Search results for: analysis methods

Authors: Nicolò Vaiana, Giorgio Serino

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The nonlinear time history analysis of seismically base-isolated structures can require a significant computational effort when the behavior of each seismic isolator is predicted by adopting the widely used differential equation Bouc-Wen model. In this paper, a nonlinear exponential model, able to simulate the response of seismic isolation bearings within a relatively large displacements range, is described and adopted in order to reduce the numerical computations and speed up the nonlinear dynamic analysis. Compared to the Bouc-Wen model, the proposed one does not require the numerical solution of a nonlinear differential equation for each time step of the analysis. The seismic response of a 3d base-isolated structure with a lead rubber bearing system subjected to harmonic earthquake excitation is simulated by modeling each isolator using the proposed analytical model. The comparison of the numerical results and computational time with those obtained by modeling the lead rubber bearings using the Bouc-Wen model demonstrates the good accuracy of the proposed model and its capability to reduce significantly the computational effort of the analysis.

Keywords: base isolation, computational efficiency, nonlinear exponential model, nonlinear time history analysis

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Authors: Goran Begović

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In recent years, many researchers are focusing on non-intrusive measuring methods when it comes to human biosignals. These methods provide solutions for everyday use, whether it’s health monitoring or finessing the workout routine. One of the biggest issues with these solutions is that the sensors’ accuracy is highly variable due to many factors, such as ambiental light, skin color diversity, etc. That is why we wanted to explore different outcomes under those kinds of circumstances in order to find the most optimal algorithm(s) for extracting heart rate (HR) information. The optimization of such algorithms can benefit the wider, cheaper, and safer application of home health monitoring, without having to visit medical professionals as often when it comes to observing heart irregularities. In this study, we explored the accuracy of infrared (IR), red, and green LED sensorics in a controlled environment and compared the results with a medically accurate ECG monitoring device.

Keywords: data science, ECG, heart rate, holter monitor, LED sensors

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Authors: P. Zamani, A. Taleshi Anbouhi, M. R. Ashory, S. Mohajerzadeh, M. M. Khatibi

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Modal analysis is a developing science in the experimental evaluation of dynamic properties of the structures. Mechanical devices such as accelerometers are one of the sources of lack of quality in measuring modal testing parameters. In this paper, eliminating the accelerometer’s mass effect of the frequency response of the structure is studied. So, a strategy is used for eliminating the mass effect by using sensitivity analysis. In this method, the amount of mass change and the place to measure the structure’s response with least error in frequency correction is chosen. Experimental modal testing is carried out on a steel plate and the effect of accelerometer’s mass is omitted using this strategy. Finally, a good agreement is achieved between numerical and experimental results.

Keywords: accelerometer mass, frequency response function, modal analysis, sensitivity analysis

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Authors: Amin Asgarian, Ghyslaine McClure

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Experiences in the past earthquakes have clearly demonstrated the necessity of seismic design and assessment of Non-Structural Components (NSCs) particularly in post-disaster structures such as hospitals, power plants, etc. as they have to be permanently functional and operational. Meeting this objective is contingent upon having proper seismic performance of both structural and non-structural components. Proper seismic design, analysis, and assessment of NSCs can be attained through generation of Floor Design Spectrum (FDS) in a similar fashion as target spectrum for structural components. This paper presents the developed methodology to generate FDS directly from corresponding Uniform Hazard Spectrum (UHS) (i.e. design spectra for structural components). The methodology is based on the experimental and numerical analysis of a database of 27 real Reinforced Concrete (RC) buildings which are located in Montreal, Canada. The buildings were tested by Ambient Vibration Measurements (AVM) and their dynamic properties have been extracted and used as part of the approach. Database comprises 12 low-rises, 10 medium-rises, and 5 high-rises and they are mostly designated as post-disaster\emergency shelters by the city of Montreal. The buildings are subjected to 20 compatible seismic records to UHS of Montreal and Floor Response Spectra (FRS) are developed for every floors in two horizontal direction considering four different damping ratios of NSCs (i.e. 2, 5, 10, and 20 % viscous damping). Generated FRS (approximately 132’000 curves) are statistically studied and the methodology is proposed to generate the FDS directly from corresponding UHS. The approach is capable of generating the FDS for any selection of floor level and damping ratio of NSCs. It captures the effect of: dynamic interaction between primary (structural) and secondary (NSCs) systems, higher and torsional modes of primary structure. These are important improvements of this approach compared to conventional methods and code recommendations. Application of the proposed approach are represented here through two real case-study buildings: one low-rise building and one medium-rise. The proposed approach can be used as practical and robust tool for seismic assessment and design of NSCs especially in existing post-disaster structures.

Keywords: earthquake engineering, operational and functional components, operational modal analysis, seismic assessment and design

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Authors: Gulshad Azatova, Aleksandr Kapitonov, Natig Aminov

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Multiagent systems have gained significant attention in various fields, such as robotics, autonomous vehicles, and distributed computing, where multiple agents cooperate and communicate to achieve complex tasks. Efficient communication among agents is a crucial aspect of these systems, as it directly impacts their overall performance and scalability. This scholarly work provides an exploration of essential communication elements and conducts a comparative assessment of diverse protocols utilized in multiagent systems. The emphasis lies in scrutinizing the strengths, weaknesses, and applicability of these protocols across various scenarios. The research also sheds light on emerging trends within communication protocols for multiagent systems, including the incorporation of machine learning methods and the adoption of blockchain-based solutions to ensure secure communication. These trends provide valuable insights into the evolving landscape of multiagent systems and their communication protocols.

Keywords: communication, multi-agent systems, protocols, consensus

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: Ashok Sachdeva

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This research paper delves into the application of digital tools, especially Voyant Tools and AntConc version 4.0, for the analysis and interpretation of Seamus Heaney's poems. Scholars and literary aficionados can acquire deeper insights into Heaney's writings by utilising these tools, revealing hidden nuances and improving their knowledge. This paper outlines the methodology used, presents sample analyses and evaluates the merits and limitations of using digital tools in literary analysis. The combination of traditional close reading with digital analysis tools promises to offer new paths for understanding Heaney's vast tapestry of poetry. Seamus Heaney, a Nobel winner known for his vivid poetry, provides a treasure mine of literary discovery. The advent of digital tools gives an exciting opportunity to reveal previously unknown layers of meaning within his works. This paper investigates the use of Voyant Tools and AntConc version 4.0 to analyse and understand Heaney's writings, demonstrating the symbiotic relationship between traditional literary analysis and cutting-edge digital methodologies. Methodology: To demonstrate the efficiency of digital tools in the analysis of Heaney's poetry, a sample of his notable works will be entered into Voyant Tools and AntConc version 4.0. The former provides a graphic representation of word frequency, word clouds, and patterns over numerous poems. The latter, a concordance tool, enables detailed linguistic analysis, revealing patterns, and linguistic subtleties.

Keywords: digital tools, resonance, assonance, alliteration, creative quotient

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Authors: Myung Hwan Na, Ho- Chun Song, EunHee Hong

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We widely use normal linear mixed-effects model to analysis data in repeated measurement. In case of detecting heteroscedasticity and the non-normality of the population distribution at the same time, normal linear mixed-effects model can give improper result of analysis. To achieve more robust estimation, we use heavy tailed linear mixed-effects model which gives more exact and reliable analysis conclusion than standard normal linear mixed-effects model.

Keywords: reliability, tires, field data, linear mixed-effects model

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Authors: Jixiang Zhang

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A dynamic of Bertrand duopoly game is analyzed, where players use different production methods and choose their prices with bounded rationality. The equilibriums of the corresponding discrete dynamical systems are investigated. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability conditions of Nash equilibrium under a local adjustment process are studied. The stability of Nash equilibrium, as some parameters of the model are varied, gives rise to complex dynamics such as cycles of higher order and chaos. On this basis, we discover that an increase of adjustment speed of bounded rational player can make Bertrand market sink into the chaotic state. Finally, the complex dynamics, bifurcations and chaos are displayed by numerical simulation.

Keywords: Bertrand duopoly model, discrete dynamical system, heterogeneous expectations, nash equilibrium

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Authors: Vadim A. Kuznetsov, Anna M. Soldatova, Tatyana N. Enina, Elena A. Gorbatenko, Dmitrii V. Krinochkin

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The aim of the study was to evaluate potential parameters related with super-response to CRT. Methods: 60 CRT patients (mean age 54.3 ± 9.8 years; 80% men) with congestive heart failure (CHF) II-IV NYHA functional class, left ventricular ejection fraction < 35% were enrolled. At baseline, 1 month, 3 months and each 6 months after implantation clinical, electrocardiographic and echocardiographic parameters, NT-proBNP level were evaluated. According to the best decrease of left ventricular end-systolic volume (LVESV) (mean follow-up period 33.7 ± 15.1 months) patients were classified as super-responders (SR) (n=28; reduction in LVESV ≥ 30%) and non-SR (n=32; reduction in LVESV < 30%). Results: At baseline groups differed in age (58.1 ± 5.8 years in SR vs 50.8 ± 11.4 years in non-SR; p=0.003), gender (female gender 32.1% vs 9.4% respectively; p=0.028), width of QRS complex (157.6 ± 40.6 ms in SR vs 137.6 ± 33.9 ms in non-SR; p=0.044). Percentage of LBBB was equal between groups (75% in SR vs 59.4% in non-SR; p=0.274). All parameters of mechanical dyssynchrony were higher in SR, but only difference in left ventricular pre-ejection period (LVPEP) was statistically significant (153.0 ± 35.9 ms vs. 129.3 ± 28.7 ms p=0.032). NT-proBNP level was lower in SR (1581 ± 1369 pg/ml vs 3024 ± 2431 pg/ml; p=0.006). The survival rates were 100% in SR and 90.6% in non-SR (log-rank test P=0.002). Multiple logistic regression analysis showed that LVPEP (HR 1.024; 95% CI 1.004–1.044; P = 0.017), baseline NT-proBNP level (HR 0.628; 95% CI 0.414–0.953; P=0.029) and age at baseline (HR 1.094; 95% CI 1.009-1.168; P=0.30) were independent predictors for CRT super-response. ROC curve analysis demonstrated sensitivity 71.9% and specificity 82.1% (AUC=0.827; p < 0.001) of this model in prediction of super-response to CRT. Conclusion: Super-response to CRT is associated with better survival in long-term period. Presence of LBBB was not associated with super-response. LVPEP, NT-proBNP level, and age at baseline can be used as independent predictors of CRT super-response.

Keywords: cardiac resynchronisation therapy, superresponse, congestive heart failure, left bundle branch block

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Authors: Bhupinder Kaur, O. P. Pandey

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An automobile industry is using variety of materials for better comfort and utility. The present work describes the details of failure analysis done for windshield glass of a four-wheeler class. The failure occurred in two different models of the heavy duty class of four wheelers, which analysed separately. The company reported that the failure has occurred only in their rear windshield when vehicles parked under shade for several days. These glasses were characterised by dilatometer, differential thermal analyzer, and X-ray diffraction. The glasses were further investigated under scanning electron microscope with energy dispersive X-ray spectroscopy and X-ray dot mapping. The microstructural analysis of the glasses done at the surface as well as at the fractured area indicates that carbon as an impurity got segregated as banded structure throughout the glass. Since carbon absorbs higher heat, it causes thermal mismatch to the entire glass system, and glass shattered down. In this work, the details of sequential analysis done to predict the cause of failure are present.

Keywords: failure, windshield, thermal mismatch, carbon

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Authors: Somaya Adwan, Rasha Majed, Lamya'a Majed, Hamzah Arof

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In order to produce images with whole body parts, X-ray of different portions of the body parts is assembled using image stitching methods. A new method for image stitching that exploits mutually feature based method and direct based method to identify and merge pairs of X-ray medical images is presented in this paper. The performance of the proposed method based on this hybrid approach is investigated in this paper. The ability of the proposed method to stitch and merge the overlapping pairs of images is demonstrated. Our proposed method display comparable if not superior performance to other feature based methods that are mentioned in the literature on the standard databases. These results are promising and demonstrate the potential of the proposed method for further development to tackle more advanced stitching problems.

Keywords: image stitching, direct based method, panoramic image, X-ray

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Authors: Amit Tribedi

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Genuine Quantumness present in Quantum Systems is the resource for implementing Quantum Information and Computation Protocols which can outperform the classical counterparts. These Quantumness measures encompass non-local ones known as quantum entanglement (QE) and quantum information theoretic (QIT) ones, e.g. Quantum Discord (QD). In this paper, some well-known measures of QE and QD in some wheel-like frustrated molecular magnetic systems have been studied. One of the systems has already been synthesized using coordination chemistry, and the other is hypothetical, where the dominant interaction is the spin-spin exchange interaction. Exact analytical methods and exact numerical diagonalization methods have been used. Some counter-intuitive non-trivial features, like non-monotonicity of quantum correlations with temperature, persistence of multipartite entanglement over bipartite ones etc. indicated by the behaviour of the correlations and the QIT measures have been found. The measures, being operational ones, can be used to realize the resource of Quantumness in experiments.

Keywords: 0D Magnets, discord, entanglement, frustration

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Authors: Minami Ito, Akihiro Iijima

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On March 11, 2011, the Great East Japan Earthquake occurred off the coast of Sanriku, Japan. It is important to build a sustainable society through the reconstruction process rather than simply restoring the infrastructure. To compare the goals of reconstruction plans of quake-stricken municipalities, Japanese language morphological analysis was performed by using text mining techniques. Frequently-used nouns were sorted into four main categories of “life”, “disaster prevention”, “economy”, and “harmony with environment”. Because Soma City is affected by nuclear accident, sentences tagged to “harmony with environment” tended to be frequent compared to the other municipalities. Results from cluster analysis and principle component analysis clearly indicated that the local government reinforces the efforts to reduce risks from radiation exposure as a top priority.

Keywords: eco-friendly reconstruction, harmony with environment, decontamination, nuclear disaster

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Authors: Muhammad Bahrul Ilmi

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The purpose of this research is to analyze the influence of Islamic financing and work relation founding simultaneously and partially towards non-performing financing in Islamic banks. This research was regression quantitative field research, and had been done in Muammalat Indonesia Bank and Islamic Danamon Bank in 3 months. The populations of this research were 15 account officers of Muammalat Indonesia Bank and Islamic Danamon Bank in Surakarta, Indonesia. The techniques of collecting data used in this research were documentation, questionnaire, literary study and interview. Regression analysis result shows that Islamic financing and work relation founding simultaneously has positive and significant effect towards non performing financing of two Islamic Banks. It is obtained with probability value 0.003 which is less than 0.05 and F value 9.584. The analysis result of Islamic financing regression towards non performing financing shows the significant effect. It is supported by double linear regression analysis with probability value 0.001 which is less than 0.05. The regression analysis of work relation founding effect towards non-performing financing shows insignificant effect. This is shown in the double linear regression analysis with probability value 0.161 which is bigger than 0.05.

Keywords: Syariah financing, work relation founding, non-performing financing (NPF), Islamic Bank

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Authors: Stefan Gruden, Charlott Brunmark, Bo Holmqvist, Erwin D. Brenndorfer, Martin Johansson, Jian Liu, Ying Zhao, Niklas Axen, Moustapha Hassan

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Aim: The study was designed to evaluate the ability of the calcium sulfate-based NanoZolid® drug delivery technology to locally release the epidermal growth factor (EGF) protein while maintaining its biological activity. Methods: NanoZolid-formulated EGF protein labelled with a near-infrared dye (EGF-NIR) depots or EGF-NIR dissolved in PBS were injected subcutaneously into mice bearing EGF receptor (EGFR) positive human A549 lung cancer tumors inoculated subcutaneously. The release and biodistribution of the EGF-NIR were investigated in vivo longitudinally up to 96 hours post-administration, utilizing whole-body fluorescence imaging. In order to confirm the in vivo findings, histological analysis of tumor cryosections was performed to investigate EGF-NIR fluorescent signal and EGFR expression level by immunofluorescence labelling. Results: The in vivo fluorescence imaging showed a controlled release profile of the EGF-NIR loaded in the NanoZolid depots compared to free EGF-NIR. Histological analysis of the tumors further demonstrated a prevailing distribution of EGF-NIR in regions with high levels of EGFR expression. Conclusion: Calcium sulfate based depots can be used to formulate EGF while maintaining its biological activity, e.g., receptor binding capability. This may have good clinical potential for local delivery of biomolecules to enhance treatment efficacy and minimize systemic adverse effects.

Keywords: bioresorbable, calcium sulfate, controlled release, NanoZolid

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Authors: Ismail Muratoglu, Ahmet Meyveci, Abdurrahman Tuncer, Erkan Demirci

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This study is dedicated to the analysis of the problems of occupational safety in Turkey, Italy and Poland. The need analysis was applied to three different countries which are Turkey; 4, Poland; 1, Italy; 1 state. The number of the subjects is 891 in Turkey. The number of the subjects is 26 in Italy and the number of the subjects is 19 in Poland. The total number of samples of study is 936. Four different forms (Job Security Experts Form, Student Form, Teacher Form and Company Form) were applied. Results of experts of job security forms are rate of 7.1%. Then, the students’ forms are rate of 34.3%, teacher or instructor forms are rate of 9.9%. The last corporation forms are rate of 48.7%.

Keywords: Europe, need analysis, occupational safety, Turkey, vocational education

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Authors: M. Movahedi Rad

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In this study, a general approach to the reliability based limit analysis of laterally loaded piles is presented. In engineering practice, the uncertainties play a very important role. The aim of this study is to evaluate the lateral load capacity of free head and fixed-head long pile when the plastic limit analysis is considered. In addition to the plastic limit analysis to control the plastic behaviour of the structure, uncertain bound on the complementary strain energy of the residual forces is also applied. This bound has a significant effect for the load parameter. The solution to reliability-based problems is obtained by a computer program which is governed by the reliability index calculation.

Keywords: reliability, laterally loaded pile, residual strain energy, probability, limit analysis

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Authors: Sidra A. Shaikh, M. A. Ahmed, M. W. Akhtar

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Global and diffuse solar radiation studies have been carried out for Islamabad (Lat: 330 43’ N, Long: 370 71’) to access the solar potential of the area using sunshine hour data. A detailed analysis of global solar radiation values measured using several methods is presented. These values are then compared with the NASA SSE model. The variation in direct and diffuse components of solar radiation is observed in summer and winter months for Islamabad along with the clearness index KT. The diffuse solar radiation is found maximum in the month of July. Direct and beam radiation is found to be high in the month of April to June. From the results it appears that with the exception of monsoon months, July and August, solar radiation for electricity generation can be utilized very efficiently throughout the year. Finally, the mean bias error (MBE), root mean square error (RMSE) and mean percent error (MPE) for global solar radiation are also presented.

Keywords: solar potential, global and diffuse solar radiation, Islamabad, errors

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Authors: Nisar Ahmad, Xuyi, Ali Akbar

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As healthcare systems worldwide strive for improvement, the integration of advanced health information systems (HIS) has emerged as a pivotal strategy. This study aims to investigate the critical role of leadership in the implementation and enhancement of HIS in Chinese hospitals and how such leadership can drive improvements in patient outcomes and overall healthcare satisfaction. We propose a comprehensive study to be conducted across various hospitals in China, targeting healthcare professionals as the primary population. The research will leverage established theories of transformational leadership and technology acceptance to underpin the analysis. In our approach, data will be meticulously gathered through surveys and interviews, focusing on the experiences and perceptions of healthcare professionals regarding HIS implementation and its impact on patient care. The study will utilize SPSS and SmartPLS software for robust data analysis, ensuring precise and comprehensive insights into the correlation between leadership effectiveness and HIS success. We hypothesize that strong, visionary leadership is essential for the successful adoption and optimization of HIS, leading to enhanced patient outcomes and increased satisfaction with healthcare services. By applying advanced statistical methods, we aim to identify key leadership traits and practices that significantly contribute to these improvements. Our research will provide actionable insights for policymakers and healthcare administrators in China, offering evidence-based recommendations to foster leadership that champions HIS and drives continuous improvement in healthcare delivery. This study will contribute to the global discourse on health information systems, emphasizing the future role of leadership in transforming healthcare environments and outcomes.

Keywords: health information systems, leadership, patient outcomes, healthcare satisfaction

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Authors: Jinn-Jong Sheu, Cang-Fu Liang, Cheng-Hsien Yu

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This paper proposed the cold roll forming process and the die design methods for a 400mm by 400 mm square tube with 16 mm in thickness. The tubular blank made by cold roll forming is 508mm in diameter. The square tube roll forming process was designed considering the layout of rolls and the compression ratio distribution for each stand. The final tube corner radius and the edge straightness in the front end of the tube are to be controlled according to the tube specification. A five-stand forming design using four rolls at each stand was proposed to establish the base reference of square tube roll forming quality. Different numbers of pass and roll designs were proposed and compared to the base design in order to find the feasibility of increase pass number to improve the square tube quality. The proposed roll forming processes were simulated using FEM analysis. The thickness variations of the corner and the edge areas were examined. The maximum loads and the torques of each stand were calculated to study the power consumption of the roll forming machine. The simulation results showed the square tube thickness variations and concavity of the edge are acceptable with the JIS tube specifications for the base design. But the maximum loads and torques are very high. By changing the layout and the number of the rolls were able to obtain better tube geometry and decrease the maximum load and torque of each stand. This paper had shown the feasibility of designing the roll forming process and the layout of dies using FEM simulation. The obtained information is helpful to the roll forming machine design for a large size square tube making.

Keywords: cold roll forming, FEM analysis, roll forming die design, tube roll forming

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Authors: Vijay Kr. Yadav, Nilam Rathi

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Accurate prediction of glucose level for diabetes mellitus is required to avoid affecting the functioning of major organs of human body. This study describes the fundamental assumptions and two different methodologies of the Blood glucose prediction. First is based on the back-propagation algorithm of Artificial Neural Network (ANN), and second is based on the Neuro-Fuzzy technique, called Fuzzy Inference System (FIS). Errors between proposed methods further discussed through various statistical methods such as mean square error (MSE), normalised mean absolute error (NMAE). The main objective of present study is to develop mathematical model for blood glucose prediction before 12 hours advanced using data set of three patients for 60 days. The comparative studies of the accuracy with other existing models are also made with same data set.

Keywords: back-propagation, diabetes mellitus, fuzzy inference system, neuro-fuzzy

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Authors: Saeid Jalilzadeh

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PID controllers are widely used to control the industrial plants because of their robustness and simple structures. Tuning of the controller's parameters to get a desired response is difficult and time consuming. With the development of computer technology and artificial intelligence in automatic control field, all kinds of parameters tuning methods of PID controller have emerged in endlessly, which bring much energy for the study of PID controller, but many advanced tuning methods behave not so perfect as to be expected. Honey Bee algorithm (HBA) and genetic algorithm (GA) are extensively used for real parameter optimization in diverse fields of study. This paper describes an application of HBA and GA to the problem of designing a PID controller whose parameters comprise proportionality constant, integral constant and derivative constant. Presence of three parameters to optimize makes the task of designing a PID controller more challenging than conventional P, PI, and PD controllers design. The suitability of the proposed approach has been demonstrated through computer simulation using MATLAB/SIMULINK.

Keywords: controller, GA, optimization, PID, PSO

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: A. H. Elkholy, A. H. Falah

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A new approach has been developed to estimate the load share and stress distribution of worm gear sets. The approach is based upon considering the instantaneous tooth meshing stiffness where the worm gear drive was modelled as a series of spur gear slices, and each slice was analyzed separately using the well established formulae of spur gears. By combining the results obtained for all slices, the entire envolute worm gear set loading and stressing was obtained. The geometric modelling method presented, allows tooth elastic deformation and tooth root stresses of worm gear drives under different load conditions to be investigated. On the basis of the method introduced in this study, the instantaneous meshing stiffness and load share were obtained. In comparison with existing methods, this approach has both good analysis accuracy and less computing time.

Keywords: gear, load/stress distribution, worm, wheel, tooth stiffness, contact line

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Authors: Kyle De Freitas, Margaret Bernard

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Enabling data mining analysis among a wider audience of educators is an active area of research within the educational data mining (EDM) community. The paper proposes a framework for developing an environment that caters for educators who have little technical data mining skills as well as for more advanced users with some data mining expertise. This framework architecture was developed through the review of the strengths and weaknesses of existing models in the literature. The proposed framework provides a modular architecture for future researchers to focus on the development of specific areas within the EDM process. Finally, the paper also highlights a strategy of enabling analysis through either the use of predefined questions or a guided data mining process and highlights how the developed questions and analysis conducted can be reused and extended over time.

Keywords: educational data mining, learning management system, learning analytics, EDM framework

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Authors: Bok Yae Chung, Eun Hee Oh

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Breast cancer patients require more nutritional interventions than others. However, a few studies have attempted to assess the overall nutritional status, to reduce body weight and BMI by improving diet, and to improve the prognosis of cancer for breast cancer patients. The purpose of this study was to evaluate the effect of diet intervention in the breast cancer patients through meta-analysis. For the study purpose, 16 studies were selected by using PubMed, ScienceDirect, ProQuest and CINAHL. Meta-analysis was performed using a random-effects model, and the effect size on outcome variables in breast cancer was calculated. The effect size for outcome variables of diet intervention was a large effect size. For heterogeneity, moderator analysis was performed using intervention type and intervention duration. All moderators did not significant difference. Diet intervention has significant positive effects on outcome variables in breast cancer. As a result, it is suggested that the timing of the intervention should be no more than six months, but a strategy for sustaining long-term intervention effects should be added if nutritional intervention is to be administered for breast cancer patients in the future.

Keywords: breast cancer, diet, mete-analysis, intervention

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Authors: Stephan Printz, Kristina Lahl, René Vossen, Sabina Jeschke

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Strategic investment decisions are characterized by high innovation potential and long-term effects on the competitiveness of enterprises. Due to the uncertainty and risks involved in this complex decision making process, the need arises for well-structured support activities. A method that considers cost and the long-term added value is the cost-benefit effectiveness estimation. One of those methods is the “profitability estimation focused on benefits – PEFB”-method developed at the Institute of Management Cybernetics at RWTH Aachen University. The method copes with the challenges associated with strategic investment decisions by integrating long-term non-monetary aspects whilst also mapping the chronological sequence of an investment within the organization’s target system. Thus, this method is characterized as a holistic approach for the evaluation of costs and benefits of an investment. This participation-oriented method was applied to business environments in many workshops. The results of the workshops are a library of more than 96 cost aspects, as well as 122 benefit aspects. These aspects are preprocessed and comparatively analyzed with regards to their alignment to a series of risk levels. For the first time, an accumulation and a distribution of cost and benefit aspects regarding their impact and probability of occurrence are given. The results give evidence that the PEFB-method combines precise measures of financial accounting with the incorporation of benefits. Finally, the results constitute the basics for using information technology and data science for decision support when applying within the PEFB-method.

Keywords: cost-benefit analysis, multi-criteria decision, profitability estimation focused on benefits, risk and uncertainty analysis

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Authors: Masoud Safdari, Jacob Fish

Abstract:

Despite vast amount of existing theoretical knowledge, the implementation of a universal multiscale modeling, analysis, and simulation software framework remains challenging. Existing multiscale software and solutions are often domain-specific, closed-source and mandate a high-level of experience and skills in both multiscale analysis and programming. Furthermore, tools currently existing for Atomistic-to-Continuum (AtC) multiscaling are developed with the assumptions such as accessibility of high-performance computing facilities to the users. These issues mentioned plus many other challenges have reduced the adoption of multiscale in academia and especially industry. In the current work, we introduce Multiscale Hub (MsHub), an effort towards making AtC more accessible through cloud services. As a joint effort between academia and industry, MsHub provides a universal web-enabled framework for practical multiscaling. Developed on top of universally acclaimed scientific programming language Python, the package currently provides an open-source, comprehensive, easy-to-use framework for AtC coupling. MsHub offers an easy to use interface to prominent molecular dynamics and multiphysics continuum mechanics packages such as LAMMPS and MFEM (a free, lightweight, scalable C++ library for finite element methods). In this work, we first report on the design philosophy of MsHub, challenges identified and issues faced regarding its implementation. MsHub takes the advantage of a comprehensive set of tools and algorithms developed for AtC that can be used for a variety of governing physics. We then briefly report key AtC algorithms implemented in MsHub. Finally, we conclude with a few examples illustrating the capabilities of the package and its future directions.

Keywords: atomistic, continuum, coupling, multiscale

Procedia PDF Downloads 166

Authors: Ali panahi-Kosar Khosravi

Abstract:

Earthquake resilience is one of the most important theoretical and practical concepts in crisis management. Over the past few decades, the rapid growth of urban areas and developing lower urban areas (especially in developing countries) have made them more vulnerable to human and natural crises. Therefore, the resilience of urban communities, especially low-income and unhealthy neighborhoods, is of particular importance. The present study seeks to assess and evaluate the resilience of neighborhoods in the center of district 6 of Tabriz in terms of awareness, knowledge and personal skills, social and psychological capital, managerial-institutional, and the ability to return to appropriate and sustainable conditions. The research method in this research is descriptive-analytical. The authors used library and survey methods to collect information and a questionnaire to assess resilience. The statistical population of this study is the total households living in the four neighborhoods of Shanb Ghazan, Khatib, Gharamalek, and Abuzar alley. Three hundred eighty-four families from four neighborhoods were selected based on the Cochran formula using a simple random sampling method. A one-sample t-test, simple linear regression, and structural equations were used to test the research hypotheses. Findings showed that only two social and psychological awareness and capital indicators in district 6 of Tabriz had a favorable and approved status. Therefore, considering the multidimensional concept of resilience, district 6 of Tabriz is in an unfavorable resilience situation. Also, the findings based on the analysis of variance indicated no significant difference between the neighborhoods of district 6 in terms of resilience, and most neighborhoods are in an unfavorable situation.

Keywords: resilience, statistical analysis, earthquake, district 6 of tabriz

Procedia PDF Downloads 69