Search results for: engine performance analysis

Authors: Riddhi Jangid, Gajendra Pratap Singh

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Petri nets, a formalized modeling language that was introduced back around 50-60 years, have been widely used for modeling discrete event dynamic systems and simulating their behavior. Reachability analysis of Petri nets gives many insights into a modeled system. This idea leads us to study the reachability technique and use it in the reachability problem in the state space of reachable markings. With the same concept, Crisp Boolean Petri nets were defined in which the marking vectors that are boolean are distinct in the reachability analysis of the nets. We generalize the concept and define ‘Crisp’ Petri nets that generate the marking vectors exactly once in their reachability-based analysis, not necessarily Boolean.

Keywords: marking vector, n-vector, Petri nets, reachability

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Authors: W. Oudad, H. Fikirini, K. Boulenouar

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Material fracture by opening (mode I) is not alone responsible for fracture propagation. Many industrial examples show the presence of mode II and mixed mode I + II. In the present work the three-dimensional and non-linear finite element method is used to estimate the performance of the bonded composite repair of metallic aircraft structures by analyzing the plastic zone size ahead of repaired cracks under mixed mode loading. The computations are made according to Von Mises and Tresca criteria. The extension of the plastic zone which takes place at the tip of a crack strictly depends on many variables, such as the yield stress of the material, the loading conditions, the crack size and the thickness of the cracked component, The obtained results show that the presence of the composite patch reduces considerably the size of the plastic zone ahead of the crack. The effects of the composite orientation layup (adhesive properties) and the patch thickness on the plastic zone size ahead of repaired cracks were analyzed.

Keywords: crack, elastic-plastic, J integral, patch, plastic zone

Procedia PDF Downloads 438

Authors: Laila Khaled Almawaldi, Hiew Khai Hang, Sugumaran A. l. Nallusamy

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Legacy systems are crucial for organizations, but their intricacy and lack of documentation pose challenges for maintenance and enhancement. Redocumentation of legacy systems is vital for automatically or semi-automatically creating documentation for software lacking sufficient records. It aims to enhance system understandability, maintainability, and knowledge transfer. However, existing redocumentation methods need improvement in data processing performance and document generation efficiency. This stems from the necessity to efficiently handle the extensive and complex code of legacy systems. This paper proposes a method for semi-automatic legacy system re-documentation using semantic parallel processing and ontology. Leveraging parallel processing and ontology addresses current challenges by distributing the workload and creating documentation with logically interconnected data. The paper outlines challenges in legacy system redocumentation and suggests a method of redocumentation using parallel processing and ontology for improved efficiency and effectiveness.

Keywords: legacy systems, redocumentation, big data analysis, parallel processing

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Authors: Loreta Kaklauskiene, Arturas Kaklauskas

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This employee productivity and work well-being effective system aims to maximise the work performance of personnel and boost well-being in offices. Affective computing, decision support, and knowledge-based systems were used in our research. The basis of this effective system is our European Patent application (No: EP 4 020 134 A1) and two Lithuanian patents (LT 6841, LT 6866). Our study examines ways to support efficient employee productivity and well-being by employing mass-customised, personalised office environment. Efficient employee performance and well-being are managed by changing mass-customised office environment factors such as air pollution levels, humidity, temperature, data, information, knowledge, activities, lighting colours and intensity, scents, media, games, videos, music, and vibrations. These aspects of management generate a customised, adaptive environment for users taking into account their emotional, affective, and physiological (MAP) states measured and fed into the system. This research aims to develop an innovative method and system which would analyse, customise and manage a personalised office environment according to a specific user’s MAP states in a cohesive manner. Various values of work spaces (e.g., employee utilitarian, hedonic, perceived values) are also established throughout this process, based on the measurements that describe MAP states and other aspects related to the office environment. The main contribution of our research is the development of a real-time mass-customised office environment to boost employee performance and well-being. Acknowledgment: This work was supported by Project No. 2020-1-LT01-KA203-078100 “Minimizing the influence of coronavirus in a built environment” (MICROBE) from the European Union’s Erasmus + program.

Keywords: effective decision support and a knowledge-based system, human resource management, employee productivity and work well-being, affective computing

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Authors: Teguh Sugiarto

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Background: This study aims to explore the fraud that occurred in the financial statements using the Benford distribution law of 1st and 2nd case study of PT AKR Corporindo Tbk. Research Methods: In this study the authors use the first digit of the analysis and the analysis of the second digit of Bedford’s law. Having obtained the results of the analysis of the first and second digits, authors will make the difference between implementations using the scale above and below 5%. The number that has the level of difference in the range of 5% above or below, then a financial report in may, to analyse in the followup to the direction of the audit investigation, and authors assume happens a confusion in the financial statements. Findings: From research done, we found that there was a difference in the results of the appearance of the first digit of the number with the proper use of Benford's law, according to PT AKR Corporindo financial reports Tbk for the fiscal year 2006-2010, above and below the level the difference in set 5%. Conclusions: From the research that has been done, it can be concluded that on PT AKR Corporindo financial report 2006, 2007, 2008, 2009 and 2010, there is a level difference of appearance of numbers according to Benford's law is significant, as presented in the table analysis.

Keywords: Benford law, first digits, second digits, Indonesian company

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Authors: M. Tehranizadeh, E. Shoushtari Rezvani

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Seismic performance of steel moment-resisting frame structures is investigated considering nonlinear soil-structure interaction (SSI) effects. 10-, 15-, and 20-story planar building frames with aspect ratio of 3 are designed in accordance with current building codes. Inelastic seismic demands of the superstructure are considered using concentrated plasticity model. The raft foundation system is designed for different soil types. Beam-on-nonlinear Winkler foundation (BNWF) is used to represent dynamic impedance of the underlying soil. Two sets of pulse-like as well as no-pulse near-fault earthquakes are used as input ground motions. The results show that the reduction in drift demands due to nonlinear SSI is characterized by a more uniform distribution pattern along the height when compared to the fixed-base and linear SSI condition. It is also concluded that beneficial effects of nonlinear SSI on displacement demands is more significant in case of pulse-like ground motions and performance level of the steel moment-resisting frames can be enhanced.

Keywords: soil-structure interaction, uplifting, soil plasticity, near-fault earthquake, tall building

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Authors: M. Al-Jepoori, D. Bennett

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Teaching Object-Oriented Programming (OOP) as part of a Computing-related university degree is a very difficult task; the road to ensuring that students are actually learning object oriented concepts is unclear, as students often find it difficult to understand the concept of objects and their behavior. This problem is especially obvious in advanced programming modules where Design Pattern and advanced programming features such as Multi-threading and animated GUI are introduced. Looking at the students’ performance at their final year on a university course, it was obvious that the level of students’ understanding of OOP varies to a high degree from one student to another. Students who aim at the production of Games do very well in the advanced programming module. However, the students’ assessment results of the last few years were relatively low; for example, in 2016-2017, the first quartile of marks were as low as 24.5 and the third quartile was 63.5. It is obvious that many students were not confident or competent enough in their programming skills. In this paper, the reasons behind poor performance in Advanced OOP modules are investigated, and a suggested practice for teaching OOP based on a complex case study is described and evaluated.

Keywords: complex programming case study, design pattern, learning advanced programming, object oriented programming

Procedia PDF Downloads 214

Authors: Linda P. M. Pluymen, Mariska M. G. Leeflang, I. Stegeman, Henock G. Yebyo, Anne E. M. Brabers, Patrick M. Bossuyt, E. Dekker, Anke J. Woudstra, Mirjam P. Fransen

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Weighing the benefits and harms of colorectal cancer screening can be difficult for individuals. An existing online decision aid was expanded with a benefit-harm analysis to help people make an informed decision about participating in colorectal cancer screening. In a randomized controlled trial, we investigated whether those in the intervention group who used the decision aid with benefit-harm analysis were more certain about their decision than those in the control group who used the decision aid without benefit-harm analysis. Participants were 623 (39% of those invited) men and women aged 45 until 75 years old. Analyses were performed in those 386 participants (62%) who reported to have completed the entire decision aid. No statistically significant differences were observed between intervention and control group in decisional conflict score (mean difference 2.4, 95% CI -0.9, 5.6), clarity of values (mean difference 1.0, 95% CI -4.4, 6.6), deliberation score (mean difference 0.5, 95% CI -0.6, 1.7), anxiety score (mean difference 0.0, 95% CI -0.3, 0.3) and risk perception score (mean difference 0.1, -0.1, 0.3). Adding a benefit-harm analysis to an online decision aid did not improve informed decision making about participating in colorectal cancer screening.

Keywords: benefit-harm analysis, decision aid, informed decision making, personalized decision making

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Authors: Ibrahim M. Mehedi, Uzair Ansari, Ubaid M. Al-Saggaf, Abdulrahman H. Bajodah

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This paper presents a methodology for balancing a rotary inverted pendulum system using Robust Generalized Dynamic Inversion (RGDI) under influence of parametric variations and external disturbances. In GDI control, dynamic constraints are formulated in the form of asymptotically stable differential equation which encapsulates the control objectives. The constraint differential equations are based on the deviation function of the angular position and its rates from their reference values. The constraint dynamics are inverted using Moore-Penrose Generalized Inverse (MPGI) to realize the control expression. The GDI singularity problem is addressed by augmenting a dynamic scale factor in the interpretation of MPGI which guarantee asymptotically stable position tracking. An additional term based on Sliding Mode Control is appended within GDI control to make it robust against parametric variations, disturbances and tracking performance deterioration due to generalized inversion scaling. The stability of the closed loop system is ensured by using positive definite Lyapunov energy function that guarantees semi-global practically stable position tracking. Numerical simulations are conducted on the dynamic model of rotary inverted pendulum system to analyze the efficiency of proposed RGDI control law. The comparative study is also presented, in which the performance of RGDI control is compared with Linear Quadratic Regulator (LQR) and is verified through experiments. Numerical simulations and real-time experiments demonstrate better tracking performance abilities and robustness features of RGDI control in the presence of parametric uncertainties and disturbances.

Keywords: generalized dynamic inversion, lyapunov stability, rotary inverted pendulum system, sliding mode control

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Authors: Pin Xiu Chen, Shang Liang Chen

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A virtualized software controller is developed in this research to replace traditional hardware control units. This virtualized software controller transfers motion interpolation calculations from the motion control units of end devices to edge computing platforms, thereby reducing the end devices' computational load and hardware requirements and making maintenance and updates easier. The study also applies the concept of microservices, dividing the control system into several small functional modules and then deploy into a cloud data server. This reduces the interdependency among modules and enhances the overall system's flexibility and scalability. Finally, with containerization technology, the system can be deployed and started in a matter of seconds, which is more efficient than traditional virtual machine deployment methods. Furthermore, this virtualized software controller communicates with end control devices via wireless networks, making the placement of production equipment or the redesign of processes more flexible and no longer limited by physical wiring. To handle the large data flow and maintain low-latency transmission, this study integrates 5G technology, fully utilizing its high speed, wide bandwidth, and low latency features to achieve rapid and stable remote machine control. An experimental setup is designed to verify the feasibility and test the performance of this framework. This study designs a smart manufacturing site with a 5G communication architecture, serving as a field for experimental data collection and performance testing. The smart manufacturing site includes one robotic arm, three Computer Numerical Control machine tools, several Input/Output ports, and an edge computing architecture. All machinery information is uploaded to edge computing servers and cloud servers via 5G communication and the Internet of Things framework. After analysis and computation, this information is converted into motion control commands, which are transmitted back to the relevant machinery for motion control through 5G communication. The communication time intervals at each stage are calculated using the C++ chrono library to measure the time difference for each command transmission. The relevant test results will be organized and displayed in the full-text.

Keywords: 5G, MEC, microservices, virtualized software controller, smart manufacturing

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Authors: Josiel Delgadillo, Johnson Kinyua, Charles Mutigwe

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The purpose of sentiment analysis is to determine the sentiment strength (e.g., positive, negative, neutral) from a textual source for good decision-making. Natural language processing in domains such as financial markets requires knowledge of domain ontology, and pre-trained language models, such as BERT, have made significant breakthroughs in various NLP tasks by training on large-scale un-labeled generic corpora such as Wikipedia. However, sentiment analysis is a strong domain-dependent task. The rapid growth of social media has given users a platform to share their experiences and views about products, services, and processes, including financial markets. StockTwits and Twitter are social networks that allow the public to express their sentiments in real time. Hence, leveraging the success of unsupervised pre-training and a large amount of financial text available on social media platforms could potentially benefit a wide range of financial applications. This work is focused on sentiment analysis using social media text on platforms such as StockTwits and Twitter. To meet this need, SkyBERT, a domain-specific language model pre-trained and fine-tuned on financial corpora, has been developed. The results show that SkyBERT outperforms current state-of-the-art models in financial sentiment analysis. Extensive experimental results demonstrate the effectiveness and robustness of SkyBERT.

Keywords: BERT, financial markets, Twitter, sentiment analysis

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Authors: Beena Sethi

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This work involves the degradation of plastic waste in the presence of three different nanocatalysts. A thin film of LLDPE was formed with all three nanocatalysts separately in the solvent. Thermo Gravimetric Analysis (TGA) and Differential Scanning Calorimetric (DSC) analysis of polymers suggest that the presence of these catalysts lowers the degradation temperature and the change mechanism of degradation. Gas chromatographic analysis was carried out for two films. In gas chromatography (GC) analysis, it was found that degradation of pure polymer produces only 32% C3/C4 hydrocarbons and 67.6% C5/C9 hydrocarbons. In the presence of these catalysts, more than 80% of polymer by weight was converted into either liquid or gaseous hydrocarbons. Change in the mechanism of degradation of polymer was observed therefore more C3/C4 hydrocarbons along with valuable feedstock are produced. Adjustment of dose of nanocatalyst, use of nano-admixtures and recycling of catalyst can make this catalytic feedstock recycling method a good tool to get sustainable environment. The obtained products can be utilized as fuel or can be transformed into other useful products. In accordance with the principles of sustainable development, chemical recycling i.e. tertiary recycling of polymers along with the reuse (zero order recycling) of plastics can be the most appropriate and promising method in this direction. The tertiary recycling is attracting much attention from the viewpoint of the energy resource.

Keywords: degradation, differential scanning calorimetry, feedstock recycling, gas chromatography, thermogravimetric analysis

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Authors: Hamed K. Arzani, Ahmad Amiri, Hamid K. Arzani, Salim Newaz Kazi, Ahmad Badarudin

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The new design of heat exchangers utilizing an annular distributor opens a new gateway for realizing higher energy optimization. To realize this goal, graphene nanoplatelet-based water nanofluids with promising thermophysical properties were synthesized in the presence of covalent and noncovalent functionalization. Thermal conductivity, density, viscosity and specific heat capacity were investigated and employed as a raw data for ANSYS-Fluent to be used in two-phase approach. After validation of obtained results by analytical equations, two special parameters of convective heat transfer coefficient and pressure drop were investigated. The study followed by studying other heat transfer parameters of annular pass in the presence of graphene nanopletelesbased water nanofluids at different weight concentrations, input powers and temperatures. As a result, heat transfer performance and friction loss are predicted for both synthesized nanofluids.

Keywords: heat transfer, nanofluid, turbulent flow, forced convection flow, graphene nanoplatelet

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Authors: Florim Grajcevci, Flamur Grajcevci, Fatos Tahiri, Hamdi Kurteshi

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The territory of Kosova is actually included in one of the most seismic-prone regions in Europe. Therefore, the earthquakes are not so rare in Kosova; and when they occurred, the consequences have been rather destructive. The importance of assessing the seismic resistance of existing masonry structures has drawn strong and growing interest in the recent years. Engineering included those of Vulnerability, Loss of Buildings and Risk assessment, are also of a particular interest. This is due to the fact that this rapidly developing field is related to great impact of earthquakes on the socioeconomic life in seismic-prone areas, as Kosova and Prishtina are, too. Such work paper for Prishtina city may serve as a real basis for possible interventions in historic buildings as are museums, mosques, old residential buildings, in order to adequately strengthen and/or repair them, by reducing the seismic risk within acceptable limits. The procedures of the vulnerability assessment of building structures have concentrated on structural system, capacity, and the shape of layout and response parameters. These parameters will provide expected performance of the very important existing building structures on the vulnerability and the overall behavior during the earthquake excitations. The structural systems of existing historical buildings in Pristina, Kosovo, are dominantly unreinforced brick or stone masonry with very high risk potential from the expected earthquakes in the region. Therefore, statistical analysis based on the observed damage-deformation, cracks, deflections and critical building elements, would provide more reliable and accurate results for the regional assessments. The analytical technique was used to develop a preliminary evaluation methodology for assessing seismic vulnerability of the respective structures. One of the main objectives is also to identify the buildings that are highly vulnerable to damage caused from inadequate seismic performance-response. Hence, the damage scores obtained from the derived vulnerability functions will be used to categorize the evaluated buildings as “stabile”, “intermediate”, and “unstable”. The vulnerability functions are generated based on the basic damage inducing parameters, namely number of stories (S), lateral stiffness (LS), capacity curve of total building structure (CCBS), interstory drift (IS) and overhang ratio (OR).

Keywords: vulnerability, ductility, seismic microzone, ductility, energy efficiency

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Authors: Ameur Ameur Abdelkader, Boukherrouba Hadjira

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The aim of the present study was to evaluate different doses of PMSG on reproductive performance in Ouled Djellal ewes synchronized during the breeding season period. A total of 200 ewes were used in this experiment, were divided in two groups, 100 uniparous (A) and 100 multiparous (B). All animals in both groups were divided equally into four groups homogeneous lots of then a single intramuscular (IM) injection of PMSG, Lot T1, A1 (400 IU), A2 (500 IU), A3 (600 IU) and (lot T2, B1 (400 IU), B2 (500UI), B3 (600UI), T1, and T2 are batch control groups received a single injection of progestin treatment without PMSG. The results showed that the fertility rate ranges from 79.16% to 92% with no significant difference (P > 0.05) between uniparous and multiparous ewes. The prolificity rate varies from 100% to 140% in uniparous ewes with the respective doses of 0 IU for the control group and 600 IU for lot A3. A significant difference between multiparous ewes prolificacy and uniparous receiving 500UI PMSG (respectively 142% vs 109%). The productivity rate has increased significantly among uniparous ewes with 82% for lot A1 to 112.5% for lot A3, as in multiparous ewes 66.66% for lot B1 to 133.33% for lot B3. At the same we recorded a positive correlation between the number of born products and increasing the dose of PMSG injected into the two categories of ewes (112.5% to 133.33% for multiparous uniparous VS 83% for and 66.66 uniparous % for multiparous).

Keywords: Ouled djellal ewe, PMSG, reproductive performance, Fertility

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Authors: Mathew Wakefield, Matthew Mitchell, Lisa Wise, Christopher McCarthy

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The properties of memory representations in artificial neural networks have cognitive implications. Distributed representations that encode instances as a pattern of activity across layers of nodes afford memory compression and enforce the selection of a single point in instance space. These encoding schemes also appear to distort the representational space, as well as trading off the ability to validate that input information is within the bounds of past experience. In contrast, a localist representation which encodes some meaningful information into individual nodes in a network layer affords less memory compression while retaining the integrity of the representational space. This allows the validity of an input to be determined. The validity (or familiarity) of input along with the capacity of localist representation for multiple instance selections affords a memory sampling approach that dynamically balances the bias-variance trade-off. When the input is familiar, bias may be high by referring only to the most similar instances in memory. When the input is less familiar, variance can be increased by referring to more instances that capture a broader range of features. Using this approach in a localist instance memory network, an experiment demonstrates a relationship between representational conflict, generalization performance, and memorization demand. Relatively small sampling ranges produce the best performance on a classic machine learning dataset of visual objects. Combining memory validity with conflict detection produces a reliable confidence judgement that can separate responses with high and low error rates. Confidence can also be used to signal the need for supervisory input. Using this judgement, the need for supervised learning as well as memory encoding can be substantially reduced with only a trivial detriment to classification performance.

Keywords: artificial neural networks, representation, memory, conflict monitoring, confidence

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Authors: Chenxiao Yang, Li Li

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In this decade, the sportswear market rapidly expanded while numerous sports brands are conducting fierce competitions to hold their market shares and trying to act as a leader in professional competition sports areas to set the trends. Thus, various advancing sports equipment is being deeply explored to improving athletes’ performance in fierce competitions. Although there is plenty protective equipment such as cuff, running legging, etc., on the market, there is still blank in the field of sportswear during prerace warm-up this important time gap, especially for those competitions host in cold environment. Because there is always time gaps between warm-up and race due to event logistics or unexpected weather factors. Athletes will be exposed to chilly condition for an unpredictable long period of time. As a consequence, the effects of warm-up will be negated, and the competition performance will be degraded. However, reviewing the current market, there is none effective sports equipment provided to help athletes against this harsh environment or the rare existing products are so blocky or heavy to restrict the actions. An ideal thermal-protective sportswear should be light, flexible, comfort and aesthetic at the same time. Therefore, this design research adopted the textile circular knitting methodology to integrate soft silver-coated conductive yarns (ab. SCCYs), elastic nylon yarn and polyester yarn to develop the proposed electrical, thermal sportswear, with the strengths aforementioned. Meanwhile, the relationship between heating performance, stretch load, and energy consumption were investigated. Further, a simulation model was established to ensure providing sufficient warm and flexibility at lower energy cost and with an optimized production, parameter determined. The proposed circular knitting technology and simulation model can be directly applied to instruct prototype developments to cater different target consumers’ needs and ensure prototypes’’ safety. On the other hand, high R&D investment and time consumption can be saved. Further, two prototypes: a kneecap and an elbow guard, were developed to facilitate the transformation of research technology into an industrial application and to give a hint on the blur future blueprint.

Keywords: cold environment, silver-coated conductive yarn, electrical thermal textile, stretchable

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Authors: Rhoda Afriyie Mensah, Lin Jiang, Solomon Asante-Okyere, Xu Qiang, Cong Jin

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Flammability analysis of extruded polystyrene (XPS) has become crucial due to its utilization as insulation material for energy efficient buildings. Using the Kissinger-Akahira-Sunose and Flynn-Wall-Ozawa methods, the degradation kinetics of two pure XPS from the local market, red and grey ones, were obtained from the results of thermogravity analysis (TG) and microscale combustion calorimetry (MCC) experiments performed under the same heating rates. From the experiments, it was discovered that red XPS released more heat than grey XPS and both materials showed two mass loss stages. Consequently, the kinetic parameters for red XPS were higher than grey XPS. A comparative evaluation of activation energies from MCC and TG showed an insignificant degree of deviation signifying an equivalent apparent activation energy from both methods. However, different activation energy profiles as a result of the different chemical pathways were presented when the dependencies of the activation energies on extent of conversion for TG and MCC were compared.

Keywords: flammability, microscale combustion calorimetry, thermogravity analysis, thermal degradation, kinetic analysis

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Authors: Margareta Rahayuningsih, Siti Alimah, Novita Hermayani, Misbahul Munir

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Wreathed Hornbill (Rhycticeros undulatus) was a protected bird that we can found in Mount Ungaran. It is known that the bird have been breeding and nesting on the mountain. The objective of the research was to analysis the materials composition of the Wreathed Hornbill nest wall plaster. The study was carried out in Curug Lawe and Gunung Gentong, Mount Ungaran Central Java. Nest wall plaster samples were collected from nest cavities were used by hornbill but after they left from the nest. The nest tree species on Gunung Gentong was Syzygium antisepticum and Syzigium glabratum on Curug Lawe. Materials analysis used proximate analysis and have been done on Chemistry Laboratory of Semarang State University. The result of proximate analysis showed that the material composition of nest wall plaster such as water, proteins. lipid, carbohydrate, and ash between Curug Lawe and Gunung Gentong was different. Except Carbohidrate, the highest componen showed in the nest wall plaster on Gunung Gentong.

Keywords: Mount Ungaran, nest cover entrance, Rhyticeros undulatus, proximate analysis

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Authors: Mohamed M. El Gendy, Ibrahim A. El Arabi, Rafeek W. Abdel-Missih, Omar A. Kandil

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Nonlinear analysis is one of the most important design and safety tools in structural engineering. Based on the finite-element method, a geometrical and material nonlinear analysis of large span reinforced concrete arches is carried out considering soil-structure interaction. The concrete section details and reinforcement distribution are taken into account. The behavior of soil is considered via Winkler's and continuum models. A computer program (NARC II) is specially developed in order to follow the structural behavior of large span reinforced concrete arches up to failure. The results obtained by the proposed model are compared with available literature for verification. This work confirmed that the geometrical and material nonlinearities, as well as soil structure interaction, have considerable influence on the structural response of reinforced concrete arches.

Keywords: nonlinear analysis, reinforced concrete arched structure, soil-structure interaction, geotechnical engineering

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Authors: Ezgi Yurdakul, Klaus-Alexander Rieder, Richard Sibbick

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Most of the shotcrete projects require compliance with meeting a specified early-age strength target (e.g., reaching 1 MPa in 1 hour) that is selected based on the underground conditions. To meet the desired early-age performance characteristics, accelerators are commonly used as they increase early-age strength development rate and accelerate the setting thereby reducing sagging and rebound. The selection of accelerator type and its dosage is made by the setting time and strength required for the shotcrete application. While alkaline and alkali-free accelerators are the two main types used in wet-mix shotcrete; alkali-free admixtures increasingly substitute the alkaline accelerators to improve the performance and working safety. This paper aims to evaluate the impact of alkali-free accelerators in wet-mix on various tests including set time, early and later-age compressive strength, boiled absorption, and electrical resistivity. Furthermore, the comparison between accelerated and non-accelerated samples will be made to demonstrate the interaction between cement and accelerators. Scanning electron microscopy (SEM), fluorescent resin impregnated thin section and cut and polished surface images will be used to understand the microstructure characterization of mixes in the presence of accelerators.

Keywords: accelerators, chemical admixtures, shotcrete, sprayed concrete

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Authors: Syed Kamran Sami, Saqib Siddiqui

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In recent times, flexible supercapacitors retaining high electrochemical performance and steadiness along with mechanical endurance has developed as a spring of attraction due to the exponential progress and innovations in energy storage devices. To meet the rampant increasing demand of energy storage device with the small form factor, a unique, low cost and high-performance supercapacitor with considerably higher capacitance and mechanical robustness is required to recognize their real-life applications. Here in this report, synthesis route of electrode materials with low rigidity and high charge storage performance is reported using 1D-1D hybrid structure of zinc oxide (ZnO) nanorods, and conductive polymer smeared polyvinylidene fluoride–trifluoroethylene (P(VDF–TrFE)) electrospun nanofibers. The ZnO nanorods were uniformly grown on poly (3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT: PSS) coated P(VDF-TrFE) nanofibers using hydrothermal growth to manufacture light weight, permeable electrodes for supercapacitor. The PEDOT: PSS coated P(VDF-TrFE) porous web of nanofibers act as framework with high surface area. The incorporation of ZnO nanorods further boost the specific capacitance by 59%. The symmetric device using the fabricated 1D-1D hybrid electrodes reveals fairly high areal capacitance of 1.22mF/cm² at a current density of 0.1 mA/cm² with a power density of more than 1600 W/Kg. Moreover, the fabricated electrodes show exceptional flexibility and high endurance with 90% and 76% specific capacitance retention after 1000 and 5000 cycles respectively signifying the astonishing mechanical durability and long-term stability. All the properties exhibited by the fabricated electrode make it convenient for making flexible energy storage devices with the low form factor.

Keywords: ZnO nanorods, electrospinning, mechanical endurance, flexible supercapacitor

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Authors: Mehravar Javid, Sadrieh Khajavi Mazanderani, Kelly Gleischman, Zoe Andris

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The present study was conducted with the aim of investigating the effectiveness of transactional analysis group training on self-knowledge and Its dimensions (self, child, and adult) in counselors working in public and private high schools in Tehran. Counseling has become an important job for society, and there is a need for consultants in organizations. Providing better and more efficient counseling is one of the goals of the education system. The personal characteristics of counselors are important for the success of the therapy. In TA, humans have three ego states, which are named parent, adult, and child, and the main concept in the transactional analysis is self-state, which means a stable feeling and pattern of thinking related to behavioral patterns. Self-knowledge, considered a prerequisite to effective communication, fosters psychological growth, and recognizing it, is pivotal for emotional development, leading to profound insights. The research sample included 30 working counselors (22 women and 8 men) in the academic year 2019-2020 who achieved the lowest scores on the self-knowledge questionnaire. The research method was quasi-experimental with a control group (15 people in the experimental group and 15 people in the control group). The research tool was a self-awareness questionnaire with 29 questions and three subscales (child, parent, and adult Ego state). The experimental group was exposed to transactional analysis training for 10 once-weekly 2-hour sessions; the questionnaire was implemented in both groups (post-test). Multivariate covariance analysis was used to analyze the data. The data showed that the level of self-awareness of counselors who received transactional analysis training is higher than that of counselors who did not receive any training (p<0.01). The result obtained from this analysis shows that transactional analysis training is an effective therapy for enhancing self-knowledge and its subscales (Adult ego state, Parent ego state, and Child ego state). Teaching transactional analysis increases self-knowledge, and self-realization and helps people to achieve independence and remove irresponsibility to improve intra-personal and interpersonal relationships.

Keywords: ego state, group, transactional analysis, self-knowledge

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Authors: Qi Xiu, Hiromu Hota, Yohsuke Ishii, Takuya Oda

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Recently, collectable manufacturing data are rapidly increasing. On the other hand, mega recall is getting serious as a social problem. Under such circumstances, there are increasing needs for preventing mega recalls by defect analysis such as root cause analysis and abnormal detection utilizing manufacturing data. However, the time to classify strings in manufacturing data by traditional method is too long to meet requirement of quick defect analysis. Therefore, we present String Length Distribution Classification method (SLDC) to correctly classify strings in a short time. This method learns character features, especially string length distribution from Product ID, Machine ID in BOM and asset list. By applying the proposal to strings in actual manufacturing data, we verified that the classification time of strings can be reduced by 80%. As a result, it can be estimated that the requirement of quick defect analysis can be fulfilled.

Keywords: string classification, data quality, feature selection, probability distribution, string length

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Authors: Richard Okyere Boadu, Godwin Adzakpah, Nathan Kumasenu Mensah, Kwame Adu Okyere Boadu, Jonathan Kissi, Christiana Dziyaba, Rosemary Bermaa Abrefa

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Information and communication technology (ICT) has significantly advanced global healthcare, with electronic health (e-Health) applications improving health records and delivery. These innovations, including electronic health records, strengthen healthcare systems. The study investigates healthcare professionals' perceptions of health information applications and their associated factors in the Cape Coast Metropolis of Ghana's health facilities. Methods: We used a descriptive cross-sectional study design to collect data from 632 healthcare professionals (HCPs), in the three purposively selected health facilities in the Cape Coast municipality of Ghana in July 2022. Shapiro-Wilk test was used to check the normality of dependent variables. Descriptive statistics were used to report means with corresponding standard deviations for continuous variables. Proportions were also reported for categorical variables. Bivariate regression analysis was conducted to determine the factors influencing the Benefits of Information Technology (BoIT); Barriers to Information Technology Use (BITU); and Motives of Information Technology Use (MoITU) in healthcare delivery. Stata SE version 15 was used for the analysis. A p-value of less than 0.05 served as the basis for considering a statistically significant accepting hypothesis. Results: Healthcare professionals (HCPs) generally perceived moderate benefits (Mean score (M)=5.67) from information technology (IT) in healthcare. However, they slightly agreed that barriers like insufficient computers (M=5.11), frequent system downtime (M=5.09), low system performance (M=5.04), and inadequate staff training (M=4.88) hindered IT utilization. Respondents slightly agreed that training (M=5.56), technical support (M=5.46), and changes in work procedures (M=5.10) motivated their IT use. Bivariate regression analysis revealed significant influences of education, working experience, healthcare profession, and IT training on attitudes towards IT utilization in healthcare delivery (BoIT, BITU, and MoITU). Additionally, the age of healthcare providers, education, and working experience significantly influenced BITU. Ultimately, age, education, working experience, healthcare profession, and IT training significantly influenced MoITU in healthcare delivery. Conclusions: Healthcare professionals acknowledge moderate benefits of IT in healthcare but encounter barriers like inadequate resources and training. Motives for IT use include staff training and support. Bivariate regression analysis shows education, working experience, profession, and IT training significantly influence attitudes toward IT adoption. Targeted interventions and policies can enhance IT utilization in the Cape Coast Metropolis, Ghana.

Keywords: health information application, utilization of information application, information technology use, healthcare

Procedia PDF Downloads 54

Authors: Dequn Teng, Tianshuo Yang, Mingrui Wang, Qiuyu Chen, Xiao Wang, Katie Atkinson

Abstract:

Currently, many students are kind of at a loss in the university due to the complex environment within the campus, where every information within the campus is isolated with fewer interactions with each other. However, if the on-campus resources are gathered and combined with the artificial intelligence modelling techniques, there will be a bridge for not only students in understanding themselves, and the teachers will understand students in providing a much efficient approach in education. The objective of this paper is to provide a competency level analysis method, apparatus, electronic equipment, and storage medium. It uses a user’s target competency level analysis model from a plurality of predefined candidate competency level analysis models by obtaining a user’s promotion target parameters, promotion target parameters including at least one of the following parameters: target profession, target industry, and the target company, according to the promotion target parameters. According to the parameters, the model analyzes the user’s ability level, determines the user’s ability level, realizes the quantitative and personalized analysis of the user’s ability level, and helps the user to objectively position his ability level.

Keywords: artificial intelligence, model, university, education, recommendation system, evaluation, job hunting

Procedia PDF Downloads 138

Authors: Isaac Ali Kwasu, Aje Tokan

Abstract:

The research was set to design a manually pedal operated water pump to aid water flow technology for irrigation activities for rural farmers. The development was carried out first by a prototype design to guide the fabrication. All items needed for the fabrication were used for the final product. The machine is operated manually by pedaling. This engages all the parts of the machine into active motion. Energy is generated and transfer finally to the pumping unit which is wired with plastic pipes. The pumping unit which is wired with PVC pipes, both linked to the water source and the reservoir respectively. The (rpm) revolution per minute of the machine is approximated at 3130 depending on the pedaling speed of the user. The machine does not have gear arrangement yet can give high (rpm) for effective performance. The pumping performance of the machine is 125 liters in one minute and can sustain small scale irrigation farming activities and to supplement water management system to sustain crop growth.

Keywords: pump, development, manual, flywheel, sprocket, pulley, machine, v belt, chain, hub, pipe, steel, mechanism, irrigation, prototype, fabrication

Procedia PDF Downloads 199

Authors: Jamie A. Prowse Turner, Jamie I. D. Campbell, Valerie A. Thompson

Abstract:

The objective of the current research was to use a dual-process theory framework to explain these age-related differences in reasoning. Seventy-two older (M = 80.0 years) and 72 younger (M = 24.6 years) adults were given a variety of reasoning tests (i.e., a syllogistic task, base rate task, the Cognitive Reflection Test, and a perspective manipulation), as well as independent tests of capacity (working memory, processing speed, and inhibition), thinking styles, and metacognitive ability, to account for these age-related differences. It was revealed that age-related differences were limited to problems that required Type 2 processing and were related to differences in cognitive capacity, individual difference factors, and strategy choice. Furthermore, older adults’ performance can be improved by reasoning from another’s’ perspective and cannot, at this time, be explained by metacognitive differences between young and older adults. All of these findings fit well within a dual-process theory of reasoning, which provides an integrative framework accounting for previous findings and the findings presented in the current manuscript.

Keywords: aging, dual-process theory, performance, reasoning ability

Procedia PDF Downloads 183

Authors: Mahesh Balan U, Rohith Srinivaas Mohanakrishnan, Venkat Subramanian

Abstract:

Positive and unlabeled learning (PU) has gained more attention in both academic and industry research literature recently because of its relevance to existing business problems today. Yet, there still seems to be some existing challenges in terms of validating the performance of PU learning, as the actual truth of unlabeled data points is still unknown in contrast to a binary classification where we know the truth. In this study, we propose a novel PU learning technique based on the Pseudo-F measure, where we address this research gap. In this approach, we train the PU model to discriminate the probability distribution of the positive and unlabeled in the validation and spy data. The predicted probabilities of the PU model have a two-fold validation – (a) the predicted probabilities of reliable positives and predicted positives should be from the same distribution; (b) the predicted probabilities of predicted positives and predicted unlabeled should be from a different distribution. We experimented with this approach on a credit marketing case study in one of the world’s biggest fintech platforms and found evidence for benchmarking performance and backtested using historical data. This study contributes to the existing literature on semi-supervised learning.

Keywords: PU learning, semi-supervised learning, pseudo f measure, classification

Procedia PDF Downloads 230

Authors: Sajjad Ahmed, Knut Hinkelmann, Flavio Corradini

Abstract:

Fake news detection research is still in the early stage as this is a relatively new phenomenon in the interest raised by society. Machine learning helps to solve complex problems and to build AI systems nowadays and especially in those cases where we have tacit knowledge or the knowledge that is not known. We used machine learning algorithms and for identification of fake news; we applied three classifiers; Passive Aggressive, Naïve Bayes, and Support Vector Machine. Simple classification is not completely correct in fake news detection because classification methods are not specialized for fake news. With the integration of machine learning and text-based processing, we can detect fake news and build classifiers that can classify the news data. Text classification mainly focuses on extracting various features of text and after that incorporating those features into classification. The big challenge in this area is the lack of an efficient way to differentiate between fake and non-fake due to the unavailability of corpora. We applied three different machine learning classifiers on two publicly available datasets. Experimental analysis based on the existing dataset indicates a very encouraging and improved performance.

Keywords: fake news detection, natural language processing, machine learning, classification techniques.

Procedia PDF Downloads 159