Search results for: adaptive neck supporter

Authors: Hassan Naseh, Javad Roozgard

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This paper represents the methodology based on Artificial Intelligent (AI) applied to Liquid Propellant Engine (LPE) optimization. The AI methodology utilized from Adaptive neural Fuzzy Inference System (ANFIS). In this methodology, the optimum objective function means to achieve maximum performance (specific impulse). The independent design variables in ANFIS modeling are combustion chamber pressure and temperature and oxidizer to fuel ratio and output of this modeling are specific impulse that can be applied with other objective functions in LPE design optimization. To this end, the LPE’s parameter has been modeled in ANFIS methodology based on generating fuzzy inference system structure by using grid partitioning, subtractive clustering and Fuzzy C-Means (FCM) clustering for both inferences (Mamdani and Sugeno) and various types of membership functions. The final comparing optimization results shown accuracy and processing run time of the Gaussian ANFIS Methodology between all methods.

Keywords: ANFIS methodology, artificial intelligent, liquid propellant engine, optimization

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Authors: Avinash S. Jagtap, Sharad D. Gore, Rajendra G. Gurao

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Decision rules become more and more complex as the number of conditions increase. As a consequence, the complexity of the decision rule also influences the time complexity of computer implementation of such a rule. Consider, for example, a decision that depends on four conditions A, B, C and D. For simplicity, suppose each of these four conditions is binary. Even then the decision rule will consist of 16 lines, where each line will be of the form: If A and B and C and D, then action 1. If A and B and C but not D, then action 2 and so on. While executing this decision rule, each of the four conditions will be checked every time until all the four conditions in a line are satisfied. The minimum number of logical comparisons is 4 whereas the maximum number is 64. This paper proposes to present a complex decision rule in the form of a decision tree. A decision tree divides the cases into branches every time a condition is checked. In the form of a decision tree, every branching eliminates half of the cases that do not satisfy the related conditions. As a result, every branch of the decision tree involves only four logical comparisons and hence is significantly simpler than the corresponding complex decision rule. The conclusion of this paper is that every complex decision rule can be represented as a decision tree and the decision tree is mathematically equivalent but computationally much simpler than the original complex decision rule

Keywords: strategic, tactical, operational, adaptive, innovative

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Authors: Mannan Malik Muhammad Naeem, Jeong Myung Yung

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Functional near infrared spectroscopy (fNIRS) has a favorable position in non-invasive brain imaging techniques. The concentration change of oxygenated hemoglobin and de-oxygenated hemoglobin during particular cognitive activity is the basis for this neuro-imaging modality. Two wavelengths of near-infrared light can be used with modified Beer-Lambert law to explain the indirect status of neuronal activity inside brain. The temporal resolution of fNIRS is very good for real-time brain computer-interface applications. The portability, low cost and an acceptable temporal resolution of fNIRS put it on a better position in neuro-imaging modalities. In this study, an optimization model for impulse response function has been used to estimate/predict initial dip using fNIRS data. In addition, the activity strength parameter related to motor based cognitive task has been analyzed. We found an initial dip that remains around 200-300 millisecond and better localize neural activity.

Keywords: fNIRS, brain-computer interface, optimization algorithm, adaptive signal processing

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Authors: Abraham Finkelman

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Computerized Surgical Guides have been proven to be a predictable way to perform dental implants, with a relatively high accuracy in comparison to a treatment plan. When using the CSG Bone supported, it allows us to make the necessary changes of the hard tissue prior to the implant placement and after the implant placement. The CSG gives us an accurate position for the drilling, and during the implant placement it allows us to alter the vertical position of the implant altering the final position of the abutment and avoiding any risk of any damage to the adjacent anatomical structures. Any Changes required to the bone level can be done prior to the fixation of the CSG using a reduction guide, which incur extra surgical fees and the need of a second surgical guide. Any changes of the bone level after the implant placement are at the risk of damaging the implant neck surface. The technique consists of a universal system that allows us to remove the excess bone around the implant sockets prior to the implant placement which then enables us to place the implant in the vertical position with accuracy as planned with the CSG. The systems consist of a hollow pin of different sizes and diameters. Depending on the implant system that we are using. Length sizes are from 6mm-16mm and a diameter of 2.6mm-4.8mm. Upon the completion of the drilling, the pin is then inserted into the implant socket-using the insertion tool. Once the insertion tool has unscrewed the pin, we can continue with the bone reduction. The bone reduction can be done using conventional methods upon the removal of all the excess bone around the pin. The insertion tool is then screwed into the pin and the pin is then removed. We now, have the new bone level at the crest of the implant socket which is our mark for the vertical position of the implant. In some cases, when we are locating the implant very close to anatomical structures, any form of deviation to the vertical position of the implant during the surgery, can cause damage to such anatomical structures, creating irreversible damages such as paresthesia or dysesthesia of the mandibular nerve. If we are planning for immediate loading and we have done our temporary restauration in base of our computerized plan, deviation in the vertical position of the implant will affect the position of the abutment, affecting the accuracy of the temporary prosthesis, extending the working time till we adapt the prosthesis to the new position.

Keywords: bone reduction, computer aided navigation, dental implant placement, surgical guides

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Authors: Ramin Zargarbashi, Hamid Rabie, Behnam Panjavi, Hooman Kamran, Seyedarad Mosalamiaghili, Zohre Erfani, Seyed Peyman Mirghaderi, Maryam Salimi

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Background: Posterior shoulder dislocation is one of the disabling complications of brachial plexus birth injury (BPBI), and various treatment options, including capsule and surrounding muscles release for open reduction, humeral derotational osteotomy, and tendon transfers, have been recommended to manage it. In the present study, we aimed to determine the clinical outcome of open reduction with soft tissue release, tendon transfer, and glenoid osteotomy inpatients with BPBI and posterior shoulder dislocation or subluxation. Methods: From 2018 to 2020, 33 patients that underwent open reduction, glenoid osteotomy, and tendon transfer were included. The glenohumeral deformity was classified according to the Waters radiographic classification. Functional assessment was performed using the Mallet grading system before and at least two years after the surgery. Results: The patients were monitored for 26.88± 5.47 months. Their average age was 27.5±14 months. Significant improvement was seen in the overall Mallet score (from 13.5 to 18.91 points) and its segments, including hand to mouth, hand to the neck, global abduction, global external rotation, abduction degree, and external rotation degree. Hand-to-back score and the presence of trumpet sign were significantly decreased in the post-operation phase (all p values<0.001). The above-mentioned variables significantly changed for both infantile and non-infantile dislocations. Conclusion: Our study demonstrated that open reduction along with glenoid osteotomy improves retroversion, and muscle strengthening with different muscle transfers is an effective technique for BPBI.

Keywords: birth injuries, nerve injury, brachial plexus birth palsy, Erb palsy, tendon transfer

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Authors: Qasim Zafar, Matthew Anderson, Esteban Garcia, Steven Drager

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Software failures can present an enormous detriment to people's lives and cost millions of dollars to repair when they are unexpectedly encountered in the wild. Despite a significant portion of the software development lifecycle and resources are dedicated to testing, software failures are a relatively frequent occurrence. Nevertheless, the evaluation of testing effectiveness remains at the forefront of ensuring high-quality software and software metrics play a critical role in providing valuable insights into quantifiable objectives to assess the level of assurance and confidence in the system. As the selection of appropriate metrics can be an arduous process, the goal of this paper is to shed light on the significance of software metrics by examining a range of testing techniques and metrics as well as identifying key areas for improvement. Additionally, through this investigation, readers will gain a deeper understanding of how metrics can help to drive informed decision-making on delivering high-quality software and facilitate continuous improvement in testing practices.

Keywords: software testing, software metrics, testing effectiveness, black box testing, random testing, adaptive random testing, combinatorial testing, fuzz testing, equivalence partition, boundary value analysis, white box testing

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Authors: Yongrong Li, Ralf Domroes

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Due to significant energy savings, enablement of higher machining speed as well as environmentally friendly features, Minimum Quantity Lubrication (MQL) has been used for many machining processes efficiently. However, in the deep hole drilling field (small tool diameter D < 5 mm) and long tool (length L > 25xD) it is always a bottle neck for a single channel MQL system. The single channel MQL, based on the Venturi principle, faces a lack of enough oil quantity caused by dropped pressure difference during the deep hole drilling process. In this paper, a system concept based on a bypass design has explored its possibility to dynamically reach the required pressure difference between the air inlet and the inside of aerosol generator, so that the deep hole drilling demanded volume of oil can be generated and delivered to tool tips. The system concept has been investigated in static and dynamic laboratory testing. In the static test, the oil volume with and without bypass control were measured. This shows an oil quantity increasing potential up to 1000%. A spray pattern test has demonstrated the differences of aerosol particle size, aerosol distribution and reaction time between single channel and bypass controlled single channel MQL systems. A dynamic trial machining test of deep hole drilling (drill tool D=4.5mm, L= 40xD) has been carried out with the proposed system on a difficult machining material AlSi7Mg. The tool wear along a 100 meter drilling was tracked and analyzed. The result shows that the single channel MQL with a bypass control can overcome the limitation and enhance deep hole drilling with a small tool. The optimized combination of inlet air pressure and bypass control results in a high quality oil delivery to tool tips with a uniform and continuous aerosol flow.

Keywords: deep hole drilling, green production, Minimum Quantity Lubrication (MQL), near dry machining

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Authors: Svetlana V. Topolyanskaya, Tatyana A. Eliseeva, Olga N. Vakulenko, Leonid I. Dvoretski

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Introduction: Limited data are available on osteoporosis in centenarians. Therefore, we evaluated bone mineral density in long-living patients with coronary artery disease (CAD). Methods: 202 patients hospitalized with CAD were enrolled in this cross-sectional study. The patients' age ranged from 90 to 101 years. The majority of study participants (64.4%) were women. The main exclusion criteria were any disease or medication that can lead to secondary osteoporosis. Bone mineral density (BMD) was measured by dual-energy X-ray absorptiometry. Results: Normal lumbar spine BMD was observed in 40.9%, osteoporosis – in 26.9%, osteopenia – in 32.2% of patients. Normal proximal femur BMD values were observed in 21.3%, osteoporosis – in 39.9%, and osteopenia – in 38.8% of patients. Normal femoral neck BMD was registered only in 10.4% of patients, osteoporosis was observed in 60.4%, osteopenia in 29.2%. Significant positive correlation was found between all BMD values and body mass index of patients (p < 0.001). Positive correlation was registered between BMD values and serum uric acid (p=0.0005). The likelihood of normal BMD values with hyperuricemia increased 3.8 times, compared to patients with normal uric acid, who often have osteoporosis (Odds Ratio=3.84; p = 0.009). Positive correlation was registered between all BMD values and body mass index (p < 0.001). Positive correlation between triglycerides levels and T-score (p=0.02), but negative correlation between BMD and HDL-cholesterol (p=0.02) were revealed. Negative correlation between frailty severity and BMD values (p=0.01) was found. Positive correlation between BMD values and functional abilities of patients assessed using Barthel index (r=0,44; p=0,000002) and IADL scale (r=0,36; p=0,00008) was registered. Fractures in history were observed in 27.6% of patients. Conclusions: The study results indicate some features of BMD in long-livers. In the study group, significant relationships were found between bone mineral density on the one hand, and patients' functional abilities on the other. It is advisable to further study the state of bone tissue in long-livers involving a large sample of patients.

Keywords: osteoporosis, bone mineral density, centenarians, coronary artery disease

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Authors: Tanveer Ahmed Choudhury

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Background: Bangladesh is one of the largest deltas in the world, with high population density and high rates of poverty and illiteracy. 80% of the country is on low-lying floodplains, leaving the country one of the most vulnerable to the adverse effects of climate change: sea level rise, cyclones and storms, salinity intrusion, rising temperatures and heavy monsoon downpours. Such climatic events already limit Economic Development in the country. Although Bangladesh has had little responsibility in contributing to global climatic change, it is vulnerable to both its direct and indirect impacts. Real threats include reduced agricultural production, worsening food security, increased incidence of flooding and drought, spreading disease and an increased risk of conflict over scarce land and water resources. Currently, 8.3 million Bangladeshis live in cyclone high risk areas. However, by 2050 this is expected to grow to 20.3 million people, if proper adaptive actions are not taken. Under a high emissions scenario, an additional 7.6 million people will be exposed to very high salinity by 2050 compared to current levels. It is also projected that, an average of 7.2 million people will be affected by flooding due to sea level rise every year between 2070-2100 and If global emissions decrease rapidly and adaptation interventions are taken, the population affected by flooding could be limited to only about 14,000 people. To combat the climate change adverse effects, Bangladesh government has initiated many adaptive measures specially in infrastructure and renewable energy sector. Government is investing huge money and initiated many projects which have been proved very success full. Objectives: The objective of this paper is to describe some successful measures initiated by Bangladesh government in its effort to make the country a Climate Resilient. Methodology: Review of operation plan and activities of different relevant Ministries of Bangladesh government. Result: The following initiative projects, programs and activities are considered as best practices for Climate Change adaptation successes for Bangladesh: 1. The Infrastructure Development Company Limited (IDCOL); 2. Climate Change and Health Promotion Unit (CCHPU); 3. The Climate Change Trust Fund (CCTF); 4. Community Climate Change Project (CCCP); 5. Health, Population, Nutrition Sector Development Program (HPNSDP, 2011-2016)- "Climate Change and Environmental Issues"; 6. Ministry of Health and Family Welfare, Bangladesh and WHO Collaboration; - National Adaptation Plan. -"Building adaptation to climate change in health in least developed countries through resilient WASH". 7. COP-21 “Climate and health country profile -2015 Bangladesh. Conclusion: Due to a vast coastline, low-lying land and abundance of rivers, Bangladesh is highly vulnerable to climate change. Having extensive experience with facing natural disasters, Bangladesh has developed a successful adaptation program, which led to a significant reduction in casualties from extreme weather events. In a low income country setting, Bangladesh had successfully adapted various projects and initiatives to combat future Climate Change challenges.

Keywords: climate, change, success, Bangladesh

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Authors: Bonchan Koo, Junhee Han, Dohyung Lee

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The research attempts to evaluate the accuracy and efficiency of a design optimization procedure which combines wavelets-based solution algorithm and proper orthogonal decomposition (POD) database management technique. Aerodynamic design procedure calls for high fidelity computational fluid dynamic (CFD) simulations and the consideration of large number of flow conditions and design constraints. Even with significant computing power advancement, current level of integrated design process requires substantial computing time and resources. POD reduces the degree of freedom of full system through conducting singular value decomposition for various field simulations. For additional efficiency improvement of the procedure, adaptive wavelet technique is also being employed during POD training period. The proposed design procedure was applied to the optimization of wing aerodynamic performance. Throughout the research, it was confirmed that the POD/wavelets design procedure could significantly reduce the total design turnaround time and is also able to capture all detailed complex flow features as in full order analysis.

Keywords: POD (Proper Orthogonal Decomposition), wavelets, CFD, design optimization, ROM (Reduced Order Model)

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Authors: Sina Saadati

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Multiprocessors Systems-On-Chips (MPSOCs) are used widely on modern computers to execute sophisticated software and applications. These systems include different processors for distinct aims. Most of the proposed task schedulers attempt to improve energy consumption. In some schedulers, the processor's temperature is considered to increase the system's reliability and performance. In this research, we have proposed a new method for thermal-aware task scheduling which is based on an artificial neural network (ANN). This method enables us to consider a variety of factors in the scheduling process. Some factors like ambient temperature, season (which is important for some embedded systems), speed of the processor, computing type of tasks and have a complex relationship with the final temperature of the system. This Issue can be solved using a machine learning algorithm. Another point is that our solution makes the system intelligent So that It can be adaptive. We have also shown that the computational complexity of the proposed method is cheap. As a consequence, It is also suitable for battery-powered systems.

Keywords: task scheduling, MOSOC, artificial neural network, machine learning, architecture of computers, artificial intelligence

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Authors: Erion Luga, Aksel Seitllari, Kemal Pervanqe

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This study investigates the relation between physical and mechanical properties of concrete paving stones using neuro-fuzzy approach. For this purpose 200 samples of concrete paving stones were selected randomly from different sources. The first phase included the determination of physical properties of the samples such as water absorption capacity, porosity and unit weight. After that the indirect tensile strength test and compressive strength test of the samples were performed. İn the second phase, adaptive neuro-fuzzy approach was employed to simulate nonlinear mapping between the above mentioned physical properties and mechanical properties of paving stones. The neuro-fuzzy models uses Sugeno type fuzzy inference system. The models parameters were adapted using hybrid learning algorithm and input space was fuzzyfied by considering grid partitioning. It is concluded based on the observed data and the estimated data through ANFIS models that neuro-fuzzy system exhibits a satisfactory performance.

Keywords: paving stones, physical properties, mechanical properties, ANFIS

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Authors: Alex Elentukh

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The paper is based on data collected from final exams administered during five years of teaching the graduate course in software engineering. The visualization instrument with four distinct personas has been used to improve the effectiveness of each class. The study offers a plethora of clues toward students' behavioral preferences. Diversity among students (professional background, physical proximity) is too significant to assume a single face of a learner. This is particularly true for a body of online graduate students in computer science. Conclusions of the study (each learner is unique, and each class is unique) are extrapolated to demystify the notion of an 'average software engineer.' An immediate direction for an educator is to ensure a course applies to a wide audience of very different individuals. On the other hand, a student should be clear about his/her abilities and preferences - to follow the most effective learning path.

Keywords: K.3.2 computer and information science education, learner profiling, adaptive learning, software engineering

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Authors: Snezana Svetozarevic

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The aim of the research was to determine whether there were significant changes in perceptions of family functioning by families in Serbia 12 months after the coronavirus (COVID-19) outbreak has been declared a global pandemic. Above all, what has protected families in the face of the global crisis caused by COVID-19. The Self-Report Family Inventory, II version (SFI-II; Beavers and Hampson, 2013) and the Inventory of Family Protective Factors (IFPF; Gardner et al., 2008) were used to assess family functioning and protective factors. Currently, families perceive their functioning as more problematic regarding family emotional expressiveness, conflict, cohesion, and global family health/competence. Adaptive appraisal based on positive coping experiences significantly predicted values on emotional expressiveness, conflict, leadership, and global family health/competence dimensions -a higher prevalence of this factor was associated with more optimal family functioning and fewer problems. The growing problem in family functioning with the beginning of the pandemic is inevitable. However, our research confirmed that it is not enough to take into account what families do to survive. It is equally important to learn about what they do to thrive i.e., to study the family resilience.

Keywords: family, coping, resilience, pandemic, COVID-19

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Authors: Yunyong Guo, Sudhakar Ganti, Bryan Guo

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The swift proliferation of telehealth Internet of Things (IoT) devices has sparked concerns regarding energy consumption and the need for streamlined data processing. This paper presents an energy-efficient model that integrates telehealth IoT devices into a platform based on fog and cloud computing. This integrated system provides a sustainable and robust solution to address the challenges. Our model strategically utilizes fog computing as a localized data processing layer and leverages cloud computing for resource-intensive tasks, resulting in a significant reduction in overall energy consumption. The incorporation of adaptive energy-saving strategies further enhances the efficiency of our approach. Simulation analysis validates the effectiveness of our model in improving energy efficiency for telehealth IoT systems, particularly when integrated with localized fog nodes and both private and public cloud infrastructures. Subsequent research endeavors will concentrate on refining the energy-saving model, exploring additional functional enhancements, and assessing its broader applicability across various healthcare and industry sectors.

Keywords: energy-efficient, fog computing, IoT, telehealth

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Peggy M. Randon, Lisa Randon

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Introduction: The post-COVID-19 era has presented unique challenges for addressing complex mental health issues, particularly due to exacerbated stress, increased social isolation, and disrupted continuity of care. This article outlines relevant health disparities and policy implications within the context of the United States while maintaining international relevance. Methods: A comprehensive literature review (including studies, reports, and policy documents) was conducted to examine concerns related to childhood-onset schizophrenia and the impact on patients and their families. Qualitative and quantitative data were synthesized to provide insights into the complex etiology of schizophrenia, the effects of the pandemic, and the challenges faced by socioeconomically disadvantaged populations. Case studies were employed to illustrate real-world examples and areas requiring policy reform. Results: Early intervention in childhood is crucial for preventing or mitigating the long-term impact of complex psychotic disorders, particularly schizophrenia. A comprehensive understanding of the genetic, environmental, and physiological factors contributing to the development of schizophrenia is essential. The COVID-19 pandemic worsened symptoms and disrupted treatment for many adolescent patients with schizophrenia, emphasizing the need for adaptive interventions and the utilization of virtual platforms. Health disparities, including stigma, financial constraints, and language or cultural barriers, further limit access to care, especially for socioeconomically disadvantaged populations. Policy implications: Current US health policies inadequately support patients with schizophrenia. The limited availability of longitudinal care, insufficient resources for families, and stigmatization represent ongoing policy challenges. Addressing these issues necessitates increased research funding, improved access to affordable treatment plans, and cultural competency training for healthcare providers. Public awareness campaigns are crucial to promote knowledge, awareness, and acceptance of mental health disorders. Conclusion: The unique challenges faced by children and families in the US affected by schizophrenia and other psychotic disorders have yet to be adequately addressed on institutional and systemic levels. The relevance of findings to an international audience is emphasized by examining the complex factors contributing to the onset of psychotic disorders and their global policy implications. The broad impact of the COVID-19 pandemic on mental health underscores the need for adaptive interventions and global responses. Addressing policy challenges, improving access to care, and reducing the stigma associated with mental health disorders are crucial steps toward enhancing the lives of adolescents and young adults with schizophrenia and their family members. The implementation of virtual platforms can help overcome barriers and ensure equitable access to support and resources for all patients, enabling them to lead healthy and fulfilling lives.

Keywords: childhood, schizophrenia, policy, United, States, health, disparities

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Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin

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This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of single-parameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.

Keywords: hybrid fault diagnosis, dynamic neural networks, nonlinear systems, fault tolerant observer

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Authors: Visa I. Tyakaray, M. Abdulaziz, O. Badmus, N. Karaye, M. Dalhat, A. Shehu, I. Bello, T. Hussaini, S. Akar, G. Effah, P. Nguku

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Introduction: Nigeria has recorded outbreaks of meningitis in the past, being in the meningitis belt. A multi-state outbreak of Cerebrospinal Meningitis (CSM) from Neisseria meningitides occurred in 2017 involving 24 states, and Kano State reported its first two confirmed CSM cases on 22nd March, 2017. We conducted the outbreak investigation to characterize the outbreak, determine its associated risk factors and institute appropriate control measures. Method: We conducted an unmatched Case-control study with ratio 1:2. A case was defined as any person with sudden onset of fever (>38.5˚C rectal or 38.0˚C axillary) and one of the following: neck stiffness, altered consciousness or bulging fontanelle in toddlers while a control was defined as any person who resides around the case such as family members, caregivers, neighbors, and healthcare personnel. We reviewed and validated line list and conducted active case search in health facilities and neighboring communities. Descriptive, bivariate, stratified and multivariate analysis were performed. Laboratory confirmation was by Latex agglutination and/or Culture. Results: We recruited 48 cases with median age of 11 years (1 month – 65 years), attack rate was 2.4/100,000 population with case fatality rate of 8%; 34 of 44 local government areas were affected.On stratification, age was found to be a confounder. Independent factors associated with the outbreak were age (Adjusted Odds Ratio, AOR =6.58; 95% Confidence Interval (CI) =2.85-15.180, history of Vaccination (AOR=0.37; 95% CI=0.13-0.99) and history of travel (AOR=10.16; (1.99-51.85). Laboratory results showed 22 positive cases for Neisseria meningitides types C and A/Y. Conclusion: Major risk factors associated with this outbreak were age (>14years), not being vaccinated and history of travel. We sensitized communities and strengthened case management. We recommended immediate reactive vaccination and enhanced surveillance in bordering communities.

Keywords: cerebrospinal, factors, Kano-Nigeria, meningitis, risk

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Authors: Noritaka Shigei, Kazuto Matsumoto, Yoshiki Nakashima, Hiromi Miyajima

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Although Mobile Wireless Sensor Networks (MWSNs), which consist of mobile sensor nodes (MSNs), can cover a wide range of observation region by using a small number of sensor nodes, they need to construct a network to collect the sensing data on the base station by moving the MSNs. As an effective method, the network construction method based on Virtual Rails (VRs), which is referred to as VR method, has been proposed. In this paper, we propose two types of effective techniques for the VR method. They can prolong the operation time of the network, which is limited by the battery capabilities of MSNs and the energy consumption of MSNs. The first technique, an effective arrangement of VRs, almost equalizes the number of MSNs belonging to each VR. The second technique, an adaptive movement method of MSNs, takes into account the residual energy of battery. In the simulation, we demonstrate that each technique can improve the network lifetime and the combination of both techniques is the most effective.

Keywords: mobile sensor node, relay of sensing data, residual energy, virtual rail, wireless sensor network

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Authors: Mallikarjuna Rao Gundavarapu, Ch. Mallikarjuna Rao, K. Anuradha Bai

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Real Time Video Tracking is a challenging task for computing professionals. The performance of video tracking techniques is greatly affected by background detection and elimination process. Local regions of the image frame contain vital information of background and foreground. However, pixel-level processing of local regions consumes a good amount of computational time and memory space by traditional approaches. In our approach we have explored the concurrent computational ability of General Purpose Graphic Processing Units (GPGPU) to address this problem. The Gaussian Mixture Model (GMM) with adaptive weighted kernels is used for detecting the background. The weights of the kernel are influenced by local regions and are updated by inter-frame variations of these corresponding regions. The proposed system has been tested with GPU devices such as GeForce GTX 280, GeForce GTX 280 and Quadro K2000. The results are encouraging with maximum speed up 10X compared to sequential approach.

Keywords: connected components, embrace threads, local weighted kernel, structuring elements

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Authors: Yousif Mohamed Y. Abdallah, Razan Manofely, Rajab M. Ben Yousef

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X-Ray images are very popular as a first tool for diagnosis. Automating the process of analysis of such images is important in order to help physician procedures. In this practice, teeth segmentation from the radiographic images and feature extraction are essential steps. The main objective of this study was to study correction preprocessing of x-rays images using local adaptive filters in order to evaluate contrast enhancement pattern in different x-rays images such as grey color and to evaluate the usage of new nonlinear approach for contrast enhancement of soft tissues in x-rays images. The data analyzed by using MatLab program to enhance the contrast within the soft tissues, the gray levels in both enhanced and unenhanced images and noise variance. The main techniques of enhancement used in this study were contrast enhancement filtering and deblurring images using the blind deconvolution algorithm. In this paper, prominent constraints are firstly preservation of image's overall look; secondly, preservation of the diagnostic content in the image and thirdly detection of small low contrast details in diagnostic content of the image.

Keywords: enhancement, x-rays, pixel intensity values, MatLab

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Authors: R. Vigneswaran, S. Thilakanathan

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Variable time-stepping algorithms for solving dynamical systems performed poorly for long time computations which pass close to a fixed point. To overcome this difficulty, several authors considered phase space error controls for numerical simulation of dynamical systems. In one generalized phase space error control, a step-size selection scheme was proposed, which allows this error control to be incorporated into the standard adaptive algorithm as an extra constraint at negligible extra computational cost. For this generalized error control, it was already analyzed the forward Euler method applied to the linear system whose coefficient matrix has real and negative eigenvalues. In this paper, this result was extended to the linear system whose coefficient matrix has complex eigenvalues with negative real parts. Some theoretical results were obtained and numerical experiments were carried out to support the theoretical results.

Keywords: adaptivity, fixed point, long time simulations, stability, linear system

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Authors: S. Nickolas, Shobha K.

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The treatment of incomplete data is an important step in the data pre-processing. Missing values creates a noisy environment in all applications and it is an unavoidable problem in big data management and analysis. Numerous techniques likes discarding rows with missing values, mean imputation, expectation maximization, neural networks with evolutionary algorithms or optimized techniques and hot deck imputation have been introduced by researchers for handling missing data. Among these, imputation techniques plays a positive role in filling missing values when it is necessary to use all records in the data and not to discard records with missing values. In this paper we propose a novel artificial neural network based clustering algorithm, Adaptive Resonance Theory-2(ART2) for imputation of missing values in mixed attribute data sets. The process of ART2 can recognize learned models fast and be adapted to new objects rapidly. It carries out model-based clustering by using competitive learning and self-steady mechanism in dynamic environment without supervision. The proposed approach not only imputes the missing values but also provides information about handling the outliers.

Keywords: ART2, data imputation, clustering, missing data, neural network, pre-processing

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Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: Tzu-Ping Lin, Shing-Ru Yang

Abstract:

Climate change has a significant impact on human living environment, while the traditional settlement may suffer extreme thermal stress due to its specific building type and living behavior. This study selected Lutaoyang, which is the largest settlement in mountainous areas of Tainan County, for the investigation area. The microclimate parameters, such as air temperature, relative humidity, wind speed, and mean radiant temperature. The micro climate parameters were also simulated by the ENVI-met model. The results showed the banyan tree area providing good thermal comfort condition due to the shading. On the contrary, the courtyard (traditionally for the crops drying) surrounded by low rise building and consisted of artificial pavement contributing heat stress especially in summer noon. In the climate change simulations, the courtyard will become very hot and are not suitable for residents activities. These analytical results will shed light on the sustainability related to thermal environment in traditional settlements and develop adaptive measure towards sustainable development under the climate change challenges.

Keywords: thermal environment, traditional settlement, ENVI-met, Taiwan

Procedia PDF Downloads 468

Authors: Jong Han Joo, Jung Hoon Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

Abstract:

In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. We propose a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector

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Authors: Hannah Kolano, Paul Nadan, Jeremy Ryan, Sophia Nielsen

Abstract:

The hooves of goats and other ruminants, or the family Ruminantia, are uniquely structured to adapt to rough terrain. Their hooves possess a hard outer shell and a soft interior that allow them to both conform to uneven surfaces and hook onto prominent features. In an effort to apply this unique mechanism to a robotics context, artificial feet for a hexapedal robot have been designed based on the hooves of ruminants to improve the robot’s ability to traverse unstructured environments such as those found on a rocky planet or asteroid, as well as in earth-based environments such as rubble, caves, and mountainous regions. The feet were manufactured using a combination of 3D printing and polyurethane casting techniques and attached to a commercially available hexapedal robot. The robot was programmed with a terrain-adaptive gait and proved capable of traversing a variety of uneven surfaces and inclines. This development of more adaptable robotic feet allows legged robots to operate in a wider range of environments and expands their possible applications.

Keywords: biomimicry, legged locomotion, robotic foot design, ruminant feet, unstructured terrain navigation

Procedia PDF Downloads 111

Authors: Pegah Zamani

Abstract:

This multidisciplinary study interrogates the reformulation of socio-ecological systems by bringing different disciplines together and incorporating ecological, social, and technological components to the sustainable design. The study seeks for a holistic sustainable system to understand the multidimensional impact of the evolving innovative technologies on responding to the variable socio-environmental conditions. Through a range of cases, from the vernacular built spaces to the sophisticated optimized systems, the research unfolds how far the environmental elements would impact the performance of a sustainable building, its micro-climatic ecological requirements, and its human inhabitation. As a product of the advancing technologies, an optimized and environmentally responsive building offers new identification, and realization of the built space through reformulating the connection to its internal and external environments (such as solar, thermal, and airflow), as well as its dwellers. The study inquires properties of optimized buildings, by bringing into the equation not only the environmental but also the socio-cultural, morphological, and phenomenal factors. Thus, the research underlines optimized built space as a product and practice which would not be meaningful without addressing and dynamically adjusting to the diversity and complexity of socio-ecological systems.

Keywords: ecology, morphology, socio-ecological systems, sustainability

Procedia PDF Downloads 189

Authors: Valentina Zhang

Abstract:

While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

Procedia PDF Downloads 127