Search results for: graph signal processing

Authors: N. Moradi, C. M. Lopez-Vazquez, H. Garcia Hernandez, F. Rubio Rincon, D. Brdanovic, Mark van Loosdrecht

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Advanced oxidation processes have been widely used for disinfection, removal of residual organic material, and for the removal of emerging contaminants from drinking water and wastewater. Yet, the application of these technologies to sludge treatment processes has not gained enough attention, mostly, considering the complexity of the sludge matrix. In this research, ozone and UV/H₂O₂ treatment were applied for the removal of emerging contaminants from a digestate supernatant. The removal of the following compounds was assessed:(i) salicylic acid (SA) (a surrogate of non-stradiol anti-inflammatory drugs (NSAIDs)), and (ii) sulfamethoxazole (SMX), sulfamethazine (SMN), and tetracycline (TCN) (the most frequent human and animal antibiotics). The ozone treatment was carried out in a plexiglass bubble column reactor with a capacity of 2.7 L; the system was equipped with a stirrer and a gas diffuser. The UV and UV/H₂O₂ treatments were done using a LED set-up (PearlLab beam device) dosing H₂O₂. In the ozone treatment evaluations, 95 % of the three antibiotics were removed during the first 20 min of exposure time, while an SA removal of 91 % occurred after 8 hours of exposure time. In the UV treatment evaluations, when adding the optimum dose of hydrogen peroxide (H₂O₂:COD molar ratio of 0.634), 36% of SA, 82% of TCN, and more than 90 % of both SMX and SMN were removed after 8 hours of exposure time. This study concluded that O₃ was more effective than UV/H₂O₂ in removing emerging contaminants from the digestate supernatant.

Keywords: digestate sludge, emerging contaminants, ozone, UV-AOP

Procedia PDF Downloads 95

Authors: A. Abdulkadir, Y. M. Bello, A. A. Okhimamhe, H. Ibrahim, M. B. Matazu, L. S. Barau

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The increasing volume of solid waste generated, collected and disposed daily complicate adequate management of solid waste by the relevant agency like Niger State Environmental Protection Agency (NISEPA). In addition, the impacts of solid waste on the natural environment and human livelihood require identification of cost-effective ways for sustainable municipal waste management in Nigeria. These signal the need for identifying environment-friendly initiative and local solution to address municipal solid waste. A research field was secured at Pago, Minna, Niger State which is located in the guinea savanna belt of Nigeria, within longitude 60 3614311- 4511 and latitude 90 291 37.6111- .6211 N. Poultry droppings, decomposed household waste manure and NPK treatment were used. The experimental field was divided into three replications and four (4) treatments on each replication making a total of twelve (12) plots. The treatments were allotted using Randomized Complete Block Design (RCBD) and Data collected was analyzed using SPSS software and RCBD. The result depicts variation in plant height and number of leaves at 50% flowering; Poultry dropping records the highest height as a number of leaves for waste manure competes fairly well with NPK treatment. Similarly, the varying treatments significantly increase vegetable yield, as the control (Nontreatment) records the least yield for the three vegetable samples. Adoption of this organic manure for cultivation does not only enhance environment quality and attainment of food security but will contribute to local economic development, poverty alleviation, and social inclusion.

Keywords: environmental issues, food security, NISEPA, solid waste

Procedia PDF Downloads 333

Authors: Rita Magdalena, N. K. Caecar Pratiwi, Yunendah Nur Fuadah, Sofia Saidah, Bima Sakti

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Vessel segmentation of retinal fundus is important for biomedical sciences in diagnosing ailments related to the eye. Segmentation can simplify medical experts in diagnosing retinal fundus image state. Therefore, in this study, we designed a software using MATLAB which enables the segmentation of the retinal blood vessels on retinal fundus images. There are two main steps in the process of segmentation. The first step is image preprocessing that aims to improve the quality of the image to be optimum segmented. The second step is the image segmentation in order to perform the extraction process to retrieve the retina’s blood vessel from the eye fundus image. The image segmentation methods that will be analyzed in this study are Morphology Operation, Discrete Wavelet Transform and combination of both. The amount of data that used in this project is 40 for the retinal image and 40 for manually segmentation image. After doing some testing scenarios, the average accuracy for Morphology Operation method is 88.46 % while for Discrete Wavelet Transform is 89.28 %. By combining the two methods mentioned in later, the average accuracy was increased to 89.53 %. The result of this study is an image processing system that can segment the blood vessels in retinal fundus with high accuracy and low computation time.

Keywords: discrete wavelet transform, fundus retina, morphology operation, segmentation, vessel

Procedia PDF Downloads 188

Authors: Leonardo A. Ambrosio, Carlos. H. Silva Santos, Ivan E. L. Rodrigues, Ayumi K. de Campos, Leandro A. Machado

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In this work, we propose an algorithm developed under Python language for the modeling of ordinary scalar Bessel beams and their discrete superpositions and subsequent calculation of optical forces exerted over dielectric spherical particles. The mathematical formalism, based on the generalized Lorenz-Mie theory, is implemented in Python for its large number of free mathematical (as SciPy and NumPy), data visualization (Matplotlib and PyJamas) and multiprocessing libraries. We also propose an approach, provided by a synchronized Software as Service (SaaS) in cloud computing, to develop a user interface embedded on a mobile application, thus providing users with the necessary means to easily introduce desired unknowns and parameters and see the graphical outcomes of the simulations right at their mobile devices. Initially proposed as a free Android-based application, such an App enables data post-processing in cloud-based architectures and visualization of results, figures and numerical tables.

Keywords: Bessel Beams and Frozen Waves, Generalized Lorenz-Mie Theory, Numerical Methods, optical forces

Procedia PDF Downloads 370

Authors: Nutnicha Wongpadungkiat, Suwit Siriwatanayotin, Aluck Thipayarat, Punchira Vongsawasdi, Chotika Viriyarattanasak

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Chicken products are major export product of Thailand. With a dramatically increasing consumption of chicken product in the world, there are abundant wastes from chicken meat processing industry. Recently, much research in the development of value-added products from chicken meat industry has focused on the production of protein hydrolysate, utilized as food ingredients for human diet and animal feed. The present study aimed to determine the effect of thermal pre-treatment on functional properties of chicken protein hydrolysate. Chicken breasts were heated at 40, 60, 80 and 100ºC prior to hydrolysis by Alcalase at 60ºC, pH 8 for 4 hr. The hydrolysate was freeze-dried, and subsequently used for assessment of its functional properties molecular weight by gel electrophoresis (SDS-PAGE). The obtained results show that increasing the pre-treatment temperature increased oil holding capacity and emulsion stability while decreasing antioxidant activity and water holding capacity. The SDS-PAGE analysis showed the evidence of protein aggregation in the hydrolysate treated at the higher pre-treatment temperature. These results suggest the connection between molecular weight of the hydrolysate and its functional properties.

Keywords: chicken protein hydrolysate, enzymatic hydrolysis, thermal pretreatment, functional properties

Procedia PDF Downloads 258

Authors: Alberto Alfano, Sergio D’ambrosio, Darshankumar Parecha, Donatella Cimini, Chiara Schiraldi.

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The main objective of this study regards the setup of an efficient small-scale platform for the conversion of local renewable waste materials, such as whey, into added-value products, thereby reducing environmental impact and costs deriving from the disposal of processing waste products. The buffalo milk whey derived from the cheese-making process, called second cheese whey, is the main by-product of the dairy industry. Whey is the main and most polluting by-product obtained from cheese manufacturing consisting of lactose, lactic acid, proteins, and salts, making whey an added-value product. In Italy, and in particular, in the Campania region, soft cheese production needs a large volume of liquid waste, especially during late spring and summer. This project is part of a circular economy perspective focused on the conversion of potentially polluting and difficult to purify waste into a resource to be exploited, and it embodies the concept of the three “R”: reduce, recycle, and reuse. Special focus was paid to the production of health-promoting biomolecules and biopolymers, which may be exploited in different segments of the food and pharmaceutical industries. These biomolecules may be recovered through appropriate processes and reused in an attempt to obtain added value products. So, ultrafiltration and nanofiltration processes were performed to fractionate bioactive components starting from buffalo milk whey. In this direction, the present study focused on the implementation of a downstream process that converts waste generated from food and food processing industries into added value products with potential applications. Owing to innovative downstream and biotechnological processes, rather than a waste product may be considered a resource to obtain high added value products, such as food supplements (probiotics), cosmeceuticals, biopolymers, and recyclable purified water. Besides targeting gastrointestinal disorders, probiotics such as Lactobacilli have been reported to improve immunomodulation and protection of the host against infections caused by viral and bacterial pathogens. Interestingly, also inactivated microbial (probiotic) cells and their metabolic products, indicated as parabiotic and postbiotics, respectively, have a crucial role and act as mediators in the modulation of the host’s immune function. To boost the production of biomass (both viable and/or heat inactivated cells) and/or the synthesis of growth-related postbiotics, such as EPS, efficient and sustainable fermentation processes are necessary. Based on a “zero-waste” approach, wastes generated from local industries can be recovered and recycled to develop sustainable biotechnological processes to obtain probiotics as well as post and parabiotic, to be tested as bioactive compounds against gastrointestinal disorders. The results have shown it was possible to recover an ultrafiltration retentate with suitable characteristics to be used in skin dehydration, to perform films (i.e., packaging for food industries), or as a wound repair agent and a nanofiltration retentate to recover lactic acid and carbon sources (e.g., lactose, glucose..) used for microbial cultivation. On the side, the last goal is to obtain purified water that can be reused throughout the process. In fact, water reclamation and reuse provide a unique and viable opportunity to augment traditional water supplies, a key issue nowadays.

Keywords: biotech process, downstream process, probiotic growth, from waste to product, buffalo whey

Procedia PDF Downloads 60

Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

Procedia PDF Downloads 87

Authors: Marlyn Mathew

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Communication is the key factor in any vocational /job set-up. However many persons with disabilities suffer a deficit in this very area in terms of comprehension, expression and cognitive skills making it difficult for them to get employed appropriately or stay employed. Vocational Rehabilitation is a continuous and coordinated process which involves the provision of vocational related services designed to enable a person with disability to obtain and maintain employment. Therefore the role of the speech language pathologist is crucial in assessing the communication deficits and needs of the individual at the various phases of employment- right from the time of seeking a job and attending interview with suitable employers and also at regular intervals of the employment. This article discusses the various communication deficits and the obstacles faced by individuals with special needs including but not limited to cognitive- linguistic deficits, execution function deficits, speech and language processing difficulties and strategies that can be introduced in the workplace to overcome these obstacles including use of visual cues, checklists, flow charts. The paper also throws light on the importance of educating colleagues and work partners about the communication difficulties faced by the individual. This would help to reduce the communication barriers in the workplace, help colleagues develop an empathetic approach and also reduce misunderstandings that can arise as a result of the communication impairment.

Keywords: vocational rehabilitation, disability, speech language pathologist, cognitive, linguistics

Procedia PDF Downloads 126

Authors: Andrés C. Cuervo Pinilla, Christian G. Quintero M., Chinthaka Premachandra

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This paper considers people’s driving skills diagnosis under real driving conditions. In that sense, this research presents an approach that uses GPS signals which have a direct correlation with driving maneuvers. Besides, it is presented a novel expert-driving-criteria approximation using fuzzy logic which seeks to analyze GPS signals in order to issue an intelligent driving diagnosis. Based on above, this works presents in the first section the intelligent driving diagnosis system approach in terms of its own characteristics properties, explaining in detail significant considerations about how an expert-driving-criteria approximation must be developed. In the next section, the implementation of our developed system based on the proposed fuzzy logic approach is explained. Here, a proposed set of rules which corresponds to a quantitative abstraction of some traffics laws and driving secure techniques seeking to approach an expert-driving- criteria approximation is presented. Experimental testing has been performed in real driving conditions. The testing results show that the intelligent driving diagnosis system qualifies driver’s performance quantitatively with a high degree of reliability.

Keywords: driver support systems, intelligent transportation systems, fuzzy logic, real time data processing

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Authors: Sai Harshini Irigineni, Suresh Kumar Reddy Narala

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The industrial applicability of aluminium metal matrix composites (AMMCs) has been rapidly growing due to their exceptional materials traits such as low weight, high strength, excellent thermal performance, and corrosion resistance. The increasing demand for AMMCs in automobile, aviation, aerospace and defence ventures has opened up windows of opportunity for the development of processing methods that facilitate low-cost production of AMMCs with superior properties. In the present work, owing to its economy, efficiency, and suitability, powder metallurgy (P/M) technique was employed to develop AMMCs with pure aluminium as matrix material and titanium diboride (TiB₂) as reinforcement. AMMC samples with different weight compositions (Al-0.1%TiB₂, Al-5%TiB₂, Al-10%TiB₂, and Al-15% TiB₂) were prepared through hot press compacting followed by traditional sintering. The developed AMMC was subjected to metallographic studies and mechanical characterization. Experimental evidences show significant improvement in mechanical properties such as tensile strength, hardness with increasing reinforcement content. The current study demonstrates the superiority of AMMCs over conventional metals and alloys and the results obtained may be of immense in material selection for different structural applications.

Keywords: AMMCs, mechanical characterization, powder metallurgy, TiB₂

Procedia PDF Downloads 123

Authors: Felix U. Asoiro, Kingsley O. Anyichie, Meshack I. Simeon, Chinenye E. Azuka

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The work was aimed at studying the effects of microwave drying (450 W) and hot air oven drying on the drying kinetics and physico-functional properties of yams and cocoyams species. The yams and cocoyams were cut into chips of thicknesses of 3mm, 5mm, 7mm, 9mm, and 11mm. The drying characteristics of yam and cocoyam chips were investigated under microwave drying and hot air oven temperatures (50oC – 90oC). Drying methods, temperature, and thickness had a significant effect on the drying characteristics and physico-functional properties of yam and cocoyam. The result of the experiment showed that an increase in the temperature increased the drying time. The result also showed that the microwave drying method took lesser time to dry the samples than the hot air oven drying method. The iodine affinity of starch for yam was higher than that of cocoyam for the microwaved dried samples over those of hot air oven-dried samples. The results of the analysis would be useful in modeling the drying behavior of yams and cocoyams under different drying methods. It could also be useful in the improvement of shelf life for yams and cocoyams as well as designs of efficient systems for drying, handling, storage, packaging, processing, and transportation of yams and cocoyams.

Keywords: coco yam, drying, microwave, modeling, energy consumption, iodine affinity, drying ate

Procedia PDF Downloads 93

Authors: Abdullah Kaya, Muammer Koc

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A levelized cost analysis of solar energy powered seawater desalination in The Emirate of Abu Dhabi is conducted to show that clean and renewable desalination is economically viable. The Emirate heavily relies on seawater desalination for its freshwater needs due to limited freshwater resources available. This trend is expected to increase further due to growing population and economic activity, rapid decline in limited freshwater reserves, and aggravating effects of climate change. Seawater desalination in Abu Dhabi is currently done through thermal desalination technologies such as multi-stage flash (MSF) and multi-effect distillation (MED) which are coupled with thermal power plants known as co-generation. Our analysis indicates that these thermal desalination methods are inefficient regarding energy consumption and harmful to the environment due to CO₂ emissions and other dangerous byproducts. Therefore, utilization of clean and renewable desalination options has become a must for The Emirate for the transition to a sustainable future. The rapid decline in the cost of solar PV system for energy production and RO technology for desalination makes the combination of these two an ideal option for a future of sustainable desalination in the Emirate of Abu Dhabi. A Levelized cost analysis for water produced by solar PV + RO system indicates that Abu Dhabi is well positioned to utilize this technological combination for cheap and clean desalination for the coming years. It has been shown that cap-ex cost of solar PV powered RO system has potential to go as low as to 101 million US $ (1111 $/m³) at best case considering the recent technological developments. The levelized cost of water (LCW) values fluctuate between 0.34 $/m³ for the baseline case and 0.27 $/m³ for the best case. Even the highly conservative case yields LCW cheaper than 100% from all thermal desalination methods currently employed in the Emirate. Exponential cost decreases in both solar PV and RO sectors along with increasing economic scale globally signal the fact that a cheap and clean desalination can be achieved by the combination of these technologies.

Keywords: solar PV, RO desalination, sustainable desalination, levelized cost of analysis, Emirate of Abu Dhabi

Procedia PDF Downloads 154

Authors: Nacera Yassa, Abdelmalek Saidoune, Ghania Ouadfel, Hamza Houassine

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The rapid advancement in electrical technologies has underscored the increasing importance of multiphase machines across various industrial sectors. These machines offer significant advantages in terms of efficiency, compactness, and reliability compared to their single-phase counterparts. However, early detection and diagnosis of electrical faults remain critical challenges to ensure the durability and safety of these complex systems. This paper presents an advanced analytical model for multiphase machines, with a particular focus on dual stator asynchronous machines. The primary objective is to develop a robust diagnostic tool capable of effectively detecting and locating electrical faults in these machines, including short circuits, winding faults, and voltage imbalances. The proposed methodology relies on an analytical approach combining electrical machine theory, modeling of magnetic and electrical circuits, and advanced signal analysis techniques. By employing detailed analytical equations, the developed model accurately simulates the behavior of multiphase machines in the presence of electrical faults. The effectiveness of the proposed model is demonstrated through a series of case studies and numerical simulations. In particular, special attention is given to analyzing the dynamic behavior of machines under different types of faults, as well as optimizing diagnostic and recovery strategies. The obtained results pave the way for new advancements in the field of multiphase machine diagnostics, with potential applications in various sectors such as automotive, aerospace, and renewable energies. By providing precise and reliable tools for early fault detection, this research contributes to improving the reliability and durability of complex electrical systems while reducing maintenance and operation costs.

Keywords: faults, diagnosis, modelling, multiphase machine

Procedia PDF Downloads 50

Authors: Rudi P. Nielsen, Karina H. Hansen, Morten E. Simonsen

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To improve the possibility of the chemical recycling of mixed plastic waste, such as municipal plastic waste, work has been conducted to gain an understanding of the effect of typical polymers from waste (PP, PET, and PA) on the quality of the pyrolysis oil produced. Plastic fractions were pyrolyzed in a lab-scale reactor system, with mixture compositions of up to 15 wt.% PET and five wt.% PA in a PP matrix and processing conditions from 400 to 450°C. The experiments were conducted as a full factorial design and in duplicates to provide reliable results and the possibility to determine any interactions between the parameters. The products were analyzed using FT-IR and GC-MS for compositional information as well as the determination of calorific value, ash content, acid number, density, viscosity, and elemental analysis to provide further data on the fuel quality of the pyrolysis oil. Oil yield was found to be between 61 and 84 wt.%, while char yield was below 2.6 wt.% in all cases. The calorific value of the produced oil was between 32 and 46 MJ/kg, averaging at approx. 41 MJ/kg, thus close to that of heavy fuel oil. The oil product was characterized to contain aliphatic and cyclic hydrocarbons, alcohols, and ethers with chain lengths between 10 and 25 carbon atoms. Overall, it was found that the addition of PET decreased oil yield, while the addition of both PA and PET decreased oil quality in general by increasing acid number (PET), decreasing calorific value (PA), and increasing nitrogen content (PA). Furthermore, it was identified that temperature increased ammonia production from PA during pyrolysis, while ammonia production was decreased by the addition of PET.

Keywords: PET, plastic waste, polyamide, polypropylene, pyrolysis

Procedia PDF Downloads 140

Authors: Franklin Thambi Jose.S

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Computational Linguistics is a branch of linguistics, which deals with the computer and linguistic levels. It is also said, as a branch of language studies which applies computer techniques to linguistics field. In Computational Linguistics, Natural Language Processing plays an important role. This came to exist because of the invention of Information Technology. In computational syntax, the syntactic analyser breaks a sentence into phrases and clauses and identifies the sentence with the syntactic information. Tamil is one of the major Dravidian languages, which has a very long written history of more than 2000 years. It is mainly spoken in Tamilnadu (in India), Srilanka, Malaysia and Singapore. It is an official language in Tamilnadu (in India), Srilanka, Malaysia and Singapore. In Malaysia Tamil speaking people are considered as an ethnic group. In Tamil syntax, the sentences in Tamil are classified into four for this research, namely: 1. Main Sentence 2. Interrogative Sentence 3. Equational Sentence 4. Elliptical Sentence. In computational syntax, the first step is to provide required information regarding the head and its constituent of each sentence. This information will be incorporated to the system using programming languages. Now the system can easily analyse a given sentence with the criteria or mechanisms given to it. Providing needful criteria or mechanisms to the computer to identify the basic types of sentences using Syntactic parser in Tamil language is the major objective of this paper.

Keywords: tamil, syntax, criteria, sentences, parser

Procedia PDF Downloads 511

Authors: N. Cetinkaya, Y. S. Kuleyin

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The aim of this study was to estimate the digestibility of the fruit internal skin of different varieties of hazelnuts to propose hazelnut fruit skin as an alternative feed source as roughage in ruminant nutrition. In 2015, the fruit internal skins of three different varieties of round hazelnuts (RH), pointed hazelnuts (PH) and almond hazelnuts (AH) were obtained from hazelnut processing factory then their crude nutrients analysis were carried out. Organic matter digestibility (OMD) and metabolisable energy (ME) values of hazelnut fruit skins were estimated from gas measured by in vitro gas production method. Their antioxidant activities were determined by spectrophotometric method. Crude nutrient values of three different varieties were; organic matter (OM): 87.83, 87.81 and 87.78%), crude protein (CP): 5.97, 5.93 and 5.89%, neutral detergent fiber (NDF): 30.30, 30.29 and 30.29%, acid detergent fiber (ADF): 48.68, 48.67 and 48.66% and acid detergent lignin (ADL): 25.43, 25.43 and 25.39% respectively. OMD from 24 h incubation time of RH, PH and AH were 22.04, 22.46 and 22.74%; ME_GP values were 3.69, 3.75 and 3.79 MJ/kg DM; and antioxidant activity values were 94.60, 94.54 and 94.52 IC 50 mg/mL respectively. The fruit internal skin of different varieties of hazelnuts may be considered as an alternative roughage for ruminant nutrition regarding to their crude and digestible nutritive values. Moreover, hazelnut fruit skin has a rich antioxidant content so it may be used as a feed additive for both ruminant and non-ruminant animals.

Keywords: antioxidant activity, hazelnut fruit skin, metabolizable energy, organic matter digestibility

Procedia PDF Downloads 297

Authors: Mehmet Nefes, Selman Demirel, Hasan H. Ertok, Cenk Sen

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A typical reliability engineering problem regarding communication satellites has been considered to determine redundancy allocation scheme of power amplifiers within payload transponder module, whose dominant function is to amplify power levels of the received signals from the Earth, through maximizing reliability against mass, power, and other technical limitations. Adding each redundant power amplifier component increases not only reliability but also hardware, testing, and launch cost of a satellite. This study investigates a multi-objective approach used in order to solve Redundancy Allocation Problem (RAP) for a communication satellite payload transponder, focusing on design cost due to redundancy and reliability factors. The main purpose is to find the optimum power amplifier redundancy configuration satisfying reliability and capacity thresholds simultaneously instead of analyzing respectively or independently. A mathematical model and calculation approach are instituted including objective function definitions, and then, the problem is solved analytically with different input parameters in MATLAB environment. Example results showed that payload capacity and failure rate of power amplifiers have remarkable effects on the solution and also processing time.

Keywords: communication satellite payload, multi-objective optimization, redundancy allocation problem, reliability, transponder

Procedia PDF Downloads 257

Authors: Annamarija Paula

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Modern psychology is divided into three distinct domains: cognition, affect, and conation. Historically, psychology devalued the importance of studying the effect in order to explain human behavior as it supposedly lacked both rational thought and a scientific foundation. As a result, affect remained the least studied domain for years to come. However, the last 30 years have marked a significant change in perspective, claiming that not only is affect highly adaptive, but it also plays a crucial role in cognitive processes. Affective states have a crucial impact on human behavior, which led to fundamental advances in the study of affective states on perception and judgment. Positive affect and negative affect are distinct entities and have different effects on social information processing. In addition, emotions of the same valence are manifested in distinct and unique physiological reactions indicating that not all forms of positive or negative affect are the same or serve the same purpose. The effect plays a vital role in perception and judgments, which impacts the validity and reliability of memory retrieval. The research paper analyzes key findings from the past three decades of observational and empirical research on affective states and cognition. The paper also addresses the limitations connected to the findings and proposes suggestions for possible future research.

Keywords: memory, affect, perception, judgement, mood congruency effect

Procedia PDF Downloads 120

Authors: Irshad Ali Khan, Jian-Ping Lu, Xiao-Hong Liu, Fu-Cheng Lin

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This study reports the functional analysis of a gene MoNUC1 in M. oryzae, which is homologous to the Saccharomyces cerevisiae NUC1 encoding a mitochondrial nuclease protein. The MoNUC1 having a gene locus MGG_05324 is 1002-bp in length and encodes an identical protein of 333 amino acids. We disrupted the gene through gene disruption strategy and isolated two mutants confirmed by southern blotting. The deleted mutants were then used for phenotypic studies and their phenotypes were compared to those of the Guy-11 strain. The mutants were first grown on CM medium to find the effect of MoNUC1 gene disruption on colony growth and the mutants were found to show normal culture colony growth similar to that of the Guy-11 strain. Conidial germination and appressorial formation were also similar in both the mutants and Guy-11 strains showing that this gene plays no significant role in these phenotypes. For pathogenicity, the mutants and Guy-11 mycelium blocks were inoculated on blast susceptible barley seedlings and it was found that both the strains exhibited full pathogenicity showing coalesced and necrotic blast lesions suggesting that this gene is not involved in pathogenicity. Mating of the mutants with 2539 strain formed numerous perithecia showing that MoNUC1 is not essential for sexual reproduction in M. oryzae. However, the mutants were found to form reduced conidia (1.06±8.03B and 1.08±9.80B) than those of the Guy-11 strain (1.46±10.61A) and we conclude that this protein is not required for the blast fungus to cause pathogenicity but plays significant role in conidiation. Proteins of signal transduction pathways that could be disrupted/ intervened genetically or chemically could lead to antifungal products of important fungal cereal diseases and reduce rice yield losses. Tipping the balance toward understanding the whole of pathogenesis, rather than simply conidiation will take some time, but clearly presents the most exciting challenge of all.

Keywords: appressorium formation, conidiation, NUC1, Magnaporthe oryzae, pathogenicity

Procedia PDF Downloads 486

Authors: Darsh N. Patel, Eric Olson

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Fractals can be found everywhere, whether it be the shape of a leaf or a system of blood vessels. Fractals are used to help study and understand different physical and mathematical processes; however, their artistic nature is also beautiful to simply explore. This project explores fractals generated by a cubically convergent extension to Newton's method. With this iteration as a starting point, a complex plane spanning from -2 to 2 is created with a color wheel mapped onto it. Next, the polynomial whose roots the fractal will generate from is established. From the Fundamental Theorem of Algebra, it is known that any polynomial has as many roots (counted by multiplicity) as its degree. When generating the fractals, each root will receive its own color. The complex plane can then be colored to indicate the basins of attraction that converge to each root. From a computational point of view, this project’s code identifies which points converge to which roots and then obtains fractal images. A zoom path into the fractal was implemented to easily visualize the self-similar structure. This path was obtained by selecting keyframes at different magnifications through which a path is then interpolated. Using parallel processing, many images were generated and condensed into a video. This project illustrates how practical techniques used for scientific visualization can also have an artistic side.

Keywords: fractals, cubic method, Julia programming language, basin of attraction

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Authors: G. Kermarrec, J. Hartmann

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Spline surfaces are a major representation of freeform surfaces in the computer-aided graphic industry and were recently introduced in the field of geodesy for processing point clouds from terrestrial laser scanner (TLS). The surface fitting consists of approximating a trustworthy mathematical surface to a large numbered 3D point cloud. The standard B-spline surfaces lack of local refinement due to the tensor-product construction. The consequences are oscillating geometry, particularly in the transition from low-to-high curvature parts for scattered point clouds with missing data. More economic alternatives in terms of parameters on how to handle point clouds with a huge amount of observations are the recently introduced T-splines. As long as the partition of unity is guaranteed, their computational complexity is low, and they are flexible. T-splines are implemented in a commercial package called Rhino, a 3D modeler which is widely used in computer aided design to create and animate NURBS objects. We have applied T-splines surface fitting to terrestrial laser scanner point clouds from a bridge under load and a sheet pile wall with noisy observations. We will highlight their potential for modelling details with high trustworthiness, paving the way for further applications in terms of deformation analysis.

Keywords: deformation analysis, surface modelling, terrestrial laser scanner, T-splines

Procedia PDF Downloads 134

Authors: Ergun Sakalar, Kubra Bilgic

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Faster detection and characterization of pathogens are the basis of the evoid from foodborne pathogens. Salmonella spp., Shigella spp. and Listeria monocytogenes are common foodborne bacteria that are among the most life-threatining. It is important to rapid and accurate detection of these pathogens to prevent food poisoning and outbreaks or to manage food chains. The present work promise to develop a sensitive, species specific and reliable PCR based detection system for simultaneous detection of Salmonella spp., Shigella spp. and Listeria monocytogenes. For this purpose, three genes were picked out, ompC for Salmonella spp., ipaH for Shigella spp. and hlyA for L. monocytogenes. After short pre-enrichment of milk was passed through a vacuum filter and bacterial DNA was exracted using commercially available kit GIDAGEN®(Turkey, İstanbul). Detection of amplicons was verified by examination of the melting temperature (Tm) that are 72° C, 78° C, 82° C for Salmonella spp., Shigella spp. and L. monocytogenes, respectively. The method specificity was checked against a group of bacteria strains, and also carried out sensitivity test resulting in under 10² CFU mL⁻¹ of milk for each bacteria strain. Our results show that the flourescence based triplex qPCR method can be used routinely to detect Salmonella spp., Shigella spp. and L. monocytogenes during the milk processing procedures in order to reduce cost, time of analysis and the risk of foodborne disease outbreaks.

Keywords: evagreen, food-born bacteria, pathogen detection, real-time pcr

Procedia PDF Downloads 239

Authors: Ma. Gracia Corazon Cayanan, Kai Yuen Cheong, Li Sha

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Training a language model for a minority language has been a challenging task. The lack of available corpora to train and fine-tune state-of-the-art language models is still a challenge in the area of Natural Language Processing (NLP). Moreover, the need for high computational resources and bulk data limit the attainment of this task. In this paper, we presented the following contributions: (1) we introduce and used a translation pair set of Tagalog and English (TL-EN) in pre-training a language model to a minority language resource; (2) we fine-tuned and evaluated top-ranking and pre-trained semantic textual similarity binary task (STSB) models, to both TL-EN and STS dataset pairs. (3) then, we reduced the size of the model to offset the need for high computational resources. Based on our results, the models that were pre-trained to translation pairs and STS pairs can perform well for STSB task. Also, having it reduced to a smaller dimension has no negative effect on the performance but rather has a notable increase on the similarity scores. Moreover, models that were pre-trained to a similar dataset have a tremendous effect on the model’s performance scores.

Keywords: semantic matching, semantic textual similarity binary task, low resource minority language, fine-tuning, dimension reduction, transformer models

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Taha Bensiradj, Samira Moussaoui

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Hybrid Sensors and Vehicular Networks (HSVN), represent a hybrid network, which uses several generations of Ad-Hoc networks. It is used especially in Intelligent Transport Systems (ITS). The HSVN allows making collaboration between the Wireless Sensors Network (WSN) deployed on the border of the road and the Vehicular Network (VANET). This collaboration is defined by messages exchanged between the two networks for the purpose to inform the drivers about the state of the road, provide road safety information and more information about traffic on the road. Moreover, this collaboration created by HSVN, also allows the use of a network and the advantage of improving another network. For example, the dissemination of information between the sensors quickly decreases its energy, and therefore, we can use vehicles that do not have energy constraint to disseminate the information between sensors. On the other hand, to solve the disconnection problem in VANET, the sensors can be used as gateways that allow sending the messages received by one vehicle to another. However, because of the short communication range of the sensor and its low capacity of storage and processing of data, it is difficult to ensure the exchange of road messages between it and the vehicle, which can be moving at high speed at the time of exchange. This represents the time where the vehicle is in communication range with the sensor. This work is the proposition of a communication protocol between the sensors and the vehicle used in HSVN. The latter has as the purpose to ensure the exchange of road messages in the available time of exchange.

Keywords: HSVN, ITS, VANET, WSN

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Authors: Abbas Mohamed Abbas, Raafat El-Shafie Fat-Helbary, Karrar Omar El Fergawy, Ahmed Hamed Sayed

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The exploration in archaeological area requires non-invasive methods, and hence the Ground Penetrating Radar (GPR) technique is a proper candidate for this task. GPR investigation is widely applied for searching for hidden ancient targets. So, in this paper GPR technique has been used in archaeological investigation. The aim of this study was to obtain information about the subsurface and associated structures beneath two selected sites at the western bank of the River Nile at Aswan city. These sites have archaeological structures of different ages starting from 6thand 12th Dynasties to the Greco-Roman period. The first site is called Nag’ El Gulab, the study area was 30 x 16 m with separating distance 2m between each profile, while the second site is Nag’ El Qoba, the survey method was not in grid but in lines pattern with different lengths. All of these sites were surveyed by GPR model SIR-3000 with antenna 200 MHz. Beside the processing of each profile individually, the time-slice maps have been conducted Nag’ El Gulab site, to view the amplitude changes in a series of horizontal time slices within the ground. The obtained results show anomalies may interpret as presence of associated tombs structures. The probable tombs structures similar in their depth level to the opened tombs in the studied areas.

Keywords: ground penetrating radar, archeology, Nag’ El Gulab, Nag’ El Qoba

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Authors: Maiss Razem

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The construction sector is considered a major consumer of materials that undergoes processes of extraction, processing, transportation, and maintaining when used in buildings. Several metrics have been devised to capture the environmental impact of the materials consumed during construction using lifecycle thinking. Rarely has the materiality of this sector been explored qualitatively and systemically. This paper aims to explore socio-cultural forces that drive the use of certain materials in the Jordanian construction industry, using practice theory as a heuristic method of analysis, more specifically Shove et al. three-element model. By conducting semi-structured interviews with architects, the results unravel contextually embedded routines when determining qualities of three materialities highlighted herein; stone, glass and spatial openness. The study highlights the inadequacy of only using efficiency as a quantitative metric of sustainable materials and argues for the need to link material consumption with socio-economic, cultural, and aesthetic driving forces. The operationalization of practice theory by tracing materials’ lifetimes as they integrate with competencies and meanings captures dynamic engagements through the analyzed routines of actors in the construction practice. This study can offer policymakers better-nuanced representation to green this sector beyond efficiency rhetoric and quantitative metrics.

Keywords: architects' practices, construction materials, Jordan, practice theory

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Authors: Stanley Dula, Oluwatosini A. Ijabadeniyi

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Biofilm formation is a major source of materials and foodstuffs contamination, contributing to occurrence of pathogenic and spoilage microbes in food processing resulting in food spoilage, transmission of diseases and significant food hygiene and safety issues. This study elucidates biofilm formation of E. coli O157:H7 and L. monocytogenes ATCC 7644 grown under food related environmental stress conditions of varying pH (5.0;7.0; and 8.5) and temperature (15, 25 and 37 ℃). Both strains showed confluent biofilm formation at 25 ℃ and 37 ℃, at pH 8.5 after 5 days. E. coli showed curli fimbriae production at various temperatures, while L. monocytogenes did not show pronounced expression. Swarm, swimming and twitching plate assays were used to determine strain motilities. Characterization of cell hydrophobicity was done using the microbial adhesion to hydrocarbons (MATH) assay using n-hexadecane. Both strains showed hydrophilic characteristics as they fell within a < 20 % interval. FT-IR revealed COOH at 1622 cm-1, and a strong absorption band at 3650 cm-1 – 3200 cm-1 indicating the presence of both -OH and -NH groups. Both strains were hydrophilic and could form biofilm at different combinations of temperature and pH. EPS produced in both species proved to be an acidic hetero-polysaccharide.

Keywords: biofilm, pathogens, hydrophobicity, motility

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Authors: Somojit Saha, Rohit K. Chatterjee, Sarit K. Das, Avijit Kar

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A new force field is designed for propagation of the parametric contour into deep narrow cortical fold in the application of knowledge based reconstruction of cerebral cortex from MR image of brain. Designing of this force field is highly inspired by the Generalized Gradient Vector Flow (GGVF) model and markedly differs in manipulation of image information in order to determine the direction of propagation of the contour. While GGVF uses edge map as its main driving force, the newly designed force field uses the map of distance between zero valued pixels and their nearest non-zero valued pixel as its main driving force. Hence, it is called Zero-Non-Zero Distance (ZNZD) force field. The objective of this force field is forceful propagation of the contour beyond spurious convergence due to partial volume effect (PVE) in to narrow sulcal fold. Being function of the corresponding non-zero pixel value, the force field has got an inherent property to determine spuriousness of the edge automatically. It is effectively applied along with some morphological processing in the application of cortical reconstruction to breach the hindrance of PVE in narrow sulci where conventional GGVF fails.

Keywords: deformable model, external force field, partial volume effect, cortical reconstruction, MR image of brain

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Authors: Nayer Mofidtabatabaei

Abstract:

Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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