Search results for: intelligent techniques

Authors: Eny Syatriana

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The purpose of this study is to find out the effective instruction for classroom management, with the main identification of organizing and managing effective learning environments, to identify characteristics of effective lesson planning, identify resources and materials dealing with positive and effective classroom management. Knowing the effective instruction management is one of the characteristics of well managed teacher. The study was carried out in three randomly selected classes of STKIP YPUP in South Sulawesi. The design adopted for the study was a descriptive survey approach. Simple descriptive analysis was used. The major instrument used in this study were student questionnaire, teacher questionnaire, data were gathered with the research instrument and were analyzed, the research question were investigated and two hypothesis were duly tested using t-test statistics. Based on the findings of this research, it was concluded that effective classroom management skills or techniques have strong and positive influence on student achievement.

Keywords: effective classroom management skills, students’ achievement, students academic, effective learning environments

Procedia PDF Downloads 333

Authors: Qasim Zafar, Matthew Anderson, Esteban Garcia, Steven Drager

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Software failures can present an enormous detriment to people's lives and cost millions of dollars to repair when they are unexpectedly encountered in the wild. Despite a significant portion of the software development lifecycle and resources are dedicated to testing, software failures are a relatively frequent occurrence. Nevertheless, the evaluation of testing effectiveness remains at the forefront of ensuring high-quality software and software metrics play a critical role in providing valuable insights into quantifiable objectives to assess the level of assurance and confidence in the system. As the selection of appropriate metrics can be an arduous process, the goal of this paper is to shed light on the significance of software metrics by examining a range of testing techniques and metrics as well as identifying key areas for improvement. Additionally, through this investigation, readers will gain a deeper understanding of how metrics can help to drive informed decision-making on delivering high-quality software and facilitate continuous improvement in testing practices.

Keywords: software testing, software metrics, testing effectiveness, black box testing, random testing, adaptive random testing, combinatorial testing, fuzz testing, equivalence partition, boundary value analysis, white box testing

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Authors: M. A. Medeiros, A. A. N. Dantas, F. A. N. França, R. F. Amaral

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There are several alternatives of coastal erosion control with geosynthetics. As an important stage of any Civil Engineering project, literature review is necessary in order to evaluate these alternatives and to guide the decisions. Ponta Negra beachfront has a very intensive urban pressure. In addition, a very short sand area induces high intensity erosion processes. Different attempts of solving the problem were already built. However, erosion issues are still an important concern since these structures collapsed. Geosynthetics present a great potential to be applied in this area. In order to study coastal erosion control alternatives with the use of geosynthetics, this paper presents a literature review about this subject. Several studies were collected in which beach conditions are similar to those found in Ponta Negra beach. It was possible to evaluate the alternatives that might be used in the area. Further studies include the application of such techniques in pilot areas and the evaluation of the erosion process. Finally, the best alternative for futures studies on Ponta Negra beach is geocontainers of geotextiles.

Keywords: geosynthetics, coastal erosion control, alternatives, Ponta Negra beach

Procedia PDF Downloads 152

Authors: Vitali Kremez

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The researcher monitored an organized ransomware campaign in order to gain significant visibility into the tactics, techniques, and procedures employed by a campaign boss operating a ransomware scheme out of Russia. As the Russian hacking community lowered the access requirements for unsophisticated Russian cybercriminals to engage in ransomware campaigns, corporations and individuals face a commensurately greater challenge of effectively protecting their data and operations from being held ransom. This report discusses two notorious ransomware campaigns. Though the loss of data can be devastating, the findings demonstrate that sending ransom payments does not always help obtain data. Key learnings: 1. From the ransomware affiliate perspective, such campaigns have significantly lowered the barriers for entry for low-tier cybercriminals. 2. Ransomware revenue amounts are not as glamorous and fruitful as they are often publicly reported. Average ransomware crime bosses make only $90K per year on average. 3. Data gathered indicates that sending ransom payments does not always help obtain data. 4. The talk provides the complete payout structure and Bitcoin laundering operation related to the ransomware-as-a-service campaign.

Keywords: bitcoin, cybercrime, ransomware, Russia

Procedia PDF Downloads 195

Authors: Priya Arora, Jaspreet K. Rajput

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Superparamagnetism has accelerated the research and use of more economical and ecological magnetically separable catalysts due to their more efficient isolation by response to an applied magnetic field. Magnetite nanomaterials coated by SiO2 shell have received a great deal of focus in the last decades as it provides high stability and also easy further surface functionalization depending upon the application. In this protocol, Fe3O4 magnetic nanoparticles have been synthesized by co-precipitation combined with sonication method. Further, Fe3O4 superparamagnetic nanoparticles have been functionalized by various moieties to serve as efficient catalysts for multicomponent reactions. The functionalized nanoparticles were characterized by techniques like Fourier transform infrared spectroscopy (FT-IR), transmission electron microscopy (TEM), scanning electron microscopy (SEM), vibrating sample magnetometer (VSM), thermogravimetric analysis (TGA), Brunauer-Emmett-Teller (BET) surface area analysis. The as prepared nanocatalysts can be reused for several times without any significant loss in its activity. The utilization of magnetic nanoparticles as catalysts for this reaction is one approach i.e. green, inexpensive, facile and widely applicable.

Keywords: functionalized, magnetite, multicomponent reactions, superparamagnetic

Procedia PDF Downloads 340

Authors: Irfan Nazir Wani, Pushpendra Kumar Shukla, Manoj Kumar

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Debris, also called waste or junk, present in orbit of Earth or orbital debris, offers a substantial challenge to space exploration. Satellite operations and other space-based activities. This research paper delves into the causes and effects of space debris accumulation, explores current mitigation techniques, and presents a hopeful outlook on the potential for future sustainable space activities. The paper emphasizes the necessity of addressing planetary fragments to ensure durable sustainability in universe exploration and utilization. It examines various strategies for mitigating space debris, including debris removal technologies, spacecraft design improvements, and international collaboration efforts. Additionally, the paper highlights the importance of space debris monitoring and tracking systems in preventing collisions and minimizing the growth of orbital debris. By comprehending the complexities of space debris and implementing effective mitigation measures, the space industry can work towards a future where sustainable space activities are achievable.

Keywords: space shuttle, debris, space junk, satellite, fragments, orbit

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Authors: M. Saadi, S. E. H. Abaidia, M. Y. Mokeddem.

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We present the results of a systematic and comparative study of the bulk, the structural properties, and phonon calculations of aluminum alloys using several exchange–correlations functional theory (DFT) with different plane-wave basis pseudo potential techniques. Density functional theory implemented by the Vienna Ab Initio Simulation Package (VASP) technique is applied to calculate the bulk and the structural properties of several structures. The calculations were performed for within several exchange–correlation functional and pseudo pententials available in this code (local density approximation (LDA), generalized gradient approximation (GGA), projector augmented wave (PAW)). The lattice dynamic code “PHON” developed by Dario Alfè was used to calculate some thermodynamics properties and phonon dispersion relation frequency distribution of Aluminium alloys using the VASP LDA PAW and GGA PAW results. The bulk and structural properties of the calculated structures were compared to different experimental and calculated works.

Keywords: DFT, exchange-correlation functional, LDA, GGA, pseudopotential, PAW, VASP, PHON, phonon dispersion

Procedia PDF Downloads 486

Authors: Dim En Nyaung, Thin Lai Lai Thein

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Due to the rapid increase of Internet, web opinion sources dynamically emerge which is useful for both potential customers and product manufacturers for prediction and decision purposes. These are the user generated contents written in natural languages and are unstructured-free-texts scheme. Therefore, opinion mining techniques become popular to automatically process customer reviews for extracting product features and user opinions expressed over them. Since customer reviews may contain both opinionated and factual sentences, a supervised machine learning technique applies for subjectivity classification to improve the mining performance. In this paper, we dedicate our work is the task of opinion summarization. Therefore, product feature and opinion extraction is critical to opinion summarization, because its effectiveness significantly affects the identification of semantic relationships. The polarity and numeric score of all the features are determined by Senti-WordNet Lexicon. The problem of opinion summarization refers how to relate the opinion words with respect to a certain feature. Probabilistic based model of supervised learning will improve the result that is more flexible and effective.

Keywords: opinion mining, opinion summarization, sentiment analysis, text mining

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Authors: Montserrrat Dopico Gonzalez, Ramon Lopez Facal

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The development of a critical, open and plural citizenship constitutes one of the main challenges of the school institution in the present multicultural societies. Didactics in Social Sciences has conducted important contributions to the development of active methodologies to promote the development of the intercultural competencies of the student body. Research in intercultural education has demonstrated the efficiency of the cooperative learning techniques to improve the intercultural relations in the classroom. Our study proposes to check the effect that, concerning the development of intercultural competencies of the student body, the emotional education can have in the context of the use of active methodologies such as the learning by projects and the cooperative learning. To that purpose, a programme of intervention based on activities focussed on controversial issues related to cultural diversity has been implemented in several secondary schools. Through a methodology which combines intercultural competence scales with interviews and also with the analysis of the school body’s productions, the persistence of stereotypes against immigration and the efficacy of the introduction of emotional education elements in the development of intercultural competencies have both been observed.

Keywords: active methodologies, didactics in social sciences, intercultural competences, intercultural education

Procedia PDF Downloads 154

Authors: Muhammad Ali Sarwar, Muhammad Farooq, Nayab Hassan, Hammad Hassan

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Pakistan is highly recognized for its agriculture and is well known for producing substantial amounts of wheat, cotton, and sugarcane. However, some factors contribute to a decline in crop quality and a reduction in overall output. One of the main factors contributing to this decline is the presence of weed and its late detection. This process of detection is manual and demands a detailed inspection to be done by the farmer itself. But by the time detection of weed, the farmer will be able to save its cost and can increase the overall production. The focus of this research is to identify and classify the four main types of weeds (Small-Flowered Cranesbill, Chick Weed, Prickly Acacia, and Black-Grass) that are prevalent in our region’s major crops. In this work, we implemented three different deep learning techniques: YOLO-v5, Inception-v3, and Deep CNN on the same Dataset, and have concluded that deep convolutions neural network performed better with an accuracy of 97.45% for such classification. In relative to the state of the art, our proposed approach yields 2% better results. We devised the architecture in an efficient way such that it can be used in real-time.

Keywords: deep convolution networks, Yolo, machine learning, agriculture

Procedia PDF Downloads 118

Authors: Franky Michael Hamonangan Siagian, Affan Maulana, Himawan Tri Bayu Murti Petrus, Widi Astuti

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In this study, the feasibility of the direct electrowinning method was used to produce zero-valent iron from red mud. The bauxite residue sample came from the Tayan mine, Indonesia, which contains high hematite (Fe₂O₃). Before electrolysis, the samples were characterized by various analytical techniques (ICP-AES, SEM, XRD) to determine their chemical composition and mineralogy. The direct electrowinning method of red mud suspended in NaOH was introduced at low temperatures ranging from 30 - 110 °C. Variations of current density, red mud: NaOH ratio and temperature were carried out to determine the optimum operation of the direct electrowinning process. Cathode deposits and residues in electrochemical cells were analyzed using XRD, XRF, and SEM to determine the chemical composition and current recovery. The low-temperature electrolysis current efficiency on Redmud can reach 20% recovery at a current density of 920,945 A/m². The moderate performance of the process was investigated with red mud, which was attributed to the troublesome adsorption of red mud particles on the cathode, making the reduction far less efficient than that with hematite.

Keywords: red mud, electrochemical reduction, Iron production, hematite

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Authors: Diego Roberto Goncalves De Pontes, Sergio Donizetti Zorzo

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Studies show that most users do not read privacy policies from the online services they use. Some authors claim that one of the main causes of this is that policies are long and usually hard to understand, which make users lose interest in reading them. In this scenario, users may agree with terms without knowing what kind of data is being collected and why. Given that, we aimed to develop a model that would present the privacy policies contents in an easy and graphical way for the user to understand. We call it the Privacy Label. Using information recovery techniques, we propose an architecture that is able to extract information about what kind of data is being collected and to what end in the policies and show it to the user in an automated way. To assess our model, we calculated the precision, recall and f-measure metrics on the information extracted by our technique. The results for each metric were 68.53%, 85.61% e 76,13%, respectively, making it possible for the final user to understand which data was being collected without reading the whole policy. Also, our proposal can facilitate the notice-and-choice by presenting privacy policy information in an alternative way for online users.

Keywords: privacy, policies, user behavior, computer human interaction

Procedia PDF Downloads 307

Authors: komal verma, V. S. Moholkar

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In this current study, the challenge of effectively treating and mineralizing industrial wastewater prior to its discharge into natural water bodies, such as rivers and lakes, is being addressed. Particularly, the focus is on the wastewater produced by chemical process industries, including refineries, petrochemicals, fertilizer, pharmaceuticals, pesticides, and dyestuff industries. These wastewaters often contain stubborn organic pollutants that conventional techniques, such as microbial processes cannot efficiently degrade. To tackle this issue, a ternary hybrid technique comprising of adsorption, heterogeneous Fenton process, and sonication has been employed. The study aims to evaluate the effectiveness of this approach for treating and mineralizing wastewater from a fertilizer industry located in Northeast India. The study comprises several key components, starting with the synthesis of the Fe3O4@AC nanocomposite using the co-precipitation method. The nanocomposite is then subjected to comprehensive characterization through various standard techniques, including FTIR, FE-SEM, EDX, TEM, BET surface area analysis, XRD, and magnetic property determination using VSM. Next, the process parameters of wastewater treatment are statistically optimized, focusing on achieving a high level of COD (Chemical Oxygen Demand) removal as the response variable. The Fe3O4@AC nanocomposite's adsorption characteristics and kinetics are also assessed in detail. The remarkable outcome of this study is the successful application of the ternary hybrid technique, combining adsorption, Fenton process, and sonication. This approach proves highly effective, leading to nearly complete mineralization (or TOC removal) of the fertilizer industry wastewater. The results highlight the potential of the Fe3O4@AC nanocomposite and the ternary hybrid technique as a promising solution for tackling challenging wastewater pollutants from various chemical process industries. This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result results from synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Micro-convection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe3O4@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater. The Fe3O4@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: chemical oxygen demand (cod), fe3o4@ac nanocomposite, kinetics, lc-ms, rsm, toxicity

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Authors: Mahdi Mottahedi, Peter Zahn, Armin Lechler, Alexander Verl

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Optimal topology of components leads to the maximum stiffness with the minimum material use. For the generation of these topologies, normally algorithms are employed, which tackle manufacturing limitations, at the cost of the optimal result. The global optimum result with penalty factor one, however, cannot be fabricated with conventional methods. In this article, an additive manufacturing method is introduced, in order to enable the production of global topology optimization results. For a benchmark, topology optimization with higher and lower penalty factors are performed. Different algorithms are employed in order to interpret the results of topology optimization with lower factors in many microstructure layers. These layers are then joined to form the final geometry. The algorithms’ benefits are then compared experimentally and numerically for the best interpretation. The findings demonstrate that by implementation of the selected algorithm, the stiffness of the components produced with this method is higher than what could have been produced by conventional techniques.

Keywords: topology optimization, additive manufacturing, 3D-printer, laminated object manufacturing

Procedia PDF Downloads 339

Authors: Saurabh Parkhedkar, Rajanikant Tenguria

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The paper proposes revamping the public transportation system in Mumbai with the use of Radio Frequency Identification (RFID) technology in order to provide better integration and compatibility across various modes of transport. In Mumbai, mass transport system suffers from poor inter-compatible ticketing system, subpar money collection techniques, and lack of planning for optimum utilization of resources. Development of suburbs and growth in population will result in growing demand for mass transportation networks. Hence, the growing demand for the already overburdened public transportation system is only going to worsen the scenario. Thus, a superior system is essential in order to regulate, manage and supervise future transportation needs. The proposed RFID based system integrates Mumbai Suburban Railway, BEST (Brihanmumbai Electric Supply and Transport Undertaking transport wing) Bus, Mumbai Monorail and Mumbai Metro systems into a Unified Public Transportation System (UPTS). The UTPS takes into account various drawbacks of the present day system and offers solution, suitable for the modern age Mumbai.

Keywords: urbanization, transportation, RFID, Mumbai, public transportation, smart city.

Procedia PDF Downloads 412

Authors: M. R. Abusrea, Shiyi Jiang, Dingding Chen, Kazuo Arakawa

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Novel wind-lens turbine designs can augment power output. Vacuum-Assisted Resin Transfer Molding (VARTM) is used to form large and complex structures from a Carbon Fiber Reinforced Polymer (CFRP) composite. Typically, wind-lens turbine structures are fabricated in segments, and then bonded to form the final structure. This paper introduces five new adhesive joints, divided into two groups: One is constructed between dry carbon and CFRP fabrics, and the other is constructed with two dry carbon fibers. All joints and CFRP fabrics were made in our laboratory using VARTM manufacturing techniques. Specimens were prepared for tensile testing to measure joint performance. The results showed that the second group of joints achieved a higher tensile strength than the first group. On the other hand, the tensile fracture behavior of the two groups showed the same pattern of crack originating near the joint ends followed by crack propagation until fracture.

Keywords: adhesive joints, CFRP, VARTM, resin transfer molding

Procedia PDF Downloads 436

Authors: Ebenezer Joseph

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Chess is a useful tool to enhance general and specific cognitive functioning in children. The present study aims to assess the impact of chess on cognitive in children and to measure the differential impact of socio-demographic factors like age and gender of the child on the effectiveness of the chess intervention.This research study used an experimental design to study the impact of the Training in Chess on the intelligence of children. The Pre-test Post-test Control Group Design was utilized. The research design involved two groups of children: an experimental group and a control group. The experimental group consisted of children who participated in the one-year Chess Training Intervention, while the control group participated in extra-curricular activities in school. The main independent variable was training in chess. Other independent variables were gender and age of the child. The dependent variable was the cognitive functioning of the child (as measured by IQ, working memory index, processing speed index, perceptual reasoning index, verbal comprehension index, numerical reasoning, verbal reasoning, non-verbal reasoning, social intelligence, language, conceptual thinking, memory, visual motor and creativity). The sample consisted of 200 children studying in Government and Private schools. Random sampling was utilized. The sample included both boys and girls falling in the age range 6 to 16 years. The experimental group consisted of 100 children (50 from Government schools and 50 from Private schools) with an equal representation of boys and girls. The control group similarly consisted of 100 children. The dependent variables were assessed using Binet-Kamat Test of Intelligence, Wechsler Intelligence Scale for Children - IV (India) and Wallach Kogan Creativity Test. The training methodology comprised Winning Moves Chess Learning Program - Episodes 1–22, lectures with the demonstration board, on-the-board playing and training, chess exercise through workbooks (Chess school 1A, Chess school 2, and tactics) and working with chess software. Further students games were mapped using chess software and the brain patterns of the child were understood. They were taught the ideas behind chess openings and exposure to classical games were also given. The children participated in mock as well as regular tournaments. Preliminary analysis carried out using independent t tests with 50 children indicates that chess training has led to significant increases in the intelligent quotient. Children in the experimental group have shown significant increases in composite scores like working memory and perceptual reasoning. Chess training has significantly enhanced the total creativity scores, line drawing and pattern meaning subscale scores. Systematically learning chess as part of school activities appears to have a broad spectrum of positive outcomes.

Keywords: chess, intelligence, creativity, children

Procedia PDF Downloads 257

Authors: Hanan Rizk

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A heat exchanger is a device used to mix liquids having different temperatures. In this case, the temperature control becomes a critical objective. This research work presents the temperature control of the double-pipe heat exchanger (multi-input multi-output (MIMO) system), which is modeled as first-order coupled hyperbolic partial differential equations (PDEs), using conventional and advanced control techniques and develops appropriate robust control strategy to meet stability requirements and performance objectives. We designed a PID controller and H-infinity controller for a heat exchanger (HE) system. Frequency characteristics of sensitivity functions and open-loop and closed-loop time responses are simulated using MATLAB software, and the stability of the system is analyzed using Kalman's test. The simulation results have demonstrated that the H-infinity controller is more efficient than PID in terms of robustness and performance.

Keywords: heat exchanger, multi-input multi-output system, MATLAB simulation, partial differential equations, PID controller, robust control

Procedia PDF Downloads 220

Authors: Samuel McLennan, Tane Moleta, Andre Brown, Marc Aurel Schnabel

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The development of Ecclesiastical buildings within New Zealand has produced some unique design characteristics that take influence from both international styles and local building methods. What this research looks at is how procedural modelling can be used to define such common characteristics and understand how they are shared and developed within different examples of a similar architectural style. This will be achieved through the creation of procedural digital reconstructions of the various timber Gothic Churches built during the 19th century in the city of Wellington, New Zealand. ‘Procedural modelling’ is a digital modelling technique that has been growing in popularity, particularly within the game and film industry, as well as other fields such as industrial design and architecture. Such a design method entails the creation of a parametric ‘ruleset’ that can be easily adjusted to produce many variations of geometry, rather than a single geometry as is typically found in traditional CAD software. Key precedents within this area of digital heritage includes work by Haegler, Müller, and Gool, Nicholas Webb and Andre Brown, and most notably Mark Burry. What these precedents all share is how the forms of the reconstructed architecture have been generated using computational rules and an understanding of the architects’ geometric reasoning. This is also true within this research as Gothic architecture makes use of only a select range of forms (such as the pointed arch) that can be accurately replicated using the same standard geometric techniques originally used by the architect. The methodology of this research involves firstly establishing a sample group of similar buildings, documenting the existing samples, researching any lost samples to find evidence such as architectural plans, photos, and written descriptions, and then culminating all the findings into a single 3D procedural asset within the software ‘Houdini’. The end result will be an adjustable digital model that contains all the architectural components of the sample group, such as the various naves, buttresses, and windows. These components can then be selected and arranged to create visualisations of the sample group. Because timber gothic churches in New Zealand share many details between designs, the created collection of architectural components can also be used to approximate similar designs not included in the sample group, such as designs found beyond the Wellington Region. This creates an initial library of architectural components that can be further expanded on to encapsulate as wide of a sample size as desired. Such a methodology greatly improves upon the efficiency and adjustability of digital modelling compared to current practices found in digital heritage reconstruction. It also gives greater accuracy to speculative design, as a lack of evidence for lost structures can be approximated using components from still existing or better-documented examples. This research will also bring attention to the cultural significance these types of buildings have within the local area, addressing the public’s general unawareness of architectural history that is identified in the Wellington based research ‘Moving Images in Digital Heritage’ by Serdar Aydin et al.

Keywords: digital forensics, digital heritage, gothic architecture, Houdini, procedural modelling

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Authors: Jalil Badamfirooz

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Soil wind erosion has a negative impact on the environment. Mulching is one of the most efficient soil protection techniques. Bitumen emulsion has recently been utilized as a soil cover that is sprayed directly over the soil and forms a thin film. The thin coating of bitumen emulsion prevents soil erosion and keeps moisture in the soil. Besides, some compounds release into the soil and cause environmental problems. In the present study, the effect of bitumen emulsion on the release of polycyclic aromatic hydrocarbons (PAHs) into the soil is studied in an arid land located in the central part of Iran. The soil was Loamy-Sand and saline with a pH of 8.03. Bitumen emulsion was used in this study as mulch at a rate of 4 L m2. The effect of this mulch on soil properties was investigated after 6 months of mulch application. Then PAHs concentrations were determined in samples collected from different depths in bitumen emulsion sprayed and control soils. In general, bitumen emulsion application on soil led to a significant increase in some PAHs, which was higher than soil pollution standards critical level of pollution for commerce, groundwater protection, pasture forest, and park and residence uses.

Keywords: mulch, bitumen emulsion, arid land, PAH

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Authors: Mehrji Khosravan, Mostafa Fathali-Sianib, Davood Soudbar, Sasan Talebnezhad, Mohammad-Reza Ebrahimi

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The late transition metal catalyst of the end group of transition metals in the periodic table as Ni, Fe, Co, and Pd was grown up rapidly in polyolefin industries recently. These metals with suitable ligands exhibited special characteristic properties and appropriate activities in the production of polyolefins. The ligand 1,4-bis (2,6-diisopropyl phenyl) acenaphthene was synthesized by reaction of 2,6-diisopropyl aniline and acenaphthenequinone. The ligand was added to nickel (II) dibromide salt for synthesis the 1,4-bis (2,6 diisopropylphenyl) acenaphthene nickel (II) dibromide catalyst. The structure of the ligand characterized by IR technique. The catalyst then deposited on graphene and graphene oxide by vander walss-attachment for use in Ethylene slurry polymerization process in the presence of catalyst activator such as methylaluminoxane (MAO) in hexane solvent. The structure of the catalyst characterized by IR and TEM techniques and some of the polymers were characterized by DSC. The highest activity was achieved at 600 C for catalyst.

Keywords: α-diimine nickel (II) complex, graphene as supported catalyst, late transition metal, ethylene polymerization

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Authors: Thiago E. Goto, Carla C. Lopes, Helena B. Nader, Anielle C. A. Silva, Noelio O. Dantas, José R. Siqueira Jr., Luciano Caseli

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Quantum dots (QD) are semiconductor nanocrystals that can be employed in biological research as a tool for fluorescence imagings, having the potential to expand in vivo and in vitro analysis as cancerous cell biomarkers. Particularly, cadmium selenide (CdSe) magic-sized quantum dots (MSQDs) exhibit stable luminescence that is feasible for biological applications, especially for imaging of tumor cells. For these facts, it is interesting to know the mechanisms of action of how such QDs mark biological cells. For that, simplified models are a suitable strategy. Among these models, Langmuir films of lipids formed at the air-water interface seem to be adequate since they can mimic half a membrane. They are monomolecular films formed at liquid-gas interfaces that can spontaneously form when organic solutions of amphiphilic compounds are spread on the liquid-gas interface. After solvent evaporation, the monomolecular film is formed, and a variety of techniques, including tensiometric, spectroscopic and optic can be applied. When the monolayer is formed by membrane lipids at the air-water interface, a model for half a membrane can be inferred where the aqueous subphase serve as a model for external or internal compartment of the cell. These films can be transferred to solid supports forming the so-called Langmuir-Blodgett (LB) films, and an ampler variety of techniques can be additionally used to characterize the film, allowing for the formation of devices and sensors. With these ideas in mind, the objective of this work was to investigate the specific interactions of CdSe MSQDs with tumorigenic and non-tumorigenic cells using Langmuir monolayers and LB films of lipids and specific cell extracts as membrane models for diagnosis of cancerous cells. Surface pressure-area isotherms and polarization modulation reflection-absorption spectroscopy (PM-IRRAS) showed an intrinsic interaction between the quantum dots, inserted in the aqueous subphase, and Langmuir monolayers, constructed either of selected lipids or of non-tumorigenic and tumorigenic cells extracts. The quantum dots expanded the monolayers and changed the PM-IRRAS spectra for the lipid monolayers. The mixed films were then compressed to high surface pressures and transferred from the floating monolayer to solid supports by using the LB technique. Images of the films were then obtained with atomic force microscopy (AFM) and confocal microscopy, which provided information about the morphology of the films. Similarities and differences between films with different composition representing cell membranes, with or without CdSe MSQDs, was analyzed. The results indicated that the interaction of quantum dots with the bioinspired films is modulated by the lipid composition. The properties of the normal cell monolayer were not significantly altered, whereas for the tumorigenic cell monolayer models, the films presented significant alteration. The images therefore exhibited a stronger effect of CdSe MSQDs on the models representing cancerous cells. As important implication of these findings, one may envisage for new bioinspired surfaces based on molecular recognition for biomedical applications.

Keywords: biomembrane, langmuir monolayers, quantum dots, surfaces

Procedia PDF Downloads 196

Authors: Sanat Ramesh, Tarun Dutt, Abhilasha Aswal, Anushka Chandrababu, G. N. Srinivasa Prasanna

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Optimal Schedule Generation for a large national railway network operating thousands of passenger trains with tens of thousands of kilometers of track is a grand computational challenge in itself. We present heuristics based on a Mixed Integer Program (MIP) formulation for local optimization. These methods provide flexibility in scheduling new trains with varying speed and delays and improve utilization of infrastructure. We propose methods that provide a robust solution with hundreds of trains being scheduled over a portion of the railway network without significant increases in delay. We also provide techniques to validate the nominal schedules thus generated over global correlated variations in travel times thereby enabling us to detect conflicts arising due to delays. Our validation results which assume only the support of the arrival and departure time distributions takes an order of few minutes for a portion of the network and is computationally efficient to handle the entire network.

Keywords: mixed integer programming, optimization, railway network, train scheduling

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Authors: Laredo Alcalá Elan Iñaky, Hernandez Castillo Daniel, Martinez Hernandez José Luis, Arredondo Valdes Roberto, Gonzalez Gallegos Esmeralda, Anguiano Cabello Julia Cecilia

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Plant hormones are a group of molecules that control different processes ranging from the growth and development of the plant until their response to biotic and abiotic stresses. In this study, the capacity of production of various phytohormones was evaluated from a strain of Botryodiplodia theobromae by liquid fermentation system using the modified Mierch medium added with a hydrolyzate compound of mead all in a reactor without agitation at 28 °C for 15 days. Quantification of the metabolites was performed using high performance liquid chromatography techniques. The results showed that a microbial broth with at least five different types of plant hormones was obtained: gibberellic acid, zeatin, kinetin, indoleacetic acid and jasmonic acid, the last one was higher than the others metabolites produced. The production of such hormones using a single type of microorganism could be in the future a great alternative to reduce production costs and similarly reduce the use of synthetic chemicals.

Keywords: biosystem, plant hormones, Botryodiplodia theobromae, fermentation

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Authors: Darwin Junnior Sabino Diego, Brando Burgos Guerrero, Diego Arroyo Villanueva

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Additive manufacturing, commonly known as 3D printing, has revolutionized modern manufacturing by enabling the agile creation of complex objects. However, challenges persist in the consistency and quality of printed parts, particularly in their mechanical properties. This study focuses on addressing these challenges through the optimization of printing parameters in FDM technology, using Machine Learning techniques. Our aim is to improve the mechanical properties of printed objects by optimizing parameters such as speed, temperature, and orientation. We implement a methodology that combines experimental data collection with Machine Learning algorithms to identify relationships between printing parameters and mechanical properties. The results demonstrate the potential of this methodology to enhance the quality and consistency of 3D printed products, with significant applications across various industrial fields. This research not only advances understanding of additive manufacturing but also opens new avenues for practical implementation in industrial settings.

Keywords: 3D printing, additive manufacturing, machine learning, mechanical properties

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Authors: E. A. Tkachenko, E. M. Rogova, A. S. Osipenko

Abstract:

The problems of technological development for the Russian Federation take on special significance in the context of modernization of the production base. The complexity of the position of the Russian economy is that it cannot be attributed fully to developing ones. Russia is a strong industrial power that has gone through the processes of destructive de-industrialization in the conditions of changing its economic and political structure. The need to find ways for re-industrialization is not a unique task for the economies of industrially developed countries. Under the influence of production outsourcing for 20 years, the industrial potential of leading economies of the world was regressed against the backdrop of the ascent of China, a new industrial giant. Therefore, methods, tools, and techniques utilized for industrial renaissance in EU may be used to achieve a technological leap in the Russian Federation, especially since the temporary gap of 5-7 years makes it possible to analyze best practices and use those technological transfer tools that have shown the greatest efficiency. In this article, methods of technological transfer are analyzed, the role of technological audit is justified, and factors are analyzed that influence the successful process of commercialization of technologies.

Keywords: technological transfer, productivity, technological audit, commercialization of technologies

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Authors: Chico Horacio Jose Sambo

Abstract:

Recently neural network has gained popularity when come to solve complex nonlinear problems. Permeability is one of fundamental reservoir characteristics system that are anisotropic distributed and non-linear manner. For this reason, permeability prediction from well log data is well suited by using neural networks and other computer-based techniques. The main goal of this paper is to predict reservoir permeability from well logs data by using neural network approach. A multi-layered perceptron trained by back propagation algorithm was used to build the predictive model. The performance of the model on net results was measured by correlation coefficient. The correlation coefficient from testing, training, validation and all data sets was evaluated. The results show that neural network was capable of reproducing permeability with accuracy in all cases, so that the calculated correlation coefficients for training, testing and validation permeability were 0.96273, 0.89991 and 0.87858, respectively. The generalization of the results to other field can be made after examining new data, and a regional study might be possible to study reservoir properties with cheap and very fast constructed models.

Keywords: neural network, permeability, multilayer perceptron, well log

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Authors: Somesh Misha, Smita Raghuvanshi, Suresh Gupta

Abstract:

Increasing concentration of green house gases (GHG's), such as CO2 is of major concern and start showing its impact nowadays. The recent studies are focused on developing the continuous system using photoautotrophs for CO2 mitigation and simultaneous production of primary and secondary metabolites as a value addition. The advent of carbon concentrating mechanism had blurred the distinction between autotrophs and heterotrophs and now the paradigm has shifted towards the carbon capture and utilization (CCU) rather than carbon capture and sequestration (CCS). In the present work, a bioreactor was developed utilizing the chemolithotrophic bacterial species using CO2 mitigation and simultaneous value addition. The kinetic modeling was done and the biokinetic parameters are obtained for developing the bioreactor. The bioreactor was developed and studied for its operation and performance in terms of volumetric loading rate, mass loading rate, elimination capacity and removal efficiency. The characterization of effluent from the bioreactor was carried out for the products obtained using the analyzing techniques such as FTIR, GC-MS, and NMR. The developed bioreactor promised an economic, efficient and effective solution for CO2 mitigation and simultaneous value addition.

Keywords: CO2 mitigation, bio-reactor, chemolithotrophic bacterial species, FTIR, GC-MS, NMR

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Authors: Iram Gul, Maria Manzoor, Muhammad Arshad

Abstract:

The enhanced phytoextraction techniques have been proposed for the remediation of heavy metals contaminated soil. Chelating agents enhance the availability of Cd, which is the main factor in the phytoremediation. This study was conducted to assessed the potential of two Pelargonium species (Pelargonium zonale, Pelargonium hortorum) in EDTA enhanced phytoextraction of Cd using pot experiment. Different doses of EDTA (0, 1, 2, 3, 4, 5 mmol kg-1) was used, and results showed that there was significant increase (approximately 2.1 folds) in the mobility of Cd at EDTA 5 mg kg-1 as compared to control. Both plants have TF and BCF more than 1 and have potential for the phytoextraction of Cd. However, the Pelargonium hortorum showed higher biomass and Cd uptake as compared to Pleragonium zonale. The maximum Cd accumulation in shoot and root of Pelargonium zonale was 484.4 and 264.41 mg kg-1 respectively at 2 mmol kg-1. However, the Pelargonium hortorum accumulate 996.9 and 350 mg kg-1 of Cd in shoot and root respectively at 4 mmol kg-1. Pelargonium hortorum uptake approximately 10.7 folds higher Cd concentration as compared to the Pelargonium zonale. Results revealed that P. hortorum performed better than P. zonal even at higher Cd and EDTA doses however toxicity and leaching potential of increased Cd and EDTA concentrations needs to be explored before field application.

Keywords: Cadmium, EDTA, Pelargonium, phytoextraction

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Authors: Sarra Hasni, Sami Faiz

Abstract:

In recent years, location prediction on social networks has gained significant attention, with short and unstructured texts like tweets posing additional challenges. Advanced geolocation models have been proposed, increasing the need to explain their predictions. In this paper, we provide explanations for a geolocation black-box model using LIME and SHAP, two state-of-the-art XAI (eXplainable Artificial Intelligence) methods. We extend our evaluations to Large Language Models (LLMs) as post hoc explainers for tweet geolocation. Our preliminary results show that LLMs outperform LIME and SHAP by generating more accurate explanations. Additionally, we demonstrate that prompts with examples and meta-prompts containing phonetic spelling rules improve the interpretability of these models, even with informal input data. This approach highlights the potential of advanced prompt engineering techniques to enhance the effectiveness of black-box models in geolocation tasks on social networks.

Keywords: large language model, post hoc explainer, prompt engineering, local explanation, tweet geolocation

Procedia PDF Downloads 26