Search results for: multilayer dyadic Green’s function

Authors: H. M. Côrtes, J. I. Da Silva Filho, M. F. Blos, B. S. Zanon

Abstract:

In a modern society the factor corresponding to the increase in the level of quality in industrial production demand new techniques of control and machinery automation. In this context, this work presents the implementation of a Paraconsistent-Fuzzy Digital PID controller. The controller is based on the treatment of inconsistencies both in the Paraconsistent Logic and in the Fuzzy Logic. Paraconsistent analysis is performed on the signals applied to the system inputs using concepts from the Paraconsistent Annotated Logic with annotation of two values (PAL2v). The signals resulting from the paraconsistent analysis are two values defined as Dc - Degree of Certainty and Dct - Degree of Contradiction, which receive a treatment according to the Fuzzy Logic theory, and the resulting output of the logic actions is a single value called the crisp value, which is used to control dynamic system. Through an example, it was demonstrated the application of the proposed model. Initially, the Paraconsistent-Fuzzy Digital PID controller was built and tested in an isolated MATLAB environment and then compared to the equivalent Digital PID function of this software for standard step excitation. After this step, a level control plant was modeled to execute the controller function on a physical model, making the tests closer to the actual. For this, the control parameters (proportional, integral and derivative) were determined for the configuration of the conventional Digital PID controller and of the Paraconsistent-Fuzzy Digital PID, and the control meshes in MATLAB were assembled with the respective transfer function of the plant. Finally, the results of the comparison of the level control process between the Paraconsistent-Fuzzy Digital PID controller and the conventional Digital PID controller were presented.

Keywords: fuzzy logic, paraconsistent annotated logic, level control, digital PID

Procedia PDF Downloads 276

Authors: Qian Zhu, Shidong Nie, Bo Yang, Gang Xiong, Guoxin Dai

Abstract:

GJ steel is a new type of high-performance structural steel which has been increasingly adopted in practical engineering. Q460GJ structural steel has a nominal yield strength of 460 MPa, which does not decrease significantly with the increase of steel plate thickness like normal structural steel. Thus, Q460GJ structural steel is normally used in medium-walled welded sections. However, research works on the residual stress in GJ steel members are few though it is one of the vital factors that can affect the member and structural behavior. This article aims to investigate the residual stresses in welded I-shaped sections fabricated from Q460GJ structural steel plates by experimental tests. A total of four full scale welded medium-walled I-shaped sections were tested by sectioning method. Both circular curve correction method and straightening measurement method were adopted in this study to obtain the final magnitude and distribution of the longitudinal residual stresses. In addition, this paper also explores the interaction between flanges and webs. And based on the statistical evaluation of the experimental data, a multilayer residual stress model is proposed.

Keywords: Q460GJ structural steel, residual stresses, sectioning method, welded medium-walled I-shaped sections

Procedia PDF Downloads 309

Authors: H. Nouri, S. Chavoshi Borujeni, S. Anderson, S. Beecham, P. Sutton

Abstract:

The potential risk of salt leaching through wastewater irrigation is of concern for most local governments and city councils. Despite the necessity of salinity monitoring and management in urban greenery, most attention has been on agricultural fields. This study was defined to investigate the capability and feasibility of monitoring and predicting soil salinity using near sensing and remote sensing approaches using EM38 surveys, and high-resolution multispectral image of WorldView3. Veale Gardens within the Adelaide Parklands was selected as the experimental site. The results of the near sensing investigation were validated by testing soil salinity samples in the laboratory. Over 30 band combinations forming salinity indices were tested using image processing techniques. The outcomes of the remote sensing and near sensing approaches were compared to examine whether remotely sensed salinity indicators could map and predict the spatial variation of soil salinity through a potential statistical model. Statistical analysis was undertaken using the Stata 13 statistical package on over 52,000 points. Several regression models were fitted to the data, and the mixed effect modelling was selected the most appropriate one as it takes to account the systematic observation-specific unobserved heterogeneity. Results showed that SAVI (Soil Adjusted Vegetation Index) was the only salinity index that could be considered as a predictor for soil salinity but further investigation is needed. However, near sensing was found as a rapid, practical and realistically accurate approach for salinity mapping of heterogeneous urban vegetation.

Keywords: WorldView3, remote sensing, EM38, near sensing, urban green spaces, green smart cities

Procedia PDF Downloads 157

Authors: Seyilnan Hannah Wadak, Dangway Monica Clement

Abstract:

This theoretical study explores distinct teaching methods and practices for integrating sustainable development principles into vocational education. It examines how vocational institutions can prepare students for a sustainability-oriented workforce while addressing environmental and social challenges. The research analyzes current literature, case studies, and emerging trends to identify effective strategies for incorporating sustainability across various vocational disciplines. Key approaches discussed include experiential learning, green skills training, and interdisciplinary projects that simulate real-world sustainability challenges. The study also investigates the role of technology, such as virtual reality and online collaboration tools, in enhancing sustainability education. Additionally, it addresses the importance of industry partnerships and community engagement in creating relevant, practical learning experiences. The paper highlights potential barriers to implementation and proposes solutions for overcoming them, including professional development for educators and curriculum redesign. Findings suggest that integrating sustainability into vocational education not only enhances students’ employability but also contributes to broader societal goals of sustainable development. This research provides a comprehensive framework for educational institutions and policymakers to transform vocational programs, ensuring they meet the evolving demands of a sustainable future.

Keywords: vocational education, sustainable development, teaching methods, experiential learning, green skills, curriculum integration, industry partnerships, educational technology

Procedia PDF Downloads 13

Authors: Vun Yee Thien, Kenneth Francis Rodrigues, Clemente Michael Vui Ling Wong, Wilson Thau Lym Yong

Abstract:

Transcriptomes associated with the process of photosynthesis have offered insights into the mechanism of gene regulation in terrestrial plants; however, limited information is available as far as macroalgae are concerned. This investigation aims to decipher the underlying mechanisms associated with photosynthesis in the red alga, Kappaphycus alvarezii, by performing a differential expression analysis on a de novo assembled transcriptomes. Comparative analysis of gene expression was designed to examine the alteration of light qualities and its effect on physiological mechanisms in the red alga. High-throughput paired-end RNA-sequencing was applied to profile the transcriptome of K. alvarezii irradiated with different wavelengths of light (blue 492-455 nm, green 577-492 nm and red 780-622 nm) as compared to the full light spectrum, resulted in more than 60 million reads individually and assembled using Trinity and SOAPdenovo-Trans. The transcripts were annotated in the NCBI non-redundant (nr) protein, SwissProt, KEGG and COG databases with a cutoff E-value of 1e-5 and nearly 30% of transcripts were assigned to functional annotation by Blast searches. Differential expression analysis was performed using edgeR. The DEGs were designated to six categories: BL (blue light) regulated, GL (green light) regulated, RL (red light) regulated, BL or GL regulated, BL or RL regulated, GL or RL regulated, and either BL, GL or RL regulated. These DEGs were mapped to terms in KEGG database and compared with the whole transcriptome background to search for genes that regulated by light quality. The outcomes of this study will enhance our understanding of molecular mechanisms underlying light-induced responses in red algae.

Keywords: de novo transcriptome sequencing, differential gene expression, Kappaphycus alvareziired, red alga

Procedia PDF Downloads 504

Authors: Alexandre Marin, Alexandra Bac, Laurent Astart

Abstract:

New numerical methods for PDE resolution (such as Finite Volumes (FV) or Virtual Elements Method (VEM)) open new needs in terms of meshing of domains of interest, and in particular, polyhedral meshes have many advantages. One way to build such meshes consists of constructing Restricted Voronoi Diagrams (RVDs) whose boundaries respect the domain of interest. By minimizing a function defined for RVDs, the shapes of cells can be controlled, e.g., elongated according to user-defined directions or adjusted to comply with given aspect ratios (anisotropy) and density variations. In this paper, our contribution is threefold: First, we introduce a new gradient formula for the Voronoi tessellation energy under a continuous anisotropy field. Second, we describe a meshing algorithm based on the optimisation of this function that we validate against state-of-the-art approaches. Finally, we propose a hierarchical approach to speed up our meshing algorithm.

Keywords: anisotropic Voronoi diagrams, meshes for numerical simulations, optimisation, volumic polyhedral meshing

Procedia PDF Downloads 98

Authors: Cristian Păuna

Abstract:

After the widespread release of electronic trading, automated trading systems have become a significant part of the business intelligence system of any modern financial investment company. An important part of the trades is made completely automatically today by computers using mathematical algorithms. The trading decisions are taken almost instantly by logical models and the orders are sent by low-latency automatic systems. This paper will present a real-time price prediction methodology designed especially for algorithmic trading. Based on the price cyclicality function, the methodology revealed will generate price cyclicality bands to predict the optimal levels for the entries and exits. In order to automate the trading decisions, the cyclicality bands will generate automated trading signals. We have found that the model can be used with good results to predict the changes in market behavior. Using these predictions, the model can automatically adapt the trading signals in real-time to maximize the trading results. The paper will reveal the methodology to optimize and implement this model in automated trading systems. After tests, it is proved that this methodology can be applied with good efficiency in different timeframes. Real trading results will be also displayed and analyzed in order to qualify the methodology and to compare it with other models. As a conclusion, it was found that the price prediction model using the price cyclicality function is a reliable trading methodology for algorithmic trading in the financial market.

Keywords: algorithmic trading, automated trading systems, financial markets, high-frequency trading, price prediction

Procedia PDF Downloads 178

Authors: Rana Sameeh

Abstract:

The city is the greatest symbol of human civilization and has been built for safety and comfort. However, uncontrolled urban growth caused some anonymous and unsightly images of the cities such as unused or abandoned spaces. When social interaction is missed in a public space it means the public space is lost since public spaces reflect the social life and interaction of people. Accordingly; this space became one of the most meaningless parts of the cities and has broken the continuity of the urban fabric. Lost urban spaces are the leftover unstructured landscape within the urban fabric. They are generally the unrecognized urban areas that are in need of redesign, since they have a great value that can add to their surrounding urban context. The research significance lies within the importance of urban open spaces, their value and their impact on the urban fabric. The research also addresses the reuse and reclamation of lost urban spaces in order to increase the percentage of green areas along the urban fabric, provide urban open spaces, develop a sustainable approach towards urban landscape and enhance the quality of the public open space and user experience. In addition, the reuse of lost space will give it the identity and function it lacks while also providing places for presence, spending time and observing. Creating continuity in a broken urban fabric represents an exploratory process in the relationship between infrastructure and the urban fabric and seeks to establish an architectural solution to leftover space within the city. In doing so, the research establishes a framework (criteria) for adaptive reuse of lost urban space throughout inductive and deductive methodology, analytical methodology; by analyzing some relevant examples and similar cases of lost spaces and finally through field methodology; by applying the achieved criteria on a case study in Alexandria and carrying on SWOT analysis and evaluation of the potentials of this case study.

Keywords: adaptive reuse, lost urban space, quality of public open space, urban fabric

Procedia PDF Downloads 635

Authors: Mohammadsadegh Zanganehfar

Abstract:

Since the introduction of fractal geometry in 1970, numerous efforts have been made by architects and researchers to transfer this area of mathematical knowledge in the discipline of architecture and postmodernist discourse. The discourse of complexity and architecture is one of the most significant ongoing discourses in the discipline of architecture from the '70s until today and has generated significant styles such as deconstructivism and parametrism in architecture. During these years, several projects were designed and presented by designers and architects using fractal geometry, but due to the lack of sufficient knowledge and appropriate comprehension of the features and characteristics of this nonlinear geometry, none of the fractal-based designs have been successful and satisfying. Fractal geometry as a geometric technology has a long presence in the history of architecture. The current research attempts to identify and discover the characteristics, features, potentials, and functionality of fractals despite their aesthetic aspect by examining case studies of pre-modern architecture in Asia and investigating the function of fractals.

Keywords: Asian architecture, fractal geometry, fractal technique, geometric properties

Procedia PDF Downloads 253

Authors: Anushaa A.

Abstract:

In this work, silver nanoparticles (AgNP) were manufactured directly without harmful chemicals utilising methanol extract (SNLME) Solanum nigrume leaves. We are using nigrum leaf extract from Solanum, which converts silver nitrate to silver ions, for synthesization purposes. An examination of the AgNP produced was performed using ultraviolet (UV-VIS) spectroscopy, infrared spectroscopy (FTIR) transformed from Fourier and scanning electrons (SEM). Biological activity was also tested. UV-VIS has proven that biosynthesized AgNP exists (420-450 nm). The FTIR spectrum has been utilised to confirm the presence of different functional groups within the biomolecules, which are a nanoparticular capping agent and the spectroscopic and crystal nature of AgNP. The viability of the silver nanoparticles was evaluated using zeta potential calculations. Negative zeta potential of -33.4 mV demonstrated the stability of silver-nanoparticles. The morphology of AgNP was examined using a scanning electron microscope. Greenly generated AgNP showed significant anti-Staphylococcus aureus, Candida, and Escherichia coli action. The green AgNP demonstration indicated that the IC50 for the human teratocarcinoma cell line was 29.24 μg/ml during 24 hours of therapy (PA1 Ovarian cell line). The dose-dependent effects were reported in both antibacterial and cytotoxicity assays and as an effective agent. Finally, the findings of this research showed that silver nanoparticles generated might serve as a viable therapeutic agent to combat microorganisms killing and curing cancer.

Keywords: antimicrobial activity, PA1 ovarian cancer cell line, silver nanoparticles, Solanum nigrum

Procedia PDF Downloads 180

Authors: Fatemeh Khalili Varnamkhasti

Abstract:

Natural administration has outside impacts such that companies regularly respect natural input as a fetched with no clear advantage. In this manner, in case natural security can bring financial benefits, showing that natural security and financial interface are in concordance, companies will effectively fulfill their obligation to ensure the environment. Contamination is, for the most part, related to the squandering of assets, misplaced vitality, and crude materials not completely utilized. Contamination avoidance and clean innovation, as inner organizational hones, can offer assistance to play down taken toll and to develop economic aptitudes for the long run, whereas outside organizational hones (item stewardship and maintainability vision) can offer assistance to coordinated partner sees into trade operations and to define future commerce directions. Taken together, these practices can drive shareholder esteem while at the same time contributing to a more feasible world. On the off chance that the company's budgetary execution is nice, it'll draw in financial specialists to contribute and progress the company's execution. In this way, budgetary execution is additionally the determinant of the progression of a company. This can be because the monetary back gotten by the company gets to be the premise for the running of trade forms in the future. Moreover, A green picture can assist firms in pulling in more clients by influencing shopper choices and moving forward with buyer brand dependability. Numerous shoppers need to purchase items from ecologically inviting firms, in spite of the fact that there are, of course, a few who will not pay premium costs for green items.

Keywords: environmental activities, financial performanance, advantage, clients

Procedia PDF Downloads 49

Authors: Farideh Namvar, Rosfarizan Mohamed

Abstract:

In the field of nanotechnology, the use of various biological units instead of toxic chemicals for the reduction and stabilization of nanoparticles, has received extensive attention. This use of biological entities to create nanoparticles has designated as “Green” synthesis and it is considered to be far more beneficial due to being economical, eco-friendly and applicable for large-scale synthesis as it operates on low pressure, less input of energy and low temperatures. The lack of toxic byproducts and consequent decrease in degradation of the product renders this technique more preferable over physical and classical chemical methods. The variety of biomass having reduction properties to produce nanoparticles makes them an ideal candidate for fabrication. Metal oxide nanoparticles have been said to represent a "fundamental cornerstone of nanoscience and nanotechnology" due to their variety of properties and potential applications. However, this also provides evidence of the fact that metal oxides include many diverse types of nanoparticles with large differences in chemical composition and behaviour. In this study, iron oxide nanoparticles (Fe3O4-NPs) were synthesized using a rapid, single step and completely green biosynthetic method by reduction of ferric chloride solution with brown seaweed (Sargassum muticum) water extract containing polysaccharides as a main factor which acts as reducing agent and efficient stabilizer. Antimicrobial activity against six microorganisms was tested using well diffusion method. The resulting S-IONPs are crystalline in nature, with a cubic shape. The average particle diameter, as determined by TEM, was found to be 18.01 nm. The S-IONPs were efficiently inhibited the growth of Listeria monocytogenes, Escherichia coli and Candida species. Our favorable results suggest that S-IONPs could be a promising candidate for development of future antimicrobial therapies. The nature of biosynthesis and the therapeutic potential by S-IONPs could pave the way for further research on design of green synthesis therapeutic agents, particularly nanomedicine, to deal with treatment of infections. Further studies are needed to fully characterize the toxicity and the mechanisms involved with the antimicrobial activity of these particles. Antioxidant activity of S-IONPs synthesized by green method was measured by ABTS (2, 2'-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (IC50= 1000µg) radical scavenging activity. Also, with the increasing concentration of S-IONPs, catalase gene expression compared to control gene GAPDH increased. For anti-angiogenesis study the Ross fertilized eggs were divided into four groups; the control and three experimental groups. The gelatin sponges containing albumin were placed on the chorioalantoic membrane and soaked with different concentrations of S-IONPs. All the cases were photographed using a photo stereomicroscope. The number and the lengths of the vessels were measured using Image J software. The crown rump (CR) and weight of the embryo were also recorded. According to the data analysis, the number and length of the blood vessels, as well as the CR and weight of the embryos reduced significantly compared to the control (p < 0.05), dose dependently. The total hemoglobin was quantified as an indicator of the blood vessel formation, and in the treated samples decreased, which showed its inhibitory effect on angiogenesis.

Keywords: anti-angiogenesis, antimicrobial, antioxidant, biosynthesis, iron oxide (fe3o4) nanoparticles, sargassum muticum, seaweed

Procedia PDF Downloads 308

Authors: Ehsanolah Assareh, Mojtaba Biglari, Mojtaba Nedaei

Abstract:

Sanar village in north of Iran is a remote region with difficult access to electricity, grid and water supply. Thus the aim of this research is to evaluate the potential of wind as a power source either for electricity generation or for water pumping. In this study the statistical analysis has been performed by Weibull distribution function. The results show that the Weibull distribution has fitted the wind data very well. Also it has been demonstrated that wind speed at 40 m height is ranged from 1.75 m/s in Dec to 3.28 m/s in Aug with average value of 2.69 m/s. In this research, different wind speed characteristics such as turbulence intensity, wind direction, monthly air temperature, humidity wind power density and other related parameters have been investigated. Finally it was concluded that the wind energy in the Sanar village may be explored by employing modern wind turbines that require very lower start-up speeds.

Keywords: wind energy, wind turbine, weibull, Sanar village, Iran

Procedia PDF Downloads 516

Authors: Melissa Hachem, Maxime Loizeau, Nadine Saleh, Isabelle Momas, Lynda Bensefa-Colas

Abstract:

Professional drivers are exposed inside their vehicles to high levels of air pollutants due to the considerable time they spend close to motor vehicle emissions. Little is known about ultrafine particles (UFP) or black carbon (BC) adverse respiratory health effects compared to the regulated pollutants. We aimed to study the short-term associations between UFP and BC concentrations inside vehicles and (1) the onset of mucosal irritation and (2) the acute changes in lung function of Parisian taxi drivers during a working day. An epidemiological study was carried out on 50 taxi drivers in Paris. UFP and BC were measured inside their vehicles with DiSCmini® and microAeth®, respectively. On the same day, the frequency and the severity of nose, eye, and throat irritations were self-reported by each participant and a spirometry test was performed before and after the work shift. Multivariate analysis was used to evaluate the associations between in-taxis UFP and BC concentrations and mucosal irritation and lung function, after adjustment for potential confounders. In-taxis UFP concentrations ranged from 17.9 to 37.9 × 103 particles/cm³ and BC concentrations from 2.2 to 3.9 μg/m³, during a mean of 9 ± 2 working hours. Significant dose-response relationships were observed between in-taxis UFP concentrations and both nasal irritation and lung function. The increase of in-taxis UFP (for an interquartile range of 20 × 103 particles/cm3) was associated to an increase in nasal irritation (adjusted OR = 6.27 [95% CI: 1.02 to 38.62]) and to a reduction in forced expiratory flow at 25–75% by −7.44% [95% CI: −12.63 to −2.24], forced expiratory volume in one second by −4.46% [95% CI: −6.99 to −1.93] and forced vital capacity by −3.31% [95% CI: −5.82 to −0.80]. Such associations were not found with BC. Incident throat and eye irritations were not related to in-vehicle particles exposure; however, they were associated with outdoor air quality (estimated by the Atmo index) and in-vehicle humidity, respectively. This study is the first to show a significant association, within a short-period of time, between in-vehicle UFP exposure and acute respiratory effects in professional drivers.

Keywords: black carbon, lung function, mucosal irritation, taxi drivers, ultrafine particles

Procedia PDF Downloads 173

Authors: Nisha Budhwar, Sunita Daniel

Abstract:

In this paper, we analyse the stability of the SEIR model of malaria with infective immigrants which was recently formulated by the authors. The model consists of an SEIR model for the human population and SI Model for the mosquitoes. Susceptible humans become infected after they are bitten by infectious mosquitoes and move on to the Exposed, Infected and Recovered classes respectively. The susceptible mosquito becomes infected after biting an infected person and remains infected till death. We calculate the reproduction number R0 using the next generation method and then discuss about the stability of the equilibrium points. We use the Lyapunov function to show the global stability of the equilibrium points.

Keywords: equilibrium points, exposed, global stability, infective immigrants, Lyapunov function, recovered, reproduction number, susceptible

Procedia PDF Downloads 355

Authors: Hailang Yang

Abstract:

To ensure the confidentiality and integrity of speech signals in communication transmission, this paper proposes a voice signal encryption scheme based on chaotic theory. Firstly, the scheme utilizes chaotic mapping to generate a key stream and then employs the key stream to perform bitwise exclusive OR (XOR) operations for encrypting the speech signal. Additionally, the scheme utilizes a chaotic hash function to generate a Message Authentication Code (MAC), which is appended to the encrypted data to verify the integrity of the data. Subsequently, we analyze the security performance and encryption efficiency of the scheme, comparing and optimizing it against existing solutions. Finally, experimental results demonstrate that the proposed scheme can resist common attacks, achieving high-quality encryption and speed.

Keywords: chaotic theory, XOR encryption, chaotic hash function, Message Authentication Code (MAC)

Procedia PDF Downloads 45

Authors: Guillaume P. Fernandez

Abstract:

Individual language use is a matter of choice in particular interactions. The paper proposes a conceptual and theoretical framework with methodological consideration to develop how language produced in dyadic relations is to be considered and situated in the larger social configuration the interaction is embedded within. An integrated and comprehensive view is taken: social interactions are expected to be ruled by a normative context, defined by the chain of interdependences that structures the personal network. In this approach, the determinants of discursive practices are not only constrained by the moment of production and isolated from broader influences. Instead, the position the individual and the dyad have in the personal network influences the discursive practices in a twofold manner: on the one hand, the network limits the access to linguistic resources available within it, and, on the other hand, the structure of the network influences the agency of the individual, by the social control inherent to particular network characteristics. Concretely, we investigate how and to what extent consistent ego is from one interaction to another in his or her use of adverbs. To do so, social network analysis (SNA) methods are mobilized. Participants (N=130) are college students recruited in the french speaking part of Switzerland. The personal network of significant ones of each individual is created using name generators and edge interpreters, with a focus on social support and conflict. For the linguistic parts, respondents were asked to record themselves with five of their close relations. From the recordings, we computed an average similarity score based on the adverb used across interactions. In terms of analyses, two are envisaged: First, OLS regressions including network-level measures, such as density and reciprocity, and individual-level measures, such as centralities, are performed to understand the tenets of linguistic similarity from one interaction to another. The second analysis considers each social tie as nested within ego networks. Multilevel models are performed to investigate how the different types of ties may influence the likelihood to use adverbs, by controlling structural properties of the personal network. Primary results suggest that the more cohesive the network, the less likely is the individual to change his or her manner of speaking, and social support increases the use of adverbs in interactions. While promising results emerge, further research should consider a longitudinal approach to able the claim of causality.

Keywords: personal network, adverbs, interactions, social influence

Procedia PDF Downloads 58

Authors: Rani Danavath, V. B. Narsimha

Abstract:

Cloud computing is emerging as a new paradigm of large scale distributed computing. Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., three service models, and four deployment networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics models. Load balancing is one of the main challenges in cloud computing, which is required to distribute the dynamic workload across multiple nodes, to ensure that no single node is overloaded. It helps in optimal utilization of resources, enhancing the performance of the system. The goal of the load balancing is to minimize the resource consumption and carbon emission rate, that is the direct need of cloud computing. This determined the need of new metrics energy consumption and carbon emission for energy-efficiency load balancing techniques in cloud computing. Existing load balancing techniques mainly focuses on reducing overhead, services, response time and improving performance etc. In this paper we introduced a Technique for energy-efficiency, but none of the techniques have considered the energy consumption and carbon emission. Therefore, our proposed work will go towards energy – efficiency. So this energy-efficiency load balancing technique can be used to improve the performance of cloud computing by balancing the workload across all the nodes in the cloud with the minimum resource utilization, in turn, reducing energy consumption, and carbon emission to an extent, which will help to achieve green computing.

Keywords: cloud computing, distributed computing, energy efficiency, green computing, load balancing, energy consumption, carbon emission

Procedia PDF Downloads 443

Authors: Youssef R. Hassan, Mohamed S. Hasanin, Reda M. Abdelhameed

Abstract:

Recently, innovations in packaging security features become more important to see the originality of packaging in industrial application. Luminescent 3d printing materials have been a promising property which can provides a unique opportunity for the design and application of 3D printing. Lack emission of terbium ions, as a source of green emission, in salt form prevent its uses in industrial applications, so searching about stable and highly emitter material become essential. Nowadays, metal organic frameworks (MOFs) play an important role in designing light emitter material. In this work, fluorescent high density polyethylene (FHDPE) composite filament with Tb-benzene 1,3,5-tricarboxylate (Tb-BTC) MOFs for 3D printing have been successfully developed.HDPE pellets were mixed with Tb-BTC and melting extrustion with single screw extruders. It was found that Tb-BTCuniformly dispersed in the HDPE matrix and significantly increased the crystallinity of PE, which not only maintained the good thermal property but also improved the mechanical properties of Tb-BTC@HDPE composites. Notably, the composite filaments emitted ultra-bright green light under UV lamp, and the fluorescence intensity increased as the content of Tb-BTC increased. Finally, several brightly luminescent exquisite articles could be manufactured by fused deposition modeling (FDM) 3D printer with these new fluorescent filaments. In this context, the development of novel fluorescent Tb-BTC@HDPE composites was combined with 3D printing technology to amplified the packaging Security Features.

Keywords: 3D printing, fluorescent, packaging, security

Procedia PDF Downloads 92

Authors: Tatiana Stanchuliak

Abstract:

It is common knowledge that intonation is not laid over a ready text. On the contrary, intonation forms and accompanies the text on the level of its birth in the speaker’s mind. As a result, intonation plays one of the fundamental roles in the process of transferring a thought into external speech. Intonation structure can highlight the semantic significance of textual elements and become a ranging mark in understanding the information structure of the text. Intonation functions by means of prosodic characteristics, one of which is intonation salience, whose function in texts results in making some textual elements more prominent than others. This function of intonation, therefore, performs as organizing. It helps to form the frame of key elements of the text. The study under consideration made an attempt to look into the inner nature of salience and create a sort of a text intonation model. This general goal brought to some more specific intermediate results. First, there were established degrees of salience on the level of the smallest semantic element - intonation group, as well as prosodic means of creating salience, were examined. Second, the most frequent combinations of prosodic means made it possible to distinguish patterns of salience, which then became constituent elements of a text intonation model. Third, the analysis of the predicate structure allowed to divide the whole text into smaller parts, or units, which performed a specific function in the developing of the general communicative intention. It appeared that such units can be found in any text and they have common characteristics of their intonation arrangement. These findings are certainly very important both for the theory of intonation and their practical application.

Keywords: accentuation , inner speech, intention, intonation, intonation functions, models, patterns, predicate, salience, semantics, sentence stress, text

Procedia PDF Downloads 262

Authors: Amir Andria Gad Shehata

Abstract:

Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenanceneural network, LSTM, MLP, forecasting demand, inventory management

Procedia PDF Downloads 51

Authors: Muhammad Saeed, Sheeba Khalid

Abstract:

Aqueous pollution due to the textile industry is an important issue. Photocatalysis using metal oxides as catalysts is one of the methods used for eradication of dyes from textile industrial effluents. In this study, the synthesis, characterization, and evaluation of photocatalytic activity of Ag-TiO₂ are reported. TiO₂ catalysts with 2, 4, 6 and 8% loading of Ag were prepared by green methods using Azadrachea indica leaves' extract as reducing agent and titanium dioxide and silver nitrate as precursor materials. The 4% Ag-TiO₂ exhibited the best catalytic activity for degradation of dyes. Prepared catalyst was characterized by advanced techniques. Catalytic degradation of methylene blue and rhodamine B were carried out in Pyrex glass batch reactor. Deposition of Ag greatly enhanced the catalytic efficiency of TiO₂ towards degradation of dyes. Irradiation of catalyst excites electrons from conduction band of catalyst to valence band yielding an electron-hole pair. These photoexcited electrons and positive hole undergo secondary reaction and produce OH radicals. These active radicals take part in the degradation of dyes. More than 90% of dyes were degraded in 120 minutes. It was found that there was no loss catalytic efficiency of prepared Ag-TiO₂ after recycling it for two times. Photocatalytic degradation of methylene blue and rhodamine B followed Eley-Rideal mechanism which states that dye reacts in fluid phase with adsorbed oxygen. 27 kJ/mol and 20 kJ/mol were found as activation energy for photodegradation of methylene blue and rhodamine B dye respectively.

Keywords: TiO₂, Ag-TiO₂, methylene blue, Rhodamine B., photo degradation

Procedia PDF Downloads 159

Authors: Parisa Golbayani, Dan Wang, Ionut¸ Florescu

Abstract:

In this work we implement machine learning techniques to financial statement reports in order to asses company’s credit rating. Specifically, the work analyzes the performance of four neural network architectures (MLP, CNN, CNN2D, LSTM) in predicting corporate credit rating as issued by Standard and Poor’s. The paper focuses on companies from the energy, financial, and healthcare sectors in the US. The goal of this analysis is to improve application of machine learning algorithms to credit assessment. To accomplish this, the study investigates three questions. First, we investigate if the algorithms perform better when using a selected subset of important features or whether better performance is obtained by allowing the algorithms to select features themselves. Second, we address the temporal aspect inherent in financial data and study whether it is important for the results obtained by a machine learning algorithm. Third, we aim to answer if one of the four particular neural network architectures considered consistently outperforms the others, and if so under which conditions. This work frames the problem as several case studies to answer these questions and analyze the results using ANOVA and multiple comparison testing procedures.

Keywords: convolutional neural network, long short term memory, multilayer perceptron, credit rating

Procedia PDF Downloads 232

Authors: Ebenezer O. Olaniyi, Oyebade K. Oyedotun, Khashman Adnan

Abstract:

In the food industry high quality production is required within a limited time to meet up with the demand in the society. In this research work, we have developed a model which can be used to replace the human operator due to their low output in production and slow in making decisions as a result of an individual differences in deciding the defective and healthy banana. This model can perform the vision attributes of human operators in deciding if the banana is defective or healthy for food production based. This research work is divided into two phase, the first phase is the image processing where several image processing techniques such as colour conversion, edge detection, thresholding and morphological operation were employed to extract features for training and testing the network in the second phase. These features extracted in the first phase were used in the second phase; the classification system phase where the multilayer perceptron using backpropagation neural network was employed to train the network. After the network has learned and converges, the network was tested with feedforward neural network to determine the performance of the network. From this experiment, a recognition rate of 97% was obtained and the time taken for this experiment was limited which makes the system accurate for use in the food industry.

Keywords: banana, food processing, identification system, neural network

Procedia PDF Downloads 465

Authors: Yungtai Lo

Abstract:

Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

Procedia PDF Downloads 344

Authors: Evangelia-Chrysanthi Kouklari, Stella Tsermentseli, Claire P. Monks

Abstract:

Executive function (EF) refers to a set of future-oriented and goal-directed cognitive skills that are crucial for problem solving and social behaviour, as well as the ability to organise oneself. It has been suggested that EF could be conceptualised as two distinct but interrelated constructs, one emotional (hot) and one cognitive (cool), as it facilitates both affective and cognitive regulation. Cool EF has been found to be strongly related to Theory of Mind (ToM) that is the ability to infer mental states, but research has not taken into account the association between hot EF and ToM in Autism Spectrum Disorder (ASD) to date. The present study investigates the associations between both hot and cool EF and ToM in school-aged children with ASD. This cross-sectional study assesses 79 school-aged children with ASD (7-15 years) and 91 controls matched for age and IQ, on tasks tapping cool EF (working memory, inhibition, planning), hot EF (effective decision making, delay discounting), and ToM (emotional understanding and false/no false belief). Significant group differences in each EF measure support a global executive dysfunction in ASD. Strong associations between hot EF and ToM in ASD are reported for the first time (i.e. ToM emotional understanding and delay discounting). These findings highlight that hot EF also makes a unique contribution to the developmental profile of ASD. Considering the role of both hot and cool EF in association with ToM in individuals with ASD may aid in gaining a greater understanding not just of how these complex multifaceted cognitive abilities relate to one another, but their joint role in the distinct developmental pathway followed in ASD.

Keywords: ASD, executive function, school age, theory of mind

Procedia PDF Downloads 285

Authors: Kajingulu Malandala, Ranganai Edmore

Abstract:

The asymmetric Laplace distribution (ADL) is commonly used as the likelihood function of the Bayesian quantile regression, and it offers different families of likelihood method for quantile regression. Notwithstanding their popularity and practicality, ADL is not smooth and thus making it difficult to maximize its likelihood. Furthermore, Bayesian inference is time consuming and the selection of likelihood may mislead the inference, as the Bayes theorem does not automatically establish the posterior inference. Furthermore, ADL does not account for greater skewness and Kurtosis. This paper develops a new aspect of quantile regression approach for count data based on inverse of the cumulative density function of the Poisson, binomial and Delaporte distributions using the integrated nested Laplace Approximations. Our result validates the benefit of using the integrated nested Laplace Approximations and support the approach for count data.

Keywords: quantile regression, Delaporte distribution, count data, integrated nested Laplace approximation

Procedia PDF Downloads 156

Authors: Charline Monnier, Rudolf Andrys, Irene Castellino, Lucie Zemanova

Abstract:

Due to their inherent sustainability and compatibility with green chemistry principles, enzymes are attracting increasing attention for various applications like bioremediation or biocatalysis. These natural catalysts boast remarkable substrate specificity and operate under mild biological conditions. However, their intrinsic limitations, such as instability at high temperatures or in organic solvents, impede their wider applicability. Enzyme immobilization on supportive matrices emerges as a promising strategy to address these challenges. This approach not only facilitates enzyme reusability but also offers the potential to modulate their stability, activity, and selectivity. The present study investigates the immobilization and application of two distinct groups of hydrolases on supportive matrices: PETases, naturally capable of PolyEthylene Terephthalate (PET) degradation, and cholinesterases (ChEs), key enzymes in neurotransmitter regulation. All tested enzymes will be immobilized on porous and non-porous particles using both covalent and non-covalent methods. Additionally, the stability of PETases and cholinesterases will be explored, followed by exposure to denaturing conditions to assess their resilience under harsh conditions. Furthermore, due to the exceptional catalytic efficiency and selectivity, their biocatalytic efficiency will be tested using xenobiotic substrates, aiming to establish them as replacements for conventional chemical catalysts in environmentally friendly processes. By exploiting the power of enzyme immobilization, this research strives to unlock the full potential of these biocatalysts for sustainable and efficient technological advancements.

Keywords: biocatalysis, bioremediation, enzyme efficiency, enzyme immobilization, green chemistry

Procedia PDF Downloads 50

Authors: Ayman M. Othman, Hassan Y. Ahmed, Tallat A. Ali

Abstract:

Inadequate maintenance programs and funds allocated for highway networks in the developed countries have led to fast deterioration of road side elements. Therefore, this research focuses on developing a performance model for road side elements periodic maintenance activities. Road side elements that receive periodic maintenance include; earthen shoulder, road signs and traffic markings. Using the level of service concept, the developed model can determine the optimal periodic maintenance intervals for those elements based on a selected level of service suitable with the available periodic maintenance budget. Data related to time periods for progressive deterioration stages for the chosen elements were collected. Ten maintenance experts in Aswan, Sohag and Assiut cities were interviewed for that purpose. Time in months related to 10%, 25%, 40%, 50%, 75%, 90% and 100% deterioration of each road side element was estimated based on the experts opinion. Least square regression analysis has shown that a power function represents the best fit for earthen shoulders edge drop-off and damage of road signs with time. It was also evident that, the progressive dirtiness of road signs could be represented by a quadratic function an a linear function could represent the paint degradation nature of both traffic markings and road signs. Actual measurements of earthen shoulder edge drop-off agree considerably with the developed model.

Keywords: deterioration, level of service, periodic maintenance, performance model, road side element

Procedia PDF Downloads 565

Authors: Ramin Rostamkhani, Thurasamy Ramayah

Abstract:

One of the most important topics of today’s industrial organizations is the challenging issue of supply chain management. In this field, scientists and researchers have published numerous practical articles and models, especially in the last decade. In this research, to our best knowledge, the discussion of data modeling of supply chain management components using well-known statistical distribution functions has been considered. The world of science owns mathematics, and showing the behavior of supply chain data based on the characteristics of statistical distribution functions is innovative research that has not been published anywhere until the moment of doing this research. In an analytical process, describing different aspects of functions including probability density, cumulative distribution, reliability, and failure function can reach the suitable statistical distribution function for each of the components of the supply chain management. It can be applied to predict the behavior data of the relevant component in the future. Providing a model to adapt the best statistical distribution function in the supply chain management components will be a big revolution in the field of the behavior of the supply chain management elements in today's industrial organizations. Demonstrating the final results of the proposed model by introducing the process capability indices before and after implementing it alongside verifying the approach through the relevant assessment as an acceptable verification is a final step. The introduced approach can save the required time and cost to achieve the organizational goals. Moreover, it can increase added value in the organization.

Keywords: analyzing, process capability indices, statistical distribution functions, supply chain management components

Procedia PDF Downloads 83