Search results for: commercial real estate

Authors: Juliet Ramohai

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This paper explores how women departmental heads in higher education experience leadership in a time of the COVID-19 crises. The focus is mostly on their care and coping as they work in virtual spaces. Most scholars have looked at the effects and challenges that different employees face while working from home during a lockdown. However, very few take a dedicated focus on women in leadership and the coping mechanisms and resources that they use for effective leadership during this difficult time. The paper draws on two aspects of Sen’s Capabilities approach, functionings, and agency, to cast a closer understanding of the institutional and individual coping mechanisms that might be at these women's disposal. The qualitative approach used for this paper and a feminist lens provides a critical and in-depth understanding of the real-life stories of the women and how they make sense of their virtual leadership. Data for this paper was collected through semi-structured interviews with 10 women in the positions of head of departments and analysed thematically using capabilities approach concepts as an analytical tool. The findings in this paper indicate that functionings and freedoms are tightly linked to institutional ethnographies. These ethnographies might support or hamper coping for women leaders, especially during times of crisis.

Keywords: capability approach, women leaders, higher education, COVID-19

Procedia PDF Downloads 186

Authors: A. J. Shah, G. R. Vesmawala

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Connections perform a fundamental role in the steel structures as global behaviour. In order to evaluate the real influence of the physical and geometrical parameters that control their behaviour, many experimental tests and analysis have been developed but a definitive answer to the problem in question still stands. Here, various configurations of bolts were tried and the resulting moment rotation (M-θ) curves were plotted. The connection configuration is such that two bolts are located above each of the flanges and beside each of the webs. The model considers the combined effects of prying action, the formation of yield lines, and failures due to punching shear and beam section failure. For many types of connections, the stiffness at the service load level falls somewhere in between the fully restrained and simple limits and designers need to account for its behaviour. The (M-θ) curves are generally assumed to be the best characterization of connection behaviour. The moment rotation curves are generally derived from experiments on cantilever type specimens. The moments are calculated directly from the statics of the specimen, while the rotations are measured over a distance typically equal to the point of loading. Thus, this paper establishes the relationship between M-θ behaviour of different types of connections tested and presents the relative strength of various possible arrangements of bolts.

Keywords: bolt, moment, rotation, stiffness, connections

Procedia PDF Downloads 392

Authors: T. Thulare, M. Herselman, A. Botha

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Poor system use, including inappropriate design of health information systems, causes difficulties in communication with patients and increased time spent by healthcare professionals in recording the necessary health information for medical records. System features like pop-up reminders, complex menus, and poor user interfaces can make medical records far more time consuming than paper cards as well as affect decision-making processes. Although errors associated with health information and their real and likely effect on the quality of care and patient safety have been documented for many years, more research is needed to measure the occurrence of these errors and determine the causes to implement solutions. Therefore, the purpose of this paper is to identify data integrity challenges in hospital information systems through a scoping review and based on the results provide recommendations on how to manage these. Only 34 papers were found to be most suitable out of 297 publications initially identified in the field. The results indicated that human and computerized systems are the most common challenges associated with data integrity and factors such as policy, environment, health workforce, and lack of awareness attribute to these challenges but if measures are taken the data integrity challenges can be managed.

Keywords: data integrity, data integrity challenges, hospital information systems, South Africa

Procedia PDF Downloads 181

Authors: Maria M. S. Pires, Andre F. X. Gloria, Pedro J. A. Sebastiao

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The technological advances in the area of Internet of Things have been creating more and more solutions in the area of agriculture. These solutions are quite important for life, as they lead to the saving of the most precious resource, water, being this need to save water a concern worldwide. The paper proposes the creation of an Internet of Things system based on a network of sensors and interconnected actuators that automatically monitors the quality of the rainwater that is stored inside a tank in order to be used for irrigation. The main objective is to promote sustainability by reusing rainwater for irrigation systems instead of water that is usually available for other functions, such as other productions or even domestic tasks. A mobile application was developed for Android so that the user can control and monitor his system in real time. In the application, it is possible to visualize the data that translate the quality of the water inserted in the tank, as well as perform some actions on the implemented actuators, such as start/stop the irrigation system and pour the water in case of poor water quality. The implemented system translates a simple solution with a high level of efficiency and tests and results obtained within the possible environment.

Keywords: internet of things, irrigation system, wireless sensor and actuator network, ESP32, sustainability, water reuse, water efficiency

Procedia PDF Downloads 149

Authors: Juan F. Muñoz-Rosas, Rosa M. García-Fernández, Encarnación Álvarez-Verdejo, Pablo J. Moya-Fernández

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Poverty measurement is a very important topic in many studies in social sciences. One of the most important indicators when measuring poverty is the low income proportion. This indicator gives the proportion of people of a population classified as poor. This indicator is generally unknown, and for this reason, it is estimated by using survey data, which are obtained by official surveys carried out by many statistical agencies such as Eurostat. The main feature of the mentioned survey data is the fact that they contain several variables. The variable used to estimate the low income proportion is called as the variable of interest. The survey data may contain several additional variables, also named as the auxiliary variables, related to the variable of interest, and if this is the situation, they could be used to improve the estimation of the low income proportion. In this paper, we use Monte Carlo simulation studies to analyze numerically the performance of estimators based on several auxiliary variables. In this simulation study, we considered real data sets obtained from the 2011 European Union Survey on Income and Living Condition. Results derived from this study indicate that the estimators based on auxiliary variables are more accurate than the naive estimator.

Keywords: inclusion probability, poverty, poverty line, survey sampling

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Authors: Ming Lu, Xiaojun Li, Bodi Lu, Juehui Xing

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Earthquake damage phenomenon of each large earthquake gives comprehensive and profound real test to the dynamic performance and failure mechanism of different engineering structures. Cognitive engineering structure characteristics through seismic damage phenomenon are often far superior to expensive shaking table experiments. After the earthquake, people will record a variety of different types of engineering damage photos. However, a large number of earthquake damage photographs lack sufficient information and reduce their using value. To improve the research value and the use efficiency of engineering seismic damage photographs, this paper objects to explore and show seismic damage background information, which includes the earthquake magnitude, earthquake intensity, and the damaged structure characteristics. From the research requirement in earthquake engineering field, the authors use the 2008 China Wenchuan M8.0 earthquake photographs, and provide four kinds of attribute indexes and classification, which are seismic information, structure types, earthquake damage parts and disaster causation factors. The final object is to set up an engineering structural seismic damage database based on these four attribute indicators and classification, and eventually build a website providing seismic damage photographs.

Keywords: attribute index, classification method, earthquake damage picture, engineering structure

Procedia PDF Downloads 765

Authors: Fariba Azizi, Firoozeh Haghighi, Viliam Makis

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In this paper, we propose a method to model the relationship between failure time and degradation for a simple step stress test where underlying degradation path is linear and different causes of failure are possible. It is assumed that the intensity function depends only on the degradation value. No assumptions are made about the distribution of the failure times. A simple step-stress test is used to shorten failure time of products and a tampered failure rate (TFR) model is proposed to describe the effect of the changing stress on the intensities. We assume that some of the products that fail during the test have a cause of failure that is only known to belong to a certain subset of all possible failures. This case is known as masking. In the presence of masking, the maximum likelihood estimates (MLEs) of the model parameters are obtained through an expectation-maximization (EM) algorithm by treating the causes of failure as missing values. The effect of incomplete information on the estimation of parameters is studied through a Monte-Carlo simulation. Finally, a real example is analyzed to illustrate the application of the proposed methods.

Keywords: cause of failure, linear degradation path, reliability function, expectation-maximization algorithm, intensity, masked data

Procedia PDF Downloads 334

Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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Authors: Vaidehi Iyer, Konstantin Borozdin

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Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

Procedia PDF Downloads 229

Authors: John Segars

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Built out of a real-world need to have better, more detailed, asset and infrastructure documentation, this project will lay out the case for using the database functionality of ArcGIS as a tool to track and maintain infrastructure location, status, maintenance and serviceability. Workflows and processes will be presented and detailed which may be applied to an organizations’ infrastructure needs that might allow them to make use of the robust tools which surround the ArcGIS platform. The end result is a value-added information system framework with a geographic component e.g., the spatial location of various I.T. assets, a detailed set of records which not only documents location but also captures the maintenance history for assets along with photographs and documentation of these various assets as attachments to the numerous feature class items. In addition to the asset location and documentation benefits, the staff will be able to log into the devices and pull SNMP (Simple Network Management Protocol) based query information from within the user interface. The entire collection of information may be displayed in ArcGIS, via a JavaScript based web application or via queries to the back-end database. The project is applicable to all organizations which maintain an IT infrastructure but specifically targets post-secondary educational institutions where access to ESRI resources is generally already available in house.

Keywords: ESRI, GIS, infrastructure, network documentation, PostgreSQL

Procedia PDF Downloads 181

Authors: Jonghyuk Yoon, Hyoungwoon Song

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Recently, there are lots of increasing interest in a smart farming that represents application of modern Information and Communication Technologies (ICT) into agriculture since it provides a methodology to optimize production efficiencies by managing growing conditions of crops automatically. In order to obtain high performance and stability for smart greenhouse, it is important to identify the effect of various working parameters such as capacity of ventilation fan, vent opening area and etc. In the present study, a 3-dimensional CFD (Computational Fluid Dynamics) simulation for single-span greenhouse was conducted using the commercial program, Ansys CFX 18.0. The numerical simulation for single-span greenhouse was implemented to figure out the internal thermal and flow characteristics. In order to numerically model solar radiation that spread over a wide range of wavelengths, the multiband model that discretizes the spectrum into finite bands of wavelength based on Wien’s law is applied to the simulation. In addition, absorption coefficient of vinyl varied with the wavelength bands is also applied based on Beer-Lambert Law. To validate the numerical method applied herein, the numerical results of the temperature at specific monitoring points were compared with the experimental data. The average error rates (12.2~14.2%) between them was shown and numerical results of temperature distribution are in good agreement with the experimental data. The results of the present study can be useful information for the design of various greenhouses. This work was supported by Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, Forestry and Fisheries (IPET) through Advanced Production Technology Development Program, funded by Ministry of Agriculture, Food and Rural Affairs (MAFRA)(315093-03).

Keywords: single-span greenhouse, CFD (computational fluid dynamics), solar radiation, multiband model, absorption coefficient

Procedia PDF Downloads 136

Authors: Harunori Kawabe, Hideyuki Aoshima, Koji Murakami, Minoru Kawakami, Yuka Nakano, David D. Ordinario, C. W. Crawford, Iri Sato-Baran

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With the recent advances in gene editing technologies allowing the rewriting of genetic sequences, additional market growth in the global floriculture market beyond previous trends is anticipated through increasingly sophisticated plant breeding techniques. As a prerequisite for gene editing, the gene sequence of the target plant must first be identified. This necessitates the genetic analysis of plants with unknown gene sequences, the extraction of RNA, and comprehensive expression analysis. Consequently, a technology capable of consistently and effectively extracting high-purity DNA and RNA from plants is of paramount importance. Although model plants, such as Arabidopsis and tobacco, have established methods for DNA and RNA extraction, floricultural species such as roses present unique challenges. Different techniques to extract DNA and RNA from various floricultural species were investigated. Upon sampling and grinding the petals of several floricultural species, it was observed that nucleic acid extraction from the ground petal solutions of low viscosity was straightforward; solutions of high viscosity presented a significant challenge. It is postulated that the presence of substantial quantities of polysaccharides and polyphenols in the plant tissue was responsible for the inhibition of nucleic acid extraction. Consequently, attempts were made to extract high-purity DNA and RNA by improving the CTAB method and combining it with commercially available nucleic acid extraction kits. The quality of the total extracted DNA and RNA was evaluated using standard methods. Finally, the effectiveness of the extraction method was assessed by determining whether it was possible to create a library that could be applied as a suitable template for a next-generation sequencer. In conclusion, a method was developed for consistent and accurate nucleic acid extraction from high-viscosity floricultural samples. These results demonstrate improved techniques for DNA and RNA extraction from flowers, help facilitate gene editing of floricultural species and expand the boundaries of research and commercial opportunities.

Keywords: floriculture, gene editing, next-generation sequencing, nucleic acid extraction

Procedia PDF Downloads 29

Authors: J. A. Batsis, G. G. Boateng, L. M. Seo, C. L. Petersen, K. L. Fortuna, E. V. Wechsler, R. J. Peterson, S. B. Cook, D. Pidgeon, R. S. Dokko, R. J. Halter, D. F. Kotz

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Resistance exercise bands are a core component of any physical activity strengthening program. Strength training can mitigate the development of sarcopenia, the loss of muscle mass or strength and function with aging. Yet, the adherence of such behavioral exercise strategies in a home-based setting are fraught with issues of monitoring and compliance. Our group developed a Bluetooth-enabled resistance exercise band capable of transmitting data to an open-source platform. In this work, we developed an application to capture this information in real-time, and conducted three usability studies in two mixed-aged groups of participants (n=6 each) and a group of older adults with obesity participating in a weight-loss intervention (n=20). The system was favorable, acceptable and provided iterative information that could assist in future deployment on ubiquitous platforms. Our formative work provides the foundation to deliver home-based monitoring interventions in a high-risk, older adult population.

Keywords: application, mHealth, older adult, resistance exercise band, sarcopenia

Procedia PDF Downloads 174

Authors: Ramzi Rihane, Yassine Benayed

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Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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Authors: Yueying Chen

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A city can be developed through memory, and memory is one of the most important elements for urban contexts. Collective memory is a collection of personal memories that can be preserved with objects, places, and events of heritage, expressing culture through spatial changes. These preserved forms can evoke a sense of community and certain emotions. Collective memory in cities reflects urban spatial alterations and historical developments. It can be preserved and reflected by revitalisation projects. A major current focus in collective memory research is how to identify and preserve memory in an intangible way. The influential elements within the preservation of collective memory mainly include institutions and objects. However, current research lacks the assessment of the collective memory after alterations of urban heritage. The assessment of urban heritage lacks visualization and qualitative methods. The emergence of the application of space syntax can fill in this gap. Hengshan Mansions was a new project in 2015. The original residential area has been replaced with a comprehensive commercial area integrating boutique shopping, upscale restaurants, and creative offices. Hengshan Mansions is located in the largest historic area in Shanghai, and its development is the epitome of the traditional culture in Shanghai. Its alteration is the newest project in this area and presents the new concept of revitalisation of urban heritage. For its physical parts, modern vitality is created, and historical information is preserved at the same time. However, most of the local people are moved away, and its functions are altered a lot. The preservation of its collective memory needs to discuss furtherly. Thus, the article builds a framework to assess the collective memory of urban heritage, including spatial configuration, spatial interaction, and cultural cognition. Then, it selects Hengshan Mansions in Shanghai as a case to analyse the assessed framework. Space syntax can be applied to visualize the assessment. Based on the analysis, the article will explore the influential reasons for the collective memory after alterations and proposes relevant advice for the preservation of the collective memory of urban heritage.

Keywords: collective memory, alternation of urban heritage, space syntax, Hengshan Mansions

Procedia PDF Downloads 140

Authors: Priyanka Yadav, Rajkumar Ghosh, Alok Saini

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Human civilization cannot exist and thrive in the absence of adequate water. As a result, even in smart cities, water plays an important role in human existence. The key causes of this catastrophic water scarcity crisis are lifestyle changes, over-exploitation of groundwater, water over usage, rapid urbanization, and uncontrolled population growth. Furthermore, salty water seeps into deeper aquifers, causing land subsidence. The purpose of this study on artificial groundwater recharge is to address the water shortage in Gomti Nagar, Lucknow. Submersibles are the most common methods of collecting freshwater from groundwater in Gomti Nagar neighbourhood of Lucknow. Gomti Nagar area has a groundwater depletion rate of 1968 m3/day/km2 and is categorized as Zone-A (very high levels) based on the existing groundwater abstraction pattern - A to D. Harvesting rainwater using roof top rainwater harvesting systems (RTRWHs) is an effective method for reducing aquifer depletion in a sustainable water management system. Rainwater collecting using roof top rainwater harvesting systems (RTRWHs) is an effective method for reducing aquifer depletion in a sustainable water conservation system. Due to a water imbalance of 24519 ML/yr, the Gomti Nagar region is facing severe groundwater depletion. According to the Lucknow Development Authority (LDA), the impact of installed RTRWHs (plot area 300 sq. m.) is 0.04 percent of rainfall collected through RTRWHs in Gomti Nagar region of Lucknow. When RTRWHs are deployed in all buildings, their influence will be greater. Bye-laws in India have mandated the installation of RTRWHs on plots greater than 300 sq.m. A better India without any water problem is a pipe dream that may be realized by installing residential and commercial rooftop rainwater collecting systems in every structure. According to the current study, RTRWHs should be used as an alternate source of water to bridge the gap between groundwater recharge and extraction in smart city viz. Gomti Nagar, Lucknow, India.

Keywords: groundwater recharge, RTRWHs, harvested rainwater, rainfall, water extraction

Procedia PDF Downloads 108

Authors: Parul Kapoor, Dheeraj Bhardwaj

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Delhi and other Indian cities accommodate thousands of Central Government employees in housing complexes called ‘General Pool Residential Accommodation’ (GPRA), located in prime parcels of the city. These residential colonies are now undergoing redevelopment at a massive scale, significantly impacting the ecology of the surrounding areas. Essentially, these colonies were low-rise, low-density planned developments with a dense tree cover and minimal parking requirements. But with increasing urbanisation and spike in parking demand, the proposed built form is an aggregate of high-rise gated complexes, redefining the skyline of the city which is a huge departure from the mediocre setup of Low-rise Walk-up apartments. The complexity of these developments is further aggravated by the need for parking which necessitates cutting huge number of trees to accommodate multiple layers of parking beneath the structures thus sidelining the authentic character of these areas which is laden with a dense tree cover. The aftermath of this whole process is the generation of a huge carbon footprint on the surrounding areas, which is unaccounted for, in the planning and design practice. These developments are currently planned as mix-use compounds with large commercial built-up spaces which have additional parking requirements over and above the residential parking. Also, they are perceived as gated complexes and not as neighborhood units, thus project isolated images of high-rise, dense systems with little context to the surroundings. The paper would analyze case studies of GPRA Redevelopment projects in Delhi, and the lack of relevant development control regulations which have led to abnormalities and complications in the entire redevelopment process. It would also suggest policy guidelines which can establish comprehensive codes for effective planning of these settlements.

Keywords: gated complexes, GPRA Redevelopment projects, increased densities, huge carbon footprint, mixed-use development

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Authors: Mahmoud Abdelrazig Mahmoud Barakat

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Achievement tests administered at national level play a significant role in the lives of test-takers as well as the whole society. This paper aims to investigate the effect of giving students a choice between two optional questions on their overall performance in a high stake achievement test for university admission. It is hypothesized that questions targeting writing-based productive skills and language system necessitate display of abilities which are different from fact-based questions designed around story content. The two items are assumed to reflect different constructs that require different criteria of assessment. Consequently, the student’s overall score is affected by the item they choose to answer, which might not be reflective of their real language abilities. An open-ended interview was carried out with ten teachers working with grade 3 students in model secondary schools to investigate the nature of the two test items and their impact on the student’s performance. The data has proved that giving choice in an achievement test generates different performances that are assessed differently. It is recommended that in order to address the question of fairness, it is important to clearly define and balance the construct of the items that affect the student’s choice and performance.

Keywords: achievement test, assessment, choice, fairness performance

Procedia PDF Downloads 222

Authors: David Nieto Simavilla, Wilco M. H. Verbeeten

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The viscoelastic behavior of polymeric flows under isothermal conditions has been extensively researched. However, most of the processing of polymeric materials occurs under non-isothermal conditions and understanding the linkage between the thermo-physical properties and the process state variables remains a challenge. Furthermore, the cost and energy required to manufacture, recycle and dispose polymers is strongly affected by the thermo-physical properties and their dependence on state variables such as temperature and stress. Experiments show that thermal conductivity in flowing polymers is anisotropic (i.e. direction dependent). This phenomenon has been previously omitted in the study and simulation of industrially relevant flows. Our work combines experimental evidence of a universal relationship between thermal conductivity and stress tensors (i.e. the stress-thermal rule) with differential constitutive equations for the viscoelastic behavior of polymers to provide predictions for the anisotropy in thermal conductivity in uniaxial, planar, equibiaxial and shear flow in commercial polymers. A particular focus is placed on the eXtended Pom-Pom model which is able to capture the non-linear behavior in both shear and elongation flows. The predictions provided by this approach are amenable to implementation in finite elements packages, since viscoelastic and thermal behavior can be described by a single equation. Our results include predictions for flow-induced anisotropy in thermal conductivity for low and high density polyethylene as well as confirmation of our method through comparison with a number of thermoplastic systems for which measurements of anisotropy in thermal conductivity are available. Remarkably, this approach allows for universal predictions of anisotropy in thermal conductivity that can be used in simulations of complex flows in which only the most fundamental rheological behavior of the material has been previously characterized (i.e. there is no need for additional adjusting parameters other than those in the constitutive model). Accounting for polymers anisotropy in thermal conductivity in industrially relevant flows benefits the optimization of manufacturing processes as well as the mechanical and thermal performance of finalized plastic products during use.

Keywords: anisotropy, differential constitutive models, flow simulations in polymers, thermal conductivity

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Authors: Manu Manu, Pardha J. Saradhi, Ramana M. V. Murthy

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Wind Energy is accepted as one of the most developed, cost effective and proven renewable energy technologies to meet increasing electricity demands in a sustainable manner. Preliminary assessment studies along Indian Coastline by Ministry of New and Renewable Energy have indicated prospects for development of offshore wind power along Tamil Nadu Coast, India. The commercial viability of a wind project mainly depends on wind characteristics on site. Hence, it is internationally recommended to perform site-specific wind resource assessment based on two years’ wind profile as a part of the feasibility study. Conventionally, guy wire met mast are used onshore for the collection of wind profile. Installation of similar structure in offshore requires complex marine spread and are very expensive. In the present study, an attempt is made to develop 120 m long lattice tower supported on the jacket, piled to the seabed at Rameshwaram, Tamil Nadu, India. Offshore met-masts are subjected to combined wind and hydrodynamic loads, and these lateral loads should be safely transferred to soil. The wind loads are estimated based on gust factor method, and the hydrodynamic loads are estimated by Morison’s equation along with suitable wave theory. The soil is modeled as three nonlinear orthogonal springs based on API standards. The structure configuration and optimum member sizes are obtained for extreme cyclone events. The dynamic behavior of mast under coupled wind and wave loads is also studied. The static responses of a mast with jacket type offshore platform have been studied using a frame model in SESAM. It is found from the study that the maximum displacement at the top of the mast for the random wave is 0.003 m and that of the tower for wind is 0.08 m during the steady state. The dynamic analysis results indicate that the structure is safe against coupled wind and wave loading.

Keywords: offshore wind, mast, static, aerodynamic load, hydrodynamic load

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Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

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Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

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Authors: Romisaa Ali

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This paper presents a comparison between twin-delayed Deep Deterministic Policy Gradient (TD3) and Soft Actor-Critic (SAC) reinforcement learning algorithms in the context of training robust navigation policies for Jackal robots. By leveraging an open-source framework and custom motion control environments, the study evaluates the performance, robustness, and transferability of the trained policies across a range of scenarios. The primary focus of the experiments is to assess the training process, the adaptability of the algorithms, and the robot’s ability to navigate in previously unseen environments. Moreover, the paper examines the influence of varying environmental complexities on the learning process and the generalization capabilities of the resulting policies. The results of this study aim to inform and guide the development of more efficient and practical reinforcement learning-based navigation policies for Jackal robots in real-world scenarios.

Keywords: Jackal robot environments, reinforcement learning, TD3, SAC, robust navigation, transferability, custom environment

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Authors: Paul Hernandez-Herrera, Fernando Montoya, Juan Manuel Rendon, Alberto Darszon, Gabriel Corkidi

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Intracellular calcium ([Ca2+]i) regulates sperm motility. The analysis of [Ca2+]i has been traditionally achieved in two dimensions while the real movement of the cell takes place in three spatial dimensions. Due to optical limitations (high speed cell movement and low light emission) important data concerning the three dimensional movement of these flagellated cells had been neglected. Visualizing [Ca2+]i in 3D is not a simple matter since it requires complex fluorescence microscopy techniques where the resulting images have very low intensity and consequently low SNR (Signal to Noise Ratio). In 4D sequences, this problem is magnified since the flagellum oscillates (for human sperm) at least at an average frequency of 15 Hz. In this paper, a novel approach to extract the flagellum’s center-line in 4D stacks is presented. For this purpose, an iterative algorithm based on the fast-marching method is proposed to extract the flagellum’s center-line. Quantitative and qualitative results are presented in a 4D stack to demonstrate the ability of the proposed algorithm to trace the flagellum’s center-line. The method reached a precision and recall of 0.96 as compared with a semi-manual method.

Keywords: flagellum, minimal path, segmentation, sperm

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Authors: Komala Arsi, Terrel Spencer, Casey M. Owens, Dan J. Donoghue, Ann M. Donoghue

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Organic poultry production is becoming increasingly popular in the United States with approximately 17% increase in the sales of organic meat and poultry in 2016. As per the National Organic Program (NOP), organic poultry production system should operate according to specific standards, including access to outdoors. In the United States, organic poultry farmers are raising both fast growing and slow growing genotypes for alternative productive systems. Even though heritage breed birds grow much slower compared to commercial breeds, many free range producers believe that they are better suited for outdoor production systems. We conducted an on-farm trial on a working pasture poultry farm to compare the performance and meat quality characteristics of a slow-growing heritage breed (Freedom Rangers, FR), and two commonly used fast growing types of chickens (Cornish cross, CC and Naked Neck, NN), raised on pasture, in side by side pens segregated by breed (n=70/breed). CC and NN group birds were reared for eight weeks whereas FR group birds were reared for 10 weeks and all the birds were commercially processed. By the end of the rearing period, the final body weight of FR group birds was significantly lower than both the fast growing genotypes (CC and NN). Both CC and NN birds showed significantly higher live weight, carcass weight as well as fillet, tender and leg yield (P < 0.05). There was no difference in the wing and rack yield among the different groups. Color of the meat was measured using CEILAB method and expressed as lightness (L), redness (a*) and yellowness (b*). The breast meat from FR birds was much redder (higher a* values) and less yellow (lesser b* values) compared to both the fast growing type of chickens (P < 0.05). Overall, fast growing genotypes produced higher carcass weight and meat yield compared to slow growing genotypes and appear to be an economical option for alternative production systems.

Keywords: fast growing chickens, meat quality, pasture, slow growing chickens

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Gerson E. Cornejo, Luis A. Gamarra, David S. Mauricio

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The Enterprise Resource Planning Systems (ERP) allows the integration of all the business processes of the functional areas of the companies, in order to automate and standardize the processes, obtain accurate information and improve decision making in time real. In Peru, 79% of medium and small companies (SMEs) do not use any management software, this is because it is believed that ERPs are expensive, complex and difficult to implement. However, for more than 20 years there have been Open Source ERPs, which are more accessible and have the same benefit as proprietary ERPs, but there is little information on the implementation process. In this work is made a case of study, in order to show the implementation process of an Open Source ERP, Odoo, based on the ASAP methodology (Accelerated SAP) and applied to a company of corrective and preventive maintenance services of vehicles. The ERP allowed the SME to standardize its business processes, increase its productivity, reducing up to 40% certain processes. The study of this case shows that it is feasible and profitable to implement an Open Source ERP in SMEs in the Automotive Sector of Peru. In addition, it is shown that the ASAP methodology is adequate to carry out Open Source ERPs implementation projects.

Keywords: ASAP, automotive sector, ERP implementation, open source

Procedia PDF Downloads 336

Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

Abstract:

The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: distillation, machine learning, neural networks, quantization

Procedia PDF Downloads 325

Authors: Manisha Choudhary, Sudarsan Neogi

Abstract:

Malachite green (MG), an organic basic dye, has been widely used for the dyeing purpose, as well as a fungicide and antiseptic in aquaculture industry to control fish parasites and disease. However, MG has now turned out to be an extremely controversial compound due to its adverse impact on living beings. Due to high toxicity, proper treatment of wastewater containing MG is utmost important. Among different available technologies, adsorption process is one of the most efficient and cost-effective treatment method due to its simplicity of design, ease of operation and regeneration of used materials. Nonetheless, commercial activated carbon is expensive leading the researchers to focus on utilizing natural resources. In the present work, a species of cactus, Opuntia ficus-indica (OFI), was used to develop a highly efficient, low-cost powdered activated carbon by chemical activation using NaOH. The biosorbent was characterized by Fourier-transform infrared spectroscopy, field emission scanning electron microscope, energy-dispersive X-ray spectroscopy, Brunauer–Emmett–Teller (BET) and X-ray diffraction analysis. Batch adsorption studies were performed to remove MG from an aqueous solution as a function of contact time, initial solution pH, initial dye concentration, biosorbent dosages, the presence of salt and temperature. By increasing the initial dye concentration from 100 to 500 mg/l, adsorption capacity increased from 165.45 to 831.58 mg/g. The adsorption kinetics followed the pseudo-second-order model and the chemisorption mechanisms were revealed. The electrostatic attractions and chemical interactions were observed between amino and hydroxyl groups of the biosorbent and amine groups of the dye. The adsorption was solely controlled by film diffusion. Different isotherm models were used to fit the adsorption data. The excellent recovery of adsorption efficiency after the regeneration of biosorbent indicated the high potential of this adsorbent to remove MG from aqueous solution and an excellent cost-effective biosorbent for wide application in wastewater treatment.

Keywords: adsorption, biosorbent, cactus, malachite green

Procedia PDF Downloads 374

Authors: Chiang-Ho Cheng, An-Shik Yang, Hon-Yi Cheng, Ming-Yu Lai

Abstract:

This paper presents the design and fabrication of a novel piezoelectric actuator for a gas micropump with check valve having the advantages of miniature size, light weight and low power consumption. The micropump is designed to have eight major components, namely a stainless steel upper cover layer, a piezoelectric actuator, a stainless steel diaphragm, a PDMS chamber layer, two stainless steel channel layers with two valve seats, a PDMS check valve layer with two cantilever-type check valves and an acrylic substrate. A prototype of the gas micropump, with a size of 52 mm × 50 mm × 5.0 mm, is fabricated by precise manufacturing. This device is designed to pump gases with the capability of performing the self-priming and bubble-tolerant work mode by maximizing the stroke volume of the membrane as well as the compression ratio via minimization of the dead volume of the micropump chamber and channel. By experiment apparatus setup, we can get the real-time values of the flow rate of micropump and the displacement of the piezoelectric actuator, simultaneously. The gas micropump obtained higher output performance under the sinusoidal waveform of 250 Vpp. The micropump achieved the maximum pumping rates of 1185 ml/min and back pressure of 7.14 kPa at the corresponding frequency of 120 and 50 Hz.

Keywords: PDMS, check valve, micropump, piezoelectric

Procedia PDF Downloads 456

Authors: Martina Drdlová, Michal Frank, Radek Řídký, Jaroslav Buchar, Josef Krátký

Abstract:

The main aim of the presented experiments is to improve behaviour of sandwich structures under dynamic loading, such as crash or explosion. This paper describes experimental investigation on the response of new advanced materials to low and high velocity load. Blast wave energy absorbers were designed using two types of porous lightweight raw particle materials based on expanded glass and ceramics with dimensions of 0.5-1 mm, combined with polymeric binder. The effect of binder amount on the static and dynamic properties of designed materials was observed. Prism shaped specimens were prepared and loaded to obtain physico-mechanical parameters – bulk density, compressive and flexural strength under quasistatic load, the dynamic response was determined using Split Hopkinson Pressure bar apparatus. Numerical investigation of the material behaviour in sandwich structure was performed using implicit/explicit solver LS-Dyna. As the last step, the developed material was used as the interlayer of blast resistant litter bin, and it´s functionality was verified by real field blast tests.

Keywords: blast energy absorber, SHPB, expanded glass, expanded ceramics

Procedia PDF Downloads 458