Search results for: multiple input multiple output

Authors: Xiaohong Li, Wenfan Yan

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Background: While it is widely considered that the university library plays a critical role in fulfilling the institution's mission and providing students’ learning experience beyond the classrooms, how the technology-enhanced library reform changed college students’ learning experience hasn’t been thoroughly investigated. The purpose of this study is to explore how technology-enhanced library reform affects students’ learning experience and career readiness and further identify the factors and effective conditions that enable the quality learning outcome of Chinese college students. Methodologies: This study selected the qualitative comparative analysis (QCA) method to explore the effects of technology-enhanced university library reform on college students’ learning experience and career readiness. QCA is unique in explaining the complex relationship between multiple factors from a holistic perspective. Compared with the traditional quantitative and qualitative analysis, QCA not only adds some quantitative logic but also inherits the characteristics of qualitative research focusing on the heterogeneity and complexity of samples. Shenyang Normal University (SNU) selected a sample of the typical comprehensive university in China that focuses on students’ learning and application of professional knowledge and trains professionals to different levels of expertise. A total of 22 current university students and 30 graduates who joined the Library Readers Association of SNU from 2011 to 2019 were selected for semi-structured interviews. Based on the data collected from these participating students, qualitative comparative analysis (QCA), including univariate necessity analysis and the multi-configuration analysis, was conducted. Findings and Discussion: QCA analysis results indicated that the influence of technology-enhanced university library restructures and reorganization on student learning experience and career readiness is the result of multiple factors. Technology-enhanced library equipment and other hardware restructured to meet the college students learning needs and have played an important role in improving the student learning experience and learning persistence. More importantly, the soft characteristics of technology-enhanced library reform, such as library service innovation space and culture space, have a positive impact on student’s career readiness and development. Technology-enhanced university library reform is not only the change in the building's appearance and facilities but also in library service quality and capability. The study also provides suggestions for policy, practice, and future research.

Keywords: career readiness, college student learning experience, qualitative comparative analysis (QCA), technology-enhanced library reform

Procedia PDF Downloads 79

Authors: Stephanie Cornish

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The use of synthetic dermal templates, also known as dermal matrices, such as PolyNovo® Biodegradable Temporising Matrix (BTM), has been well established in the reconstruction of acute wounds with a full thickness defect of the skin. Its use has become common place in the treatment of full thickness burns and is not unfamiliar in the realm of necrotising fasciitis, free flap donor site reconstruction, and the management of acute traumatic wounds. However, the use of dermal templates for more chronic wounds is rare. The authors present the successful use of BTM in the reconstruction of a chronic scalp wound following the excision of a malignancy and multiple previous failed attempts at repair, thus demonstrating the potential for an increased scope of use.

Keywords: dermal template, BTM, chronic, scalp wound, reconstruction

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Authors: Jiawen Wang, Qijun Chen

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The performance of most machine-learning methods for image inpainting depends on the quantity and quality of the training samples. However, it is very expensive or even impossible to obtain a great number of training samples in many scenarios. In this paper, an image inpainting model based on a generative adversary network (GAN) is constructed for the cases when the number of training samples is small. Firstly, a feature extraction network (F-net) is incorporated into the GAN network to utilize the available information of the inpainting image. The weighted sum of the extracted feature and the random noise acts as the input to the generative network (G-net). The proposed network can be trained well even when the sample size is very small. Secondly, in the phase of the completion for each damaged image, a genetic algorithm is designed to search an optimized noise input for G-net; based on this optimized input, the parameters of the G-net and F-net are further learned (Once the completion for a certain damaged image ends, the parameters restore to its original values obtained in the training phase) to generate an image patch that not only can fill the missing part of the damaged image smoothly but also has visual semantics.

Keywords: image inpainting, generative adversary nets, genetic algorithm, small-sample size

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Authors: Lya Porto, Giulia Giacchè, Mario Aquino Alves

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The paper aims to describe the linkage between government and civil society proposing a study on agro-ecological agriculture policy and urban action in São Paulo city underling the main achievements obtained. The negotiation processes between social movements and the government (inputs) and its results on political regulation and public action for Urban Agriculture (UA) in São Paulo city (outputs) have been investigated. The method adopted is qualitative, with techniques of semi-structured interviews, participant observation, and documental analysis. The authors conducted 30 semi-structured interviews with organic farmers, activists, governmental and non-governmental managers. Participant observation was conducted in public gardens, urban farms, public audiences, democratic councils, and social movements meetings. Finally, public plans and laws were also analyzed. São Paulo city with around 12 million inhabitants spread out in a 1522 km2 is the economic capital of Brazil, marked by spatial and socioeconomic segregation, currently aggravated by environmental crisis, characterized by water scarcity, pollution, and climate changes. In recent years, Urban Agriculture (UA) social movements gained strength and struggle for a different city with more green areas, organic food production, and public occupation. As the dynamics of UA occurs by the action of multiple actresses and institutions that struggle to build multiple senses on UA, the analysis will be based on literature about solidarity economy, governance, public action and networks. Those theories will mark out the analysis that will emphasize the approach of inter-subjectivity built between subjects, as well as the hybrid dynamics of multiple actors and spaces in the construction of policies for UA. Concerning UA we identified four main typologies based on land ownership, main function (economic or activist), form of organization of the space, and type of production (organic or not). The City Hall registers 500 productive unities of agriculture, with around 1500 producers, but researcher estimated a larger number of unities. Concerning the social movements we identified three categories that differ in goals and types of organization, but all of them work by networks of activists and/or organizations. The first category does not consider themselves as a movement, but a network. They occupy public spaces to grow organic food and to propose another type of social relations in the city. This action is similar to what became known as the green guerrillas. The second is configured as a movement that is structured to raise awareness about agro-ecological activities. The third one is a network of social movements, farmers, organizations and politicians that work focused on pressure and negotiation with executive and legislative government to approve regulations and policies on organic and agro-ecological Urban Agriculture. We conclude by highlighting how the interaction among institutions and civil society produced important achievements for recognition and implementation of UA within the city. Some results of this process are awareness for local production, legal and institutional recognition of the rural zone around the city into the planning tool, the investment on organic school public procurements, the establishment of participatory management of public squares, the inclusion of UA on Municipal Strategic Plan and Master Plan.

Keywords: public action, policies, agroecology, urban and peri-urban agriculture, Sao Paulo

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Authors: Jaime A. Palma-Mendoza

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A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

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Authors: B. Manoj Kumar, C. Malavika, E. S. Kannan

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The objective of this study is to investigate the switching behavior of two vertically aligned memristors connected by a shared top electrode, a configuration that significantly deviates from the conventional single oxide layer sandwiched between two electrodes. The device is fabricated by bridging copper electrodes with mechanically exfoliated van der Waals metal (specifically tantalum disulfide and tantalum diselenide). The device demonstrates threshold-switching behavior in its I-V characteristics. When the input voltage signal is ramped with voltages below the threshold, the output current shows spiking behavior, resembling integrated and firing actions without extra circuitry. We also investigated the self-reset behavior of the device. Using a continuous constant voltage bias, we activated the device to the firing state. After removing the bias and reapplying it shortly afterward, the current returned to its initial state. This indicates that the device can spontaneously return to its resting state. The outcome of this investigation offers a fresh perspective on memristor-based device design and an efficient method to construct hardware for neuromorphic computing systems.

Keywords: integrated and firing, memristor, spiking behavior, threshold switching

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Authors: Pitchayanin Sukholthaman

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Gradually accumulated, the enormous amount of waste has caused tremendous adverse impacts to the world. Bangkok, Thailand, is chosen as an urban city of a developing country having coped with serious MSW problems due to the vast amount of waste generated, ineffective and improper waste management problems. Waste generation is the most important factor for successful planning of MSW management system. Thus, the prediction of MSW is a very important role to understand MSW distribution and characteristic; to be used for strategic planning issues. This study aims to find influencing variables that affect the amount of Bangkok MSW generation quantity.

Keywords: MSW generation, MSW quantity prediction, MSW management, multiple regression, Bangkok

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Authors: Chaimaa Messaoudi, Rachida Fissoune, Hassan Badir

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Technological advances of computer science and data analysis are helping to provide continuously huge volumes of biological data, which are available on the web. Such advances involve and require powerful techniques for data integration to extract pertinent knowledge and information for a specific question. Biomedical exploration of these big data often requires the use of complex queries across multiple autonomous, heterogeneous and distributed data sources. Semantic integration is an active area of research in several disciplines, such as databases, information-integration, and ontology. We provide a survey of some approaches and techniques for integrating biological data, we focus on those developed in the ontology community.

Keywords: biological ontology, linked data, semantic data integration, semantic web

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Authors: Pornpimol Chaiwuttisak

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The study aims to compare the performance of the logistics for Thailand’s wholesale and retail trade industries (except motor vehicles, motorcycle, and stalls) by using data (data envelopment analysis). Thailand Standard Industrial Classification in 2009 (TSIC - 2009) categories that industries into sub-group no. 45: wholesale and retail trade (except for the repair of motor vehicles and motorcycles), sub-group no. 46: wholesale trade (except motor vehicles and motorcycles), and sub-group no. 47: retail trade (except motor vehicles and motorcycles. Data used in the study is collected by the National Statistical Office, Thailand. The study consisted of four input factors include the number of companies, the number of personnel in logistics, the training cost in logistics, and outsourcing logistics management. Output factor includes the percentage of enterprises having inventory management. The results showed that the average relative efficiency of small-sized enterprises equals to 27.87 percent and 49.68 percent for the medium-sized enterprises.

Keywords: DEA, wholesales and retails, logistics, Thailand

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Authors: Sungsik Jo, Hyeonwoo Kim, Iksu Choi, Hunmo Kim

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In the SHP, LVDT sensor is for detecting the length changes of the EHA output, and the thrust of the EHA is controlled by the pressure sensor. Sensor is possible to cause hardware fault by internal problem or external disturbance. The EHA of SHP is able to be uncontrollable due to control by feedback from uncertain information, on this paper; the sliding mode observer algorithm estimates the original sensor output information in permanent sensor fault. The proposed algorithm shows performance to recovery fault of disconnection and short circuit basically, also the algorithm detect various of sensor fault mode.

Keywords: smart hybrid powerpack (SHP), electro hydraulic actuator (EHA), permanent sensor fault tolerance, sliding mode observer (SMO), graphic user interface (GUI)

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Authors: Tulasi Rayasa, Phani Kumar Pullela

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A systematic review is a research method that involves collecting and evaluating the information on a specific topic in order to provide a comprehensive and unbiased review. This type of review aims to improve the software development process by ensuring that the research is thorough and accurate. To ensure objectivity, it is important to follow systematic guidelines and consider multiple sources, such as literature reviews, interviews, and surveys. The evaluation process should also be streamlined by incorporating research from journals and other sources, such as grey literature. The main goal of a systematic review is to identify the consistency of current models in the field of computer application and software engineering.

Keywords: computer application, software engineering, process research, data science

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Authors: A. boursali, A. Guen Bouazza, M. Khaouani, Z. Kourdi, B. Bouazza

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This paper presents the design, development and characterization of the devices simulation for X-Band Radar applications. The effect of an InAlN/GaN structure on the RF performance High Electron Mobility Transistor (HEMT) device. Systematic investigations on the small signal as well as power performance as functions of the drain biases are presented. Were improved for X-band applications. The Power Added Efficiency (PAE) was achieved over 23% for X-band. The developed devices combine two InAlN/GaN HEMTs of 30nm gate periphery and exhibited the output power of over 50W. An InAlN/GaN HEMT with 30nm gate periphery was developed and exhibited the output power of over 120W.

Keywords: InAlN/GaN, HEMT, RF analyses, PAE, X-Band, radar

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Authors: Manjit Singh

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Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG (electrocardiogram), heart rate variability (HRV), multiscale entropy, sampling frequency

Procedia PDF Downloads 271

Authors: Jihee Jang, Seowon Yoon, Gaeun Son, Minjung Kang, Joon Yeon Choeh, Kee-Hong Choi

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Background: Self-report multiple choice questionnaires have been widely utilized to quantitatively measure one’s personality and psychological constructs. Despite several strengths (e.g., brevity and utility), self-report multiple-choice questionnaires have considerable limitations in nature. With the rise of machine learning (ML) and Natural language processing (NLP), researchers in the field of psychology are widely adopting NLP to assess psychological constructs to predict human behaviors. However, there is a lack of connections between the work being performed in computer science and that psychology due to small data sets and unvalidated modeling practices. Aims: The current article introduces the study method and procedure of phase II, which includes the interview questions for the five-factor model (FFM) of personality developed in phase I. This study aims to develop the interview (semi-structured) and open-ended questions for the FFM-based personality assessments, specifically designed with experts in the field of clinical and personality psychology (phase 1), and to collect the personality-related text data using the interview questions and self-report measures on personality and psychological distress (phase 2). The purpose of the study includes examining the relationship between natural language data obtained from the interview questions, measuring the FFM personality constructs, and psychological distress to demonstrate the validity of the natural language-based personality prediction. Methods: The phase I (pilot) study was conducted on fifty-nine native Korean adults to acquire the personality-related text data from the interview (semi-structured) and open-ended questions based on the FFM of personality. The interview questions were revised and finalized with the feedback from the external expert committee, consisting of personality and clinical psychologists. Based on the established interview questions, a total of 425 Korean adults were recruited using a convenience sampling method via an online survey. The text data collected from interviews were analyzed using natural language processing. The results of the online survey, including demographic data, depression, anxiety, and personality inventories, were analyzed together in the model to predict individuals’ FFM of personality and the level of psychological distress (phase 2).

Keywords: personality prediction, psychological distress prediction, natural language processing, machine learning, the five-factor model of personality

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Authors: Tala Toonsi, Marah Alagha, Lina Alnowaiser, Hala Rajab

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This report is about the Photomath app, which is an AI application that uses image recognition technology, specifically optical character recognition (OCR) algorithms. The (OCR) algorithm translates the images into a mathematical equation, and the app automatically provides a step-by-step solution. The application supports decimals, basic arithmetic, fractions, linear equations, and multiple functions such as logarithms. Testing was conducted to examine the usage of this app, and results were collected by surveying ten participants. Later, the results were analyzed. This paper seeks to answer the question: To what level the artificial intelligence features are accurate and the speed of process in this app. It is hoped this study will inform about the efficiency of AI in Photomath to the users.

Keywords: photomath, image recognition, app, OCR, artificial intelligence, mathematical equations.

Procedia PDF Downloads 171

Authors: Bojana Tot, Goran BošKović, Goran Vujić

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Route optimisation is a process of planning one or multiple routes, with the purpose of minimizing overall costs, while achieving the highest possible performance under a set of given constraints. It combines routing or route planning, which is the process of creating the most cost-effective route by minimizing the distance or travelled time necessary to reach a set of planned stops, and route scheduling, which is the process of assigning an arrival and service time for each stop, with drivers being given shifts that adhere to their working hours. The objective of this paper is to provide benefits on the implementation of waste collection route optimisation and thus achieve economic efficiency for public utility companies, better service for citizens and positive environment and health.

Keywords: waste management, environment, collection route optimisation, GIS

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Authors: L. Rakesh, T. Y. Heblekar

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This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

Procedia PDF Downloads 143

Authors: Yunjia Yang, Peng Li, Gordon Xu, Timothy Mahony, Bing Zhang, Neena Mitter, Karishma Mody

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Sheep flystrike is one of the most economically important diseases affecting the Australian sheep and wool industry (>356M/annually). Currently, control of Lucillia cuprina relies almost exclusively on chemicals controls and the parasite has developed resistance to nearly all control chemicals used in the past. It is therefore critical to develop an alternative solution for the sustainable control and management of flystrike. RNA interference (RNAi) technologies have been successfully explored in multiple animal industries for developing parasites controls. This research project aims to develop a RNAi based biological control for sheep blowfly. Double-stranded RNA (dsRNA) has already proven successful against viruses, fungi and insects. However, the environmental instability of dsRNA is a major bottleneck for successful RNAi. Bentonite polymer (BenPol) technology can overcome this problem, as it can be tuned for the controlled release of dsRNA in the gut challenging pH environment of the blowfly larvae, prolonging its exposure time to and uptake by target cells. To investigate the potential of BenPol technology for dsRNA delivery, four different BenPol carriers were tested for their dsRNA loading capabilities, and three of them were found to be capable of affording dsRNA stability under multiple temperatures (4°C, 22°C, 40°C, 55°C) in sheep serum. Based on stability results, dsRNA from potential targeted genes was loaded onto BenPol carriers and tested in larvae feeding assays, three genes resulting in knockdowns. Meanwhile, a primary blowfly embryo cell line (BFEC) derived from L. cuprina embryos was successfully established, aim for an effective insect cell model for testing RNAi efficacy for preliminary assessments and screening. The results of this study establish that the dsRNA is stable when loaded on BenPol particles, unlike naked dsRNA rapidly degraded in sheep serum. The stable nanoparticle delivery system offered by BenPol technology can protect and increase the inherent stability of dsRNA molecules at higher temperatures in a complex biological fluid like serum, providing promise for its future use in enhancing animal protection.

Keywords: flystrike, RNA interference, bentonite polymer technology, Lucillia cuprina

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Authors: Qiang Guo, Ruying Qi

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This project aims to trace the developmental patterns of a child's Mandarin and English from China to Australia from age 3; 03 till 5; 06. In childhood bilingual studies, there is an assumption that age 3 is the dividing line between simultaneous bilinguals and sequential bilinguals. Determining similarities and differences between Bilingual First Language Acquisition, Early Second Language Acquisition, and Second Language Acquisition is of great theoretical significance. Studies on Bilingual First Language Acquisition, hereafter, BFLA in the past three decades have shown that the grammatical development of bilingual children progresses through the same developmental trajectories as their monolingual counterparts. Cross-linguistic interaction does not show changes of the basic grammatical knowledge, even in the weaker language. While BFLA studies show consistent results under the conditions of adequate input and meaningful interactional context, the research findings of Early Second Language Acquisition (ESLA) have demonstrated that this cohort proceeds their early English differently from both BFLA and SLA. The different development could be attributed to the age of migration, input pattern, and their Environmental Languages (Lε). In the meantime, the dynamic relationship between the two languages is an issue to invite further attention. The present study attempts to fill this gap. The child in this case study started acquiring L1 Mandarin from birth in China, where the environmental language (Lε) coincided with L1 Mandarin. When she migrated to Australia at 3;06, where the environmental language (Lε) was L2 English, her Mandarin exposure was reduced. On the other hand, she received limited English input starting from 1; 02 in China, where the environmental language (Lε) was L1 Mandarin, a non-English environment. When she relocated to Australia at 3; 06, where the environmental language (Lε) coincided with L2 English, her English exposure significantly increased. The child’s linguistic profile provides an opportunity to explore: (1) What does the child’s English developmental route look like? (2) What does the L1 Mandarin developmental pattern look like in different environmental languages? (3) How do input and environmental language interact in shaping the bilingual child’s linguistic repertoire? In order to answer these questions, two linguistic areas are selected as the focus of the investigation, namely, subject realization and wh-questions. The chosen areas are contrastive in structure but perform the same semantic functions in the two linguistically distant languages and can serve as an ideal testing ground for exploring the developmental path in the two languages. The longitudinal case study adopts a combined approach of qualitative and quantitative analysis. Two years’ Mandarin and English data are examined, and comparisons are made with age-matched monolinguals in each language in CHILDES. To the author’s best knowledge, this study is the first of this kind examining a Mandarin-English bilingual child's bilingual development at a critical age, in different input patterns, and in different environmental languages (Lε). It also expands the scope of the theory of Lε, adding empirical evidence on the relationship between input and Lε in bilingual acquisition.

Keywords: bilingual development, age, input, environmental language (Le)

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Authors: Yuri V. Kim

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This article presents a new approach to the Functional Testing of Space Systems (SS). It can be considered as a generic test and used for a wide class of SS that from the point of view of System Dynamics and Control may be described by the ordinary differential equations. Suggested methodology is based on using semi-natural experiment- laboratory stand that doesn’t require complicated, precise and expensive technological control-verification equipment. However, it allows for testing system as a whole totally assembled unit during Assembling, Integration and Testing (AIT) activities, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data is then inserted in laboratory PC where it is post-experiment processed by Matlab/Simulink Identification Toolbox. It allows for estimating system dynamics in form of estimation of system differential equations by the experimental way and comparing them with expected mathematical model prematurely verified by mathematical simulation during the design process.

Keywords: system dynamics, space system ground tests and space qualification, system dynamics identification, satellite attitude control, assembling, integration and testing

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Authors: Teklay Gebrecherkos, Mahmud Abdulkadir

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Abstract: The emergence and subsequent rapid worldwide spread of the COVID-19 pandemic have posed a global crisis, with a tremendously increasing burden of infection, morbidity, and mortality risks. Recent studies have suggested that severe cases of COVID-19 are characterized by massive biochemical, hematological, and inflammatory alterations whose synergistic effect is estimated to progress to multiple organ damage and failure. In this regard, biochemical monitoring of COVID-19 patients, based on comprehensive laboratory assessments and findings, is expected to play a crucial role in effective clinical management and improving the survival rates of patients. However, biochemical markers that can be informative of COVID-19 patient risk stratification and predictor of clinical outcomes are currently scarcely available. The study aims to investigate the profiles of common biochemical markers and their influence on the severity of the COVID-19 infection in Tigray, Ethiopia. Methods: A laboratory-based cross-sectional study was conducted from July to August 2020 at Quiha College of Engineering, Mekelle University COVID-19 isolation and treatment center. Sociodemographic and clinical data were collected using a structured questionnaire. Whole blood was collected from each study participant, and serum samples were separated after being delivered to the laboratory. Hematological biomarkers were analyzed using FACS count, while organ tests and serum electrolytes were analyzed using ion-selective electrode methods using a Cobas-6000 series machine. Data was analyzed using SPSS Vs 20. Results: A total of 120 SARS-CoV-2 patients were enrolled during the study. The participants ranged between 18 and 91 years, with a mean age of 52 (±108.8). The majority (40%) of participants were between the ages of 60 and above. Patients with multiple comorbidities developed severe COVID-19, though not statistically significant (p=0.34). Mann-Whitney U test analysis showed that biochemical tests such as neuropile count (p=0.003), AST levels (p=0.050), serum creatinine (p=0.000), and serum sodium (p=0.015) were significantly correlated with severe COVID-19 disease as compared to non-severe disease. Conclusion: The severity of COVID-19 was associated with higher age, organ tests AST and creatinine, serum Na+, and elevated total neutrophile count. Thus, further study needs to be conducted to evaluate the alterations of biochemical biomarkers and their impact on COVID-19.

Keywords: COVID-19, biomarkers, mortality, Tigray, Ethiopia

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Authors: Mohammad Mojtahedpoor

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In this paper, it has been studied the method of optimal design of the supersonic nozzle. It could make viscous axisymmetric nozzles that the quality of their outlet flow is quite desired. In this method, it is optimized the divergent nozzle, at first. The initial divergent nozzle contour is designed through the method of characteristics and adding a suitable boundary layer to the inviscid contour. After that, it is made a proper grid and then simulated flow by the numerical solution and AUSM+ method by using the operation boundary condition. At the end, solution outputs are investigated and optimized. The numerical method has been validated with experimental results. Also, in order to evaluate the effectiveness of the present method, the nozzles compared with the previous studies. The comparisons show that the nozzles obtained through this method are sufficiently better in some conditions, such as the flow uniformity, size of the boundary layer, and obtained an axial length of the nozzle. Designing the convergent nozzle part affects by flow uniformity through changing its axial length and input diameter. The results show that increasing the length of the convergent part improves the output flow uniformity.

Keywords: nozzle, supersonic, optimization, characteristic method, CFD

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Authors: Sher Muhammad, Mirza Muhammad Waqar

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It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79 to 24.85 degree in latitude and 66.91 to 66.97 degree in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image preprocessing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end-member extraction. Well-distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF), and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (white mangroves) and Avicennia Germinans (black mangroves) have been observed throughout the study area.

Keywords: mangrove, hyperspectral, hyperion, SAM, SFF, SID

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Authors: Sahraoui Halima, Dahani Ameur, Tigrine Abedelkader

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DigiMesh technology represents a pioneering advancement in wireless networking, offering cost-effective and energy-efficient capabilities. Its inherent simplicity and adaptability facilitate the seamless transfer of data between network nodes, extending the range and ensuring robust connectivity through autonomous self-healing mechanisms. In light of these advantages, this study introduces a medical platform harnessed with DigiMesh wireless network technology characterized by low power consumption, immunity to interference, and user-friendly operation. The primary application of this platform is the real-time, long-distance monitoring of Electrocardiogram (ECG) signals, with the added capacity for simultaneous monitoring of ECG signals from multiple patients. The experimental setup comprises key components such as Raspberry Pi, E-Health Sensor Shield, and Xbee DigiMesh modules. The platform is composed of multiple ECG acquisition devices labeled as Sensor Node 1 and Sensor Node 2, with a Raspberry Pi serving as the central hub (Sink Node). Two communication approaches are proposed: Single-hop and multi-hop. In the Single-hop approach, ECG signals are directly transmitted from a sensor node to the sink node through the XBee3 DigiMesh RF Module, establishing peer-to-peer connections. This approach was tested in the first experiment to assess the feasibility of deploying wireless sensor networks (WSN). In the multi-hop approach, two sensor nodes communicate with the server (Sink Node) in a star configuration. This setup was tested in the second experiment. The primary objective of this research is to evaluate the performance of both Single-hop and multi-hop approaches in diverse scenarios, including open areas and obstructed environments. Experimental results indicate the DigiMesh network's effectiveness in Single-hop mode, with reliable communication over distances of approximately 300 meters in open areas. In the multi-hop configuration, the network demonstrated robust performance across approximately three floors, even in the presence of obstacles, without the need for additional router devices. This study offers valuable insights into the capabilities of DigiMesh wireless technology for real-time ECG monitoring in healthcare applications, demonstrating its potential for use in diverse medical scenarios.

Keywords: DigiMesh protocol, ECG signal, real-time monitoring, medical platform

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Authors: Kanate Pantusavase, Jaramporn Hassamontr

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This research aims to develop an algorithm to generate a schedule of multiple cranes that will maximize load throughputs in anodizing operation. The algorithm proposed utilizes an enumerative strategy to search for constant time between successive loads and crane covering range over baths. The computer program developed is able to generate a near-optimal crane schedule within reasonable times, i.e. within 10 minutes. Its results are compared with existing solutions from an aluminum extrusion industry. The program can be used to generate crane schedules for mixed products, thus allowing mixed-model line balancing to improve overall cycle times.

Keywords: crane scheduling, anodizing operations, cycle time minimization

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Authors: Abir O. El Sadik

Abstract:

Introduction: Wound healing involves the interaction of multiple biological processes among different types of cells, intercellular matrix and specific signaling factors producing enhancement of cell proliferation of the epidermis over dermal granulation tissue. Several studies investigated multiple strategies to promote wound healing and to minimize infection and fluid losses. However, burn crisis, and its related morbidity and mortality are still elevated. The aim of the present study was to examine the effects of mesenchymal stem cells (MSCs) in accelerating wound healing and to compare the most efficient route of administration of MSCs, either intradermal or systemic injection, with focusing on the mechanisms producing epidermal and dermal cell regeneration. Material and methods: Forty-two adult male Sprague Dawley albino rats were divided into three equal groups (fourteen rats in each group): control group (group I); full thickness surgical skin wound model, Group II: Wound treated with systemic injection of MSCs and Group III: Wound treated with intradermal injection of MSCs. The healing ulcer was examined on day 2, 6, 10 and 15 for gross morphological evaluation and on day 10 and 15 for fluorescent, histological and immunohistochemical studies. Results: The wounds of the control group did not reach complete closure up to the end of the experiment. In MSCs treated groups, better and faster healing of wounds were detected more than the control group. Moreover, the intradermal route of administration of stem cells increased the rate of healing of the wounds more than the systemic injection. In addition, the wounds were found completely healed by the end of the fifteenth day of the experiment in all rats of the group injected intradermally. Microscopically, the wound areas of group III were hardly distinguished from the adjacent normal skin with complete regeneration of all skin layers; epidermis, dermis, hypodermis and underlying muscle layer. Fully regenerated hair follicles and sebaceous glands in the dermis of the healed areas surrounded by different arrangement of collagen fibers with a significant increase in their area percent were recorded in this group more than in other groups. Conclusion: MSCs accelerate the healing process of wound closure. The route of administration of MSCs has a great influence on wound healing as intradermal injection of MSCs was more effective in enhancement of wound healing than systemic injection.

Keywords: intradermal, mesenchymal stem cells, morphology, skin wound, systemic injection

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Authors: J. Marie Hicks

Abstract:

The art of the poetic conjoins meaning and symbolism with imagery and rhythm. Perhaps the reader might read this opening sentence as 'The art of the poetic combines meaning and symbolism with imagery and rhythm,' which holds a similar message, but is not quite the same. The reader understands that these factors are combined in this literary form, but to gain a sense of the conjoining of these factors, the reader is forced to consider that these aspects of poetry are not simply combined, but actually adjoin, abut, skirt, or touch in the poetic form. This alternative word choice is an example of substitutional inference. Poetry is, ostensibly, a literary form where language is used precisely or creatively to evoke specific images or emotions for the reader. Often, the reader can predict a coming rhyme or descriptive word choice in a poem, based on previous rhyming pattern or earlier imagery in the poem. However, there are instances when the poet uses an unexpected word choice to create multiple meanings and connections. In these cases, the reader is presented with an unusual phrase or image, requiring that they think about what that image is meant to suggest, and their mind also suggests the word they expected, creating a second, overlying image or meaning. This is what is meant by the term 'substitutional inference.' This is different than simply using a double entendre, a word or phrase that has two meanings, often one complementary and the other disparaging, or one that is innocuous and the other suggestive. In substitutional inference, the poet utilizes an unanticipated word that is either visually or phonetically similar to the expected word, provoking the reader to work to understand the poetic phrase as written, while unconsciously incorporating the meaning of the line as anticipated. In other words, by virtue of a word substitution, an inference of the logical word choice is imparted to the reader, while they are seeking to rationalize the word that was actually used. There is a substitutional inference of meaning created by the alternate word choice. For example, Louise Bogan, 4th Poet Laureate of the United States, used substitutional inference in the form of homonyms, malapropisms, and other unusual word choices in a number of her poems, lending depth and greater complexity, while actively engaging her readers intellectually with her poetry. Substitutional inference not only adds complexity to the potential interpretations of Bogan’s poetry, as well as the poetry of others, but provided a method for writers to infuse additional meanings into their work, thus expressing more information in a compact format. Additionally, this nuancing enriches the poetic experience for the reader, who can enjoy the poem superficially as written, or on a deeper level exploring gradations of meaning.

Keywords: poetic inference, poetic word play, substitutional inference, word substitution

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Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

Abstract:

This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

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Authors: S. K. Ashiquer Rahman

Abstract:

Recently, oil has become more influential in almost every economic sector as a key material. As can be seen from the news, when there are some changes in an oil price or OPEC announces a new strategy, its effect spreads to every part of the economy directly and indirectly. That’s a reason why people always observe the oil price and try to forecast the changes of it. The most important factor affecting the price is its supply which is determined by the number of wildcats drilled. Therefore, a study about the number of wellheads and other economic variables may give us some understanding of the mechanism indicated by the amount of oil supplies. In this paper, we will consider a relationship between the number of wellheads and three key factors: the price of the wellhead, domestic output, and GNP constant dollars. We also add trend variables in the models because the consumption of oil varies from time to time. Moreover, this paper will use an econometrics method to estimate parameters in the model, apply some tests to verify the result we acquire, and then conclude the model.

Keywords: price, domestic output, GNP, trend variable, wildcat activity

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Authors: Payel Datta, Abhishek Das, Abhishek Roychoudhury, Dhiman Chattopadhyay, Tanushyam Chattopadhyay

Abstract:

Machine learning (ML) and deep learning (DL) is most predominantly used in image/video processing, natural language processing (NLP), audio and speech recognition but not that much used in system performance evaluation. In this paper, authors are going to describe the architecture of an abstraction layer constructed using ML/DL to detect the system failure. This proposed system is used to detect the system failure by evaluating the performance metrics of an IoT service deployment under constrained infrastructure environment. This system has been tested on the manually annotated data set containing different metrics of the system, like number of threads, throughput, average response time, CPU usage, memory usage, network input/output captured in different hardware environments like edge (atom based gateway) and cloud (AWS EC2). The main challenge of developing such system is that the accuracy of classification should be 100% as the error in the system has an impact on the degradation of the service performance and thus consequently affect the reliability and high availability which is mandatory for an IoT system. Proposed ML/DL classifiers work with 100% accuracy for the data set of nearly 4,000 samples captured within the organization.

Keywords: machine learning, system performance, performance metrics, IoT, edge

Procedia PDF Downloads 195