Search results for: Uputaua therapeutic approach

Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Sadegh Marzban, Mohamad Sobhan Sheikh Andalibi, Farnaz Ghassemi, Farzad Towhidkhah

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Parkinson's disease (PD), which is characterized by the tremor at rest, rigidity, akinesia or bradykinesia and postural instability, affects the quality of life of involved individuals. The concept of a fractal is most often associated with irregular geometric objects that display self-similarity. Fractal dimension (FD) can be used to quantify the complexity and the self-similarity of an object such as tremor. In this work, we are aimed to propose a new method for evaluating hyperkinetic movements such as tremor, by using the FD and other correlated parameters in patients who are suffered from PD. In this study, we used 'the tremor data of Physionet'. The database consists of fourteen participants, diagnosed with PD including six patients with high amplitude tremor and eight patients with low amplitude. We tried to extract features from data, which can distinguish between patients before and after medication. We have selected fractal dimensions, including correlation dimension, box dimension, and information dimension. Lilliefors test has been used for normality test. Paired t-test or Wilcoxon signed rank test were also done to find differences between patients before and after medication, depending on whether the normality is detected or not. In addition, two-way ANOVA was used to investigate the possible association between the therapeutic effects and features extracted from the tremor. Just one of the extracted features showed significant differences between patients before and after medication. According to the results, correlation dimension was significantly different before and after the patient's medication (p=0.009). Also, two-way ANOVA demonstrates significant differences just in medication effect (p=0.033), and no significant differences were found between subject's differences (p=0.34) and interaction (p=0.97). The most striking result emerged from the data is that correlation dimension could quantify medication treatment based on tremor. This study has provided a technique to evaluate a non-linear measure for quantifying medication, nominally the correlation dimension. Furthermore, this study supports the idea that fractal dimension analysis yields additional information compared with conventional spectral measures in the detection of poor prognosis patients.

Keywords: correlation dimension, non-linear measure, Parkinson’s disease, tremor

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Authors: A. D. Paryuni, R. N. Nataria, R. Wasito

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Layer chickens are a poultry commodity that has an important role in producing eggs and meat to support the availability of animal proteins. The layer chickens still have obstacles to increasing their productivity, especially due to poultry diseases which can result not only in decreased egg production but also morbidity and mortality. To overcome this condition, phyto-therapeutic and/or phyto-preventive approaches which are efficacious, safe and cheap are needed. One of the herbal spices from Indonesia which is greatly possible to be promoted as an herbal medicine is a red onion (Allium cepa). The objective of the present study was to identify and determine the effect of red onion extract (Allium cepa) as anti-infection and immuno-modulator of Bursa fabricius in layer chickens raised in an open house system. Eighteen layer chickens at 17 days of age were divided randomly into three group of six each. Those were layer chickens without red onion extract (Group K I), Group K II gave red onion extract via drinking water and Group K III gave red onion extract peroral for 30 days. Water and feed were given ad libitum. Necropsy was conducted every 10 days by taking two samples of layer chickens/Group. Bursa fabricius was processed histopathologically and stained-routinely with hematoxylin-eosinand was then examined under light microscope. The results of the present study indicated that bursaFabricius in layer chickens in Groups K I, K II, and K III that were necropsied at days 10 and 20 had normal histologic structures. However, Bursa fabricius in Group K I at day 30, had vacuolization with mild to moderate large vacuoles containing homogenous eosinophilic fluid and atrophy of lymphoid follicles. Mild vacuolization in the follicle of Bursa fabricius was seen in layer chickens in Group K II, whereas layer chickens in Group K III had normal histologic structures of Bursa fabricius. It was concluded that apparently, red onion extract (Allium cepa) has herbal preventive effects against the pathological lesions in the Bursa fabricius of layer chickens.

Keywords: Bursa fabricius, disease of poultry, hematoxylin-eosin, layer chickens, red onion extract

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Authors: Khaled M. Alqahtani

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Copy number alterations (CNA) are variations in the structure of the genome, where certain regions deviate from the typical two chromosomal copies. These alterations are pivotal in understanding tumor progression and are indicative of patients' survival outcomes. However, effectively modeling patients' survival based on their genomic CNA profiles while identifying relevant genomic regions remains a statistical challenge. Various methods, such as the Cox proportional hazard (PH) model with ridge, lasso, or elastic net penalties, have been proposed but often overlook the inherent dependencies between genomic regions, leading to results that are hard to interpret. In this study, we enhance the elastic net penalty by incorporating an additional penalty that accounts for these dependencies. This approach yields smooth parameter estimates and facilitates variable selection, resulting in a sparse solution. Our findings demonstrate that this method outperforms other models in predicting survival outcomes, as evidenced by our simulation study. Moreover, it allows for a more meaningful interpretation of genomic regions associated with patients' survival. We demonstrate the efficacy of our approach using both real data from a lung cancer cohort and simulated datasets.

Keywords: copy number alterations, cox proportional hazard, lung cancer, regression, sparse solution

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Authors: Kernou Nassim

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The current study presents a vulnerability and a reliability-mechanical approach that focuses on evaluating the seismic performance of reinforced concrete structures to determine the probability of failure. In this case, the performance function reflecting the non-linear behavior of the structure is modeled by a response surface to establish an analytical relationship between the random variables (strength of concrete and yield strength of steel) and mechanical responses of the structure (inter-floor displacement) obtained by the pushover results of finite element simulations. The push over-analysis is executed by software SAP2000. The results acquired prove that properly designed frames will perform well under seismic loads. It is a comparative study of the behavior of the existing structure before and after reinforcement using the pushover method. The coupling indirect mechanical reliability by response surface avoids prohibitive calculation times. Finally, the results of the proposed approach are compared with Monte Carlo Simulation. The comparative study shows that the structure is more reliable after the introduction of new shear walls.

Keywords: finite element method, surface response, reliability, reliability mechanical coupling, vulnerability

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Authors: Derya Sarı, Banu Karasah

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In the recent years, urban green areas decrease dramatically as a result of increasing industrialization and population growth. At the same time, green spaces provide many ecosystem services such as controls of air pollution, noise reduction, prevents flooding and reduces the stress in the urban areas. Therefore, the plants help to these areas to get more livable and active, and also plants are one of the most significant identity elements in these open spaces. Roof gardens comes significant design comprehension as a result of global warming and also they contribute to cities with regard to ecological, economic, visual and recreational aspects. This study is mainly based on evaluation potential of green roofs and xeriscape planting design approach of Artvin (Turkey) known that generally has a remarkable floristic richness. Artvin is located on a sloping terrain, and the amount of green spaces that can be used is very limited in this city. Therefore, green roofs approach should be evaluated to supply urban green space sustainability. This study shows that it is appropriate about 20 perennial plants for green roofs and xeriscape planting design in Artvin city center. Usage of native plant species would be support to sustainable urban green spaces.

Keywords: Artvin, green roofs, urban green spaces, xeriscape planting

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Authors: Abdullah M. Alodhaiani, Yasir A. Alturki, Mohamed A. Elkady

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Complex power flow distribution factors, which relate line complex power flows to the bus injected complex powers, have been widely used in various power system planning and analysis studies. In particular, AC distribution factors have been used extensively in the recent power and energy pricing studies in free electricity market field. As was demonstrated in the existing literature, many of the electricity market related costing studies rely on the use of the distribution factors. These known distribution factors, whether the injection shift factors (ISF’s) or power transfer distribution factors (PTDF’s), are linear approximations of the first order sensitivities of the active power flows with respect to various variables. This paper presents a novel model for evaluating the universal distribution factors (UDF’s), which are appropriate for an extensive range of power systems analysis and free electricity market studies. These distribution factors are used for the calculations of lines complex power flows and its independent of bus power injections, they are compact matrix-form expressions with total flexibility in determining the position on the line at which line flows are measured. The proposed approach was tested on IEEE 9-Bus system. Numerical results demonstrate that the proposed approach is very accurate compared with exact method.

Keywords: distribution factors, power system, sensitivity factors, electricity market

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Authors: Marcel Schneider, Nils Nießen

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Microscopic simulation programs enable the description of the two processes of railway operation and the previous timetabling. Occupation conflicts are often solved based on defined train priorities on both process levels. These conflict resolutions produce knock-on delays for the involved trains. The sum of knock-on delays is commonly used to evaluate the quality of railway operations. It is either compared to an acceptable level-of-service or the delays are evaluated economically by linearly monetary functions. It is impossible to properly evaluate dispatching decisions without a well-founded objective function. This paper presents a new approach for evaluation of dispatching decisions. It uses models of choice of transport and considers the behaviour of the end-costumers. These models evaluate the knock-on delays in more detail than linearly monetary functions and consider other competing modes of transport. The new approach pursues the coupling of a microscopic model of railway operation with the macroscopic model of choice of transport. First it will be implemented for the railway operations process, but it can also be used for timetabling. The evaluation considers the possibility to change over to other transport modes by the end-costumers. The new approach first looks at the rail-mounted and road transport, but it can also be extended to air transport. The split of the end-costumers is described by the modal-split. The reactions by the end-costumers have an effect on the revenues of the railway undertakings. Various travel purposes has different pavement reserves and tolerances towards delays. Longer journey times affect besides revenue changes also additional costs. The costs depend either on time or track and arise from circulation of workers and vehicles. Only the variable values are summarised in the contribution margin, which is the base for the monetary evaluation of the delays. The contribution margin is calculated for different resolution decisions of the same conflict. The conflict resolution is improved until the monetary loss becomes minimised. The iterative process therefore determines an optimum conflict resolution by observing the change of the contribution margin. Furthermore, a monetary value of each dispatching decision can also be determined.

Keywords: choice of transport, knock-on delays, monetary evaluation, railway operations

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Authors: H. Hajimolahoseini, J. Hashemi, D. Redfearn

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Background: Catheter ablation is an effective therapy for symptomatic atrial fibrillation (AF). The intracardiac electrocardiogram (IEGM) collected during this procedure contains precious information that has not been explored to its full capacity. Novel processing techniques allow looking at these recordings from different perspectives which can lead to improved therapeutic approaches. In our previous study, we showed that variation in amplitude measured through Shannon Entropy could be used as an AF recurrence risk stratification factor in patients who received Ibutilide before the electrograms were recorded. The aim of this study is to further investigate the effect of Ibutilide on characteristics of the recorded signals from the left atrium (LA) of a patient with persistent AF before and after administration of the drug. Methods: The IEGMs collected from different intra-atrial sites of 12 patients were studied and compared before and after Ibutilide administration. First, the before and after Ibutilide IEGMs that were recorded within a Euclidian distance of 3 mm in LA were selected as pairs for comparison. For every selected pair of IEGMs, the Probability Distribution Function (PDF) of the amplitude in time domain and magnitude in frequency domain was estimated using the regression analysis. The PDF represents the relative likelihood of a variable falling within a specific range of values. Results: Our observations showed that in time domain, the PDF of amplitudes was fitted to a Gaussian distribution while in frequency domain, it was fitted to a Rayleigh distribution. Our observations also revealed that after Ibutilide administration, the IEGMs would have significantly narrower short-tailed PDFs both in time and frequency domains. Conclusion: This study shows that the PDFs of the IEGMs before and after administration of Ibutilide represents significantly different properties, both in time and frequency domains. Hence, by fitting the PDF of IEGMs in time domain to a Gaussian distribution or in frequency domain to a Rayleigh distribution, the effect of Ibutilide can easily be tracked using the statistics of their PDF (e.g., standard deviation) while this is difficult through the waveform of IEGMs itself.

Keywords: atrial fibrillation, catheter ablation, probability distribution function, time-frequency characteristics

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Authors: Shrawan Baghel, Helen Cathcart, Biall J. O'Reilly

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Amorphous drug formulations have great potential to enhance solubility and thus bioavailability of BCS class II drugs. However, the higher free energy and molecular mobility of the amorphous form lowers the activation energy barrier for crystallization and thermodynamically drives it towards the crystalline state which makes them unstable. Accurate determination of the crystallization tendency/kinetics is the key to the successful design and development of such systems. In this study, dipyridamole (DPM) and cinnarizine (CNZ) has been selected as model compounds. Thermodynamic fragility (m_T) is measured from the heat capacity change at the glass transition temperature (Tg) whereas dynamic fragility (m_D) is evaluated using methods based on extrapolation of configurational entropy to zero 〖(m〗_(D_CE )), and heating rate dependence of Tg 〖(m〗_(D_Tg)). The mean relaxation time of amorphous drugs was calculated from Vogel-Tammann-Fulcher (VTF) equation. Furthermore, the correlation between fragility and glass forming ability (GFA) of model drugs has been established and the relevance of these parameters to crystallization of amorphous drugs is also assessed. Moreover, the crystallization kinetics of model drugs under isothermal conditions has been studied using Johnson-Mehl-Avrami (JMA) approach to determine the Avrami constant ‘n’ which provides an insight into the mechanism of crystallization. To further probe into the crystallization mechanism, the non-isothermal crystallization kinetics of model systems was also analysed by statistically fitting the crystallization data to 15 different kinetic models and the relevance of model-free kinetic approach has been established. In addition, the crystallization mechanism for DPM and CNZ at each extent of transformation has been predicted. The calculated fragility, glass forming ability (GFA) and crystallization kinetics is found to be in good correlation with the stability prediction of amorphous solid dispersions. Thus, this research work involves a multidisciplinary approach to establish fragility, GFA and crystallization kinetics as stability predictors for amorphous drug formulations.

Keywords: amorphous, fragility, glass forming ability, molecular mobility, mean relaxation time, crystallization kinetics, stability

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Authors: Ghorbeli Eya, Naija Lamia, Khessairi Nayssem, Saadallah Fatma, Slimane Maher, Tarek Ben Dhiab

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INTRODUCTION: Borderline ovarian tumors account for 15 to 20% of ovarian tumors. Prognostic factors of recurrence include the stage of the disease, presence of peritoneal implants, micropapillary pattern, microinvasion and intra-epithelial carcinoma. Fertility sparing constitutes a major therapeutic issue in young patients that leads to conservative surgical treatment in specific cases. METHODS: We conducted a retrospective descriptive study including patients treated at the Salah Azaiez Institute for Borderline Ovarian Tumor who underwent conservative surgical treatment from 2003 to 2018. RESULTS: Nine patients were included in our study. The median age was 33 years. Three patients were nulliparous. Given the age, conservative treatment was indicated in all these patients. Cystectomy without ovariectomy was indicated in 5 of the 9 women, which was within the margin of tumor resection on definitive anatomopathic examination in 3 of the 5 women. In contrast, given the impossibility of ovarian conservation, total annexectomy was carried out in 4 of all these women. All of the patients were followed regularly postoperatively; three had a carcinomatous transformation as an ovarian adenocarcinoma at an average interval of 18 months. Among these three patients, a single one presented intra-peritoneal metastases, requiring radical surgical treatment and adjuvant chemotherapy with 6 cures of Carbo-Taxol, with a good tolerance and a complete response. Moreover, one patient had a recurrence on the contralateral ovary as a Borderline mucinous ovarian tumor. For the remaining four women, after a median follow-up of 35 months, one patient fell spontaneously pregnant during follow-up, and three patients were in complete remission at 16 months. CONCLUSION: Borderline tumors of the ovary usually occur in young patients, which makes conservative treatment advisable if possible, but this always comes with a risk of recurrence and/or carcinomatous transformation, especially if the conservative surgical procedure was a cystectomy instead of a total annexectomy, and even more so if the resection margins were tumoral.

Keywords: ovarian tumor, conservative treatment, surgical management, borderline ovarian tumor, recurrence management

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Authors: Terry Teo, Sun Woh Lye, Yufei Li, Zainuddin Zakaria

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Wearable devices such as Electroencephalography (EEG) hold immense potential in the monitoring and assessment of a person’s task engagement. This is especially so in remote or online sites. Research into its use in measuring an individual's cognitive state while performing task activities is therefore expected to increase. Despite the growing number of EEG research into brain functioning activities of a person, key challenges remain in adopting EEG for real-time operations. These include limited portability, long preparation time, high number of channel dimensionality, intrusiveness, as well as level of accuracy in acquiring neurological data. This paper proposes an approach using a 4-6 EEG channels to determine the cognitive states of a subject when undertaking a set of passive and active monitoring tasks of a subject. Air traffic controller (ATC) dynamic-tasks are used as a proxy. The work found that when using the channel reduction and identifier algorithm, good trend adherence of 89.1% can be obtained between a commercially available BCI 14 channel Emotiv EPOC+ EEG headset and that of a carefully selected set of reduced 4-6 channels. The approach can also identify different levels of engagement activities ranging from general monitoring ad hoc and repeated active monitoring activities involving information search, extraction, and memory activities.

Keywords: assessment, neurophysiology, monitoring, EEG

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Authors: Elsa Marta Soares, Ana Rita Valente, Cristiana Rodrigues, Filipa Gonçalves

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Background: The assessment of feelings and attitudes of preschool children in relation to stuttering is crucial. Negative experiences can lead to anxiety, worry or frustration. To avoid the worsening of attitudes and feelings related to stuttering, it is important the early detection in order to intervene as soon as possible through an individualized intervention plan. Then it is important to have Portuguese instruments that allow this assessment. Aims: The aim of the present study is to realize the translation and adaptation of the Communication Attitude Test for Children in Preschool Age and Kindergarten (KiddyCat) for EP. Methodology: For the translation and adaptation process, a methodological study was carried out with the following steps: translation, back translation, assessment by a committee of experts and pre-test. This abstract describes the results of the first two phases of this process. The translation was accomplished by two bilingual individuals without experience in health and any knowledge about the instrument. One of them was an English teacher and the other one a Translator. The back-translation was conducted by two Senior Class Teachers that live in United Kingdom without any knowledge in health and about the instrument. Results and Discussion: In translation there were differences in semantic equivalences of various expressions and concepts. A discussion between the two translators, mediated by the researchers, allowed to achieve the consensus version of the translated instrument. Taking into account the original version of KiddyCAT the results demonstrated that back-translation versions were similar to the original version of this assessment instrument. Although the back-translators used different words, they were synonymous, maintaining semantic and idiomatic equivalences of the instrument’s items. Conclusion: This project contributes with an important resource that can be used in the assessment of feelings and attitudes of preschool children who stutter. This was the first phase of the research; expert panel and pretest are being developed. Therefore, it is expected that this instrument contributes to an holistic therapeutic intervention, taking into account the individual characteristics of each child.

Keywords: assessment, feelings and attitudes, preschool children, stuttering

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Authors: Ionelia Taranu, Gina Cecilia Pistol, Mihai Alexandru Gras, Mihai Laurentiu Palade, Mariana Stancu, Veronica Sanda Chedea

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In the last decade bioactive compounds from grape waste are investigated as new therapeutic agents for the inhibition of carcinogenesis and other diseases. The objective of this study was to characterize several bioactive compounds (polyphenols and polyunsaturated fatty acids) of a dried grape pomace (GP) derived from a Romanian winery and further to evaluate their effect on inflammation and oxidative markers in liver of pig used as animal model. The total polyphenol concentration of pomace was 36.2g gallic acid equiv /100g. The pomace was rich in polyphenols from the flavonoids group, the main class being flavanols (epicatechins, catechin, epigallocatechin, procyanidins) and antocyanins (Malvidin 3-O-glucoside). The highest concentration was recorded for epicatechin (51.96g/100g) and procyanidin dimer (22.79g/100g). A high concentration of total polyunsaturated fatty acids (PUFA) especially ω-6 fatty acids (59.82 g/100g fat) was found in grape pomace. 20 crossbred TOPIG hybrid fattening pigs were randomly assigned (n = 10) to two experimental treatments: a normal diet (control group) and a diet included 5% grape pomace (GP group) for 24 days. The GP diet lowered the gene expression and protein concentration of IL-1β, IL-8, TNF-α and IFN-γ cytokines in liver suggesting an anti-inflammatory effect of GP diet. Concentration of hepatic TBARS also decreased, but the total antioxidant capacity (liver TEAC) and activity and gene expression of antioxidant enzymes (superoxide dismutase, catalase and glutathione peroxidase) did not differ between the GP and control diet. The results showed that GP diet exerted an anti-inflammatory effect, but the 5% dietary inclusion modulated only partially the oxidative stress.

Keywords: animal model, inflammation, grape waste, immune organs

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Authors: Yosr Ghozzi

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The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.

Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0

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Authors: Ejoh Nonso Francis

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: Irrigation scheduling is a critical aspect of sustainable agriculture as it ensures optimal use of water resources, reduces water waste, and enhances crop yields. This paper presents a case study of a farm in Onitsha, Anambra State, Nigeria, where irrigation scheduling was optimized using a combination of soil moisture sensors and weather data. The study aimed to evaluate the effectiveness of this approach in improving water use efficiency and crop productivity. The results showed that the optimized irrigation scheduling approach led to a 30% reduction in water use while increasing crop yield by 20%. The study demonstrates the potential of technology-based irrigation scheduling to enhance sustainable agriculture in Nigeria and beyond.

Keywords: irrigation scheduling, sustainable agriculture, soil moisture sensors, weather data, water use efficiency, crop productivity, nigeria, onitsha, anambra state, technology-based irrigation scheduling, water resources, environmental degradation, crop water requirements, overwatering, water waste, farming systems, scalability

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Authors: Sarantos Psycharis

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Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

Keywords: arduino, computational thinking, computer programming, Labview, self-efficacy, STEM

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Authors: Ritu Karwasra, Surender Singh

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Inflammation is an important physiological response of the body’s self-defense system that helps in eliminating and protecting organism from harmful stimuli and in tissue repair. It is a highly regulated protective response which helps in eliminating the initial cause of cell injury, and initiates the process of repair. The present study was designed to evaluate the ameliorative effect of pomegranate rind extract on pain and inflammation. Hydroalcoholic standardized rind extract of pomegranate at doses 50, 100 and 200 mg/kg and indomethacin (3 mg/kg) was tested against eddy’s hot plate induced thermal algesia, carrageenan (acute inflammation) and Complete Freund’s Adjuvant (chronic inflammation) induced models in Wistar rats. Parameters analyzed were inhibition of paw edema, measurement of joint diameter, levels of GSH, TBARS, SOD, TNF-α, radiographic imaging, tissue histology and synovial expression of pro-inflammatory cytokine receptor (TNF-R1). Radiological and light microscopical analysis were carried out to find out the bone damage in CFA-induced chronic inflammatory model. Findings of the present study revealed that pomegranate rind extract at a dose of 200 mg/kg caused a significant (p<0.05) reduction in paw swelling in both the inflammatory models. Nociceptive threshold was also significantly (p<0.05) improved. Immunohistochemical analysis of TNF-R1 in CFA-induced group showed elevated level, whereas reduction in level of TNF-R1 was observed in pomegranate (200 mg/kg). Henceforth, we might say that pomegranate produced a dose-dependent reduction in inflammation and pain along with the reduction in levels of oxidative stress markers and tissue histology, and the effect was found to be comparable to that of indomethacin. Thus, it can be concluded that pomegranate is a potential therapeutic target in the pathogenesis of inflammation and pain, and punicalagin is the major constituents found in rind extract might be responsible for the activity.

Keywords: carrageenan, inflammation, nociceptive-threshold, pomegranate, histopathology

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Authors: Samereh Abdoli, Amit Vora, Anusha Vora

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Background: Diabetes burnout is one of the most common contributors to decreased quality of life, poor psychosocial well-being, and increased morbidity, mortality and diabetes cost. While the term diabetes burnout is widely accepted particularly in type 1 diabetes (T1D), the state of the science on diabetes burnout is lacking a systematic approach to overcome diabetes burnout. Objective: The study aimed to explore the strategies to overcome burnout by integrating the voices of individuals with T1D. Methods: In this study, we applied a descriptive qualitative design using YouTube videos produced by individuals with T1D. Seven YouTube videos (Austria= 1, U.S=6) with the highest rate of views which met the inclusion criteria were analyzed using a qualitative content analysis approach. Results: Participants verbalized overcoming diabetes burnout as a 'difficult hole to climb out of' which make them empowered. Themes that describes their strategies to overcome burnout in T1D, in general, include; 'make plan and take action', 'start with small steps', 'ask for help', 'get engage in diabetes community' and 'do not be perfect'. Future Work: These findings can begin the examination of different strategies to overcome diabetes burnout, which may change the course of action for diabetes care and management to improve quality of diabetes care and quality of life.

Keywords: diabetes burnout, type 1 diabetes, qualitative research, YouTube videos

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Authors: Barry Ardley, Abi Hunt, Nick Taylor

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As a theoretical and practical framework, this study uses the student-as-producer approach to learning in higher education, as adopted by the Lincoln International Business School, University of Lincoln, UK. Students as producer positions learners as skilled and capable agents, able to participate as partners with tutors in live research projects. To illuminate the nature of this approach to learning and to highlight its critical issues, the authors report on two guided student consultancy projects. These were set up with the assistance of two local organisations in the city of Lincoln, UK. Using the student as a producer model to deliver the projects enabled learners to acquire and develop a range of key skills and knowledge not easily accessible in more traditional educational settings. This paper presents a systematic case study analysis of the eight organising principles of the student-as-producer model, as adopted by university tutors. The experience of tutors implementing students as producers suggests that the model can be widely applied to benefit not only the learning and teaching experiences of higher education students and staff but additionally a university’s research programme and its community partners.

Keywords: consultancy, learning, student as producer, research

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Authors: Kiana Zeighami, Morteza Ozlati Moghadam

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Designing a high accuracy and high precision motion controller is one of the important issues in today’s industry. There are effective solutions available in the industry but the real-time performance, smoothness and accuracy of the movement can be further improved. This paper discusses a complete solution to carry out the movement of three stepper motors in three dimensions. The objective is to provide a method to design a fully integrated System-on-Chip (SOC)-based motion controller to reduce the cost and complexity of production by incorporating Field Programmable Gate Array (FPGA) into the design. In the proposed method the FPGA receives its commands from a host computer via wireless internet communication and calculates the motion trajectory for three axes. A profile generator module is designed to realize the interpolation algorithm by translating the position data to the real-time pulses. This paper discusses an approach to implement the linear interpolation algorithm, since it is one of the fundamentals of robots’ movements and it is highly applicable in motion control industries. Along with full profile trajectory, the triangular drive is implemented to eliminate the existence of error at small distances. To integrate the parallelism and real-time performance of FPGA with the power of Central Processing Unit (CPU) in executing complex and sequential algorithms, the NIOS II soft-core processor was added into the design. This paper presents different operating modes such as absolute, relative positioning, reset and velocity modes to fulfill the user requirements. The proposed approach was evaluated by designing a custom-made FPGA board along with a mechanical structure. As a result, a precise and smooth movement of stepper motors was observed which proved the effectiveness of this approach.

Keywords: 3-axis linear interpolation, FPGA, motion controller, micro-stepping

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Authors: Komal Vig

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Cardiovascular disease (CVD)-related deaths occur in 17.3 million people globally each year, accounting for 30% of all deaths worldwide, with a predicted annual incidence of deaths to reach 23.3 million globally by 2030. Autologous bypass grafts remain an important therapeutic option for the treatment of CVD, but the poor quality of the donor patient’s blood vessels, the invasiveness of the resection surgery, and postoperative movement restrictions create issues. The present study is aimed to improve the endothelialization of intimal surface of graft by using low temperature plasma (LTP) to increase the cell attachment and proliferation. Polytetrafluoroethylene (PTFE) was treated with LTP. Air was used as the feed-gas, and the pressure in the plasma chamber was kept at 800 mTorr. Scaffolds were also modified with gelatin and collagen by dipping method. Human umbilical vein endothelial cells (HUVEC) were plated on the developed scaffolds, and cell proliferation was determined by the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) assay and by microscopy. mRNA expressions levels of different cell markers were investigated using quantitative real-time PCR (qPCR). XPS confirmed the introduction of oxygenated functionalities from LTP. HUVEC cells showed 80% seeding efficiency on the scaffold. Microscopic and MTT assays indicated increase in cell viability in LTP treated scaffolds, especially when treated with gelatin or collagen, compared to untreated scaffolds. Gene expression studies shows enhanced expression of cell adhesion marker Integrin- α 5 gene after LTP treatment. LTP treated scaffolds exhibited better cell proliferation and viability compared to untreated scaffolds. Protein treatment of scaffold increased cell proliferation. Based on our initial results, more scaffolds alternatives will be developed and investigated for cell growth and vascularization studies. Acknowledgments: This work is supported by the NSF EPSCoR RII-Track-1 Cooperative Agreement OIA-2148653.

Keywords: LTP, HUVEC cells, vascular graft, endothelialization

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Authors: Wu You, Burra Venkata Durga Kumar

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This study examines the promising potential of integrating Blockchain and Artificial Intelligence (AI) technologies to scalability in Distributed Systems within the field of supply chain finance. The finance industry is continually confronted with scalability challenges in its Distributed Systems, particularly within the supply chain finance sector, impacting efficiency and security. Blockchain, with its inherent attributes of high scalability and secure distributed ledger system, coupled with AI's strengths in optimizing data processing and decision-making, holds the key to innovating the industry's approach to these issues. This study elucidates the synergistic interplay between Blockchain and AI, detailing how their fusion can drive a significant transformation in the supply chain finance sector's Distributed Systems. It offers specific use-cases within this field to illustrate the practical implications and potential benefits of this technological convergence. The study also discusses future possibilities and current challenges in implementing this groundbreaking approach within the context of supply chain finance. It concludes that the intersection of Blockchain and AI could ignite a new epoch of enhanced efficiency, security, and transparency in the Distributed Systems of supply chain finance within the financial industry.

Keywords: blockchain, artificial intelligence (AI), scaled distributed systems, supply chain finance, efficiency and security

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Authors: Bernice Badal

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The South African English curriculum emphasizes the adoption of the Communicative Approach (CA) using Communicative Language Teaching (CLT) methodologies to develop English as a second language (ESL) learners’ communicative competence in contexts such as township schools in South Africa. However, studies indicate that the adoption of the approach largely remains a rhetoric. Poor English language proficiency among learners and poor student performance, which continues from the secondary to the tertiary phase, is widely attributed to a lack of English language proficiency in South Africa. Consequently, this qualitative study, using a mix of classroom observations and interviews, sought to investigate teacher knowledge of Communicative Competence and the methods and strategies ESL teachers used to develop their learners’ communicative competence. The success of learners’ ability to develop communicative competence in contexts such as township schools in South Africa is inseparable from materials, tasks, teacher knowledge and how they implement the approach in the classrooms. Accordingly, teacher knowledge of the theory and practical implications of the CLT approach is imperative for the negotiation of meaning and appropriate use of language in context in resource-impoverished areas like the township. Using a mix of interviews and observations as data sources, this qualitative study examined teachers’ definitions and knowledge of Communicative competence with a focus on how it influenced their classroom practices. The findings revealed that teachers were not familiar with the notion of communicative competence, the communication process, and the underpinnings of CLT. Teachers’ narratives indicated an awareness that there should be interactions and communication in the classroom, but a lack of theoretical understanding of the types of communication necessary scuttled their initiatives. Thus, conceptual deficiency influences teachers’ practices as they engage in classroom activities in a superficial manner or focus on stipulated learner activities prescribed by the CAPS document. This study, therefore, concluded that partial or limited conceptual and coherent understandings with ‘teacher-proof’ stipulations for classroom practice do not inspire teacher efficacy and mastery of prescribed approaches; thus, more efforts should be made by the Department of Basic Education to strengthen the existing Professional Development workshops to support teachers in improving their understandings and application of CLT for the development of Communicative competence in their learners. The findings of the study contribute to the field of teacher knowledge acquisition, teacher beliefs and practices and professional development in the context of second language teaching and learning with a recommendation that frameworks for the development of communicative competence with wider applicability in resource-poor environments be developed to support teacher understanding and application in classrooms.

Keywords: communicative competence, CLT, conceptual understanding of reforms, professional development

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Authors: Minna Pikkarainen, Yueqiang Xu

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The integration of digital technology with existing healthcare processes has been painfully slow, a huge gap exists between the fields of strictly regulated official medical care and the quickly moving field of health and wellness technology. We claim that the promises of preventive healthcare can only be fulfilled when this gap is closed – health care and self-care becomes seamless continuum “correct information, in the correct hands, at the correct time allowing individuals and professionals to make better decisions” what we call connected health approach. Currently, the issues related to security, privacy, consumer consent and data sharing are hindering the implementation of this new paradigm of healthcare. This could be solved by following MyData principles stating that: Individuals should have the right and practical means to manage their data and privacy. MyData infrastructure enables decentralized management of personal data, improves interoperability, makes it easier for companies to comply with tightening data protection regulations, and allows individuals to change service providers without proprietary data lock-ins. This paper tackles today’s unprecedented challenges of enabling and stimulating multiple healthcare data providers and stakeholders to have more active participation in the digital health ecosystem. First, the paper systematically proposes the MyData approach for healthcare and preventive health data ecosystem. In this research, the work is targeted for health and wellness ecosystems. Each ecosystem consists of key actors, such as 1) individual (citizen or professional controlling/using the services) i.e. data subject, 2) services providing personal data (e.g. startups providing data collection apps or data collection devices), 3) health and wellness services utilizing aforementioned data and 4) services authorizing the access to this data under individual’s provided explicit consent. Second, the research extends the existing four archetypes of orchestrator-driven healthcare data business models for the healthcare industry and proposes the fifth type of healthcare data model, the MyData Blockchain Platform. This new architecture is developed by the Action Design Research approach, which is a prominent research methodology in the information system domain. The key novelty of the paper is to expand the health data value chain architecture and design from centralization and pseudo-decentralization to full decentralization, enabled by blockchain, thus the MyData blockchain platform. The study not only broadens the healthcare informatics literature but also contributes to the theoretical development of digital healthcare and blockchain research domains with a systemic approach.

Keywords: blockchain, health data, platform, action design

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Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

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In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

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Authors: Slah Eddine Ben Fadhel

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Despite the development of new pedagogic methods, current teaching practices put more emphasis on the learning products than on the processes learners deploy. In school syllabi, for instance, very little time is devoted to both the explanation and analysis of strategies aimed at resolving problems by means of targeting students’ metacognitive procedures. Within a cognitive framework, teaching/learning contexts are conceived of in terms of cognitive, metacognitive and affective activities intended for the treatment of information. During these activities, learners come to develop an array of knowledge and strategies which can be subsumed within an active and constructive process. Through the investigation of strategies and metacognition concepts, the purpose is to reflect upon the modalities at the heart of the learning process and to demonstrate, similarly, the inherent significance of a cognitive approach to learning. The scope of this paper is predicated on a study where the population is a group of 76 primary school pupils who experienced difficulty with learning French. The population was divided into two groups: the first group was submitted during three months to a strategy-based training to learn French. All through this phase, the teachers centred class activities round making learners aware of the strategies the latter deployed and geared them towards appraising the steps these learners had themselves taken by means of a variety of tools, most prominent among which is the logbook. The second group was submitted to the usual learning context with no recourse whatsoever to any strategy-oriented tasks. The results of both groups point out the improvement of linguistic competences in the French language in the case of those pupils who were trained by means of strategic procedures. Furthermore, this improvement was noted in relation with the native language (Arabic), a fact that tends to highlight the importance of the interdisciplinary investigation of (meta-)cognitive strategies. These results show that strategic learning promotes in pupils the development of a better awareness of their own processes, which contributes to improving their general linguistic competences.

Keywords: constructive approach, cognitive strategies, metacognition, learning

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Authors: Anders Thorsén, Behrooz Sangchoolie, Peter Folkesson, Ted Strandberg

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As more parts of the power grid become connected to the internet, the risk of cyberattacks increases. To identify the cybersecurity threats and subsequently reduce vulnerabilities, the common practice is to carry out a cybersecurity risk assessment. For safety classified systems and products, there is also a need for safety risk assessments in addition to the cybersecurity risk assessment in order to identify and reduce safety risks. These two risk assessments are usually done separately, but since cybersecurity and functional safety are often related, a more comprehensive method covering both aspects is needed. Some work addressing this has been done for specific domains like the automotive domain, but more general methods suitable for, e.g., intelligent distributed grids, are still missing. One such method from the automotive domain is the Security-Aware Hazard Analysis and Risk Assessment (SAHARA) method that combines safety and cybersecurity risk assessments. This paper presents an approach where the SAHARA method has been modified in order to be more suitable for larger distributed systems. The adapted SAHARA method has a more general risk assessment approach than the original SAHARA. The proposed method has been successfully applied on two use cases of an intelligent distributed grid.

Keywords: intelligent distribution grids, threat analysis, risk assessment, safety, cybersecurity

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Authors: B. M. Pardeshi

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Introduction: Minerals and trace elements are chemical elements required by our bodies for numerous biological and physiological processes that are necessary for the maintenance of health. Medicinal plants are highly beneficial for the maintenance of good health and prevention of diseases. They are known as potential sources of minerals and vitamins. 30 to 40% of today’s conventional drugs used in the medicinal and curative properties of various plants are employed in herbal supplement botanicals, nutraceuticals and drug. Aim: The authors explored the mineral element content of some herbs, because mineral elements may have significant role in the development and treatment of gastrointestinal diseases, and a close connection between the presence or absence of mineral elements and inflammatory mediators was noted. Methods: Present study deals with the elemental analysis of medicinal plants by Instrumental Neutron activation Analysis and Atomic Absorption Spectroscopy. Medicinal herbals prescribed for skin diseases were purchased from markets and were analyzed by Instrumental Neutron Activation Analysis (INAA) using 252Cf Californium spontaneous fission neutron source (flux* 109 n s-1) and the induced activities were counted by γ-ray spectrometry and Atomic Absorption Spectroscopy (AAS) techniques (Perkin Elmer 3100 Model) available at Department of Chemistry University of Pune, India, was used for the measurement of major, minor and trace elements. Results: 15 elements viz. Al, K, Cl, Na, Mn by INAA and Cu, Co, Pb Ni, Cr, Ca, Fe, Zn, Hg and Cd by AAS were analyzed from different medicinal plants from India. A critical examination of the data shows that the elements Ca , K, Cl, Al, and Fe are found to be present at major levels in most of the samples while the other elements Na, Mn, Cu, Co, Pb, Ni, Cr, Ca, Zn, Hg and Cd are present in minor or trace levels. Conclusion: The beneficial therapeutic effect of the studied herbs may be related to their mineral element content. The elemental concentration in different medicinal plants is discussed.

Keywords: instrumental neutron activation analysis, atomic absorption spectroscopy, medicinal plants, trace elemental analysis, mineral contents

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Authors: Peiming Li

Abstract:

This paper presents an innovative blockchain-based approach to enhance the reliability and efficiency of federated learning systems. By integrating a decentralized oracle consensus mechanism into the federated learning framework, we address key challenges of data and model integrity. Our approach utilizes a network of redundant oracles, functioning as independent validators within an epoch-based training system in the federated learning model. In federated learning, data is decentralized, residing on various participants' devices. This scenario often leads to concerns about data integrity and model quality. Our solution employs blockchain technology to establish a transparent and tamper-proof environment, ensuring secure data sharing and aggregation. The decentralized oracles, a concept borrowed from blockchain systems, act as unbiased validators. They assess the contributions of each participant using a Hidden Markov Model (HMM), which is crucial for evaluating the consistency of participant inputs and safeguarding against model poisoning and malicious activities. Our methodology's distinct feature is its epoch-based training. An epoch here refers to a specific training phase where data is updated and assessed for quality and relevance. The redundant oracles work in concert to validate data updates during these epochs, enhancing the system's resilience to security threats and data corruption. The effectiveness of this system was tested using the Mnist dataset, a standard in machine learning for benchmarking. Results demonstrate that our blockchain-oriented federated learning approach significantly boosts system resilience, addressing the common challenges of federated environments. This paper aims to make these advanced concepts accessible, even to those with a limited background in blockchain or federated learning. We provide a foundational understanding of how blockchain technology can revolutionize data integrity in decentralized systems and explain the role of oracles in maintaining model accuracy and reliability.

Keywords: federated learning system, block chain, decentralized oracles, hidden markov model

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