Search results for: project progress prediction

Authors: Ninlawat Phuangchoke, Waraporn Viyanon, Setta Sasananan

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The most important process of the water treatment plant process is the coagulation using alum and poly aluminum chloride (PACL), and the value of usage per day is a hundred thousand baht. Therefore, determining the dosage of alum and PACL are the most important factors to be prescribed. Water production is economical and valuable. This research applies an artificial neural network (ANN), which uses the Levenberg–Marquardt algorithm to create a mathematical model (Soft Jar Test) for prediction chemical dose used to coagulation such as alum and PACL, which input data consists of turbidity, pH, alkalinity, conductivity, and, oxygen consumption (OC) of Bangkhen water treatment plant (BKWTP) Metropolitan Waterworks Authority. The data collected from 1 January 2019 to 31 December 2019 cover changing seasons of Thailand. The input data of ANN is divided into three groups training set, test set, and validation set, which the best model performance with a coefficient of determination and mean absolute error of alum are 0.73, 3.18, and PACL is 0.59, 3.21 respectively.

Keywords: soft jar test, jar test, water treatment plant process, artificial neural network

Procedia PDF Downloads 166

Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

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Authors: Wajid Ali Khan

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Extensive experimentation and numerical investigation are performed to predict the machining-induced residual stresses in the end milling of AISI 1045 steel, and an optimization code has been developed using the particle swarm optimization technique. Experiments were conducted using a single factor at a time and design of experiments approach. Regression analysis was done, and a mathematical model of the cutting process was developed, thus predicting the machining-induced residual stress with reasonable accuracy. The mathematical model served as the objective function to be optimized using particle swarm optimization. The relationship between the different cutting parameters and the output variables, force, and residual stresses has been studied. The combined effect of the process parameters, speed, feed, and depth of cut was examined, and it is understood that 85% of the variation of these variables can be attributed to these machining parameters under research. A 3D finite element model is developed to predict the cutting forces and the machining-induced residual stresses in end milling operation. The results were validated experimentally and against the Johnson-cook model available in the literature.

Keywords: residual stresses, end milling, 1045 steel, optimization

Procedia PDF Downloads 102

Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

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Authors: Ashkan Shafee, Ahamd Fahimifar, Sajjad V. Maghvan

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Promotion of the Fiber Reinforced Concrete (FRC) as a construction material for civil engineering projects has invoked numerous researchers to investigate their mechanical behavior. Even though there is satisfactory information about the effects of fiber type and length, concrete mixture, casting type and other variables on the strength and deformability parameters of FRC, the numerical modeling of such materials still needs research attention. The focus of this study is to investigate the feasibility of Concrete Damaged Plasticity (CDP) model in prediction of Macro-synthetic FRC structures behavior. CDP model requires the tensile behavior of concrete to be well characterized. For this purpose, a series of uniaxial direct tension and four point bending tests were conducted on the notched specimens to define bilinear tension softening (post-peak tension stress-strain) behavior. With these parameters obtained, the flexural behavior of macro-synthetic FRC beams were modeled and the results showed a good agreement with the experimental measurements.

Keywords: concrete damaged plasticity, fiber reinforced concrete, finite element modeling, macro-synthetic fibers, uniaxial tensile test

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Authors: Fatma Al Abdullah, Shahad Al Ameer, Ritaj Jaragh, Fatimah Khajah, Rawan Qambar, Amr Nounou

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Kuwait currently manufactures its tankers in foreign countries. Oil tankers play a role in the supply chain of the oil industry. Therefore, with Kuwait’s sufficient financial resources, the country should secure itself strategically in order to protect its oil industry to sustain economic development. The purpose of this report is designing an oil tankers’ shipyard facility. Basing the shipyard facility in Kuwait will have great economic rewards. The shipbuilding industry directly enhances the industrial chain in terms of new job and business opportunities as well as educational fields. Heavy Engineering Industries & Shipbuilding Co. K.S.C. (HEISCO) was chosen as a host due to benefits that will result from HEISCO’s existing infrastructure and expertise to reduce cost. The Facility Design methodology chosen has been used because it covers all aspects needed for the report. The oil tanker market is witnessing a shift from crude tankers to product tankers. Therefore the Panamax tanker (product tanker) was selected to be manufactured in the facility. The different departments needed in shipyards were identified based on studying different global shipyards. Technologies needed to build ships helped in the process design. It was noticed that ships are engineer to order. The new layout development of the proposed shipyard is currently in progress. A feasibility study will be conducted to ensure the success of the facility after developing the shipyard’s layout.

Keywords: oil tankers, shipbuilding, shipyard, facility design, Kuwait

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.

Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: Jui-Chien Hsieh

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Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

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Authors: Ezomoh O. Olubunmi, Chukwuma S. Anakwe, Bekewei Progress, Prohp The Prophet

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Benzene is a volatile organic compound that is recognised as carcinogenic to humans. The objective of the current investigation was to ascertain the impact of the administration of benzene at varying concentrations on the livers of Wistar rats. The 40 adult female Wistar rats were divided into 10 groups, each consisting of four rats. For 28 days, Group 1 received distilled water, while Groups 2 to 10 were administered 0.04,0.06,0.08,0.2,0.4,0.6,0.8,1.0, and 1.2 ml/kg body weight of analytical grade benzene. Blood samples were obtained through cardiac puncture for liver function assessment, while the animals in groups 1 to 5 were euthanised after the 28th day under chloroform anaesthesia. The animals in groups 6 to 10 died midway through the study period. Antioxidant analysis was conducted on liver tissues that were collected and homogenised. The results indicated a substantial (p<0.05), dose-dependent increase in serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), and alkaline phosphatase (ALP) activities as a result of benzene exposure. Additionally, benzene resulted in a substantial reduction in the activities of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GPx) in liver tissue, as well as an increase in malondialdehyde (MDA) concentrations, and this effect was dose-dependent. These findings emphasise the hepatotoxic effects of benzene, even at concentrations that are relatively low.

Keywords: benzene, alanine aminotransferase, aspartate aminotransferase, alkaline phosphate, antioxidants, superoxide dismutase, catalase, glutathione peroxidase

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Authors: Vishwas Goel, Kapil Surve, Somnath Basu

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In-situ alloying in steel during the electro-slag remelting (ESR) process has already been achieved by the addition of necessary ferroalloys into the electro-slag remelting mold. However, the use of commercially available ferroalloys during ESR processing is often found to be financially less favorable, in comparison with the conventional alloying techniques. However, a process of alloying steel with elements like chromium and manganese using the electro-slag remelting route is under development without any ferrochrome addition. The process utilizes in-situ reduction of refined mineral chromite (Cr₂O₃) and resultant enrichment of chromium in the steel ingot produced. It was established in course of this work that this process can become more advantageous over conventional alloying techniques, both economically and environmentally, for applications which inherently demand the use of the electro-slag remelting process, such as manufacturing of superalloys. A key advantage is the lower overall CO₂ footprint of this process relative to the conventional route of production, storage, and the addition of ferrochrome. In addition to experimentally validating the feasibility of the envisaged reactions, a mathematical model to simulate the reduction of chromium (III) oxide and transfer to chromium to the molten steel droplets was also developed as part of the current work. The developed model helps to correlate the amount of chromite input and the magnitude of chromium alloying that can be achieved through this process. Experiments are in progress to validate the predictions made by this model and to fine-tune its parameters.

Keywords: alloying element, chromite, electro-slag remelting, ferrochrome

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Authors: Sajjad Negahban, Ruihe Wang, Baojiang Sun

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Gas-lift dual gradient drilling is a solution for deepwater drilling challenges. As well, Continuous development of drilling technology leads to increase employment of mineral oil based drilling fluids and synthetic-based drilling fluids, which have adequate characteristics such as: high rate of penetration, lubricity, shale inhibition and low toxicity. The paper discusses utilization of nitrified mineral oil base drilling for deepwater drilling and for more accurate prediction of pressure in DGD at marine riser, solubility and bubble pressure were considered in steady state hydraulic model. The Standing bubble pressure and solubility correlations, and two models which were acquired from experimental determination were applied in hydraulic model. The effect of the black oil correlations, and new solubility and bubble pressure models was evaluated on the PVT parameters such as oil formation volume factor, density, viscosity, volumetric flow rate. Eventually, the consequent simulated pressure profile due to these models was presented.

Keywords: solubility, bubble pressure, gas-lift dual gradient drilling, steady state hydraulic model

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Authors: Hatice Yildirim

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This study is an investigation into ‘The role of teaching assistants (TAs) for deaf pupils in an English primary school’, in order not only to contribute to the education of deaf pupils but also contribute to the literature, in which there has been a lack of attention paid to the role of TAs for deaf pupils. With this in mind, the research design was planned based on using a case study as a qualitative research approach in order to have a deep and first-hand understanding of the case for ‘the role of TAs for deaf pupils’ in a real-life context. 12 semi-structured classroom observations and six semi-structured interviews were carried out with four TAs and two teachers in one English mainstream primary school. The data analysis followed a thematic analysis framework. The results indicated that TAs are utilised based on a one-on-one support model and are deployed under the class teacher in the classroom. Out of the classroom activities are carried out in small groups with the agreement of the TAs and the class teacher, as per the policy of the school. Due to the one-on-one TA support model, the study pointed out the seven different roles carried out by TAs in the education of deaf pupils in an English mainstream primary school. While supporting deaf pupils academically and socially are the main roles of TAs, they also support deaf pupils by recording their progress, communicating with their parents, taking on a pastoral care role, tutoring them in additional support lessons, and raising awareness of deaf pupils’ issues.

Keywords: deaf, mainstream, teaching assistant, teaching assistant's roles

Procedia PDF Downloads 212

Authors: Gajaanuja Megalathan, Banuka Athuraliya

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Crime is one of our society's most intimidating and threatening challenges. With the majority of the population residing in cities, many experts and data provided by local authorities suggest a rapid increase in the number of crimes committed in these cities in recent years. There has been an increasing graph in the crime rates. People living in Sri Lanka have the right to know the exact crime rates and the crime rates in the future of the place they are living in. Due to the current economic crisis, crime rates have spiked. There have been so many thefts and murders recorded within the last 6-10 months. Although there are many sources to find out, there is no solid way of searching and finding out the safety of the place. Due to all these reasons, there is a need for the public to feel safe when they are introduced to new places. Through this research, the author aims to develop a mobile application that will be a solution to this problem. It is mainly targeted at tourists, and people who recently relocated will gain advantage of this application. Moreover, the Arima Model combined with ANN is to be used to predict crime rates. From the past researchers' works, it is evidently clear that they haven’t used the Arima model combined with Artificial Neural Networks to forecast crimes.

Keywords: arima model, ANN, crime prediction, data analysis

Procedia PDF Downloads 132

Authors: Linda Jane Wells

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In 1914 Topsy Smith, a woman of the First Nations Arabana tribe arrived in Alice Springs with her seven children and a herd of goats. They had come in from the goldfields at Arltunga where they had been living, and Topsy’s husband, Welsh-born Bill Smith, had recently died. Sergeant Stott, the local policeman and sub-protector of Aborigines for the region, erected a tin shed for Topsy and the children to live in, which became known as the Bungalow for half-castes. Over the years that followed many more children of mixed descent were removed from their families and brought to live at the Bungalow until, a decade later, sixty children were growing up there, cared for predominantly by Topsy Smith; Ida Standley who was the first, white schoolteacher for the town; and Sergeant Stott. The story of the Bungalow is pivotal to the foundations of social relations in the town of Alice Springs and beyond. At the same time, it is little known, recognised or understood locally, let alone more broadly. This is typical of the dominant historic narratives that have emerged out of the Australian colonial project and led to ‘the Great Australian Silence.’ The term was coined by Australian anthropologist WEH Stanner in his 1968 Boyer Lectures, in reference to the omission of the Aboriginal experience from the dominant narratives of the nation’s history. In his lecture, he attributed this silence to something that may have begun as a simple forgetting of other possible views which turned, under habit and over time, into something like a cult of forgetfulness practised on a national scale. This doctoral project, underpinned by a methodology of practice-led research, engages a bricolage of methods including archival research, ethnography, and oral histories to research the bungalow and the context in which it operated. Techniques of fictocriticism, speculative biography, autoethnography, and archival poetics are then engaged to write the research outcomes into a post-colonial, multi-genre work of creative non-fiction that speaks into the silences in the archives. The overall intent of this doctoral work is to explore and demonstrate how techniques of creative non-fiction can be used to rewrite narratives of Australian colonial history that resonate beyond the academy, thus contributing to the bank of post-colonial stories and working towards a more just, honest and inclusive national ‘memory’ and identity.

Keywords: Australian history, collective memory, creative non-fiction, postcolonialism

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: Gyo Woo Lee, Man Young Kim

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A mathematical heat transfer model for the prediction of transient heating of the slab in a direct-fired walking beam type reheating furnace has been developed by considering the nongray thermal radiation with given furnace environments. The furnace is modeled as radiating nongray medium with carbon dioxide and water with five-zoned gas temperature and the furnace wall is considered as a constant temperature lower than furnace gas one. The slabs are moving with constant velocity depending on the residence time through the non-firing, charging, preheating, heating, and final soaking zones. Radiative heat flux obtained by considering the radiative heat exchange inside the furnace as well as convective one from the surrounding hot gases are introduced as boundary condition of the transient heat conduction within the slab. After validating thermal radiation model adopted in this work, thermal fields in both model and real reheating furnace are investigated in terms of radiative heat flux in the furnace and temperature inside the slab. The results show that the slab in the furnace can be more heated with higher slab emissivity and residence time.

Keywords: reheating furnace, steel slab, radiative heat transfer, WSGGM, emissivity, residence time

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Authors: Raana Babadi Fathipour

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Food packaging plays a crucial role in protecting food from unwanted external factors. Antibacterial edible films are a promising option for food packaging due to their biodegradability, environmental friendliness, and safety. This paper reviews recent research progress on antimicrobial edible films, focusing on those made from polysaccharides, proteins, and lipids. Polysaccharides and proteins are the primary components of antimicrobial edible films, while lipids primarily serve as plasticizers and carriers for active substances in composite films. For instance, second-generation liposomes have shown great potential as carriers for antimicrobial substances and other bioactive compounds due to their exceptional stability. Furthermore, this paper analyzes recent advancements and future trends in antimicrobial edible films. One promising direction is the integration of antimicrobial edible film materials with delivery systems, such as nanoemulsion and microencapsulation technologies, to ensure stable loading of bioactive substances. Another emerging area of interest is the development of smart and active packaging that allows consumers to assess the freshness of food products without opening the package. pH-sensitive films and smart fluorescent "on-off" sensors for humidity are currently being explored as materials for smart and active packaging to monitor food product freshness, with further exploration anticipated in the future.

Keywords: antimicrobial edible film, biopolymer, antimicrobial agent, encapsulation, antimicrobial assay

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Authors: Andrew John Zeller, Francis Pouatcha

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Working according to the DevOps principle has gained in popularity over the past decade. While its extension DevSecOps started to include elements of cybersecurity, most real-life projects do not focus risk and security until the later phases of a project as teams are often more familiar with engineering and infrastructure services. To help bridge the gap between security and engineering, this paper will take six building blocks of cybersecurity and apply them to the DevOps approach. After giving a brief overview of the stages in the DevOps lifecycle, the main part discusses to what extent six cybersecurity blocks can be utilized in various stages of the lifecycle. The paper concludes with an outlook on how to stay up to date in the dynamic world of cybersecurity.

Keywords: information security, data security, cybersecurity, devOps, IT management

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Authors: Samia Rabet, Rachida Chemini, Gerhard Schäfer, Farid Aiouache

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The textile industry generates large quantities of wastewater, which poses significant environmental problems due to its complex composition and high levels of pollutants loaded principally with heavy metals, large amounts of COD, and dye. Separation treatment methods are often known for their effectiveness in removing contaminants whereas membrane separation techniques are a promising process for the treatment of textile effluent due to their versatility, efficiency, and low energy requirements. This study focuses on the modeling and simulation of membrane separation technologies with a cross-flow filtration process for textile effluent treatment. It aims to explore the application of mathematical models and computational simulations using ASPEN Plus Software in the prediction of a complex and real effluent separation. The results demonstrate the effectiveness of modeling and simulation techniques in predicting pollutant removal efficiencies with a global deviation percentage of 1.83% between experimental and simulated results; membrane fouling behavior, and overall process performance (hydraulic resistance, membrane porosity) were also estimated and indicating that the membrane losses 10% of its efficiency after 40 min of working.

Keywords: membrane separation, ultrafiltration, textile effluent, modeling, simulation

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Authors: Khadija Amin

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The significant contribution of foreign investment in promoting economic recovery, especially in countries recovering from conflict, is generally recognized. This study examines the influence of foreign investment on the economic development of countries that have had long-lasting internal conflicts. The study examines the complex correlation between foreign investment and economic progress using the production function framework based on endogenous growth theory. In addition to foreign investment, the research considers a range of factors that affect economic growth, such as trade dynamics, the spread of information, attempts to promote peace, changes in the labor market, and the accumulation of domestic capital. The study challenges common beliefs by revealing a statistically negligible negative association between GDP growth and foreign investment (FI) inflows in post-war economies. The existing literature highlights the positive impact of trade and foreign investment on economic growth. However, this study emphasizes that these impacts are complex and depend on various contextual factors such as trade policies, infrastructure development, domestic investment levels, human capital development, and macroeconomic stability. The results emphasize the crucial significance of foreign investment in stimulating development while also drawing attention to the intricacies of precisely assessing its economic consequences. Measuring the economic impact of foreign investment is a difficult task that requires detailed analysis considering many contextual elements and changing socioeconomic conditions.

Keywords: economic grouths, foreign investment, trade policies, domestic investment

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Authors: Igor Peraza Curiel, Suzanne Strum

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Today, when many foreign architects are receiving commissions in the United Arab Emirates, it is essential to analyze how their designs are influenced by the region's culture, environment, and building traditions. This study examines the approach to siting, geometry, construction methods, and material choices in two private homes for a family in Dubai, a project being constructed on adjacent sites by the acclaimed Spanish team of RCR Architects. Their third project in Dubai, the houses mark a turning point in their design approach to the desert. The Pritzker Prize-winning architects of RCR gained renown for building works deeply responsive to the history, landscape, and customs of their hometown in a volcanic area of the Catalonia region of Spain. Key formative projects and their entry to practice in UAE will be analyzed according to the concepts of place identity, the poetics of construction, and material imagination. The poetics of construction, a theoretical position with a long practical tradition, was revived by the British critic Kenneth Frampton. The idea of architecture as a constructional craft is related to the concepts of material imagination and place identity--phenomenological concerns with the creative engagement with local matter and topography that are at the very essence of RCR's way of designing, detailing, and making. Our study situates RCR within the challenges of building in the region, where western forms and means have largely replaced the ingenious responsiveness of indigenous architecture to the climate and material scarcity. The dwellings, iterations of the same steel and concrete vaulting system, highlight the conceptual framework of RCR's design approach to offer a study in contemporary critical regionalism. The Kama House evokes Bedouin tents, while the Alwah House takes the form of desert dunes in response to the temporality of the winds. Metal mesh screens designed to capture the shifting sands will complete the forms. The original research draws on interviews with the architects and unique documentation provided by them and collected by the authors during on-site visits. By examining the two houses in-depth, this paper foregrounds a series of timely questions: 1) What is the impact of the local climatic, cultural, and material conditions on their project in the UAE? 2) How does this work further their experiences in the region? 3) How has RCR adapted their construction techniques as their work expands beyond familiar settings? The investigation seeks to understand how the design methodology developed for more than 20 years and enmeshed in the regional milieu of their hometown can transform as the architects encounter unique characteristics and values in the Middle East. By focusing on the contemporary interpretation of Arabic geometry and elements, the houses reveal the role of geometry, tectonics, and material specificity in the realization from conceptual sketches to built form. In emphasizing the importance of regional responsiveness, the dynamics of international construction practice, and detailing this study highlights essential issues for professionals and students looking to practice in an increasingly global market.

Keywords: material imagination, regional responsiveness, place identity, poetics of construction

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Authors: Beilei Xu, Wencheng Wu, Lei Lin, Rachel Melnyk, Ahmed Ghazi

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In operating rooms, excessive cognitive stress can impede the performance of a surgeon, while low engagement can lead to unavoidable mistakes due to complacency. As a consequence, there is a strong desire in the surgical community to be able to monitor and quantify the cognitive stress of a surgeon while performing surgical procedures. Quantitative cognitiveload-based feedback can also provide valuable insights during surgical training to optimize training efficiency and effectiveness. Various physiological measures have been evaluated for quantifying cognitive stress for different mental challenges. In this paper, we present a study using the cognitive stress measured by the task evoked pupillary response extracted from the time series eye-tracking measurements to predict task difficulties in a virtual reality based robotic surgery training environment. In particular, we proposed a differential-task-difficulty scale, utilized a comprehensive feature extraction approach, and implemented a multitask learning framework and compared the regression accuracy between the conventional single-task-based and three multitask approaches across subjects.

Keywords: surgical metric, task evoked pupillary response, multitask learning, TSFresh

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Authors: Frimpong Kyeremeh, Albert Y. Appiah, Ben B. K. Ayawli

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Energy storage system (ESS) is an essential part of a microgrid (MG) because of its immense benefits to the economics and the stability of MG. For a direct current (DC) MG (DCMG) in which the generating units are mostly variable renewable energy generators, DC bus voltage fluctuation is inevitable; hence ESS is vital in managing the mismatch between load demand and generation. Besides, to accrue the maximum benefits of ESS in the microgrid, there is the need for proper sizing and location of the ESSs. In this paper, a performance comparison is made between two configurations of ESS; distributed battery energy storage system (D-BESS) and an aggregated (centralized) battery energy storage system (A-BESS), on the basis of stability and operational cost for a DCMG. The configuration consists of four households with rooftop PV panels and a wind turbine. The objective is to evaluate and analyze the technical efficiencies, cost effectiveness as well as controllability of each configuration. The MG is first modelled with MATLAB Simulink then, a mathematical model is used to determine the optimal size of the BESS that minimizes the total operational cost of the MG. The performance of the two configurations would be tested with simulations. The two configurations are expected to reduce DC bus voltage fluctuations, but in the cases of voltage stability and optimal cost, the best configuration performance will be determined at the end of the research. The work is in progress, and the result would help MG designers and operators to make the best decision on the use of BESS for DCMG configurations.

Keywords: aggregated energy storage system, DC bus voltage, DC microgrid, distributed battery energy storage, stability

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Authors: Tienfuan Kerh, Hsienchang Lu, Rob Saunders

Abstract:

Shoreline erosion problems caused by global warming and sea level rising may result in losing of land areas, so it should be examined regularly to reduce possible negative impacts. Initially in this study, three sets of survey images obtained from the years of 1990, 2001, and 2010, respectively, are digitalized by using graphical software to establish the spatial coordinates of six major beaches around the island of Taiwan. Then, by overlaying the known multi-period images, the change of shoreline can be observed from their distribution of coordinates. In addition, the neural network approximation is used to develop a model for predicting shoreline variation in the years of 2015 and 2020. The comparison results show that there is no significant change of total sandy area for all beaches in the three different periods. However, the prediction results show that two beaches may exhibit an increasing of total sandy areas under a statistical 95% confidence interval. The proposed method adopted in this study may be applicable to other shorelines of interest around the world.

Keywords: digitalized shoreline coordinates, survey image overlaying, neural network approximation, total beach sandy areas

Procedia PDF Downloads 273

Authors: Khaled M.Naguib, Ahmed M.Noureldin

Abstract:

This paper aims to achieve many goals such as knowing (quantities produced- main properties- characteristics) of sludge produced from Bahr EL-Baqar drains treatment plant. This prediction or projection was made by laboratory analysis and modelling of Model samples from sludge depending on many studies that have previously done, second check the feasibility and do a risk analysis to know the best alternatives for reuse in producing secondary products that add value to sludge. Also, to know alternatives that have no value to add. All recovery methods are relatively very expensive and challenging to be done in this mega plant, so the recommendation from this study is to use the sludge as a coagulant to reduce some compounds or in secondary products. The study utilized sludge-cement replacement percentages of 10%, 20%, 30%, 40% and 50%. Produced tiles were tested for water absorption and breaking (bending) strength. The study showed that all produced tiles exhibited a water absorption ratio of around 10%. The study concluded that produced tiles, except for 50% sludge-cement replacement, comply with the breaking strength requirements of 2.8 MPa for tiles for external use.

Keywords: cement, tiles, water treatment sludge, breaking strength, absorption, heavy metals, risk analysis

Procedia PDF Downloads 108

Authors: Yayra Dzakadzie

Abstract:

The descriptive cross-sectional survey study assessed dishonest academic intention, mediating academic goals, and attitude relationship with academic dishonesty among university undergraduate students in Ghana. The target population for this study was all the final-year undergraduate students enrolled full-time in Ghanaian public universities. One thousand two hundred (1,200) undergraduate students participated in the study. Multistage sampling was used to select the sample for the study. A structured questionnaire was used to collect the needed data to test hypotheses. Structural Equation Modelling (PLS-SEM) was used for the analyses. The results revealed that academic goals and attitudes had direct and indirect effects on academic dishonesty behaviour. Also, academic intention was statistically a significant mediator in the relationship that academic goals and attitude have with academic dishonesty. It was concluded that when academic goals are high, it compels individual students to try new strategies, and when academic goals are low, the students would like to “cut corners” to meet expectations. It was also concluded that when the attitude towards academic dishonesty is low, students are more unlikely to form an intention to be academically dishonest. It is recommended that lecturers should make their students aware of the goals that need to be attained in their courses and provide them with feedback on goal progress. Students should set their proximal goals and enhance their commitment so that they avoid putting things off. Enforcement of rules and regulations against academic dishonesty must be fully adhered to since students’ positive attitudes can result in high intention, which would lead to academic dishonesty behaviour.

Keywords: intention, academic goals, attitude, academic dishonesty, public university

Procedia PDF Downloads 99

Authors: Chro Kavian

Abstract:

The studies conducted show that cancer is a disease caused by populations of microbes, a notion gaining traction as the interaction between the human microbiome and the tumor microenvironment (TME) increasingly shows how environment and microbes dictate the progress and treatment of neoplastic diseases. A person’s human microbiome is defined as a collection of bacteria, fungi, viruses, and other microorganisms whose structure and composition influence biological processes like immune system modulation and nutrient metabolism, which, in turn, affect how susceptible a person is to neoplastic diseases, and response to different therapies. Recent reports demonstrated the influence specific microbiome bacterial populations have on the TME, thereby altering tumoral behaviors and the TME’s contributing factors that impact patients' lives. In addition, gut microbes and their SCFA products are important determinants of the inflammatory landscape of tumors and augment anti-tumor immunity, which can influence immunotherapy outcomes. Studies have also found that dysbiosis, or microbial imbalance, correlates with biological processes such as cancer progression, metastasis, and therapy resistance, leading scientists to explore the use of microbiome deficiencies as adjunctive approaches to chemotherapy and other, more traditional treatments. Nonetheless, mental health practitioners struggling to comprehend the existent gap between cancer patients with pronounced resolutive capabilities and the profound clinical impact Microbiome-targeted cancer therapy has been proven to possess.

Keywords: microbiome, cancer, tumor, immune system

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Authors: Valencia P. L. Rodrigo, Morita A. Adelina, Vargas V. Martin

Abstract:

This proposal consists of an analysis of macro concepts involved within an organization growth using educational technologies, which will relate each concept, in a mathematical way with a vision of harmonic work. Working collaboratively, competitively and cooperatively so that this growth is harmonious and homogenous, coining a new term, Harmonic Work. The Harmonic Work ensures that the organization grows in all business directions, allowing managers to project a much more accurate growth, making clear the contribution of each department, resulting in an algorithm that analyzes each of the variables both endogenous and exogenous, establishing different performance indicators in its process of growth.

Keywords: business projection, collaboration, competitiveness, educational technology, harmonious growth

Procedia PDF Downloads 321