Search results for: tool tuning

Authors: Oxana Lukoshus

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The methods of corpus linguistics, a well-established field of research, are being increasingly applied in cognitive linguistics. Corpora data are especially useful for different quantitative studies of grammatical and other aspects of language. The main objective of this paper is to demonstrate how present-day corpora can be applied in semantic studies in general and in semantic studies of adjectives in particular. Polysemantic adjectives have been the subject of numerous studies. But most of them have been carried out on dictionaries. Undoubtedly, dictionaries are viewed as one of the basic data sources, but only at the initial steps of a research. The author usually starts with the analysis of the lexicographic data after which s/he comes up with a hypothesis. In the research conducted three polysemantic synonyms true, loyal, faithful have been analyzed in terms of differences and similarities in their semantic structure. A corpus-based approach in the study of the above-mentioned adjectives involves the following. After the analysis of the dictionary data there was the reference to the following corpora to study the distributional patterns of the words under study – the British National Corpus (BNC) and the Corpus of Contemporary American English (COCA). These corpora are continually updated and contain thousands of examples of the words under research which make them a useful and convenient data source. For the purpose of this study there were no special needs regarding genre, mode or time of the texts included in the corpora. Out of the range of possibilities offered by corpus-analysis software (e.g. word lists, statistics of word frequencies, etc.), the most useful tool for the semantic analysis was the extracting a list of co-occurrence for the given search words. Searching by lemmas, e.g. true, true to, and grouping the results by lemmas have proved to be the most efficient corpora feature for the adjectives under the study. Following the search process, the corpora provided a list of co-occurrences, which were then to be analyzed and classified. Not every co-occurrence was relevant for the analysis. For example, the phrases like An enormous sense of responsibility to protect the minds and hearts of the faithful from incursions by the state was perceived to be the basic duty of the church leaders or ‘True,’ said Phoebe, ‘but I'd probably get to be a Union Official immediately were left out as in the first example the faithful is a substantivized adjective and in the second example true is used alone with no other parts of speech. The subsequent analysis of the corpora data gave the grounds for the distribution groups of the adjectives under the study which were then investigated with the help of a semantic experiment. To sum it up, the corpora-based approach has proved to be a powerful, reliable and convenient tool to get the data for the further semantic study.

Keywords: corpora, corpus-based approach, polysemantic adjectives, semantic studies

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Authors: Nadia Bachir (Dahmani), Fatima Zohra Otmani

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Due to its interesting optoelectronic properties, methylammonium perovskite CH3NH3PbI3 is used as the active layer in the development of several solar cells. In this work, the hybrid (organic-inorganic) cell with the architecture FTO/pedotpss/CH3NH3PbI3/pcdtbt/Al is simulated using the Organic and Hybrid Material Nano Simulation Tool (OghmaNano). We studied the influence of certain parameters, such as thickness, on the characteristics of the solar cell. The effect of the device temperature was also investigated. The photovoltaic characteristic curves, such as current-voltage (j-V), are presented in this work. The optimized final parameters are Voc = 0.947 V, FF = 0.8034%, and PCE = 23.16%.

Keywords: OghmaNano software, hybrid perovskite cell, CH3NH3PbI3, conversion efficiency

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Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

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The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

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Authors: Ahmed Amin Mousa, Tamer M. Ismail, M. Abd El Salam

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This work presents a robot called Conceptual Robotic Cube, CR-Cube. The robot can be used as an educational tool for children from the age of three. It has a cube shape attached with a camera colours sensor. In addition, it contains four wheels to move smoothly. The researchers prepared a questionnaire to measure the efficiency of the robot. The design and the questionnaire was presented to 11 experts who agreed that the robot is appropriate for learning numbering and colours for preschool children.

Keywords: CR-Cube, robotic cube, conceptual robot, conceptual cube, colour concept, early childhood education

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Authors: Chandra Shekhar Prasad, Ludek Pesek Prasad

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In the present day fan blade of aero engine, turboprop propellers, gas turbine or steam turbine low-pressure blades are getting bigger, lighter and thus, become more flexible. Therefore, flutter, forced blade response and vibration related failure of the high aspect ratio blade are of main concern for the designers, thus need to be address properly in order to achieve successful component design. At the preliminary design stage large number of design iteration is need to achieve the utter free safe design. Most of the numerical method used for aeroelastic analysis is based on field-based methods such as finite difference method, finite element method, finite volume method or coupled. These numerical schemes are used to solve the coupled fluid Flow-Structural equation based on full Naiver-Stokes (NS) along with structural mechanics’ equations. These type of schemes provides very accurate results if modeled properly, however, they are computationally very expensive and need large computing recourse along with good personal expertise. Therefore, it is not the first choice for aeroelastic analysis during preliminary design phase. A reduced order aeroelastic model (ROAM) with acceptable accuracy and fast execution is more demanded at this stage. Similar ROAM are being used by other researchers for aeroelastic and force response analysis of turbomachinery. In the present paper new medium fidelity ROAM is successfully developed and implemented in numerical tool to simulated the aeroelastic stability phenomena in turbomachinery and well as flexible wings. In the present, a hybrid flow solver based on 3D viscous-inviscid coupled 3D panel method (PM) and 3d discrete vortex particle method (DVM) is developed, viscous parameters are estimated using boundary layer(BL) approach. This method can simulate flow separation and is a good compromise between accuracy and speed compared to CFD. In the second phase of the research work, the flow solver (PM) will be coupled with ROM non-linear beam element method (BEM) based FEM structural solver (with multibody capabilities) to perform the complete aeroelastic simulation of a steam turbine bladed disk, propellers, fan blades, aircraft wing etc. The partitioned based coupling approach is used for fluid-structure interaction (FSI). The numerical results are compared with experimental data for different test cases and for the blade cascade test case, experimental data is obtained from in-house lab experiments at IT CAS. Furthermore, the results from the new aeroelastic model will be compared with classical CFD-CSD based aeroelastic models. The proposed methodology for the aeroelastic stability analysis of gas turbine or steam turbine blades, or propellers or fan blades will provide researchers and engineers a fast, cost-effective and efficient tool for aeroelastic (classical flutter) analysis for different design at preliminary design stage where large numbers of design iteration are required in short time frame.

Keywords: aeroelasticity, beam element method (BEM), discrete vortex particle method (DVM), classical flutter, fluid-structure interaction (FSI), panel method, reduce order aeroelastic model (ROAM), turbomachinery, viscous-inviscid coupling

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Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Lamar Alhindi, Madhawi Alsharif

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This report explores Canva, a user-friendly graphic design platform designed to empower individuals of all skill levels in creating diverse visual content. The study provides a comprehensive overview of Canva’s features, such as its drag-and-drop interface, AI tools, and extensive asset library. A survey was conducted to assess users’ perceptions of Canva’s AI-driven features, highlighting their utility in saving time and improving efficiency. Key insights include the popularity of design suggestions and accessibility for beginners. The report underscores Canva’s versatility for personal and professional applications, emphasizing its role as a go-to design tool for individuals and businesses alike.

Keywords: Canva, Ai, Ai driven tools, beginner, editing

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Authors: Vinda B. Manurung, Laila Warkhaida, David Hutabarat, Sentanu Wisnuwardhana, Christovik Simatupang, Dhani Sanjaya, Ashadi, Redha B. Putra, Kiki Yustendi

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The geothermal drilling environment presents many obstacles that have limited the use of directional drilling and logging-while-drilling (LWD) technologies, such as borehole washout, mud losses, severe vibration, and high temperature. The case study presented in this paper demonstrates a practice to enhance data logging in geothermal drilling by deploying advanced telemetry and LWD technologies. This operation is aiming continuous improvement in geothermal drilling operations. The case study covers a 12.25-in. hole section of well XX-05 in Pad XX of the Sorik Marapi Geothermal Field. LWD string consists of electromagnetic (EM) telemetry, pressure while drilling (PWD), vibration (DDSr), and acoustic calliper (ACAL). Through this tool configuration, the operator acquired drilling mechanics and caliper logs in real-time and recorded mode, enabling effective monitoring of wellbore stability. Throughout the real-time acquisition, EM-PPM telemetry had provided a three times faster data rate to the surface unit. With the integration of Caliper data and Drilling mechanics data (vibration and ECD -equivalent circulating density), the borehole conditions were more visible to the directional driller, allowing for better control of drilling parameters to minimize vibration and achieve optimum hole cleaning in washed-out or tight formation sequences. After reaching well TD, the recorded data from the caliper sensor indicated an average of 8.6% washout for the entire 12.25-in. interval. Washout intervals were compared with loss occurrence, showing potential for the caliper to be used as an indirect indicator of fractured intervals and validating fault trend prognosis. This LWD case study has given added value in geothermal borehole characterization for both drilling operation and subsurface. Identified challenges while running LWD in this geothermal environment need to be addressed for future improvements, such as the effect of tool eccentricity and the impact of vibration. A perusal of both real-time and recorded drilling mechanics and caliper data has opened various possibilities for maximizing sensor usage in future wells.

Keywords: geothermal drilling, geothermal formation, geothermal technologies, logging-while-drilling, vibration, caliper, case study

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Authors: Pernille K. Christiansen, Mette Maria Skjøth, Line Lorenzen, Eva Draborg, Christina Anne Vinter, Trine Kjær, Mette Juel Rothmann

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Background and aims: Overweight and obesity are an increasing challenge on a global level. In Denmark, more than one-third of all pregnant women are overweight or obese, and many women exceed the gestational weight gain recommendations from the Institute of Medicine. Being overweight or obese, is associated with a higher risk of adverse maternal and fetal outcomes, including gestational diabetes and childhood obesity. Thus, it is important to focus on the women’s lifestyles between their pregnancies to lower the risk of gestational weight retention in the long run. The objective of this study was to explorer what barriers and challenges postpartum women experience with respect to healthy lifestyles during the postpartum period and to access whether an Information Technology based intervention might be a supportive tool to assist and motivate postpartum women to a healthy lifestyle. Materials and methods: The method is inspired by participatory design. A systematic text condensation was applied to semi-structured focus groups. Five focus group interviews were carried out with a total of 17 postpartum women and two interviews with a total of six health professionals. Participants were recruited through the municipality in Svendborg, Denmark, and at Odense University Hospital in Odense, Denmark, during a four-month period in early 2018. Results: From the women’s perspective, better assistance is needed from the health professionals to obtain or maintain a healthy lifestyle. The women need tools that inform and help them understand and prioritise their own health-related risks, and to motivate them to plan and take care of their own health. As the women use Information Technology on a daily basis, the solution could be delivered through Information Technology. Finally, there is room for engaging the partner more in the communication related to the baby and family’s lifestyle. Conclusion: Postpartum women need tools that inform and motivate a healthy lifestyle postpartum. The tools should allow access to high-quality information from health care professionals, when the information is needed, and also allow engagement from the partner. Finally, Information Technology is a potential tool for delivering tools.

Keywords: information technology, lifestyle, overweight, postpartum

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Authors: Ali Yaro Kankia

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Millennium Development Goals are eight goals set by the 189 United Nations member States with 2015 as its target year of achievement. Since its signing in September 2000, individual nations have been finding ways and means of actualizing them. This paper consider how a refocused basic Mathematics curriculum could serve as an appropriate tool in achieving these goals. This was done by considering the theme in the following sub-headings. Basic Mathematics curriculum before now, basic Mathematics curriculum and the millennium development Goals and challenges of a refocused basic Mathematics curriculum for the MDGs. The appropriate conclusion was reached.

Keywords: actualizing, curriculum, MDGs, refocused

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Authors: Prapoj Na Bangchang

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This research aimed to study the satisfaction of university students on the Suan Sunandha Rajabhat University television station. The sample were 250 undergraduate students from Year 1 to Year 4. The tool used to collect data was a questionnaire. Statistics used in data analysis were percentage, mean and standard deviation. The results showed that student satisfaction on the University's television station location received high score, followed by the number of devices, and the content presented received the lowest score. Most students want the content of the programs to be improved especially entertainment content, followed by sports content.

Keywords: student satisfaction, university TV channel, media, broadcasting

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Authors: Faizul Azly Abd Dzubir, Muhammad F. Othman

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Conventional structural health monitoring approach for mechanical equipment uses inspection data from Non-Destructive Testing (NDT) during plant shut down window and fitness for service evaluation to estimate the integrity of the equipment that is prone to crack damage. Yet, this forecast is fraught with uncertainty because it is often based on assumptions of future operational parameters, and the prediction is not continuous or online. Advanced Diagnostic and Prognostic Technology (ADaPT) uses Acoustic Emission (AE) technology and a stochastic prognostic model to provide real-time monitoring and prediction of mechanical defects or cracks. The forecast can help the plant authority handle their cracked equipment before it ruptures, causing an unscheduled shutdown of the facility. The ADaPT employs process historical data trending, finite element analysis, fitness for service, and probabilistic statistical analysis to develop a prediction model for crack initiation and growth due to mechanical damage. The prediction model is combined with live equipment operating data for real-time prediction of the remaining life span owing to fracture. ADaPT was devised at a hot combined feed exchanger (HCFE) that had suffered creep crack damage. The ADaPT tool predicts the initiation of a crack at the top weldment area by April 2019. During the shutdown window in April 2019, a crack was discovered and repaired. Furthermore, ADaPT successfully advised the plant owner to run at full capacity and improve output by up to 7% by April 2019. ADaPT was also used on a coke drum that had extensive fatigue cracking. The initial cracks are declared safe with ADaPT, with remaining crack lifetimes extended another five (5) months, just in time for another planned facility downtime to execute repair. The prediction model, when combined with plant information data, allows plant operators to continuously monitor crack propagation caused by mechanical damage for improved maintenance planning and to avoid costly shutdowns to repair immediately.

Keywords: mechanical damage, cracks, continuous monitoring tool, remaining life, acoustic emission, prognostic model

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: P. Pérez-Martín, G. Pedrós, P. Martínez-Jiménez, M. Varo-Martínez

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In recent decades, family habits related to children’s displacements to school have changed, increasing motorized travels against active modes. This entails a major negative impact on the urban environment, road safety in cities and the physical and psychological development of children. One of the more common actions used to reverse this trend is Walking School Bus (WSB), which consists of a predefined adult-scorted pedestrian route to school with several stops along the path where schoolchildren are collected. At Tirso de Molina School in Cordoba (Spain), a new ICT-based methodology to deploy WSB has been tested. A mobile app that allows the geoposition of the group, the notification of the arrival and real-time communication between the WSB participants have been presented to the families in order to organize and register the daily participation. After an initial survey to know the travel mode and the spatial distribution of the interested families, three WSB routes have been established and the families have been trained in the app usage. During nine weeks, 33 children have joined the WSB and their parents have accompanied the groups in turns. A high recurrence in the attendance has been registered. Through a final survey, participants have valued highly the tool and the methodology designed, emphasizing as most useful features of the mobile app: notifications system, chat and real-time monitoring. It has also been found that the tool has had a major impact on the degree of confidence of parents regarding the autonomous on foot displacement of their children to school. Moreover, 37,9% of the participant families have reported a total or partial modal shift from car to walking, and the benefits more reported are an increment of the parents available time and less problems in the travel to school daily organization. As a consequence, It has been proved the effectiveness of this user-centric innovative ICT-based methodology to reduce the levels of private car drop offs, minimize barriers of time constraints, volunteer recruitment, and parents’ safety concerns, while, at the same time, increase convenience and time savings for families. This pilot study can offer guidance for community coordinated actions and local authority interventions to support sustainable school travel outcomes.

Keywords: active travel, mobile app, sustainable mobility, urban transportation planning, walking school bus

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Authors: Wael M. Rabeh, Cesar Carrasco-Lopez, Juliana C. Ferreira, Pance Naumov

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Bioluminescence, the emission of light from a biological process, is found in various living organisms including bacteria, fireflies, beetles, fungus and different marine organisms. Luciferase is an enzyme that catalyzes a two steps oxidation of luciferin in the presence of Mg2+ and ATP to produce oxyluciferin and releases energy in the form of light. The luciferase assay is used in biological research and clinical applications for in vivo imaging, cell proliferation, and protein folding and secretion analysis. The luciferase enzyme consists of two domains, a large N-terminal domain (1-436 residues) that is connected to a small C-terminal domain (440-544) by a flexible loop that functions as a hinge for opening and closing the active site. The two domains are separated by a large cleft housing the active site that closes after binding the substrates, luciferin and ATP. Even though all insect luciferases catalyze the same chemical reaction and share 50% to 90% sequence homology and high structural similarity, they emit light of different colors from green at 560nm to red at 640 nm. Currently, the majority of the structural and biochemical studies have been conducted on green-emitting firefly luciferases. To address the color emission mechanism, we expressed and purified two luciferase enzymes with blue-shifted green and red emission from indigenous Brazilian species Amydetes fanestratus and Phrixothrix, respectively. The two enzymes naturally emit light of different colors and they are an excellent system to study the color-emission mechanism of luciferases, as the current proposed mechanisms are based on mutagenesis studies. Using a vapor-diffusion method and a high-throughput approach, we crystallized and solved the crystal structure of both enzymes, at 1.7 Å and 3.1 Å resolution respectively, using X-ray crystallography. The free enzyme adopted two open conformations in the crystallographic unit cell that are different from the previously characterized firefly luciferase. The blue-shifted green luciferase crystalized as a monomer similar to other luciferases reported in literature, while the red luciferases crystalized as an octamer and was also purified as an octomer in solution. The octomer conformation is the first of its kind for any insect’s luciferase, which might be relate to the red color emission. Structurally designed mutations confirmed the importance of the transition between the open and close conformations in the fine-tuning of the color and the characterization of other interesting mutants is underway.

Keywords: bioluminescence, enzymology, structural biology, x-ray crystallography

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Authors: Solaf Badahman, Wala Alasbahi, Wajan Bamehraz, Hiba Nawwab

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This research delves into ChatGPT, OpenAI’s leading conversational AI, exploring its journey from early language models to the cutting-edge GPT-4. A survey of 35 users highlights ChatGPT’s strengths in creative writing, summarization, and user engagement while revealing areas for enhancement, particularly in technical tasks. Through scenario-based testing and direct feedback, this study uncovers ChatGPT’s real-world impact, examining its accuracy, privacy, and versatility. Positioned in a competitive landscape, ChatGPT emerges as a powerful, evolving tool for education, creativity, and problem-solving. This research offers a concise snapshot of AI’s growing role in shaping the future of human-AI interaction.

Keywords: AI, NLP, ChatGPT, conversational AI, human–AI interaction

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Authors: Kritchakhris Na-Wattanaprasert

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The objective of this research is to design and develop a prototype of a key performance indicator system this is suitable for warehouse management in a case study and use requirement. In this study, we design a prototype of key performance indicator system (KPI) for warehouse case study of furniture business by methodology in step of identify scope of the research and study related papers, gather necessary data and users requirement, develop key performance indicator base on balance scorecard, design pro and database for key performance indicator, coding the program and set relationship of database and finally testing and debugging each module. This study use Balance Scorecard (BSC) for selecting and grouping key performance indicator. The system developed by using Microsoft SQL Server 2010 is used to create the system database. In regard to visual-programming language, Microsoft Visual C# 2010 is chosen as the graphic user interface development tool. This system consists of six main menus: menu login, menu main data, menu financial perspective, menu customer perspective, menu internal, and menu learning and growth perspective. Each menu consists of key performance indicator form. Each form contains a data import section, a data input section, a data searches – edit section, and a report section. The system generates outputs in 5 main reports, the KPI detail reports, KPI summary report, KPI graph report, benchmarking summary report and benchmarking graph report. The user will select the condition of the report and period time. As the system has been developed and tested, discovers that it is one of the ways to judging the extent to warehouse objectives had been achieved. Moreover, it encourages the warehouse functional proceed with more efficiency. In order to be useful propose for other industries, can adjust this system appropriately. To increase the usefulness of the key performance indicator system, the recommendations for further development are as follows: -The warehouse should review the target value and set the better suitable target periodically under the situation fluctuated in the future. -The warehouse should review the key performance indicators and set the better suitable key performance indicators periodically under the situation fluctuated in the future for increasing competitiveness and take advantage of new opportunities.

Keywords: key performance indicator, warehouse management, warehouse operation, logistics management

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Authors: Pablo Chico De Guzman, Cesar Sanchez

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Microservice architectures are increasingly in distributed cloud applications due to the advantages on the software composition, development speed, release cycle frequency and the business logic time to market. On the other hand, these architectures also introduce some challenges on the testing and release phases of applications. Container technology solves some of these issues by providing reproducible environments, easy of software distribution and isolation of processes. However, there are other issues that remain unsolved in current container technology when dealing with multiple machines, such as networking for multi-host communication, service discovery, load balancing or data persistency (even though some of these challenges are already solved by traditional cloud vendors in a very mature and widespread manner). Container cluster management tools, such as Kubernetes, Mesos or Docker Swarm, attempt to solve these problems by introducing a new control layer where the unit of deployment is the container (or the pod — a set of strongly related containers that must be deployed on the same machine). These tools are complex to configure and manage and they do not follow a pure immutable infrastructure approach since servers are reused between deployments. Indeed, these tools introduce dependencies at execution time for solving networking or service discovery problems. If an error on the control layer occurs, which would affect running applications, specific expertise is required to perform ad-hoc troubleshooting. As a consequence, it is not surprising that container cluster support is becoming a source of revenue for consulting services. This paper presents i2kit, a deployment tool based on the immutable infrastructure pattern, where the virtual machine is the unit of deployment. The input for i2kit is a declarative definition of a set of microservices, where each microservice is defined as a pod of containers. Microservices are built into machine images using linuxkit —- a tool for creating minimal linux distributions specialized in running containers. These machine images are then deployed to one or more virtual machines, which are exposed through a cloud vendor load balancer. Finally, the load balancer endpoint is set into other microservices using an environment variable, providing service discovery. The toolkit i2kit reuses the best ideas from container technology to solve problems like reproducible environments, process isolation, and software distribution, and at the same time relies on mature, proven cloud vendor technology for networking, load balancing and persistency. The result is a more robust system with no learning curve for troubleshooting running applications. We have implemented an open source prototype that transforms i2kit definitions into AWS cloud formation templates, where each microservice AMI (Amazon Machine Image) is created on the fly using linuxkit. Even though container cluster management tools have more flexibility for resource allocation optimization, we defend that adding a new control layer implies more important disadvantages. Resource allocation is greatly improved by using linuxkit, which introduces a very small footprint (around 35MB). Also, the system is more secure since linuxkit installs the minimum set of dependencies to run containers. The toolkit i2kit is currently under development at the IMDEA Software Institute.

Keywords: container, deployment, immutable infrastructure, microservice

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Authors: R. Joseph Raviselvan, K. Ramanathan, P. Perumal, M. R. Thansekhar

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Hard coatings are widely used in cutting and forming tool industries. Titanium Nitride (TiN) possesses good hardness, strength and corrosion resistant. The coating properties are influenced by many process parameters. The coatings were deposited on steel substrate by changing the process parameters such as substrate temperature, nitrogen flow rate and target power in a D.C planer magnetron sputtering. The structure of coatings were analysed using XRD. The hardness of coatings was found using Micro hardness tester. From the experimental data, a regression model was developed and the optimum response was determined using Response Surface Methodology (RSM).

Keywords: hardness, RSM, sputtering, TiN XRD

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Authors: M. Reza Hashemi, Chris Small, Scott Hayward

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The Northeast Coast of the US faces damaging effects of coastal flooding and winds due to Atlantic tropical and extratropical storms each year. Historically, several large storm events have produced substantial levels of damage to the region; most notably of which were the Great Atlantic Hurricane of 1938, Hurricane Carol, Hurricane Bob, and recently Hurricane Sandy (2012). The objective of this study was to develop an integrated modeling system that could be used as a forecasting/hindcasting tool to evaluate and communicate the risk coastal communities face from these coastal storms. This modeling system utilizes the ADvanced CIRCulation (ADCIRC) model for storm surge predictions and the Simulating Waves Nearshore (SWAN) model for the wave environment. These models were coupled, passing information to each other and computing over the same unstructured domain, allowing for the most accurate representation of the physical storm processes. The coupled SWAN-ADCIRC model was validated and has been set up to perform real-time forecast simulations (as well as hindcast). Modeled storm parameters were then passed to a coastal risk assessment tool. This tool, which is generic and universally applicable, generates spatial structural damage estimate maps on an individual structure basis for an area of interest. The required inputs for the coastal risk model included a detailed information about the individual structures, inundation levels, and wave heights for the selected region. Additionally, calculation of wind damage to structures was incorporated. The integrated coastal risk assessment system was then tested and applied to Charlestown, a small vulnerable coastal town along the southern shore of Rhode Island. The modeling system was applied to Hurricane Sandy and a synthetic storm. In both storm cases, effect of natural dunes on coastal risk was investigated. The resulting damage maps for the area (Charlestown) clearly showed that the dune eroded scenarios affected more structures, and increased the estimated damage. The system was also tested in forecast mode for a large Nor’Easters: Stella (March 2017). The results showed a good performance of the coupled model in forecast mode when compared to observations. Finally, a nearshore model XBeach was then nested within this regional grid (ADCIRC-SWAN) to simulate nearshore sediment transport processes and coastal erosion. Hurricane Irene (2011) was used to validate XBeach, on the basis of a unique beach profile dataset at the region. XBeach showed a relatively good performance, being able to estimate eroded volumes along the beach transects with a mean error of 16%. The validated model was then used to analyze the effectiveness of several erosion mitigation methods that were recommended in a recent study of coastal erosion in New England: beach nourishment, coastal bank (engineered core), and submerged breakwater as well as artificial surfing reef. It was shown that beach nourishment and coastal banks perform better to mitigate shoreline retreat and coastal erosion.

Keywords: ADCIRC, coastal flooding, storm surge, coastal risk assessment, living shorelines

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Authors: Ella Tyuryumina, Alexey Neznanov

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Finding algorithms to predict the growth of tumors has piqued the interest of researchers ever since the early days of cancer research. A number of studies were carried out as an attempt to obtain reliable data on the natural history of breast cancer growth. Mathematical modeling can play a very important role in the prognosis of tumor process of breast cancer. However, mathematical models describe primary tumor growth and metastases growth separately. Consequently, we propose a mathematical growth model for primary tumor and primary metastases which may help to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoM-IV and corresponding software. We are interested in: 1) modelling the whole natural history of primary tumor and primary metastases; 2) developing adequate and precise CoM-IV which reflects relations between PT and MTS; 3) analyzing the CoM-IV scope of application; 4) implementing the model as a software tool. The CoM-IV is based on exponential tumor growth model and consists of a system of determinate nonlinear and linear equations; corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and primary metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for primary metastases; 3) ‘visible period’ for primary metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-IV model and predictive software: a) detect different growth periods of primary tumor and primary metastases; b) make forecast of the period of primary metastases appearance; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of BC and facilitate optimization of diagnostic tests. The following are calculated by CoM-IV: the number of doublings for ‘nonvisible’ and ‘visible’ growth period of primary metastases; tumor volume doubling time (days) for ‘nonvisible’ and ‘visible’ growth period of primary metastases. The CoM-IV enables, for the first time, to predict the whole natural history of primary tumor and primary metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-IV describes correctly primary tumor and primary distant metastases growth of IV (T1-4N0-3M1) stage with (N1-3) or without regional metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and manifestation of primary metastases.

Keywords: breast cancer, exponential growth model, mathematical modelling, primary metastases, primary tumor, survival

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Authors: Ossama Al-Maliki

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The Europay, MasterCard, and Visa (EMV) is the transaction protocol for most of the world and especially in Europe and the UK. EMV protocol consists of three main stages which are: card authentication, cardholder verification methods, and transaction authorization. This paper details in full the EMV card authentications. We have used AVISPA and SPAN tools to do our modulization for the EMV card authentications. The code for each type of the card authentication was written by using CAS+ language. The results showed that our modulations were successfully addressed all the steps of the EMV card authentications and the entire process of the EMV card authentication are secured. Also, our modulations were successfully addressed all the main goals behind the EMV card authentications according to the EMV specifications.

Keywords: EMV, card authentication, contactless card, SDA, DDA, CDA AVISPA

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Authors: Beata Zatwarnicka-Madura

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The objective of the article was to identify the impacts of gamification on customers' behaviour. The most important applications of games in marketing and mechanisms of gamification are presented in the article. A detailed analysis of the influence of gamification on customers using two brands, Foursquare and Nike, was also presented. Research studies using auditory survey methods were carried out among 176 young respondents, who are potential targets of gamification. The studies confirmed a huge participation of young people in customer loyalty programs with relatively low participation in other gamification-based marketing activities. The research findings clearly indicate that gamification mechanisms are the most attractive.

Keywords: customer loyalty, games, gamification, social aspects

Procedia PDF Downloads 492

Authors: Schröde C., Rodriguez D., Sánchez A., Abdul Malak, Churchill J., Boksmati T., Alharbi, Alsulmi H., Maghrabi S., Mowalad, Mutwalli R., Abualnaja Y.

Abstract:

Formulating a strategy for sustainable development of the Kingdom of Saudi Arabia’s coastal and marine environment is at the core of the “Marine and Coastal Protection Assessment Study for the Kingdom of Saudi Arabia Coastline (MCEP)”; that was set up in the context of the Vision 2030 by the Saudi Arabian government and aimed at providing a first comprehensive ‘Status Quo Assessment’ of the Kingdom’s marine environment to inform a sustainable development strategy and serve as a baseline assessment for future monitoring activities. This baseline assessment relied on scientific evidence of the drivers, pressures and their impact on the environments of the Red Sea and Arabian Gulf. A key element of the assessment was the cumulative pressure hotspot analysis developed for both national waters of the Kingdom following the principles of the Driver-Pressure-State-Impact-Response (DPSIR) framework and using the cumulative pressure and impact assessment methodology. The ultimate goals of the analysis were to map and assess the main hotspots of environmental pressures, and identify priority areas for further field surveillance and for urgent management actions. The study identified maritime transport, fisheries, aquaculture, oil, gas, energy, coastal industry, coastal and maritime tourism, and urban development as the main drivers of pollution in the Saudi Arabian marine waters. For each of these drivers, pressure indicators were defined to spatially assess the potential influence of the drivers on the coastal and marine environment. A list of hotspots of 90 locations could be identified based on the assessment. Spatially grouped the list could be reduced to come up with of 10 hotspot areas, two in the Arabian Gulf, 8 in the Red Sea. The hotspot mapping revealed clear spatial patterns of drivers, pressures and hotspots within the marine environment of waters under KSA’s maritime jurisdiction in the Red Sea and Arabian Gulf. The cascading assessment approach based on the DPSIR framework ensured that the root causes of the hotspot patterns, i.e. the human activities and other drivers, can be identified. The adapted CPIA methodology allowed for the combination of the available data to spatially assess the cumulative pressure in a consistent manner, and to identify the most critical hotspots by determining the overlap of cumulative pressure with areas of sensitive biodiversity. Further improvements are expected by enhancing the data sources of drivers and pressure indicators, fine-tuning the decay factors and distances of the pressure indicators, as well as including trans-boundary pressures across the regional seas.

Keywords: Arabian Gulf, DPSIR, hotspot, red sea

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Authors: Kadda Boumediene, Mohamed Bouzit

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The prediction of the flow around marine propellers and vessel hulls propeller interaction is one of the challenges of Computational fluid dynamics (CFD). The CFD has emerged as a potential tool in recent years and has promising applications. The objective of the current study is to predict the hydrodynamic performances of HSP marine propeller in open water and behind a vessel. The unsteady 3-D flow was modeled numerically along with respectively the K-ω standard and K-ω SST turbulence models for steady and unsteady cases. The hydrodynamic performances such us a torque and thrust coefficients and efficiency show good agreement with the experiment results.

Keywords: seiun maru propeller, steady, unstead, CFD, HSP

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Authors: Solehah Yaacob

Abstract:

The study focuses on revisiting the effectiveness of Critical Thinking in human mind capability as a major faculty in human life. The tool used as a measurement of this knowledge ability consists of several processes including experience and education background. To emphasize the `Overview` concept, the researcher highlights two major aspects of philosophical approach, they are; Divine Revelation Concept and Modern Scientific Theory. The research compares between the both parties to introduce the Divine Revelation into Modern Scientific theory. An analytical and critical study of the both concepts become the methodology of the discussion.

Keywords: critical thinking, knowledge, intellectual, language

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Authors: A. Mostaani, M. P. Pereira, B. F. Rolfe

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The increasing application of Advanced High Strength Steel (AHSS) in the automotive industry to fulfill crash requirements has introduced higher levels of wear in stamping dies and parts. Therefore, understanding wear behaviour in sheet metal forming is of great importance as it can help to reduce the high costs currently associated with tool wear. At the contact between the die and the sheet, the tips of hard tool asperities interact with the softer sheet material. Understanding the deformation that occurs during this interaction is important for our overall understanding of the wear mechanisms. For these reasons, the scratching of a perfectly plastic material by a rigid indenter has been widely examined in the literature; with finite element modelling (FEM) used in recent years to further understand the behaviour. The ‘wear mode diagram’ has been commonly used to classify the deformation regime of the soft work-piece during scratching, into three modes: ploughing, wedge formation, and cutting. This diagram, which is based on 2D slip line theory and upper bound method for perfectly plastic work-piece and rigid indenter, relates different wear modes to attack angle and interfacial strength. This diagram has been the basis for many wear studies and wear models to date. Additionally, it has been concluded that galling is most likely to occur during the wedge formation mode. However, there has been little analysis in the literature of how the material behaviour and deformation conditions associated with metal forming processes influence the wear behaviour. Therefore, the first aim of this work is first to use a commercial FEM package (Abaqus/Explicit) to build a 3D model to capture wear modes during scratching with indenters with different attack angles and different interfacial strengths. The second goal is to utilise the developed model to understand how wear modes might change in the presence of bulk deformation of the work-piece material as a result of the metal forming operation. Finally, the effect of the work-piece material properties, including strain hardening, will be examined to understand how these influence the wear modes and wear behaviour. The results show that both strain hardening and substrate deformation can change the critical attack angle at which the wedge formation regime is activated.

Keywords: finite element, pile-up, scratch test, wear mode

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Authors: Ejikeme Ugiri

Abstract:

In an executive summary, UNESCO describes Framework for Cultural Statistics as a tool for organizing cultural statistics both nationally and internationally. This is based on conceptual foundation and a common understanding of culture that will enable the measurement of a wide range of cultural expressions. This means therefore that cultural expression in whatever guise has the potentiality of contributing reasonably to the development of a given society. The paper looked into the various tangible and intangible cultures in Imo State of Nigeria. Due to government’s insensitivity, there is need to remind ourselves of the need to pay adequate attention to the cultural heritage bequeathed to us by our forefathers for the sake of posterity. Documenting this information in written form therefore becomes imperative. The study concludes that culture if developed, could reasonably contribute to economic and social growth of the society.

Keywords: culture, detonation, development, statistics

Procedia PDF Downloads 471

Authors: Qiaoyue Kuang, Yang Li, Mizuki Endo, Takeaki Ozawa

Abstract:

G protein-coupled receptors (GPCR) are the largest family of receptor proteins that detect molecules outside the cell and activate cellular responses. Of the GPCRs, dopamine receptors, which recognize extracellular dopamine, are essential to mammals due to their roles in numerous physiological events, including autonomic movement, hormonal regulation, emotions, and the reward system in the brain. To precisely understand the physiological roles of dopamine receptors, it is important to spatiotemporally control the signaling mediated by dopamine receptors, which is strongly dependent on their surface expression. Conventionally, chemical-induced interactions were applied to trigger the endocytosis of cell surface receptors. However, these methods were subjected to diffusion and therefore lacked temporal and special precision. To further understand the receptor-mediated signaling and to control the plasma membrane expression of receptors, an optogenetic tool called E-fragment was developed. The C-terminus of a light-sensitive photosensory protein cyptochrome2 (CRY2) was attached to β-Arrestin, and the E-fragment was generated by fusing the C-terminal peptide of vasopressin receptor (V2R) to CRY2’s binding partner protein CIB. The CRY2-CIB heterodimerization triggered by blue light stimulation brings β-Arrestin to the vicinity of membrane receptors and results in receptor endocytosis. In this study, the E-fragment system was applied to dopamine receptors 1 and 2 (DRD1 and DRD2) to control dopamine signaling. First, confocal fluorescence microscope observation qualitatively confirmed the light-induced endocytosis of E-fragment fused receptors. Second, NanoBiT bioluminescence assay verified quantitatively that the surface amount of E-fragment labeled receptors decreased after light treatment. Finally, GloSensor bioluminescence assay results suggested that the E-fragment-dependent receptor light-induced endocytosis decreased cAMP production in DRD1 signaling and attenuated the inhibition effect of DRD2 on cAMP production. The developed optogenetic tool was able to induce receptor endocytosis by external light, providing opportunities to further understand numerous physiological activities by controlling receptor-mediated signaling spatiotemporally.

Keywords: dopamine receptors, endocytosis, G protein-coupled receptors, optogenetics

Procedia PDF Downloads 104

Authors: Newton Muhury, Armando A. Apan, Tek Maraseni

Abstract:

This study modelled the relationships between vegetation response and available water below the soil surface using the Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS) generated Normalised Difference Vegetation Index (NDVI) and soil water content (SWC) data. The Soil & Water Assessment Tool (SWAT) interface known as ArcSWAT was used in ArcGIS for the groundwater analysis. The SWAT model was calibrated and validated in SWAT-CUP software using 10 years (2001-2010) of monthly streamflow data. The average Nash-Sutcliffe Efficiency during the calibration and validation was 0.54 and 0.51, respectively, indicating that the model performances were good. Twenty years (2001-2020) of monthly MODIS NDVI data for three different types of vegetation (forest, shrub, and grass) and soil water content for 43 sub-basins were analysed using the WEKA, machine learning tool with a selection of two supervised machine learning algorithms, i.e., support vector machine (SVM) and random forest (RF). The modelling results show that different types of vegetation response and soil water content vary in the dry and wet season. For example, the model generated high positive relationships (r=0.76, 0.73, and 0.81) between the measured and predicted NDVI values of all vegetation in the study area against the groundwater flow (GW), soil water content (SWC), and the combination of these two variables, respectively, during the dry season. However, these relationships were reduced by 36.8% (r=0.48) and 13.6% (r=0.63) against GW and SWC, respectively, in the wet season. On the other hand, the model predicted a moderate positive relationship (r=0.63) between shrub vegetation type and soil water content during the dry season, which was reduced by 31.7% (r=0.43) during the wet season. Our models also predicted that vegetation in the top location (upper part) of the sub-basin is highly responsive to GW and SWC (r=0.78, and 0.70) during the dry season. The results of this study indicate the study region is suitable for seasonal crop production in dry season. Moreover, the results predicted that the growth of vegetation in the top-point location is highly dependent on groundwater flow in both dry and wet seasons, and any instability or long-term drought can negatively affect these floodplain vegetation communities. This study has enriched our knowledge of vegetation responses to groundwater in each season, which will facilitate better floodplain vegetation management.

Keywords: ArcSWAT, machine learning, floodplain vegetation, MODIS NDVI, groundwater

Procedia PDF Downloads 120