Search results for: energy storage systems

Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

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Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

Procedia PDF Downloads 171

Authors: Alireza Rahimi, Abdolreza Farhadian, Arash Tajik, Elaheh Sadeh, Avni Berisha, Esmaeil Akbari Nezhad

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Although natural polymers have been shown to have some inhibitory properties on sour corrosion, they are not considered very effective green corrosion inhibitors. Accordingly, effective corrosion inhibitors should be developed based on natural resources to mitigate sour corrosion in the oil and gas industry. Here, Arabic gum was employed as an eco-friendly precursor for the synthesis of innovative polyurethanes designed as highly efficient corrosion inhibitors for sour oilfield solutions. A comprehensive assessment, combining experimental and computational analyses, was conducted to evaluate the inhibitory performance of the inhibitor. Electrochemical measurements demonstrated that a concentration of 200 mM of the inhibitor offered substantial protection to mild steel against sour corrosion, yielding inhibition efficiencies of 98% and 95% at 25 ºC and 60 ºC, respectively. Additionally, the presence of the inhibitor led to a smoother steel surface, indicating the adsorption of polyurethane molecules onto the metal surface. X-ray photoelectron spectroscopy results further validated the chemical adsorption of the inhibitor on mild steel surfaces. Scanning Kelvin probe microscopy revealed a shift in the potential distribution of the steel surface towards negative values, indicating inhibitor adsorption and corrosion process inhibition. Molecular dynamic simulation indicated high adsorption energy values for the inhibitor, suggesting its spontaneous adsorption onto the Fe (110) surface. These findings underscore the potential of Arabic gum as a viable resource for the development of polyurethanes under mild conditions, serving as effective corrosion inhibitors for sour solutions.

Keywords: environmental effect, Arabic gum, corrosion inhibitor, sour corrosion, molecular dynamics simulation

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Authors: Melissa Valle

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This paper draws upon the studies of visual culture and intersectionality to illuminate how visuality can naturalize social hierarchies. Through the use of iconography, it decodes the denotative, connotative and ideological meanings of symbols of ritualistic events in the context of the Colombian Atlantic Coast. An examination of such exceptional moments, i.e. of the spectacle, brings into focus how such performances are imbued with meaning by both the on-looker and the performer. Through an analysis of preexisting visuals (e.g., advertisements, social media) and visual materials produced by the researcher for the purpose of photo-elicitation interviews, this paper provides a contextual analysis of the ways in which three representations, popular during Colombian Atlantic coastal festivals (Negrita Puloy, Las Palenqueras, and El Son de Negro), have been historically, culturally and politically constituted. This work reveals that the visualizations are born out of and reproduce typifications systems heavily based upon race, gender, class, and ethnicity. Understanding the ways these categories are mutually constituted through the cultural practice of visual representation is essential to a more comprehensive understanding of the role such representation plays in the reproduction of social difference.

Keywords: Colombia, festivals, intersectionality, visual culture

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Authors: Eugene Stepanov, Arkadi Ponossov

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Many mathematical models used in biological and other applications are ill-posed. The reason for that is the nature of differential equations, where the nonlinearities are assumed to be step functions, which is done to simplify the analysis. Prominent examples are switched systems arising from gene regulatory networks and neural field equations. This simplification leads, however, to theoretical and numerical complications. In the presentation, it is proposed to apply the theory of hybrid feedback controls to regularize the problem. Roughly speaking, one attaches a finite state control (‘automaton’), which follows the trajectories of the original system and governs its dynamics at the points of ill-posedness. The construction of the automaton is based on the classification of the attractors of the specially designed adjoint dynamical system. This ‘hybridization’ is shown to regularize the original switched system and gives rise to efficient hybrid numerical schemes. Several examples are provided in the presentation, which supports the suggested analysis. The method can be of interest in other applied fields, where differential equations contain step-like nonlinearities.

Keywords: hybrid feedback control, ill-posed problems, singular perturbation analysis, step-like nonlinearities

Procedia PDF Downloads 248

Authors: Khaled M. Alhawiti

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Natural Language Processing (NLP) is an effective approach for bringing improvement in educational setting. This involves initiating the process of learning through the natural acquisition in the educational systems. It is based on following effective approaches for providing the solution for various problems and issues in education. Natural Language Processing provides solution in a variety of different fields associated with the social and cultural context of language learning. It is based on involving various tools and techniques such as grammar, syntax, and structure of text. It is effective approach for teachers, students, authors, and educators for providing assistance for writing, analysis, and assessment procedure. Natural Language Processing is widely integrated in the large number of educational contexts such as research, science, linguistics, e-learning, evaluations system, and various other educational settings such as schools, higher education system, and universities. Natural Language Processing is based on applying scientific approach in the educational settings. In the educational settings, NLP is an effective approach to ensure that students can learn easily in the same way as they acquired language in the natural settings.

Keywords: natural language processing, education, application, e-learning, scientific studies, educational system

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Authors: Xin Chen

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It has been widely observed that marine food webs have significantly larger predator–prey body-size ratios compared with their terrestrial counterparts. A number of hypotheses have been proposed to account for such difference on the basis of primary productivity, trophic structure, biophysics, bioenergetics, habitat features, energy efficiency, etc. In this study, an alternative explanation is suggested based on the difference in the spatial dimensions of foraging arenas: terrestrial animals primarily forage in two dimensional arenas, while marine animals mostly forage in three dimensional arenas. Using 2-dimensional and 3-dimensional random walk simulations, it is shown that marine predators with 3-dimensional foraging would normally have a greater foraging efficiency than terrestrial predators with 2-dimensional foraging. Marine prey with 3-dimensional dispersion usually has greater swarms or aggregations than terrestrial prey with 2-dimensional dispersion, which again favours a greater predator foraging efficiency in marine animals. As an analytical tool, a Lotka-Volterra based adaptive dynamical model is developed with the predator-prey ratio embedded as an adaptive variable. The model predicts that high predator foraging efficiency and high prey conversion rate will dynamically lead to the evolution of a greater predator-prey ratio. Therefore, marine food webs with 3-dimensional foraging space, which generally have higher predator foraging efficiency, will evolve a greater predator-prey ratio than terrestrial food webs.

Keywords: predator-prey, body size, lotka-volterra, random walk, foraging efficiency

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Authors: Zubair Khaliq, M. Bilal Qadir, Amir Shahzad, Zulfiqar Ali, Ahsan Nazir, Ali Afzal, Abdul Jabbar

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Carbon fibers are one of the most demanding materials on earth due to their potential application in energy, high strength materials, and conductive materials. The nanostructure of carbon fibers offers enhanced properties of conductivity due to the larger surface area. The next generation carbon nanofibers demand the porous structure as it offers more surface area. Multiple techniques are used to produce carbon fibers. However, electrospinning followed by carbonization of the polymeric materials is easy to carry process on a laboratory scale. Also, it offers multiple diversity of changing parameters to acquire the desired properties of carbon fibers. Polyacrylonitrile (PAN) is the most used material for the production of carbon fibers due to its promising processing parameters. Also, cellulose is one of the highest yield producers of carbon fibers. However, the electrospinning of cellulosic materials is difficult due to its rigid chain structure. The combination of PAN and cellulose can offer a suitable solution for the production of carbon fibers. Both materials are miscible in the mixed solvent of N, N, Dimethylacetamide and lithium chloride. This study focuses on the production of porous carbon fibers as a function of PAN/Cellulose blend ratio, solution properties, and electrospinning parameters. These single polymer and blend with different ratios were electrospun to give fine fibers. The higher amount of cellulose offered more difficulty in electrospinning of nanofibers. After carbonization, the carbon fibers were studied in terms of their blend ratio, surface area, and texture. Cellulose contents offered the porous structure of carbon fibers. Also, the presence of LiCl contributed to the porous structure of carbon fibers.

Keywords: cellulose, polyacrylonitrile, carbon nanofibers, electrospinning, blend

Procedia PDF Downloads 206

Authors: Ian A. McCulloh, Madelaine Zinser, Jesse Patsolic, Michael Ramos

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Recommender systems are a common artificial intelligence (AI) application. For any given input, a search system will return a rank-ordered list of similar items. As users review returned items, they must decide when to halt the search and either revise search terms or conclude their requirement is novel with no similar items in the database. We present a statistically designed experiment that investigates the impact of similarity ratings on human judgement to conclude a search item is novel and halt the search. 450 participants were recruited from Amazon Mechanical Turk to render judgement across 12 decision tasks. We find the inclusion of ratings increases the human perception that items are novel. Percent similarity increases novelty discernment when compared with star-rated similarity or the absence of a rating. Ratings reduce the time to decide and improve decision confidence. This suggests the inclusion of similarity ratings can aid human decision-makers in knowledge search tasks.

Keywords: ratings, rankings, crowdsourcing, empirical studies, user studies, similarity measures, human-centered computing, novelty in information retrieval

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Authors: Bhawat Chiamjinnawat

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The agri-food market transformation has implied market growth for the fruit industry in Thailand. This article focuses on analysis of farmer competence and farm resources which affect market strategies used by fruit farmers in Chanthaburi province of Thailand. The survey data were collected through the use of face-to-face interviews with structured questionnaires. This study identified 14 drivers related to farmer competence and farm resources of which some had significant effect on the decision to use either high-value markets or traditional markets. The results suggest that farmers who used high-value markets were better educated and they had longer experience and larger sized business. Identifying the important factors that match with the market transformation provides policy with opportunities to support the fruit farmers to increase their market power. Policies that promote business expansion of agricultural cooperatives and knowledge sharing among farmers are recommended to reduce limitations due to limited knowledge, low experience, and small business sizes.

Keywords: farmer competence, farm resources, fruit industry, high-value markets, Thailand

Procedia PDF Downloads 168

Authors: Omaima N. Ahmad AL-Allaf

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Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

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Authors: Mikhail Sandzhiev

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The monitoring of metal pollution in environmental waters is crucial for the protection of ecosystems, human health and agricultural activities. Traditional laboratory-based metal analysis methods are time-consuming and expensive, which often leads to delays in the availability of information. This study presents an approach to real-time water quality monitoring using portable X-ray fluorescence (p-XRF) technology coupled with geographic information systems (GIS). Using a custom Python script, p-XRF data is processed and formatted into a GIS-compatible format, facilitating spatial visualization of metal concentrations in ǪGIS. Field-usable filters, especially bisphosphonate-functionalized thermally carbonized porous silicon (BP-TCPSi), preformed metals such as Mn, Ni, Cu, Zn, and Pb allow direct detection in the field by using p-XRF. Key objectives include robust data collection, spatial visualization and validation processes to ensure accuracy and efficiency. This provides quick and efficient insights into metal contamination trends and allows proactive decision-making.

Keywords: metal concentrations, predictive mapping, environmental monitoring, environmental waters

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Authors: Zunnu Raen Akhtar

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Brevicoryne brassicae, aphid feeds on cabbage and Brassica sp. as preferred host. Brassica plants usually ripen when maize starts growing in multiple cropping systems. Experiment was conducted to observe suitability of B. brassicae by rearing it on maize as host. In a tritrophic eco-system, predator coccinellids can be found in the fields of brassica and maize. This experiment emphasized on issue of aphids growing incidence in a cropping system. Brassica is sown and harvested earlier than maize and is attacked by aphids, while maize is also attacked by aphids. Five mortality tests were conducted of B. brassicae fed on maize. Out of five mortality tests, 3 tests were conducted using 1st instar, while in two mortality tests, 2nd instars of aphids were used. Mortality tests revealed that first instar mortality was quite high on the second day, while in second instar larvae mortality was delayed up to third to the fourth day. These experiments reveal that aphids can use maize as substitute host at later instars as compared to young ones. These experiments can be foundation for studying further crop-insect interaction and sampling techniques used for this purpose.

Keywords: host suitability, B. brassicae, maize, tritrophic interaction

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Authors: Edwin Forero-Garcia, Jaime Vitola, Brayan Cardenas, Johan Casagua

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This research article presents the integration of electronic and computer systems, which developed an ultrasonic signal processing system that performs the capture, adaptation, and analog-digital conversion to later carry out its processing and visualization. The capture and adaptation of the signal were carried out from the design and implementation of an analog electronic system distributed in stages: 1. Coupling of impedances; 2. Analog filter; 3. Signal amplifier. After the signal conditioning was carried out, the ultrasonic information was digitized using a digital microcontroller to carry out its respective processing. The digital processing of the signals was carried out in MATLAB software for the elaboration of A-Scan, B and D-Scan types of ultrasonic images. Then, advanced processing was performed using the SAFT technique to improve the resolution of the Scan-B-type images. Thus, the information from the ultrasonic images was displayed in a user interface developed in .Net with Visual Studio. For the validation of the system, ultrasonic signals were acquired, and in this way, the non-invasive inspection of the structures was carried out and thus able to identify the existing pathologies in them.

Keywords: acquisition, signal processing, ultrasound, SAFT, HMI

Procedia PDF Downloads 111

Authors: S. Ziaran, M. Musil, M. Cekan, O. Chlebo

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The paper analyzes the response of buildings and industrially structures on seismic waves (low frequency mechanical vibration) generated by blasting operations. The principles of seismic analysis can be applied for different kinds of excitation such as: earthquakes, wind, explosions, random excitation from local transportation, periodic excitation from large rotating and/or machines with reciprocating motion, metal forming processes such as forging, shearing and stamping, chemical reactions, construction and earth moving work, and other strong deterministic and random energy sources caused by human activities. The article deals with the response of seismic, low frequency, mechanical vibrations generated by nearby blasting operations on a residential home. The goal was to determine the fundamental natural frequencies of the measured structure; therefore it is important to determine the resonant frequencies to design a suitable modal damping. The article also analyzes the package of seismic waves generated by blasting (Primary waves – P-waves and Secondary waves S-waves) and investigated the transfer regions. For the detection of seismic waves resulting from an explosion, the Fast Fourier Transform (FFT) and modal analysis, in the frequency domain, is used and the signal was acquired and analyzed also in the time domain. In the conclusions the measured results of seismic waves caused by blasting in a nearby quarry and its effect on a nearby structure (house) is analyzed. The response on the house, including the fundamental natural frequency and possible fatigue damage is also assessed.

Keywords: building structure, seismic waves, spectral analysis, structural response

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Authors: Yassa Nacera, Badji Abderrezak, Saidoune Abdelmalek, Houassine Hamza

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Several kinds of faults can occur in a permanent magnet synchronous machine (PMSM) systems: bearing faults, electrically short/open faults, eccentricity faults, and demagnetization faults. Demagnetization fault means that the strengths of permanent magnets (PM) in PMSM decrease, and it causes low output torque, which is undesirable for EVs. The fault is caused by physical damage, high-temperature stress, inverse magnetic field, and aging. Motor current signature analysis (MCSA) is a conventional motor fault detection method based on the extraction of signal features from stator current. a simulation model of the PMSM under partial demagnetization and uniform demagnetization fault was established, and different degrees of demagnetization fault were simulated. The harmonic analyses using the Fast Fourier Transform (FFT) show that the fault diagnosis method based on the harmonic wave analysis is only suitable for partial demagnetization fault of the PMSM and does not apply to uniform demagnetization fault of the PMSM.

Keywords: permanent magnet, diagnosis, demagnetization, modelling

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Authors: S. P. Jordan, G. Christian, S. P. Jeffs

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Modern composite materials are increasingly being chosen in replacement of heavier metallic material systems within many engineering fields including aerospace and automotive industries. The increasing push towards satisfying environmental targets are fuelling new material technologies and manufacturing processes. This paper will introduce materials and manufacturing processes using metal matrix composites along with manufacturing processes optimized at Alvant Ltd., based in Basingstoke in the UK which offers modern, cost effective, selectively reinforced composites for light-weighting applications within engineering. An overview and introduction into modern optimized manufacturing methods capable of producing viable replacements for heavier metallic and lower temperature capable polymer composites are offered. A review of the capabilities and future applications of this viable material is discussed to highlight the potential involved in further optimization of old manufacturing techniques, to fully realize the potential to lightweight material using cost-effective methods.

Keywords: aluminium matrix composites, light-weighting, hybrid squeeze casting, strategically placed reinforcements

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Authors: Baoubadi Atozou, Koffi Akakpo

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Since the decade 2000, the use of foodstuffs such as corn, wheat, and soybeans in biofuel production has been growing sharply in the United States, Canada, and Europe. Thus, prices for these agricultural products are rising in the world market. These cereals are the most important source of calorific energy for West African Economic and Monetary Union (WAEMU) countries members’ population. These countries are highly dependent on imports of most of these products. Thereby, rising prices can have an important impact on import levels and consequently on food security in these countries. This study aims to analyze the interrelationship between the prices of these commodities and their volatilities, and their effects on imports of these agricultural products by each WAEMU ’country member. The Autoregressive Distributed Lag (ARDL) model, the GARCH Multivariate model, and the Granger Causality Test are used in this investigation. The results show that import levels are highly and significantly sensitive to price changes as well as their volatility. In the short term as well as in the long term, there is a significant relationship between the prices of these products. There is a positive relationship in general between price volatility. And these volatilities have negative effects on the level of imports. The market characteristics affect food security in these countries, especially access to food for vulnerable and low-income populations. The policies makers must adopt viable strategies to increase agricultural production and limit their dependence on imports.

Keywords: price volatility, import of agricultural products, food safety, WAEMU

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Authors: Adam J. Bowen

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Abstract— Should robots have rights or legal protections. Often debates concerning whether robots and AI should be afforded rights focus on conditions of personhood and the possibility of future advanced forms of AI satisfying particular intrinsic cognitive and moral attributes of rights-holding persons. Such discussions raise compelling questions about machine consciousness, autonomy, and value alignment with human interests. Although these are important theoretical concerns, especially from a future design perspective, they provide limited guidance for addressing the moral and legal standing of current and near-term AI that operate well below the cognitive and moral agency of human persons. Robots and AI are already being pressed into service in a wide range of roles, especially in healthcare and biomedical contexts. The design and large-scale implementation of robots in the context of core societal institutions like healthcare systems continues to rapidly develop. For example, we bring them into our homes, hospitals, and other care facilities to assist in care for the sick, disabled, elderly, children, or otherwise vulnerable persons. We enlist surgical robotic systems in precision tasks, albeit still human-in-the-loop technology controlled by surgeons. We also entrust them with social roles involving companionship and even assisting in intimate caregiving tasks (e.g., bathing, feeding, turning, medicine administration, monitoring, transporting). There have been advances to enable severely disabled persons to use robots to feed themselves or pilot robot avatars to work in service industries. As the applications for near-term AI increase and the roles of robots in restructuring our biomedical practices expand, we face pressing questions about the normative implications of human-robot interactions and collaborations in our collective worldmaking, as well as the moral and legal status of robots. This paper argues that robots operating in public and private spaces be afforded some protections as either moral patients or legal agents to establish prohibitions on robot abuse, misuse, and mistreatment. We already implement robots and embed them in our practices and institutions, which generates a host of human-to-machine and machine-to-machine relationships. As we interact with machines, whether in service contexts, medical assistance, or home health companions, these robots are first encountered in relationship to us and our respective roles in the encounter (e.g., surgeon, physical or occupational therapist, recipient of care, patient’s family, healthcare professional, stakeholder). This proposal aims to outline a framework for establishing limiting factors and determining the extent of moral or legal protections for robots. In doing so, it advocates for a relational approach that emphasizes the priority of mapping the complex contextually sensitive roles played and the relations in which humans and robots stand to guide policy determinations by relevant institutions and authorities. The relational approach must also be technically informed by the intended uses of the biomedical technologies in question, Design History Files, extensive risk assessments and hazard analyses, as well as use case social impact assessments.

Keywords: biomedical robots, robot ethics, robot laws, human-robot interaction

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Authors: Gurjit Kaur, Shashank Johri, Arpit Mehrotra

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In this paper we have analyzed and compared the performance of various coding schemes. The basic ID prime sequence codes are unique in only dimension i.e. time slots whereas 2D coding techniques are not unique by their time slots but with their wavelengths also. In this research we have evaluated and compared the performance of 1D and 2D coding techniques constructed using prime sequence coding pattern for OCDMA system on a single platform. Results shows that 1D Extended Prime Code (EPC) can support more number of active users compared to other codes but at the expense of larger code length which further increases the complexity of the code. Modified Prime Code (MPC) supports lesser number of active users at λc=2 but it has a lesser code length as compared to 1D prime code. Analysis shows that 2D prime code supports lesser number of active users than 1D codes but they are having large code family and are the most secure codes compared to other codes. The performance of all these codes is analyzed on basis of number of active users supported at a Bit Error Rate (BER) of 10-9.

Keywords: CDMA, OCDMA, BER, OOC, PC, EPC, MPC, 2-D PC/PC, λc, λa

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Authors: Kaan Koyuncu, Umut Celen Arican, Sevilay Can

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In the maritime industry, there have been regulations to prevent pollution, and the first attempt to offer a legal basis was Marpol Convention which was held in 1973 in order to provide a framework for the disposal of ship wastes. Based on this convention, ports are obliged to build waste receiving facilities. European Union regulations make several member countries to follow these directions, In Turkey, under Blue Card System, the quantity and types of wastes, the delivery time, the capacity of the receiving facilities, and other required information can be monitored online. Therefore, yachts and other boats with the bilge, sewage, and waste which illegally discharge into the sea, can be blocked. This system is an outcome of the law adopted from European Union regulations. In this study, the present systems in Turkey which occurred in 2010 after the integration of the system, which has been put in the force in 2000 in Europe will be analyzed and interpreted to provide a useful comparison, a practical guide, and a roadmap for potential improvements.

Keywords: Europe-Turkey, blue card, marine environment, ship waste tracking system

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Authors: Houda Najeh, Stéphane Ploix, Mahendra Pratap Singh, Karim Chabir, Mohamed Naceur Abdelkrim

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Building systems are highly vulnerable to different kinds of faults and failures. In fact, various faults, failures and human behaviors could affect the building performance. This paper tackles the detection of unreliable sensors in buildings. Different literature surveys on diagnosis techniques for sensor grids in buildings have been published but all of them treat only bias and outliers. Occurences of data gaps have also not been given an adequate span of attention in the academia. The proposed methodology comprises the automatic thresholding for data gap detection for a set of heterogeneous sensors in instrumented buildings. Sensor measurements are considered to be regular time series. However, in reality, sensor values are not uniformly sampled. So, the issue to solve is from which delay each sensor become faulty? The use of time series is required for detection of abnormalities on the delays. The efficiency of the method is evaluated on measurements obtained from a real power plant: an office at Grenoble Institute of technology equipped by 30 sensors.

Keywords: building system, time series, diagnosis, outliers, delay, data gap

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Authors: Vatsal M. Patel, Navin B. Patel

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The present studies deal with the developing a series bearing a diphenyl ethers nucleus using structure-based drug design concept. A newer series of diphenyl ether based azetidinone namely N-(3-chloro-2-oxo-4-(3-phenoxyphenyl)azetidin-1-yl)-2-(substituted amino)acetamide (2a-j) have been synthesized by condensation of m-phenoxybenzaldehyde with 2-(substituted-phenylamino)acetohydrazide followed by the cyclisation of resulting Schiff base (1a-j) by conventional method as well as microwave heating approach as a part of an environmentally benign synthetic protocol. All the synthesized compounds were characterized by spectral analysis and were screened for in vitro antimicrobial, antitubercular and antiprotozoal activity. The compound 2f was found to be most active M. tuberculosis (6.25 µM) MIC value in the primary screening as well as this same derivative has been found potency against L. mexicana and T. cruzi with MIC value 2.09 and 6.69 µM comparable to the reference drug Miltefosina and Nifurtimox. To provide understandable evidence to predict binding mode and approximate binding energy of a compound to a target in the terms of ligand-protein interaction, all synthesized compounds were docked against an enoyl-[acyl-carrier-protein] reductase of M. tuberculosis (PDB ID: 4u0j). The computational studies revealed that azetidinone derivatives have a high affinity for the active site of enzyme which provides a strong platform for new structure-based design efforts. The Lipinski’s parameters showed good drug-like properties and can be developed as an oral drug candidate.

Keywords: antimycobacterial, antiprotozoal, azetidinone, diphenylether, docking, microwave

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Authors: Rezzan Alagoz, Seda Gonul

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This study examines the migration, work, and social life experiences of undocumented Afghan migrants employed as shepherds in Igdır. Despite their high visibility in informal labor markets, their undocumented status renders them invisible in everyday life. Their invisibility in both official status and social life, coupled with their vulnerability to exploitation in the labor market, renders them particularly susceptible to marginalization. This research employs the concept of the subaltern to examine the characteristics of Afghan migrants as unrepresented, unheard, and invisible. It also analyzes their experiences in the labor market based on the concept of biopolitics. Undocumented Afghan migrants are engaged in labor-intensive occupations such as shepherding, thereby addressing an essential gap in the workforce that local workers are reluctant to undertake. The reliance of employers on the labor of these employees is significant; however, the undocumented status of these workers leaves them vulnerable to exploitation. In addition to serving as a critical source of low-cost labor, these individuals are susceptible to exploitation in the form of non-payment for their work, extended and intensive work schedules, and, on some occasions, physical violence. In the event of a conflict between shepherds and their employers, undocumented workers are unable to seek legal recourse, which serves to reinforce their marginalized status further. The predominant practice among Afghan shepherds is to utilize the workplace as a place of residence. In the context of shepherding work, the prevailing conditions at the workplace frequently pose a significant threat to the health and well-being of the individuals engaged in such activities. As a result of their lack of official status, these individuals lack access to basic services such as healthcare, which has the consequence of rendering them invisible in public and institutional spaces. Attempts to engage with public systems carry the risk of deportation, reinforcing the already fragile and precarious nature of their existence. This study examines the socio-political implications of undocumented status and addresses these experiences in the context of national and international migration policies. In line with Agamben's concept of the "state of exception" undocumented migrants exist in a state where fundamental rights are effectively nullified, and they are rendered outside the protection of the law. This exclusion is further exacerbated by the intersection of economic exploitation, political and physical invisibility, and limited access to basic services, which collectively contribute to a cycle of vulnerability. This research is based on in-depth interviews with 18 Afghan shepherds in Igdir province in August 2024. The research contributes to the ongoing critical debates on migration, labor exploitation, and biopolitics by focusing on the experiences of Afghan shepherds. The article examines how undocumented migrants maneuver between visibility and invisibility within the context of a system that relies on exploitation in the labor market and migration policies. The research findings demonstrate the necessity for policy intervention to address the structural exclusion of undocumented Afghan migrants from national and international protection systems, as well as their indispensable role in local economies.

Keywords: Afghan migrants, biopolitics, border economy, informal labour market, migration policy, sheepherding, Subaltern

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Authors: Wichan Lertlop, Boonyarat Chaleephay

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The objective of this research was to study the appropriate thermal level and time for dabbing customers with the massage compressed pack reported from their perception. The investigation was conducted by comparing different angles of tilted heads done by the customers together with their perception before and after the dabbing. The variables included different temperature of the compressed packs and different dabbing duration. Samples in this study included volunteers who got massage therapy and dabbing with hot compressed packs by traditional Thai medical students. The experiment was conducted during January to June 2013. The research tool consisted of angle meters, stop watches, thermometers, and massage compressed packs. The customers were interviewed for their perceptions before and after the dabbing. The results showed that: 1. There was a difference of the average angles of tilted heads before and after the dabbing. 2. There was no difference of the average angles at different temperatures but constant duration. 3. There was no difference of the average angles at different durations. 4. The customers reported relaxation no matter what the various temperatures and various dabbing durations were. However, they reported too hot at the temperature 70 °C and over.

Keywords: massage, therapy, therapeutic systems, technologies

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Authors: A. Hol

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21^st century brought waves of business and industry eTransformations. The impact of change is also being seen in education. To identify the extent of this, scenario analysis methodology was utilised with the aim to assess business transformations across industry sectors ranging from craftsmanship, medicine, finance and manufacture to innovations and adoptions of new technologies and business models. Firstly, scenarios were drafted based on the current eTransformation models and its dimensions. Following this, eTransformation framework was utilised with the aim to derive the key eTransformation parameters, the essential characteristics that have enabled eTransformations across the sectors. Following this, identified key parameters were mapped to the transforming domain-education. The mapping assisted in deriving a cognitive eTransformation framework for education sector. The framework highlights the importance of context and the notion that education today needs not only to deliver content to students but it also needs to be able to meet the dynamically changing demands of specific student and industry groups. Furthermore, it pinpoints that for such processes to be supported, specific technology is required, so that instant, on demand and periodic feedback as well as flexible, dynamically expanding study content can be sought and received via multiple education mediums.

Keywords: education sector, business transformation, eTransformation model, cognitive model, cognitive systems, eTransformation

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Authors: Saurav S. Rath, Birendra K. David

Abstract:

Generic pharmaceutical industry has to operate in strict timelines of product development and scale-up from lab to plant. Hence, detailed product & process understanding and implementation of appropriate mechanistic modelling and Quality-by-design (QbD) approaches are imperative in the product life cycle. This work provides example cases of such efforts in topical dosage products. Topical products are typically in the form of emulsions, gels, thick suspensions or even simple solutions. The efficacy of such products is determined by characteristics like rheology and morphology. Defining, and scaling up the right manufacturing process with a given set of ingredients, to achieve the right product characteristics presents as a challenge to the process engineer. For example, the non-Newtonian rheology varies not only with CPPs and CMAs but also is an implicit function of globule size (CQA). Hence, this calls for various mechanistic models, to help predict the product behaviour. This paper focusses on such models obtained from computational fluid dynamics (CFD) coupled with population balance modelling (PBM) and constitutive models (like shear, energy density). In a special case of the use of high shear homogenisers (HSHs) for the manufacture of thick emulsions/gels, this work presents some findings on (i) scale-up algorithm for HSH using shear strain, a novel scale-up parameter for estimating mixing parameters, (ii) non-linear relationship between viscosity and shear imparted into the system, (iii) effect of hold time on rheology of product. Specific examples of how this approach enabled scale-up across 1L, 10L, 200L, 500L and 1000L scales will be discussed.

Keywords: computational fluid dynamics, morphology, quality-by-design, rheology

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Authors: Mohamed Gouda

Abstract:

Antibacterial wound dressings based on cellulose nanofibers containing different metal nanoparticles (CMC-MNPs) were synthesized using an electrospinning technique. First, the composite of carboxymethyl cellulose containing different metal nanoparticles (CMC/MNPs), such as copper nanoparticles (CuNPs), iron nanoparticles (FeNPs), zinc nanoparticles (ZnNPs), cadmium nanoparticles (CdNPs) and cobalt nanoparticles (CoNPs) were synthesized, and finally, these composites were transferred to the electrospinning process. Synthesized CMC-MNPs were characterized using scanning electron microscopy (SEM) coupled with high-energy dispersive X-ray (EDX) and UV-visible spectroscopy used to confirm nanoparticle formation. The SEM images clearly showed regular flat shapes with semi-porous surfaces. All MNPs were well distributed inside the backbone of the cellulose without aggregation. The average particle diameters were 29-39 nm for ZnNPs, 29-33 nm for CdNPs, 25-33 nm for CoNPs, 23-27 nm for CuNPs and 22-26 nm for FeNPs. Surface morphology, water uptake and release of MNPs from the nanofibers in water and antimicrobial efficacy were studied. SEM images revealed that electrospun CMC-MNPs nanofibers are smooth and uniformly distributed without bead formation with average fiber diameters in the range of 300 to 450 nm. Fiber diameters were not affected by the presence of MNPs. TEM images showed that MNPs are present in/on the electrospun CMC-MNPs nanofibers. The diameter of the electrospun nanofibers containing MNPs was in the range of 300–450 nm. The MNPs were observed to be spherical in shape. The CMC-MNPs nanofibers showed good hydrophilic properties and had excellent antibacterial activity against the Gram-negative bacteria Escherichia coli and the Gram-positive bacteria Staphylococcus aureus.

Keywords: electrospinning technique, metal nanoparticles, cellulosic nanofibers, wound dressing

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Authors: Oladapo Tolulope Ibitoye

Abstract:

Neural networks have become prominent and widely engaged in algorithmic-based machine learning networks. They are perfect in solving day-to-day issues to a certain extent. Neural networks are computing systems with several interconnected nodes. One of the numerous areas of application of neural networks is object detection. This is a prominent area due to the coronavirus disease pandemic and the post-pandemic phases. Wearing a face mask in public slows the spread of the virus, according to experts’ submission. This calls for the development of a reliable and effective model for detecting face masks on people's faces during compliance checks. The existing neural network models for facemask detection are characterized by their black-box nature and large dataset requirement. The highlighted challenges have compromised the performance of the existing models. The proposed model utilized Faster R-CNN Model on Inception V3 backbone to reduce system complexity and dataset requirement. The model was trained and validated with very few datasets and evaluation results shows an overall accuracy of 96% regardless of skin tone.

Keywords: convolutional neural network, face detection, face mask, masked faces

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Authors: Josef Wolfartsberger, Michael Heiml, Georg Schwarz, Sabrina Egger

Abstract:

Growing individualization and higher numbers of variants in industrial assembly products raise the complexity of manufacturing processes. Technical assistance systems considering both procedural and human factors allow for an increase in product quality and a decrease in required learning times by supporting workers with precise working instructions. Due to varying needs of workers, the presentation of working instructions leads to several challenges. This paper presents an approach for a multi-modal visualization application to support assembly work of complex parts. Our approach is integrated within an interconnected assistance system network and supports the presentation of cloud-streamed textual instructions, images, videos, 3D animations and audio files along with multi-modal user interaction, customizable UI, multi-platform support (e.g. tablet-PC, TV screen, smartphone or Augmented Reality devices), automated text translation and speech synthesis. The worker benefits from more accessible and up-to-date instructions presented in an easy-to-read way.

Keywords: assembly, assistive technologies, augmented reality, manufacturing, visualization

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Authors: Dupe Olufunke Ogunbosoye, Thaofik Badmos Mustapha, Lanre Shaffihy Adeaga, R. O. Imam

Abstract:

Efforts have been made to reduce ruminants' methane emissions while improving animal productivity. Hence, an experiment was conducted to investigate the in vitro fermentation pattern, methane production, and performance of West African dwarf (WAD) rams-fed diets at graded levels of ginger. Sixteen (16) rams were randomly allocated into four dietary treatments with four animals per treatment in a completely randomized design for 84 days. Ginger powder was added at 0.00%, 0.25%, 0.50% and 0.75% as T1, T2, T3 and T4 respectively. The results indicated that at the 24-hour diet incubation, gas production, methane, metabolizable energy (ME), organic matter digestibility (OMD), and short-chain fatty acids (SCFA) concentrations decreased with the increasing level of ginger. Conversely, the sheep-fed T4 recorded the highest daily weight gain (47.61g/day), while the least daily weight gain (17.86g/day) was recorded in ram-fed T1. The daily weight gain of the rams fed T3 and T4 was similar but significantly different from the daily weight gain in T1 (17.86g/day) and T2 (29.76g/day). Daily feed intake was not significantly different across the treatments. T4 recorded the best response regarding feed conversion ratio (18.59) compared with other treatments. Based on the results obtained, rams fed T4 perform best in terms of growth and methane production. It is therefore concluded that the addition of ginger powder into the diet of sheep up to 0.75% enhances the growth rate of WAD sheep and reduces enteric methane production to create a smart nutrition system in ruminant animal production.

Keywords: enteric methane, growth, in vitro, sheep, nutrition system

Procedia PDF Downloads 82