deep learning to revolutionize dental X-ray analysis, leading to faster, more accurate diagnoses and improved patient care.
Design Of Osteosynthesis Plates With Reduced Stress Shielding Effect Using Topology Optimization
The article presents analysis of stress shielding effect (SSE) in osteosynthesis plates, its adverse effects on healing of bone fractures and possible solutions for its minimization. It is shown that SSE can be reduced by using plates made of materials with low elastic modulus (β titanium alloys, bioresorbable polymers etc.) or by optimization of their geometric shape. The latter possibility is analysed in a more detailed way with special accent on topology optimization (TO) as a relatively new optimization tool widely used by biomedical engineering community. As a practical example, TO using Comsol Multiphysics software is applied to solution of 2D design problem of osteosynthesis plate. It is shown that longitudinal stiffness of optimized plate can be reduced up to 84 % relative to initial non-optimized design depending on the value of prescribed reduction of weight used as constraint during analysis. Optimized design demonstrates increase in maximum von Mises stress, but overall distribution of stresses becomes more uniform in comparison with initial design. Prototype of optimized plate can be easily manufactured using laser cutting or wire electric discharge machining.
Co-Cr-Mo Alloys for Medical Endoprostheses: Review
The article presents a literature review of Co-Cr-Mo alloys used in medicine for the manufacture of endoprostheses. The basic compositions of alloys of this type, as well as microstructure and their properties are considered. The questions of manufacturing by casting as well as methods of heat treatment of medical products are touched upon. It was found that the use of heat treatment allows to obtain the necessary microstructure, as well as to increase the strength properties. In addition, the methods of finishing of medical devices, which contribute to the improvement of tribological properties, were considered.
Highly efficient power supply systems for medical technology
To guarantee continuous operation of medical equipment, it is essential to use dependable and uninterrupted power sources. This paper proposes a portable power supply system that is based on rechargeable batteries and a PV system to ensure the operation of EMS-apparatus. The photovoltaic panel of the presented system uses semiconductor silicon converters with nano-modified receiving surfaces.
Mechanical characteristics of nitinol stent elements
The article examines the influence of heat treatment conditions, such as device design and wire tension force, on the mechanical characteristics of nitinol wire stent elements. Stent elements are components of an aortic stentgraft for the surgical treatment of aortic aneurysms. It has been shown that with increasing wire tension force, the radial stiffness of the finished heat-treated stent elements decreases. Therefore, it is necessary to fix the wire on the device, providing a minimum tensile force. For experimental studies, samples of Ti-44.48 wire were taken; Ni-49.16; Cu-6.02 from Fukarawa (Japan) with a diameter of 0.45 mm, used for the manufacture of wire frames of stentgrafts. The results obtained will be proposed for implementation in the technological process of manufacturing medical products from nitinol in the Scientific and Technological Park of BNTU "Polytechnic". After production tests, conclusions will be drawn about the advisability of using them in production conditions.