Search results for: intuitionistic fuzzy cycle

Authors: Md. Abud Darda

Abstract:

Different options for natural gas production in wide geographic areas may be described through diffusion of innovation models. This type of modeling approach provides an indirect estimate of an ultimately recoverable resource, URR, capture the quantitative effects of observed strategic interventions, and allow ex-ante assessments of future scenarios over time. In order to ensure a sustainable energy policy, it is important to forecast the availability of this natural resource. Considering a finite life cycle, in this paper we try to investigate the natural gas production of Myanmar and Algeria, two important natural gas provider in the world energy market. A number of homogeneous and heterogeneous diffusion models, with convenient extensions, have been used. Models validation has also been performed in terms of prediction capability.

Keywords: diffusion models, energy forecast, natural gas, nonlinear production

Procedia PDF Downloads 227

Authors: Lin Po-Hsi, Sheu Ming-Thau

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Urea cycle disorders (UCD) are rare genetic metabolic disorders that compromise the body's urea cycle. Sodium phenylbutyrate (SPB) is a medication commonly administered in tablet or powder form to lower ammonia levels. Nonetheless, its high sodium content poses risks to sodium-sensitive UCD patients. This necessitates the creation of an alternative drug formulation to mitigate sodium load and optimize drug delivery for UCD patients. This study focused on crafting a novel oral drug formulation for UCD, leveraging choline bicarbonate and phenylbutyric acid. The active pharmaceutical ingredient-ionic liquids (API-ILs) and therapeutic deep eutectic systems (THEDES) were formed by combining these with choline chloride. These systems display characteristics like maintaining a liquid state at room temperature and exhibiting enhanced solubility. This in turn amplifies drug dissolution rate, permeability, and ultimately oral bioavailability. Incorporating choline-based phenylbutyric acid as a substitute for traditional SPB can effectively curtail the sodium load in UCD patients. Our in vitro dissolution experiments revealed that the ILs and DESs, synthesized using choline bicarbonate and choline chloride with phenylbutyric acid, surpassed commercial tablets in dissolution speed. Pharmacokinetic evaluations in SD rats indicated a notable uptick in the oral bioavailability of phenylbutyric acid, underscoring the efficacy of choline salt ILs in augmenting its bioavailability. Additional in vitro intestinal permeability tests on SD rats authenticated that the ILs, formulated with choline bicarbonate and phenylbutyric acid, demonstrate superior permeability compared to their sodium and acid counterparts. To conclude, choline salt ILs developed from choline bicarbonate and phenylbutyric acid present a promising avenue for UCD treatment, with the added benefit of reduced sodium load. They also hold merit in formulation engineering. The sustained-release capabilities of DESs position them favorably for drug delivery, while the low toxicity and cost-effectiveness of choline chloride signal potential in formulation engineering. Overall, this drug formulation heralds a prospective therapeutic avenue for UCD patients.

Keywords: phenylbutyric acid, sodium phenylbutyrate, choline salt, ionic liquids, deep eutectic systems, oral bioavailability

Procedia PDF Downloads 116

Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-Pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 470

Authors: Shiva Kumar, G. S. Vijay, Srinivas Pai P., Shrinivasa Rao B. R.

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In the present study RBF neural networks were used for predicting the performance and emission parameters of a biodiesel engine. Engine experiments were carried out in a 4 stroke diesel engine using blends of diesel and Honge methyl ester as the fuel. Performance parameters like BTE, BSEC, Tech and emissions from the engine were measured. These experimental results were used for ANN modeling. RBF center initialization was done by random selection and by using Clustered techniques. Network was trained by using fixed and varying widths for the RBF units. It was observed that RBF results were having a good agreement with the experimental results. Networks trained by using clustering technique gave better results than using random selection of centers in terms of reduced MRE and increased prediction accuracy. The average MRE for the performance parameters was 3.25% with the prediction accuracy of 98% and for emissions it was 10.4% with a prediction accuracy of 80%.

Keywords: radial basis function networks, emissions, performance parameters, fuzzy c means

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Authors: Li Ni, Pen ManMan, Li KenLi

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Clustering is an intensive research for some years because of its multifaceted applications, such as biology, information retrieval, medicine, business and so on. The expectation maximization (EM) is a kind of algorithm framework in clustering methods, one of the ten algorithms of machine learning. Traditionally, optimization of objective function has been the standard approach in EM. Hence, research has investigated the utility of evolutionary computing and related techniques in the regard. Chemical Reaction Optimization (CRO) is a recently established method. So the property embedded in CRO is used to solve optimization problems. This paper presents an algorithm framework (EM-CRO) with modified CRO operators based on EM cluster problems. The hybrid algorithm is mainly to solve the problem of initial value sensitivity of the objective function optimization clustering algorithm. Our experiments mainly take the EM classic algorithm:k-means and fuzzy k-means as an example, through the CRO algorithm to optimize its initial value, get K-means-CRO and FKM-CRO algorithm. The experimental results of them show that there is improved efficiency for solving objective function optimization clustering problems.

Keywords: chemical reaction optimization, expection maimization, initia, objective function clustering

Procedia PDF Downloads 715

Authors: Mujahid Sultan

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The IT industry has seen many transformations in the Software Development Life Cycle (SDLC) methodologies and development approaches. SDLCs range from waterfall to agile, and the development approaches from monolith to microservices. Management, orchestration, and monetization of microservices have created an API economy in the modern enterprise. There are two approaches to API design, code first and design first. Design first is gaining popularity in the industry as this allows capturing the API needs from the stakeholders rather than the development teams guesstimating the needs and associating a monetary value with the APIs and microservices. In this publication, we describe an approach to organizing and creating stakeholder needs and requirements for designing microservices and APIs.

Keywords: requirements engineering, enterprise architecture, APIs, microservices, DevOps, continuous delivery, continuous integration, stakeholder viewpoints

Procedia PDF Downloads 191

Authors: Pauline Nyssen, Ange Mouithys-Mickalad, Maryse Hoebeke

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Inflammation is a complex physiological phenomenon involving chemical and enzymatic mechanisms. Polymorphonuclear neutrophil leukocytes (PMNs) play an important role by producing reactive oxygen species (ROS) and releasing myeloperoxidase (MPO), a pro-oxidant enzyme. Released both in the phagolysosome and the extracellular medium, MPO produces during its peroxidase and halogenation cycles oxidant species, including hypochlorous acid, involved in the destruction of pathogen agents, like bacteria or viruses. Inflammatory pathologies, like rheumatoid arthritis, atherosclerosis induce an excessive stimulation of the PMNs and, therefore, an uncontrolled release of ROS and MPO in the extracellular medium, causing severe damages to the surrounding tissues and biomolecules such as proteins, lipids, and DNA. The treatment of chronic inflammatory pathologies remains a challenge. For many years, MPO has been used as a target for the development of effective treatments. Numerous studies have been focused on the design of new drugs presenting more efficient MPO inhibitory properties. However, some designed inhibitors can be toxic. An alternative consists of assessing the potential inhibitory action of clinically-known molecules, having antioxidant activity. Propofol, 2,6-diisopropyl phenol, which is used as an intravenous anesthetic agent, meets these requirements. Besides its anesthetic action employed to induce a sedative state during surgery or in intensive care units, propofol and its injectable form Diprivan indeed present antioxidant properties and act as ROS and free radical scavengers. A study has also evidenced the ability of propofol to inhibit the formation of the neutrophil extracellular traps fibers, which are important to trap pathogen microorganisms during the inflammation process. The aim of this study was to investigate the potential inhibitory action mechanism of propofol and Diprivan on MPO activity. To go into the anti-inflammatory action of propofol in-depth, two of its oxidative derivatives, 2,6-diisopropyl-1,4-p-benzoquinone (PPFQ) and 3,5,3’,5’-tetra isopropyl-(4,4’)-diphenoquinone (PPFDQ), were studied regarding their inhibitory action. Specific immunological extraction followed by enzyme detection (SIEFED) and molecular modeling have evidenced the low anti-catalytic action of propofol. Stopped-flow absorption spectroscopy and direct MPO activity analysis have proved that propofol acts as a reversible MPO inhibitor by interacting as a reductive substrate in the peroxidase cycle and promoting the accumulation of redox compound II. Overall, Diprivan exhibited a weaker inhibitory action than the active molecule propofol. In contrast, PPFQ seemed to bind and obstruct the enzyme active site, preventing the trigger of the MPO oxidant cycles. PPFQ induced a better chlorination cycle inhibition at basic and neutral pH in comparison to propofol. PPFDQ did not show any MPO inhibition activity. The three interest molecules have also demonstrated their inhibition ability on an important step of the inflammation pathway, the PMNs superoxide anions production, thanks to EPR spectroscopy and chemiluminescence. In conclusion, propofol presents an interesting immunomodulatory activity by acting as a reductive substrate in the peroxidase cycle of MPO, slowing down its activity, whereas PPFQ acts more as an anti-catalytic substrate. Although PPFDQ has no impact on MPO, it can act on the inflammation process by inhibiting the superoxide anions production by PMNs.

Keywords: Diprivan, inhibitor, myeloperoxidase, propofol, spectroscopy

Procedia PDF Downloads 148

Authors: Irum Matloob, Shoab Ahmad Khan, Fahim Arif

Abstract:

As Indo-pak has been the victim of heart diseases since many decades. Many surveys showed that percentage of cardiac patients is increasing in Pakistan day by day, and special attention is needed to pay on this issue. The framework is proposed for performing detailed analysis of ECG survey data which is conducted for measuring the prevalence of heart diseases statistics in Pakistan. The ECG survey data is evaluated or filtered by using automated Minnesota codes and only those ECGs are used for further analysis which is fulfilling the standardized conditions mentioned in the Minnesota codes. Then feature selection is performed by applying proposed algorithm based on discernibility matrix, for selecting relevant features from the database. Clustering is performed for exposing natural clusters from the ECG survey data by applying spectral clustering algorithm using fuzzy c means algorithm. The hidden patterns and interesting relationships which have been exposed after this analysis are useful for further detailed analysis and for many other multiple purposes.

Keywords: arrhythmias, centroids, ECG, clustering, discernibility matrix

Procedia PDF Downloads 351

Authors: Salima Smiti, Ines Gasmi, Makram Soui

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Credit risk is the most important issue for financial institutions. Its assessment becomes an important task used to predict defaulter customers and classify customers as good or bad payers. To this objective, numerous techniques have been applied for credit risk assessment. However, to our knowledge, several evaluation techniques are black-box models such as neural networks, SVM, etc. They generate applicants’ classes without any explanation. In this paper, we propose to assess credit risk using rules classification method. Our output is a set of rules which describe and explain the decision. To this end, we will compare seven classification algorithms (JRip, Decision Table, OneR, ZeroR, Fuzzy Rule, PART and Genetic programming (GP)) where the goal is to find the best rules satisfying many criteria: accuracy, sensitivity, and specificity. The obtained results confirm the efficiency of the GP algorithm for German and Australian datasets compared to other rule-based techniques to predict the credit risk.

Keywords: credit risk assessment, classification algorithms, data mining, rule extraction

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Authors: Moulay Youssef El Hafidi

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In this research, an enhanced room-temperature magnetic refrigerator based on nanofluid, consisting of permanent magnets as a magnetism source, gadolinium as magnetocaloric material, water as base liquid, and carbon nanotubes (CNT) as nanoparticles, has been designed. The magnetic field is supplied by NdFeB permanent magnets and is about 1.3 Tesla. Two similar heat exchangers are employed to absorb and expel heat. The cycle performance of this self-designed device is analyzed theoretically. The results provide useful data for future optimization of room-temperature magnetic refrigeration using nanofluids.

Keywords: magnetic cooling, nanofluid, gadolinium, permanent magnets, heat exchange

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Authors: Lukas Reznak, Maria Reznakova

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Recession of an economy has a profound negative effect on all involved stakeholders. It follows that timely prediction of recessions has been of utmost interest both in the theoretical research and in practical macroeconomic modelling. Current mainstream of recession prediction is based on standard OLS models of continuous GDP using macroeconomic data. This approach is not suitable for two reasons: the standard continuous models are proving to be obsolete and the macroeconomic data are unreliable, often revised many years retroactively. The aim of the paper is to explore a different branch of recession forecasting research theory and verify the findings on real data of the Czech Republic and Germany. In the paper, the authors present a family of discrete choice probit models with parameters estimated by the method of maximum likelihood. In the basic form, the probits model a univariate series of recessions and expansions in the economic cycle for a given country. The majority of the paper deals with more complex model structures, namely dynamic and bivariate extensions. The dynamic structure models the autoregressive nature of recessions, taking into consideration previous economic activity to predict the development in subsequent periods. Bivariate extensions utilize information from a foreign economy by incorporating correlation of error terms and thus modelling the dependencies of the two countries. Bivariate models predict a bivariate time series of economic states in both economies and thus enhance the predictive performance. A vital enabler of timely and successful recession forecasting are reliable and readily available data. Leading indicators, namely the yield curve and the stock market indices, represent an ideal data base, as the pieces of information is available in advance and do not undergo any retroactive revisions. As importantly, the combination of yield curve and stock market indices reflect a range of macroeconomic and financial market investors’ trends which influence the economic cycle. These theoretical approaches are applied on real data of Czech Republic and Germany. Two models for each country were identified – each for in-sample and out-of-sample predictive purposes. All four followed a bivariate structure, while three contained a dynamic component.

Keywords: bivariate probit, leading indicators, recession forecasting, Czech Republic, Germany

Procedia PDF Downloads 248

Authors: Garry Gorman, Nigel McKelvey, James Connolly

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This study will evaluate a growth mindset intervention with Junior Cycle Coding and Senior Cycle Computer Science students in Ireland, where gamification will be used to incentivise growth mindset behaviour. An artificial intelligence (AI) driven personalised learning system will be developed to present computer programming learning tasks in a manner that is best suited to the individuals’ own learning preferences while incentivising and rewarding growth mindset behaviour of persistence, mastery response to challenge, and challenge seeking. This research endeavours to measure mindset with before and after surveys (conducted nationally) and by recording growth mindset behaviour whilst playing a digital game. This study will harness the capabilities of AI and aims to determine how a personalised learning (PL) experience can impact the mindset of a broad range of students. The focus of this study will be to determine how personalising the learning experience influences female and disadvantaged students' sense of belonging in the computer science classroom when tasks are presented in a manner that is best suited to the individual. Whole Brain Learning will underpin this research and will be used as a framework to guide the research in identifying key areas such as thinking and learning styles, cognitive potential, motivators and fears, and emotional intelligence. This research will be conducted in multiple school types over one academic year. Digital games will be played multiple times over this period, and the data gathered will be used to inform the AI algorithm. The three data sets are described as follows: (i) Before and after survey data to determine the grit scores and mindsets of the participants, (ii) The Growth Mind-Set data from the game, which will measure multiple growth mindset behaviours, such as persistence, response to challenge and use of strategy, (iii) The AI data to guide PL. This study will highlight the effectiveness of an AI-driven personalised learning experience. The data will position AI within the Irish educational landscape, with a specific focus on the teaching of CS. These findings will benefit coding and computer science teachers by providing a clear pedagogy for the effective delivery of personalised learning strategies for computer science education. This pedagogy will help prevent students from developing a fixed mindset while helping pupils to exhibit persistence of effort, use of strategy, and a mastery response to challenges.

Keywords: computer science education, artificial intelligence, growth mindset, pedagogy

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Authors: Huiru Chen, Xuran Zhang

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At present, the residential architecture in China are still causing high energy consumption and high pollution during their whole life cycle, which can be backward compared with the developed countries. The aim of this paper is to discuss the application of green technology to residential architecture in Hangzhou. This article will start with the development of green buildings, then analyzes the use status of green technology in Hangzhou from several specific measures. Analysis of the typical existing green residential buildings in Hangzhou is an attempt to form a preliminary Hangzhou’s green technology application strategy system. Through research, it has been found that the application of green technology in Hangzhou has changed from putting green to the facade, to the combination of the preservation of the traditional green concept and the modern green technology.

Keywords: application, green technology, Hangzhou, residential architecture

Procedia PDF Downloads 207

Authors: Veena Chaudhary, Rakesh P. Gakkhar

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In this study, energy and exergy analysis are applied to the experimental data of an internal combustion engine operating on conventional diesel cycle. The experimental data are collected using an engine unit which enables accurate measurements of fuel flow rate, combustion air flow rate, engine load, engine speed and all relevant temperatures. First and second law efficiencies are calculated for different engine speed and compared. Results indicate that the first law (energy) efficiency is maximum at 1700 rpm whereas exergy efficiency is maximum and exergy destruction is minimum at 1900 rpm.

Keywords: diesel engine, exergy destruction, exergy efficiency, second law of thermodynamics

Procedia PDF Downloads 330

Authors: Abdulkadir Abu Lawal

Abstract:

For the dearth of reliable cardinal numerical data, the linked phenomena in productivity indices such as operational costs and company turnovers, etc. could not be investigated. This would not give us insight to the root of productivity problems at unique sites. So, ordinal ranking by professionals who were most directly involved with construction sites was applied for Kendall’s concordance. Responses gathered from independent architects, builders/engineers, and quantity surveyors were herein analyzed. They were responses based on factors that affect sites productivity, and these factors were categorized as head office factors, resource management effectiveness factors, motivational factors, and training/skill development factors. It was found that productivity is low and has to be improved in order to facilitate Nigerian efforts in bridging its infrastructure deficit. The significance of this work is underlined with the Kendall’s coefficient of concordance of 0.78, while remedial measures must be emphasized to stimulate better productivity. Further detailed study can be undertaken by using Fuzzy logic analysis on wider Delphi survey.

Keywords: factors, Kendall's coefficient of concordance, magnitude of agreement, percentage magnitude of dichotomy, ranking variables

Procedia PDF Downloads 627

Authors: Dongjae Kang, Sokho Son, Jinmee Kim

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Cloud service brokering is a new service paradigm that provides interoperability and portability of application across multiple Cloud providers. In this paper, we designed cloud service brokerage system, any broker, supporting integrated service provisioning and SLA based service life cycle management. For the system design, we introduce the system concept and whole architecture, details of main components and use cases of primary operations in the system. These features ease the Cloud service provider and customer’s concern and support new Cloud service open market to increase cloud service profit and prompt Cloud service echo system in cloud computing related area.

Keywords: cloud service brokerage, multiple Clouds, Integrated service provisioning, SLA, network service

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Authors: Zavkiddin Mirtoshev, Mirabbos Mirkamalov

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We have analyzed the time series of full disk integrated soft X-ray (SXR) and hard X-ray (HXR) emission from the solar corona during 2004 January 1 to 2009 December 31, covering the descending phase of solar cycle 23. We employed the daily X-ray index (DXI) derived from X-ray observations from the Solar X-ray Spectrometer (SOXS) mission in four different energy bands: 4-5.5; 5.5-7.5 keV (SXR) and 15-20; 20-25 keV (HXR). The application of Lomb-Scargle periodogram technique to the DXI time series observed by the Silicium detector in the energy bands reveals several short and intermediate periodicities of the X-ray corona. The DXI explicitly show the periods of 13.6 days, 26.7 days, 128.5 days, 151 days, 180 days, 220 days, 270 days, 1.24 year and 1.54 year periods in SXR as well as in HXR energy bands. Although all periods are above 70% confidence level in all energy bands, they show strong power in HXR emission in comparison to SXR emission. These periods are distinctly clear in three bands but somehow not unambiguously clear in 5.5-7.5 keV band. This might be due to the presence of Ferrum and Ferrum/Niccolum line features, which frequently vary with small scale flares like micro-flares. The regular 27-day rotation and 13.5 day period of sunspots from the invisible side of the Sun are found stronger in HXR band relative to SXR band. However, flare activity Rieger periods (150 and 180 days) and near Rieger period 220 days are very strong in HXR emission which is very much expected. On the other hand, our current study reveals strong 270 day periodicity in SXR emission which may be connected with tachocline, similar to a fundamental rotation period of the Sun. The 1.24 year and 1.54 year periodicities, represented from the present research work, are well observable in both SXR as well as in HXR channels. These long-term periodicities must also have connection with tachocline and should be regarded as a consequence of variation in rotational modulation over long time scales. The 1.24 year and 1.54 year periods are also found great importance and significance in the life formation and it evolution on the Earth, and therefore they also have great astro-biological importance. We gratefully acknowledge support by the Indian Centre for Space Science and Technology Education in Asia and the Pacific (CSSTEAP, the Centre is affiliated to the United Nations), Physical Research Laboratory (PRL) at Ahmedabad, India. This work has done under the supervision of Prof. Rajmal Jain and paper consist materials of pilot project and research part of the M. Tech program which was made during Space and Atmospheric Science Course.

Keywords: corona, flares, solar activity, X-ray emission

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Authors: Martin Alexander Eder, Sergei Semenov

Abstract:

Many glass-epoxy composite structures, such as large utility wind turbine rotor blades (WTBs), comprise of adhesive joints with typically thick bond lines used to connect the different components during assembly. Performance optimization of rotor blades to increase power output by simultaneously maintaining high stiffness-to-low-mass ratios entails intricate geometries in conjunction with complex anisotropic material behavior. Consequently, adhesive joints in WTBs are subject to multiaxial stress states with significant stress gradients depending on the local joint geometry. Moreover, the dynamic aero-elastic interaction of the WTB with the airflow generates non-proportional, variable amplitude stress histories in the material. Empiricism shows that a prominent failure type in WTBs is high cycle fatigue failure of adhesive bond line interfaces, which in fact over time developed into a design driver as WTB sizes increase rapidly. Structural optimization employed at an early design stage, therefore, sets high demands on computationally efficient interface fatigue models capable of predicting the critical locations prone for interface failure. The numerical stress-based interface fatigue model presented in this work uses the Drucker-Prager criterion to compute three different damage indices corresponding to the two interface shear tractions and the outward normal traction. The two-parameter Drucker-Prager model was chosen because of its ability to consider shear strength enhancement under compression and shear strength reduction under tension. The governing interface damage index is taken as the maximum of the triple. The damage indices are computed through the well-known linear Palmgren-Miner rule after separate rain flow-counting of the equivalent shear stress history and the equivalent pure normal stress history. The equivalent stress signals are obtained by self-similar scaling of the Drucker-Prager surface whose shape is defined by the uniaxial tensile strength and the shear strength such that it intersects with the stress point at every time step. This approach implicitly assumes that the damage caused by the prevailing multiaxial stress state is the same as the damage caused by an amplified equivalent uniaxial stress state in the three interface directions. The model was implemented as Python plug-in for the commercially available finite element code Abaqus for its use with solid elements. The model was used to predict the interface damage of an adhesively bonded, tapered glass-epoxy composite cantilever I-beam tested by LM Wind Power under constant amplitude compression-compression tip load in the high cycle fatigue regime. Results show that the model was able to predict the location of debonding in the adhesive interface between the webfoot and the cap. Moreover, with a set of two different constant life diagrams namely in shear and tension, it was possible to predict both the fatigue lifetime and the failure mode of the sub-component with reasonable accuracy. It can be concluded that the fidelity, robustness and computational efficiency of the proposed model make it especially suitable for rapid fatigue damage screening of large 3D finite element models subject to complex dynamic load histories.

Keywords: adhesive, fatigue, interface, multiaxial stress

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Authors: J. Otegui, M. Agirre, M. A. Cestau, H. Erauskin

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The increasing accessibility of mid-priced additive manufacturing (AM) systems offers a chance to incorporate this technology into engineering instruction. Furthermore, AM facilitates the creation of manufacturing designs, enhancing the efficiency of various machines. One example of these machines is the Stirling cycle engine. It encompasses complex thermodynamic machinery, revealing various aspects of mechanical engineering expertise upon closer inspection. In this publication, the application of Stirling Engines fabricated via additive manufacturing techniques will be showcased for the purpose of instructive design and product enhancement. The performance of a Stirling engine's conventional displacer and piston is contrasted. The outcomes of utilizing this instructional tool in teaching are demonstrated.

Keywords: 3D printing, additive manufacturing, mechanical design, stirling engine.

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Authors: Lars Laußat, Manfred Helmus, Kamil Szczesny, Markus König

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As one result of the project “Reactive Construction Project Scheduling using Real Time Construction Logistic Data and Simulation”, a procedure for using data about uncertain resource availability assumptions in reactive scheduling processes has been developed. Prediction data about resource availability is generated in a formalized way using real-time monitoring data e.g. from auto-ID systems on the construction site and in the supply chains. The paper focuses on the formalization of the procedure for monitoring construction logistic processes, for the detection of disturbance and for generating of new and uncertain scheduling assumptions for the reactive resource constrained simulation procedure that is and will be further described in other papers.

Keywords: auto-ID, construction logistic, fuzzy, monitoring, RFID, scheduling

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Authors: Liping Qiu, Xiaofeng Zhang

Abstract:

In its long history, precious tomb murals suffered from various diseases due to natural and man-made destruction. The key to how to protect tomb murals is how to strengthen and protect the tomb murals. In order to maximize the life of the tomb murals, the artistic, historic, and scientific values of the tomb murals can be continued. In this paper, four kinds of traditional reinforcement materials (silicone acrylic lotion, pure acrylic lotion, polyvinyl acetate lotion, and B72) are selected to reinforce the ground support layer of tomb murals, and the reinforcement effect of each reinforcement material on the ground support layer of murals is compared and analyzed, and the best protection material is obtained.

Keywords: mural, destruction cycle, reinforcement material, disease

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Authors: Nazanin Forouz

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The textile industry faces increasing criticism due to its resource-intensive nature and the negative environmental and societal impacts associated with the manufacturing, use, and disposal of clothes. To address these concerns, there is a growing desire to transition towards a circular economy for textiles, implementing recycling concepts and technologies to protect resources, the environment, and people. While existing recycling processes have focused on chemical and mechanical reuse of textile fibers, bio-based processes have received limited attention beyond end-of-life composting. However, bio-based technologies hold great promise for circularizing the textile life cycle and reducing environmental impacts.

Keywords: textile industry, circular economy, bio-based processes, recycling, environmental impacts

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Authors: Nigatu Tadesse, Li Juan, Liuhong Ming

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Gastric cancer (GC) is the fifth most common and fourth deadly cancer in the world with limited treatment options at late advanced stage in which surgical therapy is not recommended with chemotherapy remain as the mainstay of treatment. However, the occurrence of chemoresistance as well as intera-tumoral and inter-tumoral heterogeneity of response to targeted and immunotherapy underlined a clear unmet treatment need in gastroenterology. Several molecular and cellular alterations ascribed for chemo resistance in GC including cancer stem cells (CSC) and tumor microenvironment (TME) remodeling. Cancer cells including CSC bears higher metabolic demand and major changes in TME involves alterations of gut microbiota interacting with nutrients metabolism. Metabolic upregulation in lipids, carbohydrates, amino acids, fatty acids biosynthesis pathways identified as a common hall mark in GC. Metabolic addiction to methionine metabolism occurs in many cancer cells to promote the biosynthesis of S-Adenosylmethionine (SAM), a universal methyl donor molecule for high rate of transmethylation in GC and promote cell proliferation. Targeting methionine metabolism found to promotes chemo-sensitivity with treatment non-heterogeneity. Methionine restriction (MR) promoted the arrest of cell cycle at S/G2 phase and enhanced downregulation of GC cells resistance to apoptosis (including ferroptosis), which suggests the potential of synergy with chemotherapies acting at S-phase of the cell cycle as well as inducing cell apoptosis. Accumulated evidences showed both the biogenesis as well as intracellular metabolism of exogenous methionine could be safe and effective target for therapy either alone or in combination with chemotherapies. This review article provides an over view of the upregulation in methionine biosynthesis pathway and the molecular signaling through the PI3K/Akt/mTOR-c-MYC axis to promote metabolic reprograming through activating the expression of L-type aminoacid-1 (LAT1) transporter and overexpression of Methionine adenosyltransferase 2A(MAT2A) for intercellular metabolic conversion of exogenous methionine to SAM in GC, and the potential of targeting with novel therapeutic agents such as methioninase (METase), Methionine adenosyltransferase 2A (MAT2A), c-MYC, methyl like transferase 16 (METTL16) inhibitors that are currently under clinical trial development stages and future perspectives.

Keywords: gastric cancer, methionine metabolism, pi3k/akt/mtorc1-c-myc axis, gut microbiota, MAT2A, c-MYC, METTL16, methioninase

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Authors: Debbarma Asis, Guha Chandan

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Tumor Protein-53 (P53) is one of the tumor suppressor proteins. P53 regulates the cell cycle that conserves stability by preventing genome mutation. It is named so as it runs as 53-kilodalton (kDa) protein on Polyacrylamide gel electrophoresis although the actual mass is 43.7 kDa. Experimental evidence has indicated that P53 cancer mutants loses tumor suppression activity and subsequently gain oncogenic activities to promote tumourigenesis. Tumor-specific DNA has recently been detected in the plasma of breast cancer patients. Detection of tumor-specific genetic materials in cancer patients may provide a unique and valuable tumor marker for diagnosis and prognosis. Commercially available MDA-468 breast cancer cell line was used for the proposed study.

Keywords: tumor protein (P53), cancer mutants, MDA-468, tumor suppressor gene

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Authors: David Nantes, George Gilbert

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There are a lot of risks that might crop up as a tunneling project develops, and it's crucial to be aware of them. Due to the unexpected nature of tunneling projects and the interconnectedness of risk occurrences, the risk assessment approach presents a significant challenge. The purpose of this study is to provide a hybrid FDEMATEL-ANP model to help prioritize risks during tunnel construction projects. The ambiguity in expert judgments and the relative severity of interdependencies across risk occurrences are both taken into consideration by this model, thanks to the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). The Analytic Network Process (ANP) method is used to rank priorities and assess project risks. The authors provide a case study of a subway tunneling construction project to back up the validity of their methodology. The results showed that the proposed method successfully isolated key risk factors and elucidated their interplay in the case study. The proposed method has the potential to become a helpful resource for evaluating dangers associated with tunnel construction projects.

Keywords: risk, prioritization, FDEMATEL, ANP, tunneling construction projects

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Authors: Adriano Bessa Albuquerque, Francisco Jose Barreto Nunes

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Software vulnerabilities are increasing and not only impact services and processes availability as well as information confidentiality, integrity and privacy, but also cause changes that interfere in the development process. Security test could be a solution to reduce vulnerabilities. However, the variety of test techniques with the lack of real case studies of applying tests focusing on software development life cycle compromise its effective use. This paper offers an overview of how a Systematic Mapping Study (MS) about security verification, validation and test (VVT) was performed, besides presenting general results about this study.

Keywords: software test, software security verification validation and test, security test institutionalization, systematic mapping study

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Authors: U. Paniveni

Abstract:

A few parameters of supergranular cells are studied using intensity patterns from the Kodaikanal Solar Observatory and Dopplergrams from SOHO. The turbulent aspect of the solar supergranulation is established by examining the interrelationships amongst the parameters characterizing a supergranular cell, namely size, lifetime, area, perimeter, fractal dimension, and horizontal flow velocity. The complexity of supergranular cells depicted by their fractal dimension is indicative of their non-laminar characteristics. The findings corroborate Kolmogorov’s theory of turbulence. Some parameters of supergranular cells also show a latitudinal dependence. Supergranulation is a synonym of convective phenomenon and hence can shed light on the physical conditions in the convection zone of the Sun. It plays a major role in the transport and dispersal of magnetic fields that may have a relation to the phases of the solar cycle.

Keywords: sun, granulation, convection, turbulence

Procedia PDF Downloads 42

Authors: Najla Althuniyan

Abstract:

Online discussions take place across different platforms. These discussions have the potential to extract crowd wisdom and capture the collective intelligence from a different perspective. However, certain phenomena, such as controversy, often appear in online argumentation that makes the discussion between participants heated. Heated discussions can be used to extract new knowledge. Therefore, detecting the presence of controversy is an essential task to determine if collective intelligence can be extracted from online discussions. This paper uses existing measures for estimating controversy quantitatively in cyber-argumentation. First, it defines controversy in different fields, and then it identifies the attributes of controversy in online discussions. The distributions of user opinions and the distance between opinions are used to calculate the controversial degree of a discussion. Finally, the results from each controversy measure are discussed and analyzed using an empirical study generated by a cyber-argumentation tool. This is an improvement over the existing measurements because it does not require ground-truth data or specific settings and can be adapted to distribution-based or distance-based opinions.

Keywords: online argumentation, controversy, collective intelligence, agreement analysis, collaborative decision-making, fuzzy logic

Procedia PDF Downloads 116

Authors: Chanhyuck Jeon, Jongho Park, Jinwoong Choi, Sungnam Hong, Sun-Kyu Park

Abstract:

Many industries put emphasis on environmentally-friendliness as environmental problems are on the rise all over the world. Among themselves, the Modular Bridge research is going on. Also performing cross-section optimization and duration reducing, this research aims at developing the modular bridge with Environment-Friendliness and economic feasibility. However, the difficulty lies in verifying environmental effectiveness because there are no field applications of the modular bridge until now. Therefore, this thesis is categorized according to the form of the modular bridge superstructure and assessed CO₂ emission quantification per work types and materials according to each form to verify the environmental effectiveness of the modular bridge.

Keywords: modular bridge, CO2 emission, environmentally friendly, quantification, carbon emission factor, LCA (Life Cycle Assessment)

Procedia PDF Downloads 555

Authors: Behnaz Pahlousay, Farshad Kazemnejad, Elisa Palezzato, Michele Torielli

Abstract:

In this paper, we study the notions of connected domination number and of outer-connected domination number for middle graphs. Indeed, we obtain tight bounds for these numbers in terms of the order of the middle graph M(G). We also compute the outer-connected domination number of some families of graphs such as star graphs, cycle graphs, wheel graphs, complete graphs, complete bipartite graphs and some operation on graphs, explicitly. Moreover, some Nordhaus-Gaddum-like relations are presented for the outer-connected domination number of middle graphs.

Keywords: connected domination number, outer-connected dom- ination number, domination number, middle graph, nordhaus- gaddum-like relation.

Procedia PDF Downloads 39