Search results for: overall equipment effectiveness

Authors: Sarai Guerrero, Lijia Liu

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Zinc gallogermanate (ZGGO) is a persistent phosphor that can emit in the near infrared (NIR) range once dopped with Cr³⁺ enabling its use for in-vivo deep-tissue bio-imaging. Such a property also allows for its application in cancer diagnosis and therapy. Given this, work into developing a synthetic procedure that can be done using common laboratory instruments and equipment as well as understanding ZGGO overall, is in demand. However, the ZGGO nanoparticles must have a size compatible for cell intake to occur while still maintaining sufficient photoluminescence. The nanoparticle must also be made biocompatible by functionalizing the surface for hydrophilic solubility and for high particle uniformity in the final product. Additionally, most research is completed on doped ZGGO, leaving a gap in understanding the base form of ZGGO. It also leaves a gap in understanding how doping affects the synthesis of ZGGO. In this work, the first step of optimizing the particle size via the crystalline size of ZGGO was done with undoped ZGGO using the organic acid, oleic acid (OA) for organic ligand-assisted biphasic hydrothermal synthesis. The effects of this synthesis procedure on ZGGO’s crystallinity were evaluated using Powder X-Ray Diffraction (PXRD). OA was selected as the capping ligand as experiments have shown it beneficial in synthesizing sub-10 nm zinc gallate (ZGO) nanoparticles as well as palladium nanocrystals and magnetite (Fe₃O₄) nanoparticles. Later it is possible to substitute OA with a different ligand allowing for hydrophilic solubility. Attenuated Total Reflection Fourier-Transform Infrared (ATR-FTIR) was used to investigate the surface of the nanoparticle to investigate and verify that OA had capped the nanoparticle. PXRD results showed that using this procedure led to improved crystallinity, comparable to the high-purity reagents used on the ZGGO nanoparticles. There was also a change in the crystalline size of the ZGGO nanoparticles. ATR-FTIR showed that once capped ZGGO cannot be annealed as doing so will affect the OA. These results point to this new procedure positively affecting the crystallinity of ZGGO nanoparticles. There are also repeatable implying the procedure is a reliable source of highly crystalline ZGGO nanoparticles. With this completed, the next step will be working on substituting the OA with a hydrophilic ligand. As these ligands effect the solubility of the nanoparticle as well as the pH that the nanoparticles can dissolve in, further research is needed to verify which ligand is best suited for preparing ZGGO for bio-imaging.

Keywords: biphasic hydrothermal synthesis, crystallinity, oleic acid, zinc gallogermanate

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Authors: Qing Wu, Fei-Yan Li, Heng-Chang Zhang

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Multitask learning support vector machines (SVMs) have recently attracted increasing research attention. Given several related tasks, the single-task learning methods trains each task separately and ignore the inner cross-relationship among tasks. However, multitask learning can capture the correlation information among tasks and achieve better performance by training all tasks simultaneously. In addition, the asymmetric squared loss function can better improve the generalization ability of the models on the most asymmetric distributed data. In this paper, we first make two assumptions on the relatedness among tasks and propose two multitask learning proximal support vector machine algorithms, named MTL-a-PSVM and EMTL-a-PSVM, respectively. MTL-a-PSVM seeks a trade-off between the maximum expectile distance for each task model and the closeness of each task model to the general model. As an extension of the MTL-a-PSVM, EMTL-a-PSVM can select appropriate kernel functions for shared information and private information. Besides, two corresponding special cases named MTL-PSVM and EMTLPSVM are proposed by analyzing the asymmetric squared loss function, which can be easily implemented by solving linear systems. Experimental analysis of three classification datasets demonstrates the effectiveness and superiority of our proposed multitask learning algorithms.

Keywords: multitask learning, asymmetric squared loss, EMTL-a-PSVM, classification

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Authors: Deepak Chaudhary

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This paper attempts to analyze the leadership phenomena, its challenges, and prospects in Nepal. Literature is reviewed rigorously to explain the theoretical and empirical aspects of leadership. Besides, In-depth interviews with three national leaders were interviewed to know the challenges regarding polity and leadership. Similarly, a survey among 434 households in Katahari rural municipality and Godavari municipality was carried out to assess people’s perceptions of leaders. Leadership is normally pronounced in the wake of the success of the country’s development or crisis management. Real leaders are those who can avert any crisis successfully and proceed with the country in a progressive and normal way. Leadership’s working style can create a favorable institutional environment in the public institution that can lead development programs successfully. However, the literature suggests that Nepal is still struggling towards modernization in comparison to some East-Asian countries whose socio-economic situation was more similar in the 1950s. Similarly, Nepal has been facing several social movements after the 1990s, which resulted in a new political system, though the performance of the public institution has been a question and it goes to the leadership’s role. The poor tackling of natural disasters like earthquakes flooding, and pandemics raises the questions of the leadership’s role to some extent. The government of Nepal's record of developmental expenditures is dismal. However, leadership has been the central part of people, community, and country, and hence, the study of leadership phenomena in relation to a country’s well-being is intrinsic.

Keywords: challenges, leadership, institutionalization, effectiveness

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Authors: Kai Yip Michael Tsang

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Science writing has played a crucial part in science assessments. This paper reports a study in an area that has received little research attention – how Language across the Curriculum (LAC, i.e. science language and literacy) learning activities in science lessons can increase the science knowledge development of English as a foreign language (EFL) students in Hong Kong. The data comes from a school-based interventional study in chemistry classrooms, with written data from questionnaires, assessments and teachers’ logs and verbal data from interviews and classroom observations. The effectiveness of the LAC teaching and learning activities in various chemistry classrooms were compared and evaluated, with discussion of some implications. Students in the treatment group with lower achieving students received LAC learning and teaching activities while students in the control group with higher achieving students received conventional learning and teaching activities. After the study, they performed better in control group in formative assessments. Moreover, they had a better attitude to learning chemistry content with a richer language support. The paper concludes that LAC teaching and learning activities yielded positive learning outcomes among chemistry learners with low English ability.

Keywords: science learning and teaching, content and language integrated learning, language across the curriculum, English as a foreign language

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Authors: Shu-Hui Jan, Shih-Ping Ho, Hui-Ping Tserng

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Construction knowledge can be referred to and reused among involved project managers and job-site engineers to alleviate problems on a construction job-site and reduce the time and cost of solving problems related to constructability. This paper proposes a new methodology to provide sharing of construction knowledge by using the Building Information Modeling (BIM) approach. The main characteristics of BIM include illustrating 3D CAD-based presentations and keeping information in a digital format, and facilitation of easy updating and transfer of information in the 3D BIM environment. Using the BIM approach, project managers and engineers can gain knowledge related to 3D BIM and obtain feedback provided by job-site engineers for future reference. This study addresses the application of knowledge sharing management in the construction phase of construction projects and proposes a BIM-based Knowledge Sharing Management (BIMKSM) system for project managers and engineers. The BIMKSM system is then applied in a selected case study of a construction project in Taiwan to verify the proposed methodology and demonstrate the effectiveness of sharing knowledge in the BIM environment. The combined results demonstrate that the BIMKSM system can be used as a visual BIM-based knowledge sharing management platform by utilizing the BIM approach and web technology.

Keywords: construction knowledge management, building information modeling, project management, web-based information system

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Authors: Henry R. Troy

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Corpora are becoming more prevalent in the language classroom, especially in the development of dictionaries and course materials. Nevertheless, corpora are still perceived by many educators as difficult to use directly in the classroom, a process which is also known as “data-driven learning” (DDL). Action research has been identified as a method by which DDL’s efficiency can be increased, but it is also an approach few studies on DDL have employed. Studies into the effectiveness of DDL in language education in Japan are also rare, and investigations focused more on student and teacher reactions rather than pre and post-test scores are rarer still. This study investigates the student and teacher reactions to the use of SkELL, a free online corpus designed to be user-friendly, for vocabulary learning at a university in Japan. Action research is utilized to refine the teaching methodology, with changes to the method based on student and teacher feedback received via surveys submitted after each of the four implementations of DDL. After some training, the students used tablets to study the target vocabulary autonomously in pairs and groups, with the teacher acting as facilitator. The results show that the students enjoyed using SkELL and felt it was effective for vocabulary learning, while the teaching methodology grew in efficiency throughout the course. These findings suggest that action research can be a successful method for increasing the efficacy of DDL in the language classroom, especially with teachers and students who are new to the practice.

Keywords: action research, corpus linguistics, data-driven learning, vocabulary learning

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Authors: Jiamin Huang, Shuliang Gui, Zengshan Tian, Fei Yan, Xiaodong Wu

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In recent years, with the rapid development of radio frequency technology, the differences between radar sensing and wireless communication in terms of receiving and sending channels, signal processing, data management and control are gradually shrinking. There has been a trend of integrated communication radar sensing. However, most of the existing radar imaging technologies based on communication signals are combined with synthetic aperture radar (SAR) imaging, which does not conform to the practical application case of the integration of communication and radar. Therefore, in this paper proposes a high-precision imaging method using communication signals based on the imaging mechanism of inverse synthetic aperture radar (ISAR) imaging. This method makes full use of the structural characteristics of the orthogonal frequency division multiplexing (OFDM) signal, so the sidelobe effect in distance compression is removed and combines radon transform and Fractional Fourier Transform (FrFT) parameter estimation methods to achieve ISAR imaging of non-cooperative targets. The simulation experiment and measured results verify the feasibility and effectiveness of the method, and prove its broad application prospects in the field of intelligent transportation.

Keywords: integration of communication and radar, OFDM, radon, FrFT, ISAR

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Authors: Shirazu Issahaku, Isaac Kwesi Acquah, Simon Mensah Amoh, George Nunoo

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Introduction: Diagnostic Reference Levels are important indicators for monitoring and optimizing protocol and procedure in medical imaging between facilities and equipment. This helps to evaluate whether, in routine clinical conditions, the median value obtained for a representative group of patients within an agreed range from a specified procedure is unusually high or low for that procedure. This study aimed to propose Diagnostic Reference Levels for Computed Tomography examination of the most common routine examination of the head, chest and abdominal pelvis regions at the University of Ghana Medical Centre. Methods: The Diagnostic Reference Levels were determined based on the investigation of the most common routine examinations, including head Computed Tomography examination with and without contrast, abdominopelvic Computed Tomography examination with and without contrast, and chest Computed Tomography examination without contrast. The study was based on two dose indicators: the volumetric Computed Tomography Dose Index and Dose-Length Product. Results: The estimated median distribution for head Computed Tomography with contrast for volumetric-Computed Tomography dose index and Dose-Length Product were 38.33 mGy and 829.35 mGy.cm, while without contrast, were 38.90 mGy and 860.90 mGy.cm respectively. For an abdominopelvic Computed Tomography examination with contrast, the estimated volumetric-Computed Tomography dose index and Dose-Length Product values were 40.19 mGy and 2096.60 mGy.cm. In the absence of contrast, the calculated values were 14.65 mGy and 800.40 mGy.cm, respectively. Additionally, for chest Computed Tomography examination, the estimated values were 12.75 mGy and 423.95 mGy.cm for volumetric-Computed Tomography dose index and Dose-Length Product, respectively. These median values represent the proposed diagnostic reference values of the head, chest, and abdominal pelvis regions. Conclusions: The proposed Diagnostic Reference Level is comparable to the recommended International Atomic Energy Agency and International Commission Radiation Protection Publication 135 and other regional published data by the European Commission and Regional National Diagnostic Reference Level in Africa. These reference levels will serve as benchmarks to guide clinicians in optimizing radiation dose levels while ensuring accurate diagnostic image quality at the facility.

Keywords: diagnostic reference levels, computed tomography dose index, computed tomography, radiation exposure, dose-length product, radiation protection

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Authors: Riddhiman Sherlekar, Umang Paladia, Rachit Desai, Yash Patel

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The competitive scenario of the oil and gas market is a challenge for today’s plant designers to achieve designs that meet client expectations with shrinking budgets, safety requirements, and operating flexibility. Natural Gas Liquids have three main industrial uses. They can be used as fuels, or as petrochemical feedstock or as refinery blends that can be further processed and sold as straight run cuts, such as naphtha, kerosene and gas oil. NGL extraction is not a chemical reaction. It involves the separation of heavier hydrocarbons from the main gas stream through pressure as temperature reduction, which depending upon the degree of NGL extraction may involve cryogenic process. Previous technologies i.e. short cycle dry desiccant absorption, Joule-Thompson or Low temperature refrigeration, lean oil absorption have been giving results of only 40 to 45% ethane recoveries, which were unsatisfying depending upon the current scenario of down turn market. Here new technology has been suggested for boosting up the recoveries of ethane+ up to 95% and up to 99% for propane+ components. Cryogenic plants provide reboiling to demethanizers by using part of inlet feed gas, or inlet feed split. If the two stream temperatures are not similar, there is lost work in the mixing operation unless the designer has access to some proprietary design. The concept introduced in this process consists of reboiling the demethanizer with the residue gas, or residue gas split. The innovation of this process is that it does not use the typical inlet gas feed split type of flow arrangement to reboil the demethanizer or deethanizer column, but instead uses an open heat pump scheme to that effect. The residue gas compressor provides the heat pump effect. The heat pump stream is then further cooled and entered in the top section of the column as a cold reflux. Because of the nature of this design, this process offers the opportunity to operate at full ethane rejection or recovery. The scheme is also very adaptable to revamp existing facilities. This advancement can be proven not only in enhancing the results but also provides operational flexibility, optimize heat exchange, introduces equipment cost reduction, opens a future for the innovative designs while keeping execution costs low.

Keywords: deethanizer, demethanizer, residue gas, NGL

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Authors: Shreya Goyal

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The study aims to build user-friendly software to understand patient arrival patterns and compute the number of potential patients who will visit a particular health facility for a given period by using a machine learning algorithm. The underlying machine learning algorithm used in this study is the Support Vector Machine (SVM). Accurate prediction of patient arrival allows hospitals to operate more effectively, providing timely and efficient care while optimizing resources and improving patient experience. It allows for better allocation of staff, equipment, and other resources. If there's a projected surge in patients, additional staff or resources can be allocated to handle the influx, preventing bottlenecks or delays in care. Understanding patient arrival patterns can also help streamline processes to minimize waiting times for patients and ensure timely access to care for patients in need. Another big advantage of using this software is adhering to strict data protection regulations such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States as the hospital will not have to share the data with any third party or upload it to the cloud because the software can read data locally from the machine. The data needs to be arranged in. a particular format and the software will be able to read the data and provide meaningful output. Using software that operates locally can facilitate compliance with these regulations by minimizing data exposure. Keeping patient data within the hospital's local systems reduces the risk of unauthorized access or breaches associated with transmitting data over networks or storing it in external servers. This can help maintain the confidentiality and integrity of sensitive patient information. Historical patient data is used in this study. The input variables used to train the model include patient age, time of day, day of the week, seasonal variations, and local events. The algorithm uses a Supervised learning method to optimize the objective function and find the global minima. The algorithm stores the values of the local minima after each iteration and at the end compares all the local minima to find the global minima. The strength of this study is the transfer function used to calculate the number of patients. The model has an output accuracy of >95%. The method proposed in this study could be used for better management planning of personnel and medical resources.

Keywords: machine learning, SVM, HIPAA, data

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Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures

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Authors: Naser Shagerdi Esmaeli, Mohsen Hamidpour

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Purposes: The activation of coagulation in patients with cancer contributes significantly to morbidity and mortality rates and may play a fundamental role in the host response to growing tumor’s. Patients with cancer are clearly at high risk for the development of venous thromboembolism (VTE), particularly during chemotherapy and surgery. This situation is aggravated by the use of venous access catheters and possibly growth factors. Methods: Data derived from large, randomized, controlled trials have been used to determine the true incidence of this complication of cancer and its treatment. The incidence based on the analyses of these randomized controlled trials varies from 1% for limited stage patients with breast cancer treated with tamoxifen to 60% for patients with any type of cancer who are subjected to orthopedic surgery and do not receive prophylactic therapy. Results: In view of the morbidity and mortality attributable to VTE in cancer, widespread utilization of prophylactic anticoagulation therapy, which has proven safe and effective in a variety of situations, should be considered. While migratory thrombophlebitis is a clear indicator of an underlying neoplasm, the risk of cancer in patients with the more typical form of VTE has been the subject of intense debate over recent years. Conclusion: Some investigators have suggested that the relative risk of being diagnosed with occult cancer within six months of an episode of VTE (particularly recurrent VTE) could be up to 10-fold. However, the cost-effectiveness of aggressive screening for cancer in patients with VTE has not yet been defined adequately.

Keywords: venous thromboembolism, malignancy, cancer, tumor, heparin

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Authors: Priyanka Kalra

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Background: Complementary and alternative medicine (CAM) includes various practices like Ayurveda, Yoga & Meditation Acupressure Acupuncture and Reiki. These practices are frequently used by patients with spinal cord injury (SCI). They have shown effectiveness in the management of pain and stress consequently improving overall quality of life post injury. Objective: The goals of the present case series were to evaluate the feasibility of 1) Using of Ayurvedic herbal oil massages in shoulder pain management, 2) Using yoga & meditation on managing the stress in spinal cord injury. Methodology: 15 SCI cases with muscular pain around shoulder were treated with Ayurvedic herbal oil massage for 10 days in CAM Department. Each session consisted of 30 min oil massage followed by 10 min hot towel fomentation. The patients continued regular therapy medications along with CAM. Another 15 SCI cases were treated with yoga and meditation for 15 days 30 min yoga (20 min Asana+ 10 min Pranayam + 15 min Meditation) in isolated yoga room of CAM department. Results: On the VAS scale the patients reported a reduction in their pain score by 70 %. On the PSS scale, the patients reported a reduction in their stress score by 80 %. Conclusion: These case series may encourage more people to explore CAM therapies.

Keywords: spinal cord injury, Ayurveda, complementary and alternative medicine, yoga, meditation

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Authors: Min-Chih Yang, Shih-Jen Feng, Bo-Tsang Li

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The concept of “Brownfield” has been developed for nearly 35 years since it was put forward in 《Comprehensive Environmental Response, Compensation, and Liability Act, CERCLA》of USA in 1980 for solving the problem of soil contamination of those old industrial lands, and later, many countries have put forward relevant policies and researches continuously. But the related concept in Taiwan, a country has developed its industry for 60 years, is still in its infancy. This leads to the slow development of Brownfield related research and policy in Taiwan. When it comes to build the foundation of Brownfield development, we have to depend on the related experience and research of other countries. They are four aspects about Brownfield: 1. Contaminated Land; 2. Derelict Land; 3. Vacant Land; 4. Previously Development Land. This study will focus on and deeply investigate the Vacant land and contaminated land. The subject of this study is Formosa Chemicals & Fibre Corporation, Changhua branch in Taiwan. It has been operating for nearly 50 years and contributing a lot to the local economy. But under the influence of the toxic waste and sewage which was drained regularly or occasionally out from the factory, the environment has been destroyed seriously. There are three factors of pollution: 1. environmental toxicants, carbon disulfide, released from producing processes and volatile gases which is hard to monitor; 2. Waste and exhaust gas leakage caused by outdated equipment; 3. the wastewater discharge has seriously damage the ecological environment of the Dadu river estuary. Because of all these bad influences, the factory has been closed nowadays and moved to other places to spare the opportunities for the contaminated lands to re-develop. So we collect information about related Brownfield management experience and policies in different countries as background information to investigate the current Taiwanese Brownfield redevelopment issues and built the environmental assessment framework for it. We hope that we can set the environmental assessment indexes for Formosa Chemicals & Fibre Corporation, Changhua branch according to the framework. By investigating the theory and environmental pollution factors, we will carry out deep analysis and expert questionnaire to set those indexes and prove a sample in Taiwan for Brownfield redevelopment and remediation in the future.

Keywords: brownfield, industrial land, redevelopment, assessment index

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Authors: Asim Qureshi, R. S. Jangid

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Seismic response control of structures is generally achieved by using control devices which either dissipate the input energy or modify the dynamic properties of structure.In this paper, the response of a 20-storey benchmark building supplemented by viscous dampers and Negative Stiffness Device (NSD) is assessed by numerical simulations using the Newmark-beta method. True negative stiffness is an adaptive passive device which assists the motion unlike positive stiffness. The structure used in this study is subjected to four standard ground motions varying from moderate to severe, near fault to far-field earthquakes. The objective of the present study is to show the effectiveness of the adaptive negative stiffness device (NSD and passive dampers together) relative to passive dampers alone. This is done by comparing the responses of the above uncontrolled structure (i.e., without any device) with the structure having passive dampers only and also with the structure supplemented with adaptive negative stiffness device. Various performance indices, top floor displacement, top floor acceleration and inter-storey drifts are used as comparison parameters. It is found that NSD together with passive dampers is quite effective in reducing the response of aforementioned structure relative to structure without any device or passive dampers only. Base shear and acceleration is reduced significantly by incorporating NSD at the cost of increased inter-storey drifts which can be compensated using the passive dampers.

Keywords: adaptive negative stiffness device, apparent yielding, NSD, passive dampers

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Authors: Hanqing Yang, Xiang Meng, Qi Li, Weirong Chen

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The SOC (state of charge) based droop control has limitations on the load power sharing among different energy storage units, due to the line impedance. In this paper, a distributed control strategy for dispersed energy storage units in the DC microgrid based on discrete consensus is proposed. Firstly, a sparse information communication network is built. Thus, local controllers can communicate with its neighbors using voltage, current and SOC information. An average voltage of grid can be evaluated to compensate voltage offset by droop control, and an objective virtual resistance fulfilling above requirement can be dynamically calculated to distribute load power according to the SOC of the energy storage units. Then, the stability of the whole system and influence of communication delay are analyzed. It can be concluded that this control strategy can improve the robustness and flexibility, because of having no center controller. Finally, a model of DC microgrid with dispersed energy storage units and loads is built, the discrete distributed algorithm is established and communication protocol is developed. The co-simulation between Matlab/Simulink and JADE (Java agent development framework) has verified the effectiveness of proposed control strategy.

Keywords: dispersed energy storage units, discrete consensus algorithm, state of charge, communication delay

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Authors: Omid Kalatpour, Mohammadreza Ajdari

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This article studied the possible causes of human error-induced incidents in the petrochemical industry maintenance activities by using Human Factors Analysis and Classification System (HFACS). The purpose of the study was anticipating and identifying these causes and proposing corrective and preventive actions. Maintenance department in a petrochemical company was selected for research. A checklist of human error-induced incidents was developed based on four HFACS main levels and nineteen sub-groups. Hierarchical task analysis (HTA) technique was used to identify maintenance activities and tasks. The main causes of possible incidents were identified by checklist and recorded. Corrective and preventive actions were defined depending on priority. Analyzing the worksheets of 444 activities in four levels of HFACS showed 37.6% of the causes were at the level of unsafe actions, 27.5% at the level of unsafe supervision, 20.9% at the level of preconditions for unsafe acts and 14% of the causes were at the level of organizational effects. The HFACS sub-groups showed errors (24.36%) inadequate supervision (14.89%) and violations (13.26%) with the most frequency. According to findings of this study, increasing the training effectiveness of operators and supervision improvement respectively are the most important measures in decreasing the human error-induced incidents in petrochemical industry maintenance.

Keywords: human error, petrochemical industry, maintenance, HFACS

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Authors: Abdmohammad Mousavi, Mohsen Shams, Mehdi Akbartabar Toori, Ali Mousavizadeh, Mohammad Ali Morowatisharifabad

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The effectiveness of Transtheoretical Model (TTM) on nutritional behavior change and lose weight has been subject to questions by some studies. The objective of this study was to determine the effect of nutritional behavior change and lose weight interventions based on TTM in obese and overweight women. This experimental study that was a 8 months trial nutritional behavior change and weight loss program based on TTM with two conditions and pre–post intervention measurements weight mean. 299 obese and overweight 20-44 years old women were selected from two health centers include training (142) and control (157) groups in Yasuj, a city in south west of Iran. Data were analyzed using paired T-test and One–Way ANOVA tests. In baseline, adherence with nutritional healthy behavior in training group(9.4%) compare with control(38.8%) were different significantly(p=.003), weight mean of training(Mean=78.02 kg, SD=11.67) compared with control group(Mean=77.23 kg, SD=10.25) were not (P=.66). In post test, adherence with nutritional healthy behavior in training group(70.1%) compare with control (37.4%) were different significantly (p=.000), weight mean of training (Mean=74.65 kg, SD=10.93, p=.000) compare with pre test were different significantly and control (Mean=77.43 kg, SD=10.43, p=.411) were not. The training group has lost 3.37 kg weight, whereas the control group has increased .2 kg weight. These results supported the applicability of the TTM for women weight lose intervention.

Keywords: nutritional behavior, Transtheoretical Model, weight lose, women

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Authors: Anjian Chen, Joseph C. Chen

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This paper studies a case where the targeted surface roughness of fused deposition modeling (FDM) additive manufacturing process is improved. The process is designing to reduce or eliminate the defects and improve the process capability index Cp and Cpk for an FDM additive manufacturing process. The baseline Cp is 0.274 and Cpk is 0.654. This research utilizes the Taguchi methodology, to eliminate defects and improve the process. The Taguchi method is used to optimize the additive manufacturing process and printing parameters that affect the targeted surface roughness of FDM additive manufacturing. The Taguchi L9 orthogonal array is used to organize the parameters' (four controllable parameters and one non-controllable parameter) effectiveness on the FDM additive manufacturing process. The four controllable parameters are nozzle temperature [°C], layer thickness [mm], nozzle speed [mm/s], and extruder speed [%]. The non-controllable parameter is the environmental temperature [°C]. After the optimization of the parameters, a confirmation print was printed to prove that the results can reduce the amount of defects and improve the process capability index Cp from 0.274 to 1.605 and the Cpk from 0.654 to 1.233 for the FDM additive manufacturing process. The final results confirmed that the Taguchi methodology is sufficient to improve the surface roughness of FDM additive manufacturing process.

Keywords: additive manufacturing, fused deposition modeling, surface roughness, six-sigma, Taguchi method, 3D printing

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Authors: Linyao Qiu, Zhiqiang Du

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As the rapid development of urbanization, economic developments, and steady population growth in China, the widespread devastation, economic damages, and loss of human lives caused by numerous forms of natural disasters are becoming increasingly serious every year. Disaster management requires available and effective cooperation of different roles and organizations in whole process including mitigation, preparedness, response and recovery. Due to the imbalance of regional development in China, the disaster management capabilities of national and provincial disaster reduction centers are uneven. When an undeveloped area suffers from disaster, neither local reduction department could get first-hand information like high-resolution remote sensing images from satellites and aircrafts independently, nor sharing mechanism is provided for the department to access to data resources deployed in other place directly. Most existing disaster management systems operate in a typical passive data-centric mode and work for single department, where resources cannot be fully shared. The impediment blocks local department and group from quick emergency response and decision-making. In this paper, we introduce a collaborative platform for distributed disaster reduction. To address the issues of imbalance of sharing data sources and technology in the process of disaster reduction, we propose a multi-role oriented collaboration business mechanism, which is capable of scheduling and allocating for optimum utilization of multiple resources, to link various roles for collaborative reduction business in different place. The platform fully considers the difference of equipment conditions in different provinces and provide several service modes to satisfy technology need in disaster reduction. An integrated collaboration system based on focusing services mechanism is designed and implemented for resource scheduling, functional integration, data processing, task management, collaborative mapping, and visualization. Actual applications illustrate that the platform can well support data sharing and business collaboration between national and provincial department. It could significantly improve the capability of disaster reduction in China.

Keywords: business collaboration, data sharing, distributed disaster reduction, focusing service

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Authors: Ursula D. C. Resende, Yan G. Santos, Lucas M. de O. Andrade

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The recent and fast development of the internet, wireless, telecommunication technologies and low-power electronic devices has led to an expressive amount of electromagnetic energy available in the environment and the smart applications technology expansion. These applications have been used in the Internet of Things devices, 4G and 5G solutions. The main feature of this technology is the use of the wireless sensor. Although these sensors are low-power loads, their use imposes huge challenges in terms of an efficient and reliable way for power supply in order to avoid the traditional battery. The radio frequency based energy harvesting technology is especially suitable to wireless power sensors by using a rectenna since it can be completely integrated into the distributed hosting sensors structure, reducing its cost, maintenance and environmental impact. The rectenna is an equipment composed of an antenna and a rectifier circuit. The antenna function is to collect as much radio frequency radiation as possible and transfer it to the rectifier, which is a nonlinear circuit, that converts the very low input radio frequency energy into direct current voltage. In this work, a set of rectennas, mounted on a paper substrate, which can be used for the inner coating of buildings and simultaneously harvest electromagnetic energy from the environment, is proposed. Each proposed individual rectenna is composed of a 2.45 GHz patch antenna and a voltage doubler rectifier circuit, built in the same paper substrate. The antenna contains a rectangular radiator element and a microstrip transmission line that was projected and optimized by using the Computer Simulation Software (CST) in order to obtain values of S11 parameter below -10 dB in 2.45 GHz. In order to increase the amount of harvested power, eight individual rectennas, incorporating metamaterial cells, were connected in parallel forming a system, denominated Electromagnetic Wall (EW). In order to evaluate the EW performance, it was positioned at a variable distance from the internet router, and a 27 kΩ resistive load was fed. The results obtained showed that if more than one rectenna is associated in parallel, enough power level can be achieved in order to feed very low consumption sensors. The 0.12 m2 EW proposed in this work was able to harvest 0.6 mW from the environment. It also observed that the use of metamaterial structures provide an expressive growth in the amount of electromagnetic energy harvested, which was increased from 0. 2mW to 0.6 mW.

Keywords: electromagnetic energy harvesting, metamaterial, rectenna, rectifier circuit

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Authors: Jayanth C., Anirudh Sai Yetikuri, Kavitha S. N.

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This paper explores the development and application of computer vision and machine learning techniques for real-time pose detection, facial recognition, and number plate extraction. Utilizing MediaPipe for pose estimation, the research presents methods for detecting hand raises and ducking postures through real-time video analysis. Complementarily, facial recognition is employed to compare and verify individual identities using the face recognition library. Additionally, the paper demonstrates a robust approach for extracting and storing vehicle number plates from images, integrating Optical Character Recognition (OCR) with a database management system. The study highlights the effectiveness and versatility of these technologies in practical scenarios, including security and surveillance applications. The findings underscore the potential of combining computer vision techniques to address diverse challenges and enhance automated systems for both individual and vehicular identification. This research contributes to the fields of computer vision and machine learning by providing scalable solutions and demonstrating their applicability in real-world contexts.

Keywords: computer vision, pose detection, facial recognition, number plate extraction, machine learning, real-time analysis, OCR, database management

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Authors: Abdulkabir Abdullahi

Abstract:

Nigeria has not yet welcomed phonics into its primary schools. In government-owned primary schools teachers are functionally ignorant of the stories of the reading wars amongst international scholars. There are few or no Nigerian-authored phonics textbooks, and there has been no government-owned phonics curriculum either. There are few or no academic journal articles on phonics in the country and there is, in fact, a certain danger of confusion between phonics and phonetics among Nigerian publishers, authors, writers and academics as if Nigerian teachers of English and the educational policy makers of the country were unaware of reading failures/problems amongst Nigerian children, or had never heard of phonics or read of the stories of the reading wars or the annual phonics test in the United Kingdom, the United States of America and other parts of the world. It is on this note that this article reviews and examines, in the style of a qualitative inquiry, the body of arguments on phonics, and explores the effectiveness of phonics teaching, particularly, in a second-language learning contexts. While the merit of the paper is, perhaps, situated in its supreme effort to draw global attention to reading failures/problems in Nigeria and the ways the situation may affect English language learning, international academic relations and the educational future of the country, it leaves any quantitative verification of its claims to interested quantitative researchers in the world.

Keywords: graphemes, phonics, reading, reading wars, reading theories, phonemic awareness

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Authors: M. Dimitri, M. Ricci, F. Bigi, M. Romiti, A. Corvi

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Tissue engineering has reached a significant milestone with the integration of 3D printing for the creation of complex bioconstructs equipped with vascular networks, crucial for cell maintenance and growth. This study aims to demonstrate the effectiveness of a portable microperfusion system designed to adapt dynamically to the evolving conditions of cell growth within 3D-printed bioconstructs. The microperfusion system was developed to provide a constant and controlled flow of nutrients and oxygen through the integrated vessels in the bioconstruct, replicating in vivo physiological conditions. Through a series of preliminary experiments, we evaluated the system's ability to maintain a favorable environment for cell proliferation and differentiation. Measurements of cell density and viability were performed to monitor the health and functionality of the tissue over time. Preliminary results indicate that the portable microperfusion system not only supports but optimizes cell growth, effectively adapting to changes in metabolic needs during the bioconstruct maturation process. This research opens perspectives in tissue engineering, demonstrating that a portable microperfusion system can be successfully integrated into 3D-printed bioconstructs, promoting sustainable and uniform cell growth. The implications of this study are far-reaching, with potential applications in regenerative medicine and pharmacological research, providing a platform for the development of functional and complex tissues.

Keywords: biofabrication, microfluidic perfusion system, 4D bioprinting

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Authors: Amine Ez-Zoubi, Abdellah Farah

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Because of their effectiveness and environmental safety, many essential oils have been investigated as biopesticides. Nevertheless, the encapsulation process is necessary to improve its physical, chemical, and biological properties. Therefore, the purpose of this paper was to study the physicochemical characteristics, and antifungal activity of the Artemisia Herba-Alba essential oil (HAEO) encapsulated in succinic acid modified β-CD (SACD). A yellowish oil was obtained from plant A. Herba-Alba using hydrodistillation and GC-MS was used to identify the chemical composition, in which α-Thujone (65.0%) was the main component in HAEO. The succinic acid has been esterified via the hydroxyl groups in β-CD to produce SACD. In addition, the inclusion complex formation of HAEO and SACD was generated according to the co-precipitation method and was analyzed by several techniques. The antifungal activity in vitro was examined against Botrytis cinerea by direct contact with a potato dextrose agar culture medium. At a 0.1 % concentration, the HAEO in encapsulated form showed higher potential for the control of B. cinerea when compared to the EO in free form (38.34 to 12%). Thus, these results produced evidence that the encapsulation of EOs in SACD can be useful for the development of B.cinerea inhibitors and a promising alternative biopesticide.

Keywords: Artemisia Herba-Alba essential oil, succinic acid modified β-cyclodextrin, inclusion complex, co-precipitation, Botrytis cinerea, direct contact

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Authors: Yooseo Pang, Jongwoong Choi, Yong Cho, Yongchae Jeong

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Climate crisis, such as environmental problems related to energy supply, is getting emerged issues, so the use of renewable energy is essentially required to solve these problems, which are mainly managed by the Paris Agreement, the international treaty on climate change. The government of the Republic of Korea announced that the key long-term goal for a low-carbon strategy is “Carbon neutrality by 2050”. It is focused on the role of the internet data centers (IDC) in which large amounts of data, such as artificial intelligence (AI) and big data as an impact of the 4th industrial revolution, are managed. The demand for the cooling system market for IDC was about 9 billion US dollars in 2020, and 15.6% growth a year is expected in Korea. It is important to control the temperature in IDC with an efficient air conditioning system, so hydrothermal energy is one of the best options for saving energy in the cooling system. In order to save energy and optimize the operating conditions, it has been considered to apply ‘the dam deep water air conditioning system. Deep water at a specific level from the dam can supply constant water temperature year-round. It will be tested & analyzed the amount of energy saving with a pilot plant that has 100RT cooling capacity. Also, a target of this project is 1.2 PUE (Power Usage Effectiveness) which is the key parameter to check the efficiency of the cooling system.

Keywords: hydrothermal energy, HVAC, internet data center, free-cooling

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Authors: S. Assylbekova, D. Zolotareva, A. Dauletbakov, Ye. Belyankova, S. Bayazit, A. Basharimova, A. Zazybin, A. Isimberlenova, A. Kakimova, M. Aydemir, A. Kairullinova

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Transfer hydrogenation (TH) is a key process in organic chemistry, especially in pharmaceutical and agrochemical synthesis, offering a safer and more sustainable approach compared to traditional methods. This work is devoted to the synthesis and use of ruthenium catalysts containing phosphinite ligands in TH reactions. Ruthenium complexes are particularly noteworthy for their effectiveness in asymmetric TH. Their stability and adaptability to different reaction environments make them ideal for both laboratory-scale and industrial applications. Phosphinite ligands (P(OR)R'2) are used in the synthesis of complexes to improve their properties. These ligands are known for their ability to finely tune the electronic and steric properties of metal centers. The electron-donating nature of the phosphorus atom, combined with the variability in the R and R' groups, allows for significant customization of the catalyst's properties. The purpose and difference of the work is to study the incorporation of a hydrophilic ionic liquid into the composition of a phosphinite ligand, which will then be converted into a catalyst. The technique involves the synthesis of a phosphinite ligand with an ionic liquid at room temperature under an inert atmosphere and then a ruthenium complex. Next, the TH reactions of acetophenone and its derivatives are carried out using the resulting catalyst. The conversion of ketone to alcohol is analyzed using a gas chromatograph. This study contributes to the understanding of the influence of catalyst physico-chemical properties on transfer hydrogenation results.

Keywords: transfer hydrogenation, ruthenium, catalysts, phosphinite ligands

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Authors: Muhammad Mazhar, Yong Zhu, Likang Qin

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Foods contain endogenous components known as dietary fibers, which are classified into soluble and insoluble forms. Dietary fibers are resistant to gut digestive enzymes, modulating anaerobic intestinal microbiota (AIM) and fabricating short-chain fatty acids (SCFAs). Acetate, butyrate, and propionate dominate in the gut, and different pathways, including Wood-Ljungdahl and acrylate pathways, generate these SCFAs. In pancreatic dysfunction, the release of insulin/glucagon is impaired, which leads to hyperglycemia. SCFAs enhance insulin sensitivity or secretion, beta-cell functions, leptin release, mitochondrial functions, and intestinal gluconeogenesis in human organs, which positively affect type 2 diabetes (T2D). Research models presented that SCFAs either enhance the release of peptide YY (PYY) and glucagon-like peptide-1 (GLP-1) from L-cells (entero-endocrine) or promote the release of leptin hormone satiation in adipose tissues through G-protein receptors, i.e., GPR-41/GPR-43. Dietary fibers are the components of foods that influence AIM and produce SCFAs, which may be offering beneficial effects on T2D. This review addresses the effectiveness of SCFAs in modulating gut AIM in the fermentation of dietary fiber and their worth against T2D.

Keywords: dietary fibers, intestinal microbiota, short-chain fatty acids, fermentation, type 2 diabetes

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Authors: Hui Fang Huang Su, Jia Borror

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This study compared two interventions for teaching math to preschool-aged students with autism spectrum disorder (ASD). The first is considered the business as usual (BAU) intervention, which uses the Strategies for Teaching Based on Autism Research (STAR) curriculum and discrete trial teaching as the instructional methodology. The second is the Math is Not Difficult (Project MIND) activity-embedded, naturalistic intervention. These interventions were randomly assigned to four preschool students with ASD classrooms and implemented over three months for Project Mind. We used measurement gained during the same three months for the STAR intervention. In addition, we used A quasi-experimental, pre-test/post-test design to compare the effectiveness of these two interventions in building mathematical knowledge and skills. The pre-post measures include three standardized instruments: the Test of Early Math Ability-3, the Problem Solving and Calculation subtests of the Woodcock-Johnson Test of Achievement IV, and the Bracken Test of Basic Concepts-3 Receptive. The STAR curriculum-based assessment is administered to all Baudhuin students three times per year, and we used the results in this study. We anticipated that implementing these two approaches would improve the mathematical knowledge and skills of children with ASD. Still, it is crucial to see whether a behavioral or naturalistic teaching approach leads to more significant results.

Keywords: early learning, autism, math for pre-schoolers, special education, teaching strategies

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

Procedia PDF Downloads 127