Search results for: methods of reducing slipping

Authors: Sara Muhammad Elqudah, Vigh László Gergely

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Catastrophic events, such as earthquakes, are sudden, short, and devastating, threatening lives, demolishing futures, and causing huge economic losses. Current seismic analyses and design standards are based on life safety levels where only some residual strength and stiffness are left in the structure leaving it beyond economical repair. Consequently, it has become necessary to introduce and implement the concept of resilient design. Resilient design is about designing for ductility over time by resisting, absorbing, and recovering from the effects of a hazard in an appropriate and efficient time manner while maintaining the functionality of the structure in the aftermath of the incident. Resilient analysis is mainly based on the fragility, vulnerability, and functionality curves where eventually a resilience index is generated from these curves, and the higher this index is, the better is the performance of the structure. In this paper, seismic performances of a simple two story reinforced concrete building, located in a moderate seismic region, has been evaluated using the conventional seismic analyses methods, which are the linear static analysis, the response spectrum analysis, and the pushover analysis, and the generated results of these analyses methods are compared to those of the resilient analysis. Results highlight that the resilience analysis was the most convenient method in generating a more ductile and functional structure from a socio-economic perspective, in comparison to the standard seismic analysis methods.

Keywords: conventional analysis methods, functionality, resilient analysis, seismic performance

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Authors: Munirah Alaboudi

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This paper discusses a research project carried out with 12 first-year graduate students enrolled in research methods course prior to undertaking a graduate thesis during the academic year 2019. The research was designed for the objective of creating research methods course structure that embraces an individualized and activity-based approach to learning in a highly engaging group environment. This approach targeted innovating the traditional research methods lecture-based, theoretical format where students reported less engagement and limited learning. This study utilized action research methodology in developing a different approach to research methods course instruction where student performance indicators and feedback were periodically collected to assess the new teaching method. Student learning was achieved through utilizing the flipped classroom approach where students learned the material at home and classroom activities were designed to implement and experiment with the newly acquired information, with the guidance of the course instructor. Student learning in class was practiced through a series of activities based on different research methods. With the goal of encouraging student engagement, a wide range of activities was utilized including workshops, role play, mind-mapping, presentations, peer evaluations. Data was collected through an open-ended qualitative questionnaire to establish whether students were engaged in the material they were learning, and to what degree were they engaged, and to test their mastery level of the concepts discussed. Analysis of the data presented positive results as around 91% of the students reported feeling more engaged with the active learning experience and learning research by “actually doing research, not just reading about it”. The students expressed feeling invested in the process of their learning as they saw their research “gradually come to life” through peer learning and practice during workshops. Based on the results of this study, the research methods course structure was successfully remodeled and continues to be delivered.

Keywords: research methods, higher education instruction, flipped classroom, graduate education

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Authors: Fadi Awawdeh

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In this work, we highlight the key concepts in using semigroup theory as a methodology used to construct efficient formulas for solving inverse problems. The proposed method depends on some results concerning integral equations. The experimental results show the potential and limitations of the method and imply directions for future work.

Keywords: identification problems, semigroup theory, methods for inverse problems, scientific computing

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Authors: Jui-Hung Hung, Ching-Liang Hsieh, Yi-Wen Lin

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Modern medicine highly emphasizes the importance of palliative treatment. The inception of palliative and hospice care recently developed into the concept of caring for the patients’ and families’ physical, psychological and spiritual problems. There are several benefits related to palliative care such as reducing medical expenses, decreasing patients’ suffer, and supporting patient go through the finale of the life. Nowadays, in Taiwan, over 60-70% terminal cancer patients were covered in hospice care, and the coverage rate increased annually. Acupuncture is a well-known therapy used more than thousand years to relieve symptoms of cancer patient. Many reports showed that, even in the Western society, many reputable medical centers can provide Acupuncture therapy for patients. Accordingly, using Acupuncture for cancer patient care is a global trend. There are increased evidences indicate that Acupuncture can relieve the symptoms for cancer patients including pain, reduce the dosage of anesthetic, improve the cancer-related fatigue, relieve the chemotherapy-related nausea and vomiting, ease anxiety mood and even improving the quality of life. Furthermore, some trials show that Acupuncture may help relieve xerostomia, hot flash, sleep disorders, and some GI discomfort and so on. Acupuncture therapy has many advantages for clinical use with effective, low-cost, minimal side effect, suitable for cancer patients and even for elderly population. Especially in nowadays, there are more diversified challenges in modern medicine, all of them will make the higher medical budget. We suggest that Acupuncture will be one of methods for palliative care for cancer patients.

Keywords: Acupuncture, cancer, integrative medicine, palliative care

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Authors: Ionut Vintu, Stefan Laible, Ruth Schulz

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Agricultural robotics has been developing steadily over recent years, with the goal of reducing and even eliminating pesticides used in crops and to increase productivity by taking over human labor. The majority of crops are arranged in rows. The first step towards autonomous robots, capable of driving in fields and performing crop-handling tasks, is for robots to robustly detect the rows of plants. Recent work done towards autonomous driving between plant rows offers big robotic platforms equipped with various expensive sensors as a solution to this problem. These platforms need to be driven over the rows of plants. This approach lacks flexibility and scalability when it comes to the height of plants or distance between rows. This paper proposes instead an algorithm that makes use of cheaper sensors and has a higher variability. The main application is in tree nurseries. Here, plant height can range from a few centimeters to a few meters. Moreover, trees are often removed, leading to gaps within the plant rows. The core idea is to combine row detection algorithms with graph-based localization methods as they are used in SLAM. Nodes in the graph represent the estimated pose of the robot, and the edges embed constraints between these poses or between the robot and certain landmarks. This setup aims to improve individual plant detection and deal with exception handling, like row gaps, which are falsely detected as an end of rows. Four methods were developed for detecting row structures in the fields, all using a point cloud acquired with a 3D LiDAR as an input. Comparing the field coverage and number of damaged plants, the method that uses a local map around the robot proved to perform the best, with 68% covered rows and 25% damaged plants. This method is further used and combined with a graph-based localization algorithm, which uses the local map features to estimate the robot’s position inside the greater field. Testing the upgraded algorithm in a variety of simulated fields shows that the additional information obtained from localization provides a boost in performance over methods that rely purely on perception to navigate. The final algorithm achieved a row coverage of 80% and an accuracy of 27% damaged plants. Future work would focus on achieving a perfect score of 100% covered rows and 0% damaged plants. The main challenges that the algorithm needs to overcome are fields where the height of the plants is too small for the plants to be detected and fields where it is hard to distinguish between individual plants when they are overlapping. The method was also tested on a real robot in a small field with artificial plants. The tests were performed using a small robot platform equipped with wheel encoders, an IMU and an FX10 3D LiDAR. Over ten runs, the system achieved 100% coverage and 0% damaged plants. The framework built within the scope of this work can be further used to integrate data from additional sensors, with the goal of achieving even better results.

Keywords: 3D LiDAR, agricultural robots, graph-based localization, row detection

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Authors: Badoiu Mihaela Catalina

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Main focus of COHESION policy was reducing social and economic disparities between member states and regions, sustainable development and equal opportunities. In this perspective, the present study intend to analyze the evolution of the European architecture and its direct impact over the real convergence in the member states.

Keywords: cooperation, European union, member states, cohesion policy

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Authors: Debasmita Misra, Arthur Nash

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Energy security and sufficiency enables the economic development and welfare of a nation or a society. Currently, the global energy system is dominated by fossil fuels, which is a non-renewable energy resource, which renders vulnerability to energy security. Hence, many nations have begun augmenting their energy system with renewable energy resources, such as solar, wind, biomass and hydro. However, with climate change, how sustainable are some of the renewable energy resources in the future is a matter of concern. Geothermal energy resources have been underexplored or underexploited in global renewable energy production and security, although it is gaining attractiveness as a renewable energy resource. The question is, whether geothermal energy resources are more sustainable than other renewable energy resources. High-temperature reservoirs (> 220 °F) can produce electricity from flash/dry steam plants as well as binary cycle production facilities. Most of the world’s high enthalpy geothermal resources are within the seismo-tectonic belt. However, exploration for geothermal energy is of great importance in conventional geothermal systems in order to improve its economic viability. In recent years, there has been an increase in the use and development of several exploration methods for geo-thermal resources, such as seismic or electromagnetic methods. The thermal infrared band of the Landsat can reflect land surface temperature difference, so the ETM+ data with specific grey stretch enhancement has been used to explore underground heat water. Another way of exploring for potential power is utilizing fairway play analysis for sites without surface expression and in rift zones. Utilizing this type of analysis can improve the success rate of project development by reducing exploration costs. Identifying the basin distribution of geologic factors that control the geothermal environment would help in identifying the control of resource concentration aside from the heat flow, thus improving the probability of success. The first step is compiling existing geophysical data. This leads to constructing conceptual models of potential geothermal concentrations which can then be utilized in creating a geodatabase to analyze risk maps. Geospatial analysis and other GIS tools can be used in such efforts to produce spatial distribution maps. The goal of this paper is to discuss how climate change may impact renewable energy resources and how could a synthesized analysis be developed for geothermal resources to ensure sustainable and cost effective exploitation of the resource.

Keywords: exploration, geothermal, renewable energy, sustainable

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Authors: Nicolas Zufferey

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Ant algorithms are well-known metaheuristics which have been widely used since two decades. In most of the literature, an ant is a constructive heuristic able to build a solution from scratch. However, other types of ant algorithms have recently emerged: the discussion is thus not limited by the common framework of the constructive ant algorithms. Generally, at each generation of an ant algorithm, each ant builds a solution step by step by adding an element to it. Each choice is based on the greedy force (also called the visibility, the short term profit or the heuristic information) and the trail system (central memory which collects historical information of the search process). Usually, all the ants of the population have the same characteristics and behaviors. In contrast in this paper, a new type of ant metaheuristic is proposed, namely SMART (for Solution Methods with Ants Running by Types). It relies on the use of different population of ants, where each population has its own personality.

Keywords: ant algorithms, evolutionary procedures, metaheuristics, optimization, population-based methods

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Authors: M. Devaki, K. B. Jayanthi

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The identification of water bodies from satellite images has recently received a great deal of attention. Different methods have been developed to distinguish water bodies from various satellite images that vary in terms of time and space. Urban water identification issues body manifests in numerous applications with a great deal of certainty. There has been a sharp rise in the usage of satellite images to map natural resources, including urban water bodies and forests, during the past several years. This is because water and forest resources depend on each other so heavily that ongoing monitoring of both is essential to their sustainable management. The relevant elements from satellite pictures have been chosen using a variety of techniques, including machine learning. Then, a convolution neural network (CNN) architecture is created that can identify a superpixel as either one of two classes, one that includes water or doesn't from input data in a complex metropolitan scene. The deep learning technique, CNN, has advanced tremendously in a variety of visual-related tasks. CNN can improve classification performance by reducing the spectral-spatial regularities of the input data and extracting deep features hierarchically from raw pictures. Calculate the water body using the satellite image's resolution. Experimental results demonstrate that the suggested method outperformed conventional approaches in terms of water extraction accuracy from remote-sensing images, with an average overall accuracy of 97%.

Keywords: water body, Deep learning, satellite images, convolution neural network

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Authors: Gangadhara Siva Naga Venkata Krishna Satya Narayana Swamy Undi

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Particulate matter (PM) pollution in ambient air is a major environmental health risk factor contributing to disease and mortality worldwide. Current air pollution control methods have limitations in reducing real-world ambient PM levels. This study demonstrates the efficacy of using pulsed radio wave technology as a distinct approach to lower outdoor particulate pollution. Experimental data were compared with computational models to evaluate the efficiency of pulsed waves in coagulating and settling PM. Results showed 50%+ reductions in PM2.5 and PM10 concentrations at the city scale, with particle removal rates exceeding gravity settling by over 3X. Historical air quality data further validated the significant PM reductions achieved in test cases. Computational analyses revealed the underlying coagulation mechanisms induced by the pulsed waves, supporting the feasibility of this strategy for ambient particulate control. The pulsed electromagnetic technology displayed robustness in sustainably managing PM levels across diverse urban and industrial environments. Findings highlight the promise of this advanced approach as a next-generation solution to mitigate particulate air pollution and associated health burdens globally. The technology's scalability and energy efficiency can help address a key gap in current efforts to improve ambient air quality.

Keywords: particulate matter, mitigation technologies, clean air, ambient air pollution

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Authors: Elham Allahmoradi, Bahman Allahmoradi, Ali Bonyadi Naeini

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Complex systems have many aspects. A variety of methods have been developed to analyze these systems. The most efficient of these methods should not only be simple, but also provide useful and comprehensive information about many aspects of the system. Matrix methods are considered the most commonly methods used to analyze and design systems. Each matrix method can examine a particular aspect of the system. If these methods are combined, managers can access to more comprehensive and broader information about the system. This study was conducted in four steps. In the first step, a process model of a real project has been extracted through IDEF3. In the second step, activity levels have been attained by writing a process model in the form of a design structure matrix (DSM) and sorting it through triangulation algorithm (TA). In the third step, sub-processes have been obtained by writing the process model in the form of an interface structure matrix (ISM) and clustering it through cluster identification algorithm (CIA). In the fourth step, a mixed model has been developed to provide a unified picture of the project structure through the simultaneous presentation of activities and sub-processes. Finally, the paper is completed with a conclusion.

Keywords: integrated definition for process description capture (IDEF3) method, design structure matrix (DSM), interface structure matrix (ism), mixed matrix model, activity level, sub-process

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Authors: V. Verma, Syed Riyaz-ul-Hassan

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Staphylococcus aureus is one of the most commonly found pathogenic bacteria and is hard to eliminate from the human environment. It is responsible for many nosocomial infections, besides being the main causative agent of food intoxication by virtue of its variety of enterotoxins. Routine detection of S. aureus in food is usually carried out by traditional methods based on morphological and biochemical characterization. These methods are time-consuming and tedious. In addition, misclassifications with automated susceptibility testing systems or commercially available latex agglutination kits have been reported by several workers. Consequently, there is a need for methods to specifically discriminate S. aureus from other staphylococci as quickly as possible. Data on protocols developed using molecular means like PCR technology will be presented for rapid and specific detection of this pathogen in food, clinical and environmental samples, especially milk.

Keywords: food Pathogens, PCR technology, rapid and specific detection, staphylococcus aureus

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Authors: Mohamad R. Moshtagh, Ahmad Bagheri

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Accurate fault detection in rotating machinery is of utmost importance to ensure optimal performance and prevent costly downtime in industrial applications. This study presents a robust fault detection system based on vibration data collected from rotating gears under various operating conditions. The considered scenarios include: (1) both gears being healthy, (2) one healthy gear and one faulty gear, and (3) introducing an imbalanced condition to a healthy gear. Vibration data was acquired using a Hentek 1008 device and stored in a CSV file. Python code implemented in the Spider environment was used for data preprocessing and analysis. Winner features were extracted using the Wiener feature selection method. These features were then employed in multiple machine learning algorithms, including Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), K-Nearest Neighbors (KNN), and Random Forest, to evaluate their performance in detecting and classifying faults in both the training and validation datasets. The comparative analysis of the methods revealed the superior performance of the Wiener-CNN approach. The Wiener-CNN method achieved a remarkable accuracy of 100% for both the two-class (healthy gear and faulty gear) and three-class (healthy gear, faulty gear, and imbalanced) scenarios in the training and validation datasets. In contrast, the other methods exhibited varying levels of accuracy. The Wiener-MLP method attained 100% accuracy for the two-class training dataset and 100% for the validation dataset. For the three-class scenario, the Wiener-MLP method demonstrated 100% accuracy in the training dataset and 95.3% accuracy in the validation dataset. The Wiener-KNN method yielded 96.3% accuracy for the two-class training dataset and 94.5% for the validation dataset. In the three-class scenario, it achieved 85.3% accuracy in the training dataset and 77.2% in the validation dataset. The Wiener-Random Forest method achieved 100% accuracy for the two-class training dataset and 85% for the validation dataset, while in the three-class training dataset, it attained 100% accuracy and 90.8% accuracy for the validation dataset. The exceptional accuracy demonstrated by the Wiener-CNN method underscores its effectiveness in accurately identifying and classifying fault conditions in rotating machinery. The proposed fault detection system utilizes vibration data analysis and advanced machine learning techniques to improve operational reliability and productivity. By adopting the Wiener-CNN method, industrial systems can benefit from enhanced fault detection capabilities, facilitating proactive maintenance and reducing equipment downtime.

Keywords: fault detection, gearbox, machine learning, wiener method

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Authors: Ginés Hernández-Cánovas, Mª Camino Ramón-Llorens, Johanna Koëter-Kant

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This paper uses a survey data-set of 837 Spanish SMEs to analyze the association between borrower discouragement and prior firm´s strategic decisions, while controlling for firm and owner characteristics. While existing literature has neglected factors limiting the demand for resources by an overreliance on arguments which attempt to explain the existence of discouraged borrowers solely in terms of lack of access to supply of credit. The objective of this paper is to show that factors limiting the demand for resources and, therefore, reducing the availability of funds, can be traced back to the firm manager´s decision. Our hypothesis is that managers that undertake strategic decisions seeking growth or improvement in their business performance participate more in the banking market than those showing contentment with their current business situation. Our results shows that SMEs that undertake an active role in research and development activities and that achieve improvements in the operating performance of their business are less likely to be discouraged from applying for a loan. Who needs credit and who applies for credit is important for firms, prospective lenders and policymakers interested in the financial health of these firms. Credit constrained firms are less likely to invest in R&D and to introduce new products, possibly harming long-term economic growth. Knowing how important borrower discouragement is in Europe, is important for judging the priority which should be attached to government policies aimed at reducing its effects. For example, policy makers could encourage the transparency about credit eligibility and conditions in order to reduce discouragement.

Keywords: discouragement, financial constraints, SMEs financing

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Authors: Mina Ganji Morad, Maziar Azadisoleimanieh, Sina Ganji Morad

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A green roof is formed by green plants alive and has many positive impacts in the regional climatic, as well as indoor. Green roof system to prevent solar radiation plays a role in the cooling space. The cooling is done by reducing thermal fluctuations on the exterior of the roof and by increasing the roof heat capacity which cause to keep the space under the roof cool in the summer and heating rate increases during the winter. A roof garden is one of the recommended ways to reduce energy consumption in large cities. Despite the scale of the city green roofs have effective functions, such as beautiful view of city and decontaminating the urban landscape and reduce mental stress, and in an exchange of energy and heat from outside to inside spaces. This article is based on a review of 20 articles and 10 books and valid survey results on the positive effects of green roofs to prevent energy waste in the building. According to these publications, three of the conventional roof, green roof typical and green roof with certain administrative details (layers of glass) and the use of resistant plants and shrubs have been analyzed and compared their heat transfer. The results of these studies showed that one of the best green roof systems for mountainous climate is tree and shrub system that in addition to being resistant to climate change in mountainous regions, will benefit from the other advantages of green roof. Due to the severity of climate change in mountainous areas it is essential to prevent the waste of buildings heating and cooling energy. Proper climate design can greatly help to reduce energy.

Keywords: green roof, heat transfer, reducing energy consumption, mountainous areas, sustainable architecture

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Authors: Benjamin Ankomah-Asare, Richard Adade

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Sea level rise (SLR) poses a significant threat to coastal communities globally. Ghana has over the years implemented protective measures such as the construction of groynes and revetment to serve as barriers to sea waves in major cities and towns to prevent sea erosion and flooding. For vulnerable rural coastal communities, the planned retreat is often proposed; however, relocation costs are often underestimated as losses of future social and cultural value are not always adequately taken into account. Through a mixed-methods approach combining qualitative interviews, surveys, and spatial analysis, the study examined the experiences of coastal rural communities in Ghana and assess the effectiveness of relocation strategies in addressing the socio-economic and environmental challenges posed by sea level rise. The study revealed the devastating consequences of sea level rise on these communities, including increased flooding, erosion, and saltwater intrusion into freshwater sources. Moreover, it highlights the adaptive capacities within these communities and how factors such as infrastructure, economic activities, cultural heritage, and governance structures shape their resilience in the face of environmental change. While relocation can be an effective strategy in reducing the risks associated with sea level rise, the study recommends that proper implementation of this adaptation strategy can be achieved when coupled with community-led planning, participatory decision-making, and targeted support for vulnerable groups.

Keywords: sea level rise, relocation, socio-ecological impacts, rural communities

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Authors: Elizabeth Valenti

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Objective: To date, there remains an absence of literature examining perceptions of mindfulness and mindful practices among college students, particularly among Christian students. The purpose of this mixed-methods, exploratory study was to gain a better understanding of students’ perception of mindfulness and assess current mindful practices. Methods: The mixed-methods, exploratory study examined data from freshmen undergraduate college students (N=107) enrolled in an introductory psychology course at a private, non-profit Christian university. Students completed a researcher-developed questionnaire containing both Likert and opened ended questions to assess knowledge about and perceptions of mindfulness, as well as current mindful practices. Results: Results of the thematic analysis revealed approximately half of the students had a limited understanding of mindfulness, with several reporting disadvantages. Most students listed prayer as a consistent practice, with a much smaller percentage of students consistently engaging in other mindful activities. Discussion: Implications for mindfulness education and the promotion of evidence-based methods, particularly in Christian communities, are discussed.

Keywords: mindfulness, mindful practices, perception, Christian, university students, mental health

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Authors: M. Ravindiran, P. Shankar

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This paper deals with the comparison of two synthesis methods, namely, sol-gel, and combustion to prepare Fe doped ZnO nano material. Characterization results for structural, optical and magnetic properties were analyzed for the sol gel and combustion synthesis derived materials. Magnetic studies of the prepared compounds reveal that the combustion synthesis derived material has good magnetization of 50 emu/gm with a better hysteresis loop curve.

Keywords: DMS, combustion, ferromagnetic, synthesis methods

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Authors: R. Kerbachi, S. Chikhi, M. Boughedaoui

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The study presents an analysis of the Algerian vehicle fleet and resultant emissions. The emission measurement of air pollutants emitted by road transportation (CO, THC, NOX and CO2) was conducted on 17 light duty vehicles in real traffic. This sample is representative of the Algerian light vehicles in terms of fuel quality (gasoline, diesel and liquefied petroleum gas) and the technology quality (injection system and emission control). The experimental measurement methodology of unit emission of vehicles in real traffic situation is based on the use of the mini-Constant Volume Sampler for gas sampling and a set of gas analyzers for CO2, CO, NOx and THC, with an instrumentation to measure kinematics, gas temperature and pressure. The apparatus is also equipped with data logging instrument and data transfer. The results were compared with the database of the European light vehicles (Artemis). It was shown that the technological injection liquefied petroleum gas (LPG) has significant impact on air pollutants emission. Therefore, with the exception of nitrogen oxide compounds, uncatalyzed LPG vehicles are more effective in reducing emissions unit of air pollutants compared to uncatalyzed gasoline vehicles. LPG performance seems to be lower under real driving conditions than expected on chassis dynamometer. On the other hand, the results show that uncatalyzed gasoline vehicles emit high levels of carbon monoxide, and nitrogen oxides. Overall, and in the absence of standards in Algeria, unit emissions are much higher than Euro 3. The enforcement of pollutant emission standard in developing countries is an important step towards introducing cleaner technology and reducing vehicular emissions.

Keywords: on-board measurements of unit emissions of CO, HC, NOx and CO2, light vehicles, mini-CVS, LPG-fuel, artemis, Algeria

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Authors: Sizar Abed Mohammed, Zahraa Ghazi Sadeeq

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The use of the classic method, least squares (OLS) to estimate the linear regression parameters, when they are available assumptions, and capabilities that have good characteristics, such as impartiality, minimum variance, consistency, and so on. The development of alternative statistical techniques to estimate the parameters, when the data are contaminated with outliers. These are powerful methods (or resistance). In this paper, three of robust methods are studied, which are: Maximum likelihood type estimate M-estimator, Modified Maximum likelihood type estimate MM-estimator and Least Trimmed Squares LTS-estimator, and their results are compared with OLS method. These methods applied to real data taken from Duhok company for manufacturing furniture, the obtained results compared by using the criteria: Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Mean Sum of Absolute Error (MSAE). Important conclusions that this study came up with are: a number of typical values detected by using four methods in the furniture line and very close to the data. This refers to the fact that close to the normal distribution of standard errors, but typical values in the doors line data, using OLS less than that detected by the powerful ways. This means that the standard errors of the distribution are far from normal departure. Another important conclusion is that the estimated values of the parameters by using the lifeline is very far from the estimated values using powerful methods for line doors, gave LTS- destined better results using standard MSE, and gave the M- estimator better results using standard MAPE. Moreover, we noticed that using standard MSAE, and MM- estimator is better. The programs S-plus (version 8.0, professional 2007), Minitab (version 13.2) and SPSS (version 17) are used to analyze the data.

Keywords: Robest, LTS, M estimate, MSE

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Authors: Reham H. Diab, Amira A. A. Abdallah, Eman A. Embaby

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Background: The effectiveness of bracing on preventing spino-pelvic alignment deterioration in idiopathic scoliosis has been extensively studied especially in the frontal plane. Yet, there is lack of knowledge regarding the effect of soft braces on spino-pelvic alignment in the sagittal plane. Achieving harmonious sagittal plane spino-pelvic balance is critical for the preservation of physiologic posture and spinal health. Purpose: This study examined the kyphotic angle, lordotic angle and pelvic inclination in the sagittal plane and trunk imbalance in the frontal plane before and after a six-month rehabilitation period. Methods: Nineteen patients with idiopathic scoliosis participated in the study. They were divided into two groups; experimental and control. The experimental group (group I) used the SpineCor brace in addition to a rehabilitation exercise program while the control group (group II) had the exercise program only. The mean ±SD age, weight and height were 16.89±2.15 vs. 15.3±2.5 years; 59.78±6.85 vs. 62.5±8.33 Kg and 162.78±5.76 vs. 159±5.72 cm for group I vs. group II. Data were collected using for metric Π system. Results: Mixed design MANOVA showed that there were significant (p < 0.05) decreases in all the tested variables after the six-month period compared with “before” in both groups. Moreover, there was a significant decrease in the kyphotic angle in group I compared with group II after the six-month period. Interpretation and conclusion: SpineCor brace is beneficial in reducing spino-pelvic alignment deterioration in both sagittal and frontal planes.

Keywords: adolescent idiopathic scoliosis, SpineCor, spino-pelvic alignment, biomechanics

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Authors: Yi-Fung Lin, Shiow-Ching Shun, Wen-Yu Hu

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Background: A skill mix model is regarded as one of the most effective methods of reducing nursing shortages, as well as easing nursing staff workloads and labor costs. Although this model shows several benefits for the health workforce, the relationship between the optimal model of skill mix and the patient mortality rate remains to be discovered. Objectives: This review aimed to explore the relationship between the skill mix model and patient mortality rate in acute care hospitals. Data Sources: A systematic search of the PubMed, Web of Science, Embase, and Cochrane Library databases and researchers retrieved studies published between January 1986 and March 2022. Review methods: Two independent reviewers screened the titles and abstracts based on selection criteria, extracted the data, and performed critical appraisals using the STROBE checklist of each included study. The studies focused on adult patients in acute care hospitals, and the skill mix model and patient mortality rate were included in the analysis. Results: Six included studies were conducted in the USA, Canada, Italy, Taiwan, and European countries (Belgium, England, Finland, Ireland, Spain, and Switzerland), including patients in medical, surgical, and intensive care units. There were both nurses and nursing assistants in their skill mix team. This main finding is that three studies (324,592 participants) show evidence of fewer mortality rates associated with hospitals with a higher percentage of registered nurse staff (range percentage of registered nurse staff 36.1%-100%), but three articles (1,122,270 participants) did not find the same result (range of percentage of registered nurse staff 46%-96%). However, based on appraisal findings, those showing a significant association all meet good quality standards, but only one-third of their counterparts. Conclusions: In light of the limited amount and quality of published research in this review, it is prudent to treat the findings with caution. Although the evidence is not insufficient certainty to draw conclusions about the relationship between nurse staffing level and patients' mortality, this review lights the direction of relevant studies in the future. The limitation of this article is the variation in skill mix models among countries and institutions, making it impossible to do a meta-analysis to compare them further.

Keywords: nurse staffing level, nursing assistants, mortality, skill mix

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Authors: Md Habibur Rahman, Jaeho Kim

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Efficient process scheduling is a crucial factor in ensuring optimal system performance and resource utilization in computer systems. While various algorithms have been proposed over the years, there are still limitations to their effectiveness. This paper introduces a new Wait-Optimized Scheduler (WOS) algorithm that aims to minimize process waiting time by dividing them into two layers and considering both process time and waiting time. The WOS algorithm is non-preemptive and prioritizes processes with the shortest WOS. In the first layer, each process runs for a predetermined duration, and any unfinished process is subsequently moved to the second layer, resulting in a decrease in response time. Whenever the first layer is free or the number of processes in the second layer is twice that of the first layer, the algorithm sorts all the processes in the second layer based on their remaining time minus waiting time and sends one process to the first layer to run. This ensures that all processes eventually run, optimizing waiting time. To evaluate the performance of the WOS algorithm, we conducted experiments comparing its performance with traditional scheduling algorithms such as First-Come-First-Serve (FCFS) and Shortest-Job-First (SJF). The results showed that the WOS algorithm outperformed the traditional algorithms in reducing the waiting time of processes, particularly in scenarios with a large number of short tasks with long wait times. Our study highlights the effectiveness of the WOS algorithm in improving process scheduling efficiency in computer systems. By reducing process waiting time, the WOS algorithm can improve system performance and resource utilization. The findings of this study provide valuable insights for researchers and practitioners in developing and implementing efficient process scheduling algorithms.

Keywords: process scheduling, wait-optimized scheduler, response time, non-preemptive, waiting time, traditional scheduling algorithms, first-come-first-serve, shortest-job-first, system performance, resource utilization

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Authors: T. Tommasi, E. Batuecas, G. Mancini, G. Saracco, D. Fino

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Extra virgin olive-oil (EVO) production is an important economic activity for several countries, especially in the Mediterranean area such as Spain, Italy, Greece and Tunisia. The two major by-products from olive oil production, solid-liquid Olive Pomace (OP) and the Olive Mill Waste Waters (OMWW), are still mainly disposed on soil, in spite of the existence of legislation which already limits this practice. The present study compares the environmental impacts associated with two different scenarios for the management of waste from olive oil production through a comparative Life Cycle Assessment (LCA). The two alternative scenarios are: (I) Anaerobic Digestion and (II) current Disposal on soil. The analysis was performed through SimaPro software and the assessment of the impact categories was based on International Life Cycle Data and Cumulative Energy Demand methods. Both the scenarios are mostly related to the cultivation and harvesting phase and are highly dependent on the irrigation practice and related energy demand. Results from the present study clearly show that as the waste disposal on soil causes the worst environmental performance of all the impact categories here considered. Important environmental benefits have been identified when anaerobic digestion is instead chosen as the final treatment. It was consequently demonstrated that anaerobic digestion should be considered a feasible alternative for olive mills, to produce biogas from common olive oil residues, reducing the environmental burden and adding value to the olive oil production chain.

Keywords: anaerobic digestion, waste management, agro-food waste, biogas

Procedia PDF Downloads 144

Authors: W. S. Lawal, T. Akande

Abstract:

Abstract— Four (4) difference methods were employed to detoxify Jatropha carcas, they were physical method (it include soaking and sun drying) Chemical (the use of methylated sprit, hexane and methane). Biological (the use of Aspergillus niger and then sundry for 7days and then Bacillus lichiformis) and Combined method (the combination of chemical and biological methods). Phobol esther analysis was carried out after the detoxification methods and it was found that the combined method is better off (P<0.05). Detoxified Jatropha from each of this methods was sundry and grinded for easy inclusion into poultry feed, detoxified jatropha was included at 0%, 0.5%, 1%, 2%, 3%, 4%, and 5% but the combined method was increased up to 7% because the birds were able to tolerate it, the 0% was the control experiment. 405 day old broiler chicks was used to test the effect of detoxified Jatropha carcas on their performance, there are 5birds per treatment and there are 3 replicates, the experiment lasted for 8weeks,highest number of mortality was obtained in physical method, birds in chemical method tolerated up to 3% Jatropha carcas, biological method is better, as birds there were comfortable at 5% but the best of them is combined method the birds did very well at 7% as there were less mortality and highest weight gain was achieved here (P<0.05) and it was recommended.

Keywords: phobol esther, inclusion level, tolerance level, Jatropha carcas

Procedia PDF Downloads 400

Authors: Saheb Yousefi, Kim T. Zebehazy, Parviz Sharifi Daramadi, Tahereh Najafi Fard, Kevin Murfitt

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Context: Children with visual impairments often face challenges in their cognitive, motor, and social development. Sensory-motor and spatial perception therapies can be beneficial for these children, but many existing programs only focus on a limited set of therapies. This study aims to investigate the effectiveness of a rehabilitation program for sensory- motor and spatial perception in reducing the fear of mobility in visually impaired children. Research Aim: The aim of this study is to determine if a rehabilitation program based on parent-child interaction can reduce the fear of mobility in visually impaired children. Methodology: This study uses a semi-experimental approach with an uneven control group design. Visually impaired children aged 10 to 14 and their parents from the Board of the Blind and Visually Impaired in Tehran Province were included in the study. The sample was divided into experimental and control groups, with a total of 30 participants. The experimental group participated in a rehabilitation program for sensory-motor and spatial perception based on parent-child interaction, while the control group did not receive this intervention. Data was collected using questionnaires on transportation issues and analyzed using multivariate and univariate mixed analysis of variance tests. Findings: The analysis of the data showed that the fear of movement was significantly improved in the experimental group compared to the control group after the intervention. Theoretical Importance: This study highlights the effectiveness of a rehabilitation program for sensory- motor and spatial perception based on parent-child interaction in reducing the fear of mobility in visually impaired children. It contributes to the existing knowledge by demonstrating the positive impact of this type of intervention on the cognitive, motor, and social development of these children. Data Collection and Analysis Procedures: Data was collected through the use of questionnaires administered to the children before and after the intervention. The data was analyzed using multivariate and univariate mixed analysis of variance tests to examine the effects of the rehabilitation program. Questions Addressed: This study addresses the question of whether a rehabilitation program based on parent-child interaction can reduce the fear of mobility in visually impaired children. Conclusion: The findings of this study support the effectiveness of the sensory-motor and spatial perception rehabilitation program based on parent-child interaction in reducing the fear of movement in visually impaired children. This intervention can be considered as a suitable method to enhance the fear of mobility in these children.

Keywords: vision impairment, sensory-motor rehabilitation, space perception, parent-child interaction, fear of movement.

Procedia PDF Downloads 56

Authors: C. C. Kruger, P. Van Tonder

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Concrete deteriorates over time and the deterioration can be escalated due to multiple factors. When deteriorations are beneath the concrete’s surface, they could be unknown, even more so when they are located at high elevations. Establishing the severity of such defects could prove difficult and therefore the need to find efficient, safe and economical methods to find these defects becomes ever more important. Current methods using thermography to find defects require equipment such as scaffolding to reach these higher elevations. This could become time- consuming and costly. The risks involved with personnel scaffold or abseil to such heights are high. Accordingly, by combining the technologies of a thermal camera and a Remotely Piloted Aerial System it could be used to find better diagnostic methods. The data could then be constructed into a 3D thermal model to easy representation of the results

Keywords: concrete, infrared thermography, 3D thermal models, diagnostic

Procedia PDF Downloads 167

Authors: Dionisio Andujar, Juan lópez-Correa, Hugo Moreno, Angela Ri

Abstract:

The increased number of weeds in tomato crops highly lower yields. Weed identification with the aim of machine learning is important to carry out site-specific control. The last advances in computer vision are a powerful tool to face the problem. The analysis of RGB (Red, Green, Blue) images through Artificial Neural Networks had been rapidly developed in the past few years, providing new methods for weed classification. The development of the algorithms for crop and weed species classification looks for a real-time classification system using Object Detection algorithms based on Convolutional Neural Networks. The site study was located in commercial corn fields. The classification system has been tested. The procedure can detect and classify weed seedlings in tomato fields. The input to the Neural Network was a set of 10,000 RGB images with a natural infestation of Cyperus rotundus l., Echinochloa crus galli L., Setaria italica L., Portulaca oeracea L., and Solanum nigrum L. The validation process was done with a random selection of RGB images containing the aforementioned species. The mean average precision (mAP) was established as the metric for object detection. The results showed agreements higher than 95 %. The system will provide the input for an online spraying system. Thus, this work plays an important role in Site Specific Weed Management by reducing herbicide use in a single step.

Keywords: deep learning, object detection, cnn, tomato, weeds

Procedia PDF Downloads 101

Authors: S. Abbasi, M. R. Hadian, M. Abdolvahab, M. Jalili, S. H. Jalaei

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Background: Rehabilitation treatments have significant role in reducing the disabilities of Cerebro Vascular Accident (CVA). Due to great role of upper limb in the function of individuals particularly in Activity of Daily Living and the effect of stability of shoulder girdle on hand function, the aim of this study was to study the effects of Progressive Resistive Exercise on shoulder extensor and abductor muscles isometric strengths in adult hemiplegic. Methods: 17 adult hemiplegics patients (50-70 yrs., mean 60/52, SD7/22); with RT side dominancy and 6 months after stroke, participated in this study. All procedures were approved by ethical committee of TUMS and written consents were also taken. Patients were familiarized with the procedure and shoulder extensor and abductor muscles isometric strengths were measured by dynamometer. Results: according to result to our study, shoulder extensor and abductor muscles isometric strengths showed Significant differences between mean scores of pre and post intervention (P<0/05). Progressive Resistive Exercise improved 34% shoulder extensor muscles isometric strength and 27% shoulder abductor muscle isometric strength. Conclusion: Results of our research showed that progressive resistive exercise approach is a useful method for increasing the isometric strength of shoulder extensor and abductor muscles. Therefore, it might be concluded that improvement of strength of shoulder muscles could result in stability in shoulder girdle and consequently might effect on hand function in hemiplegic patients.

Keywords: shoulder extensor muscles isometric strength, shoulder abductor muscles isometric strength, hemiplegic, physical therapy

Procedia PDF Downloads 314

Authors: Gustavo G. Shimamoto, Matthieu Tubino

Abstract:

The characterization and the quality of biodiesel samples are checked by determining several parameters. Considering a large number of analysis to be performed, as well as the disadvantages of the use of toxic solvents and waste generation, multivariate calibration is suggested to reduce the number of tests. In this work, hydrogen nuclear magnetic resonance (1H NMR) spectra were used to build multivariate models, from partial least squares (PLS) regression, in order to determine simultaneously six important characterizing and/or quality parameters of biodiesels: density at 20 ºC, kinematic viscosity at 40 ºC, iodine value, acid number, oxidative stability, and water content. Biodiesels from twelve different oils sources were used in this study: babassu, brown flaxseed, canola, corn, cottonseed, macauba almond, microalgae, palm kernel, residual frying, sesame, soybean, and sunflower. 1H NMR reflects the structures of the compounds present in biodiesel samples and showed suitable correlations with the six parameters. The PLS models were constructed with latent variables between 5 and 7, the obtained values of r(cal) and r(val) were greater than 0.994 and 0.989, respectively. In addition, the models were considered suitable to predict all the six parameters for external samples, taking into account the analytical speed to perform it. Thus, the alliance between 1H NMR and PLS showed to be appropriate to characterize and evaluate the quality of biodiesels, reducing significantly analysis time, the consumption of reagents/solvents, and waste generation. Therefore, the proposed methods can be considered to adhere to the principles of green chemistry.

Keywords: biodiesel, multivariate calibration, nuclear magnetic resonance, quality parameters

Procedia PDF Downloads 536