Search results for: threshold selection

Authors: Selvam M., Vadthya Poornachandar, Surender Singh

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These Reclaimed Asphalt Pavement (RAP) aggregates are generally dumped in the open area after the demolition of Asphalt Pavements. The utilization of RAP aggregates in cement concrete pavements may provide several socio-economic-environmental benefits and could embrace the circular economy. The cross recycling of RAP aggregates in the concrete pavement could reduce the consumption of virgin aggregates and saves the fertile land. However, the structural, as well as functional properties of RAP-concrete could be significantly lower than the conventional Pavement Quality Control (PQC) pavements. This warrants judicious selection of RAP fraction (coarse and fine aggregates) along with the accurate proportion of the same for PQC highways. Also, the selection of the RAP fraction and its proportion shall not be solely based on the mechanical properties of RAP-concrete specimens but also governed by the structural and functional behavior of the pavement system. In this study, an effort has been made to predict the optimum RAP fraction and its corresponding proportion for cement concrete pavements by considering the low-volume and high-volume roads. Initially, the effect of inclusions of RAP on the fresh and mechanical properties of concrete pavement mixes is mapped through an extensive literature survey. Almost all the studies available to date are considered for this study. Generally, Indian Roads Congress (IRC) methods are the most widely used design method in India for the analysis of concrete pavements, and the same has been considered for this study. Subsequently, fatigue damage analysis is performed to evaluate the required safe thickness of pavement slab for different fractions of RAP (coarse RAP). Consequently, the performance of RAP-concrete is predicted by employing the AASHTO-1993 model for the following distresses conditions: faulting, cracking, and smoothness. The performance prediction and total cost analysis of RAP aggregates depict that the optimum proportions of coarse RAP aggregates in the PQC mix are 35% and 50% for high volume and low volume roads, respectively.

Keywords: concrete pavement, RAP aggregate, performance prediction, pavement design

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Authors: Manju Kanu, Subrata Sinha, Surabhi Johari

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Viral proteins of Ebola viruses belong to one of the best studied viruses; however no effective prevention against EBOV has been developed. Epitope-based vaccines provide a new strategy for prophylactic and therapeutic application of pathogen-specific immunity. A critical requirement of this strategy is the identification and selection of T-cell epitopes that act as vaccine targets. This study describes current methodologies for the selection process, with Ebola virus as a model system. Hence great challenge in the field of ebola virus research is to design universal vaccine. A combination of publicly available bioinformatics algorithms and computational tools are used to screen and select antigen sequences as potential T-cell epitopes of supertypes Human Leukocyte Antigen (HLA) alleles. MUSCLE and MOTIF tools were used to find out most conserved peptide sequences of viral proteins. Immunoinformatics tools were used for prediction of immunogenic peptides of viral proteins in zaire strains of Ebola virus. Putative epitopes for viral proteins (VP) were predicted from conserved peptide sequences of VP. Three tools NetCTL 1.2, BIMAS and Syfpeithi were used to predict the Class I putative epitopes while three tools, ProPred, IEDB-SMM-align and NetMHCII 2.2 were used to predict the Class II putative epitopes. B cell epitopes were predicted by BCPREDS 1.0. Immunogenic peptides were identified and selected manually by putative epitopes predicted from online tools individually for both MHC classes. Finally sequences of predicted peptides for both MHC classes were looked for common region which was selected as common immunogenic peptide. The immunogenic peptides were found for viral proteins of Ebola virus: epitopes FLESGAVKY, SSLAKHGEY. These predicted peptides could be promising candidates to be used as target for vaccine design.

Keywords: epitope, b cell, immunogenicity, ebola

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Authors: Muktadir Ahmed, Sayed Akhlakur Rahaman, Mridha Shihab Mahmud

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The parents of Bangladesh have scarcity of knowledge about children play. Most of them do not know which toys are perfect for their children. Appropriate toys for playing is one of the most significant parts of children development from early age, besides for proper amelioration of children’s mental growth and brain capacities, toys play an emergent role. So selection of proper toy for children is very important. A toy forms the sagacity of a child and instructs child’s attitude. In this era of globalization to keep pace with everything children toys are also going forward but in a deleterious way. Maximum toys are now battery-driven and for this psychological developments of children are not increasing in effective way; therefore, pedagogical toys are proper selection. This type of toy inspires the wisdom and helps a child to reveal himself/herself. Pedagogical toys are attractive to children and help to stimulate their imagination. Pedagogical toys help them to build senso-motoric skills and hand-eye coordination. In this study, some children divided into two groups, one group played with pedagogical toys and another group played with conventional toys. This study is going to exhibit the difference between pedagogical and conventional toys for kids. The main aim of this study is to reveal the potency of pedagogical toy for children. To implement this study two Daycare Centers (DCC) Projapoti 1 & 3 of Mymensingh city had chosen. Every DCC having 1.5-6 years old children but for this study 2-5 years old children had been selected. The children of Projapoti-1 played with pedagogical toys and the children of Projapoti-2 played with conventional toys. After 6 weeks of study, the children of Projapoti-1 proved that they have improved their skills more than those children of Projapoti-3 who were playing with conventional toys. The children of Projapoti-1 have developed their touch sensation, muscular movement, imitation power, hand-eye coordination whereas the children of Projapoti-3 have only developed their muscular movement fairly (while running after battery driven toys) which is not better than those children of Projapoti-1. They cannot imitate like the children of Projapoti-1. They just had fun from playing virtual games, battery driven toys, watching cartoons etc. Actually, it is not possible to develop a child’s brain without pedagogical toy.

Keywords: brain development, mental growth, pedagogical toys, play for children

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Authors: Zhaoming Yang, Qi Xiang, Qian He, Michael Havbro Faber, Enrico Zio, Huai Su, Jinjun Zhang

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Resilience is one of the key factors for system safety assessment and optimization, and resilience studies of natural gas pipeline systems (NGPS), especially in terms of process descriptions, are still being explored. Based on the three main stages, which are function loss process, recovery process, and waiting process, the paper has built functions and models which are according to the practical characteristics of NGPS and mainly analyzes the characteristics of deterministic interruptions. The resilience of NGPS also considers the threshold of the system function or users' satisfaction. The outcomes, which quantify the resilience of NGPS in different evaluation views, can be combined with the max flow and shortest path methods, help with the optimization of extra gas supplies and gas routes as well as pipeline maintenance strategies, the quick analysis of disturbance effects and the improvement of NGPS resilience evaluation accuracy.

Keywords: natural gas pipeline system, resilience, process modeling, deterministic disturbance

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Authors: Jae-Hyun Ro, Jong-Kwang Kim, Chang-Hee Kang, Hyoung-Kyu Song

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In multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, QR decomposition-M algorithm (QRD-M) has suboptimal error performance. However, the QRD-M has still high complexity due to many calculations at each layer in tree structure. To reduce the complexity of the QRD-M, proposed QRD-M modifies existing tree structure by eliminating unnecessary candidates at almost whole layers. The method of the elimination is discarding the candidates which have accumulated squared Euclidean distances larger than calculated threshold. The simulation results show that the proposed QRD-M has same bit error rate (BER) performance with lower complexity than the conventional QRD-M.

Keywords: complexity, MIMO-OFDM, QRD-M, squared Euclidean distance

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Authors: David A. Harness

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Natural evolution of ATP cognitive systems is to meet AI peer review standards. ATP process of axiom selection from Mizar to prove a conjecture would be further refined, as in all human and machine learning, by solving the real world problem of the proposed AI peer review challenge: Determine which conjecture forms the higher confidence level constructive proof between Standard Model of Physics SU(n) lattice gauge group operation vs. present non-standard 4D GEM EOS SU(n) lattice gauge group spatially extended operation in which the photon and electron are the first two trace angular momentum invariants of a gravitoelectromagnetic (GEM) energy momentum density tensor wavetrain integration spin-stress pressure-volume equation of state (EOS), initiated via 32 lines of Mathematica code. Resulting gravitoelectromagnetic spectrum ranges from compressive through rarefactive of the central cosmological constant vacuum energy density in units of pascals. Said self-adjoint group operation exclusively operates on the stress energy momentum tensor of the Einstein field equations, introducing quantization directly on the 4D spacetime level, essentially reformulating the Yang-Mills virtual superpositioned particle compounded lattice gauge groups quantization of the vacuum—into a single hyper-complex multi-valued GEM U(1) × SU(1,3) lattice gauge group Planck spacetime mesh quantization of the vacuum. Thus the Mizar corpus already contains all of the axioms required for relevant DeepMath premise selection and unambiguous formal natural language parsing in context deep learning.

Keywords: automated theorem proving, constructive quantum field theory, information theory, neural networks

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Authors: Nguyen Van Loi, Le Thanh Son, Tran Trung Kien

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The paper deals with the problem of the formation of range profiles (RPs) for an X-band coastal surveillance radar. Two popular methods, the difference operator method, and the window-based method, are reviewed and analyzed via two tests with different datasets. The test results show that although the original window-based method achieves a better performance than the difference operator method, it has three main drawbacks that are the use of 3 or 4 peaks of an RP for creating the windows, the extension of the window size using the power sum of three adjacent cells in the left and the right sides of the windows and the same threshold applied for all types of vessels to finish the formation process of RPs. These drawbacks lead to inaccurate RPs due to the low signal-to-clutter ratio. Therefore, some suggestions are proposed to improve the original window-based method.

Keywords: range profile, difference operator method, window-based method, automatic target recognition

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Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

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Authors: Van Huong Do, Simon Walton, German Amaya, Madeline Batsiokis, Sally Catt, Andrew Taylor-Robinson

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Identification of the most suitable stages of bovine in vitro-derived blastocysts (early, expanded and hatching) prior to vitrification is a straightforward process that facilitates the decision as to which blastocyst stage to use for transfer of fresh and vitrified embryos. Research on in vitro evaluation of suitable stages has shown that the more advanced developmental stage of blastocysts is recommended for fresh embryo transfer while the earlier stage is proposed for embryo transfer following vitrification. There is, however, limited information on blastocyst stages using in vivo assessment. Hence, the aim of the present study was to determine the optimal stage of a blastocyst for vitrification and embryo transfer through a two-step procedure of embryo transfer followed by pregnancy testing at 35, 60 and 90 days of pregnancy. 410 good quality oocytes aspirated by the ovum pick-up technique from 8 donor cows were subjected to in vitro embryo production, vitrification and embryo transfer. Good quality embryos were selected, subjected to vitrification and embryo transfer. Subsequently, 77 vitrified embryos at different blastocyst stages were transferred to synchronised recipient cows. The overall cleavage and blastocyst rates of oocytes were 68.8% and 41.7%, respectively. In addition, the fertility and blastocyst production of 6 bulls used for in vitro fertilization was examined and shown to be statistically different (P<0.05). Results of ongoing pregnancy trials conducted at 35 days, 60 days and 90 days will be discussed. However, preliminary data indicate that individual bulls demonstrate distinctly different fertility performance in vitro. Findings from conception rates would provide a useful tool to aid selection of bovine in vitro-derived embryos for vitrification and embryo transfer in commercial settings.

Keywords: blastocyst, embryo transfer, in vitro-derived embryos, ovum pick-up, vitrification

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Authors: Ali Aydin, Mert Sudagidan, Aysen Coban, Alparslan Kadir Devrim

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Pseudomonas spp. (specifically, P. fluorescens and P. fragi) are considered the principal spoilage microorganisms of refrigerated poultry meats. The higher the level psychrophilic spoilage Pseudomonas spp. on carcasses at the end of processing lead to decrease the shelf life of the refrigerated product. The aim of the study was the identification of psychrophilic Pseudomonas spp. having proteolytic and lipolytic activities from poultry meats by 16S rRNA and rpoB gene sequencing, investigation of protease and lipase related genes and determination of proteolytic activity of Pseudomonas spp. In the of isolation procedure, collected chicken meat samples from local markets and slaughterhouses were homogenized and the lysates were incubated on Standard method agar and Skim Milk agar for selection of proteolytic bacteria and tributyrin agar for selection of lipolytic bacteria at +4 °C for 7 days. After detection of proteolytic and lipolytic colonies, the isolates were firstly analyzed by biochemical tests such as Gram staining, catalase and oxidase tests. DNA gene sequencing analysis and comparison with GenBank revealed that 126 strong enzyme Pseudomonas spp. were identified as predominantly P. fluorescens (n=55), P. fragi (n=42), Pseudomonas spp. (n=24), P. cedrina (n=2), P. poae (n=1), P. koreensis (n=1), and P. gessardi (n=1). Additionally, protease related aprX gene was screened in the strains and it was detected in 69/126 strains, whereas, lipase related lipA gene was found in 9 Pseudomonas strains. Protease activity was determined using commercially available protease assay kit and 5 strains showed high protease activity. The results showed that psychrophilic Pseudomonas strains were present in chicken meat samples and they can produce important levels of proteases and lipases for food spoilage to decrease food quality and safety.

Keywords: Pseudomonas, chicken meat, protease, lipase

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Authors: Mahla Zabet, Navid Zanganeh, Hafez Balavi, Farbod Sharif

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Electrodeposition is a method for applying coatings with uniform thickness on complex objects. A conductive surface can be produced using the electrical current in this method. Carbon nanotubes are known to have high electrical conductivity and mechanical properties. In this report, NH2-multiwalled carbon nanotubes (MWCNTs) were used in epoxy resin with different weight percent. The weight percent of incorporated MWCNTS into the matrix was changed in the range of 0.6-3.6 wt% to obtain a series of electrocoatings. The electrocoats were then applied on steel substrates by a cathodic electrodeposition technique. Scanning electron microscopy (SEM) and optical microscopy were used to characterize the electrocoated films. The results illustrated the increase in conductivity by increasing of MWCNT load. However, at the percolation threshold, throwing power was dropped with increase in recoating ability.

Keywords: electrodeposition, carbon nanotube, electrical conductivity, throwing power

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Authors: Gansukh Erdenedelger, Doljinsuren Sukhbaatar, Trung Dung Dao, Byeong-Kyu Lee, Han Mo Jeong

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Two kinds of carboxylated thermally reduced graphenes (C-TRGs) having different lateral sizes are examined as a Pickering stabilizer in the suspension polymerization of methyl methacrylate. The size and the shape of the prepared composite particles are irregular due to agglomeration, more evidently when the larger C-TRG is used. In addition, C-TRG is distributed not only on the surface but also inside the composite particles. It indicates that the C-TRG alone is not a stable Pickering agent. However, a very small dosage of acrylic acid remedies all these issues, because acrylic acid interacts with C-TRG and synergizes the stabilizing effect. The compression molded composite of the core/shell poly(methyl methacrylate)/C-TRG particles exhibits a very low percolation threshold of electrical conductivity of 0.03 vol%. It demonstrates that the C-TRG shells of the composite particles effectively form a segregated conductive network throughout the composite.

Keywords: pickering, graphene, polymerization, PMMA

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Authors: Valentina Bonetti

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Exergy analysis successfully helps optimizing processes in various sectors. In the built environment, a second-law approach can enhance potential interactions between constructions and their surrounding environment and minimise fossil fuel requirements. Despite the research done in this field in the last decades, practical applications are hard to encounter, and few integrated exergy simulators are available for building designers. Undoubtedly, an obstacle for the diffusion of exergy methods is the strong dependency of results on the definition of its 'reference state', a highly controversial issue. Since exergy is the combination of energy and entropy by means of a reference state (also called "reference environment", or "dead state"), the reference choice is crucial. Compared to other classical applications, buildings present two challenging elements: They operate very near to the reference state, which means that small variations have relevant impacts, and their behaviour is dynamical in nature. Not surprisingly then, the reference state definition for the built environment is still debated, especially in the case of dynamic assessments. Among the several characteristics that need to be defined, a crucial decision for a dynamic analysis is between a fixed reference environment (constant in time) and a variable state, which fluctuations follow the local climate. Even if the latter selection is prevailing in research, and recommended by recent and widely-diffused guidelines, the fixed reference has been analytically demonstrated as the only choice which defines exergy as a proper function of the state in a fluctuating environment. This study investigates the impact of that crucial choice: Fixed or variable reference. The basic element of the building energy chain, the envelope, is chosen as the object of investigation as common to any building analysis. Exergy fluctuations in the building envelope of a case study (a typical house located in a Mediterranean climate) are confronted for each time-step of a significant summer day, when the building behaviour is highly dynamical. Exergy efficiencies and fluxes are not familiar numbers, and thus, the more easy-to-imagine concept of exergy storage is used to summarize the results. Trends obtained with a fixed and a variable reference (outside air) are compared, and their meaning is discussed under the light of the underpinning dynamical energy analysis. As a conclusion, a fixed reference state is considered the best choice for dynamic exergy analysis. Even if the fixed reference is generally only contemplated as a simpler selection, and the variable state is often stated as more accurate without explicit justifications, the analytical considerations supporting the adoption of a fixed reference are confirmed by the usefulness and clarity of interpretation of its results. Further discussion is needed to address the conflict between the evidence supporting a fixed reference state and the wide adoption of a fluctuating one. A more robust theoretical framework, including selection criteria of the reference state for dynamical simulations, could push the development of integrated dynamic tools and thus spread exergy analysis for the built environment across the common practice.

Keywords: exergy, reference state, dynamic, building

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Authors: Nader Al-Rashidi, David Greenhalgh

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Mathematical modelling techniques are now being used by health organizations worldwide to help understand the likely impact that intervention strategies treatment options and combinations of these have on the prevalence and incidence of hepatitis C virus (HCV) in the people who inject drugs (PWID) population. In this poster, we develop a deterministic, compartmental mathematical model to approximate the spread of the HCV in a PWID population that has been divided into two groups by time since onset of injection. The model assumes that after injection needles adopt the most infectious state of their previous state or that of the PWID who last injected with them. Using analytical techniques, we find that the model behaviour is determined by the basic reproductive number R₀, where R₀ = 1 is a critical threshold separating two different outcomes. The disease-free equilibrium is globally stable if R₀ ≤ 1 and unstable if R₀ > 1. Additionally, we make some simulations where have confirmed that the model tends to this endemic equilibrium value with realistic parameter values giving an HCV prevalence.

Keywords: hepatitis C, people who inject drugs, HCV, PWID

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Authors: Benjamin Legros, Jan Fransoo, Oualid Jouini

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This study aims to evaluate street-turn strategies for empty container repositioning in the hinterland. Containers arrive over time at the (importer) consignee, while the demand for containers arises from the (exporter) shipper. A match can be operated between an empty container from the consignee and the load from the shipper. Therefore, we model the system as a double-ended queue with non-zero matching time and a limited number of resources in order to optimize the reposition- ing decisions. We determine the performance measures when the consignee operates using a fixed withholding threshold policy. We show that the matching time mainly plays a role in the matching proportion, while under a certain duration, it only marginally impacts the consignee’s inventory policy and cost per container. Also, the withholding level is mainly determined by the shipper’s production rate.

Keywords: container, double-ended queue, inventory, Markov decision process, non-zero matching time, street-turn

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Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

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Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

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Authors: Setapo Moloi, Jun-Ichiro Giorgos Tsutsumi

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South Africa’s need for the provision of housing within its major city centres, specifically Gauteng Province (GP), is a major concern. Initiatives for converting misused/ unused buildings to suitable housing for residents who work in the city as well as prospective citizens are currently underway, one aspect that is needed currently, is the re-possession of these buildings repurposing, into housing communities for quality low cost mixed density housing and for this process to have minimal strain on existing infrastructure like energy, emission reduction etc. Unfortunately, there are instances in Johannesburg, the country’s economic capital, with 2017 estimates claiming that 700 buildings lay unused or misused due to issues that will be discussed in this paper, these then become hubs for illegal activity and are an unacceptable form of shelter. It can be argued that the provision of inner-city social housing is lacking, but not due to the unavailability of funding or usable land and buildings, but that these assets are not being used appropriately nor to their full potential. Currently the GP government has mandated the re-purposing of all buildings that meet their criteria (structural stability, feasibility, adaptability, etc.) with the intention of inviting interested parties to propose conversions of the buildings into densified social housing. Going forward, the proposed focus is creation of social housing communities within existing buildings which may be retrofitted with sustainable technologies, green design strategies and principles, aiming for the finished buildings to achieve ‘Net-Zero/Positive’ status. A Net-Zero building, according to The Green Building Council of South Africa (GBCSA) is a building which manages to produce resources it needs to function, and reduces wastage, emissions and demand of these resources during its lifespan. The categories which GBCSA includes are carbon, water, waste and ecology, this may include material selection, construction methods, etc.

Keywords: adaptive reuse, conversion, net-zero, social housing, sustainable communities

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Kannapha Amaruchkul

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We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

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Authors: Shumaila Shakoor

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The levels of metal pollution (Pb, Cd, Cu, Zn) were investigated in the leaves of Dalbergia sisso in urban areas of the Sahiwal and Faisalabad City. For this purpose, three habitats were selected for sampling (roads, residential areas and parks). High concentration of metal was found in roadside samples as compared to residential areas and parks. In Sahiwal city the mean concentration of Copper (7.68µgg-¹) Zinc (43.55µgg-¹) and lead (4.79µgg-¹) were detected. Similarly, concentration of Cu, Zn, Pb and Cd in leaves of Faisalabad city ranged from 14.4-11.3µgg-¹, 49.7-49.5µgg-¹,138.7-47.1µgg-¹. Highest concentration of heavy metals was detected in Faisalabad as compared to Sahiwal city and level of heavy metals was below the threshold limits, therefore, the concentration of heavy metals was not high in Dalbergia sissoo.

Keywords: cadmium, copper, lead, zinc

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Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Peter Olasupo Ogunjuyigbe, Sarafa Shittu

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This paper emphasizes the relevance of conjugal relationship and spousal communication towards enhancing men’s involvement in contraceptive use among the Yorubas of South Western Nigeria. An understanding of males influence and the role they play in reproductive decision making can throw better light on mechanisms through which egalitarianness of husband/wife decision making influences contraceptive use. The objective of this study was to investigate how close conjugal relationships can be a good indicator of joint decision making among couples using data derived from a survey conducted in three states of South Western Nigeria. The study sample consisted of five hundred and twenty one (521) male respondents aged 15-59 years and five hundred and forty seven (547) female respondents aged 15-49 years. The study used both quantitative and qualitative approached to elicit information from the respondents. In order that the study would be truly representative of the towns, each of the study locations in the capital cities was divided into four strata: The traditional area, the migrant area, the mixed area (i.e. traditional and migrant), and the elite area. In the rural areas, selection of the respondents was by simple random sampling technique. However, the random selection was made in such a way that all the different parts of the locations were represented. Generally, the data collected were analysed at univariate, bivariate, and multivariate levels. Logistic regression models were employed to examine the interrelationships between male reproductive behaviour, conjugal relationship and contraceptive use. The study indicates that current use of contraceptive is high among this major ethnic group in Nigeria because of the improved level of communication among couples. The problem, however, is that men still have lower exposure rate when it comes to question of family planning information, education and counseling. This has serious implications on fertility regulation in Nigeria.

Keywords: behavior, conjugal, communication, counseling, spouse

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Authors: A. Ozel

Abstract:

The ductile to brittle transition temperature is a very important criterion that is used for selection of materials in some applications, especially in low-temperature conditions. For that reason, in this study transition temperature of as-cast and austempered unalloyed ductile iron in the temperature interval from -60 to +100 degrees C have been investigated. The microstructures of samples were examined by light microscope. The impact energy values obtained from the experiments were found to depend on the austempering time and temperature.

Keywords: Austempered Ductile Iron (ADI), Charpy test, microstructure, transition temperature

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Authors: Milena Gojny-Zbierowska

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In the last decades psychological tests have been gaining in popularity as a method used for evaluating personnel, and they bring consulting companies solid profits rising by up to 10% each year. The market is offering a growing range of tools for the assessment of personality. Tests are used in organizations mainly in the recruitment and selection of staff. This paper is an attempt to initially diagnose the state of the use of psychological tests in Polish companies on the basis of empirical research.

Keywords: psychological tests, personality, content analysis, NEO FFI, big five personality model

Procedia PDF Downloads 344

Authors: Ho-Hsin Lee, Yue-Min Jiang, Shu-Hui Tsai, Jian-Ren Chen, Mei-Yu XU, Wen-Tien Wu

Abstract:

This project presents an AI-based method and system for wound status analysis. The system uses a three-in-one sensor device to analyze wound status, including color, temperature, and a 3D sensor to provide wound information up to 2mm below the surface, such as redness, heat, and blood circulation information. The system has a 90% accuracy rate, requiring only one manual correction in 70% of cases, with a one-second delay. The system also provides an offline application that allows for manual correction of the wound bed range using color-based guidance to estimate wound bed size with 96% accuracy and a maximum of one manual correction in 96% of cases, with a one-second delay. Additionally, AI-assisted wound bed range selection achieves 100% of cases without manual intervention, with an accuracy rate of 76%, while AI-based wound tissue type classification achieves an 85.3% accuracy rate for five categories. The AI system also includes similar case search and expert recommendation capabilities. For AI-assisted wound range selection, the system uses WIFI6 technology, increasing data transmission speeds by 22 times. The project aims to save up to 64% of the time required for human wound record keeping and reduce the estimated time to assess wound status by 96%, with an 80% accuracy rate. Overall, the proposed AI method and system integrate multiple sensors to provide accurate wound information and offer offline and online AI-assisted wound bed size estimation and wound tissue type classification. The system decreases delay time to one second, reduces the number of manual corrections required, saves time on wound record keeping, and increases data transmission speed, all of which have the potential to significantly improve wound care and management efficiency and accuracy.

Keywords: wound status analysis, AI-based system, multi-sensor integration, color-based guidance

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Authors: Farahnaz Karami

Abstract:

Routing is an important, challenging task in mobile ad hoc networks due to node mobility, lack of central control, unstable links, and limited resources. An ant colony has been found to be an attractive technique for routing in Mobile Ad Hoc Networks (MANETs). However, existing swarm intelligence based routing protocols find an optimal path by considering only one or two route selection metrics without considering correlations among such parameters making them unsuitable lonely for routing real time applications. Fuzzy logic combines multiple route selection parameters containing uncertain information or imprecise data in nature, but does not have multipath routing property naturally in order to provide load balancing. The objective of this paper is to design a routing algorithm using fuzzy logic and ant colony that can solve some of routing problems in mobile ad hoc networks, such as nodes energy consumption optimization to increase network lifetime, link failures rate reduction to increase packet delivery reliability and providing load balancing to optimize available bandwidth. In proposed algorithm, the path information will be given to fuzzy inference system by ants. Based on the available path information and considering the parameters required for quality of service (QoS), the fuzzy cost of each path is calculated and the optimal paths will be selected. NS2.35 simulation tools are used for simulation and the results are compared and evaluated with the newest QoS based algorithms in MANETs according to packet delivery ratio, end-to-end delay and routing overhead ratio criterions. The simulation results show significant improvement in the performance of these networks in terms of decreasing end-to-end delay, and routing overhead ratio, and also increasing packet delivery ratio.

Keywords: mobile ad hoc networks, routing, quality of service, ant colony, fuzzy logic

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Authors: Brahim Mahfoud

Abstract:

A three-dimensional (3D) numerical technique is used to investigate the possibility of reducing the price of manufacturing some silicon-based devices, particularly those in which minor temperature gradients can significantly reduce performance. The silicon melt under the magnetic field produces Lorentz force, which can effectively suppress the flow which is caused by temperature gradients. This might allow some silicon-based products, such as solar cells, to be manufactured using a less pure, and hence less expensive. The thermocapillary effect of the silicon melt flow in thin annular pools subjected to an externally induced magnetic field was observed. The results reveal that with a strong enough magnetic field, isothermal lines change form and become concentric circles. As the amplitude of the magnetic field (Ha) grows, the azimuthal velocity and temperature at the free surface reduce, and the asymmetric 3D flow becomes axisymmetric steady when Ha surpasses a threshold value.

Keywords: magnetic field, manufacturing, silicon melt, thermocapillary

Procedia PDF Downloads 58

Authors: Yahia. Kourd, N. Guersi D. Lefebvre

Abstract:

In this paper we propose to study the faults diagnosis in squirrel-cage induction motor using MLP neural networks. We use neural healthy and faulty models of the behavior in order to detect and isolate some faults in machine. In the first part of this work, we have created a neural model for the healthy state using Matlab and a motor located in LGEB by acquirins data inputs and outputs of this engine. Then we detected the faults in the machine by residual generation. These residuals are not sufficient to isolate the existing faults. For this reason, we proposed additive neural networks to represent the faulty behaviors. From the analysis of these residuals and the choice of a threshold we propose a method capable of performing the detection and diagnosis of some faults in asynchronous machines with squirrel cage rotor.

Keywords: faults diagnosis, neural networks, multi-models, squirrel-cage induction motor

Procedia PDF Downloads 612

Authors: S. N. C. M. Dias, Niels Schuetze, Franz Lennartz

Abstract:

The current focus in irrigated agriculture will move from maximizing crop production per unit area towards maximizing the crop production per unit amount of water (water productivity) used. At the same time, inadequate water supply or deficit irrigation will be the only solution to cope with water scarcity in the near future. Soil matric potential based irrigation plays an important role in such deficit irrigated agriculture to grow any crop including rice. Rice as the staple food for more than half of the world population, grows mainly under flooded conditions. It requires more water compared to other upland cereals. A major amount of this water is used in the land preparation and is lost at field level due to evaporation, deep percolation, and seepage. A field experimental study was conducted in the experimental premises of rice research and development institute of Sri Lanka in Kurunegala district to estimate the water productivity of rice under deficit irrigation. This paper presents the feasibility of improving current irrigation management in rice cultivation under water scarce conditions. The experiment was laid out in a randomized complete block design with four different irrigation treatments with three replicates. Irrigation treatments were based on soil matric potential threshold values. Treatment W0 was maintained between 60-80mbars. W1 was maintained between 80-100mbars. Other two dry treatments W2 and W3 were maintained at 100-120 mbar and 120 -140 mbar respectively. The sprinkler system was used to irrigate each plot individually upon reaching the maximum threshold value in respective treatment. Treatments were imposed two weeks after seed establishment and continued until two weeks before physiological maturity. Fertilizer applications, weed management, and other management practices were carried out per the local recommendations. Weekly plant growth measurements, daily climate parameters, soil parameters, soil tension values, and water content were measured throughout the growing period. Highest plant growth and grain yield (5.61t/ha) were observed in treatment W2 followed by W0, W1, and W3 in comparison to the reference yield (5.23t/ha) of flooded rice grown in the study area. Water productivity was highest in W3. Concerning the irrigation water savings, grain yield, and water productivity together, W2 showed the better performance. Rice grown under unsaturated conditions (W2) shows better performance compared to the continuously saturated conditions(W0). In conclusion, soil matric potential based irrigation is a promising practice in irrigation management in rice. Higher irrigation water savings can be achieved in this method. This strategy can be applied to a wide range of locations under different climates and soils. In future studies, higher soil matric potential values can be applied to evaluate the maximum possible values for rice to get higher water savings at minimum yield losses.

Keywords: irrigation, matric potential, rice, water scarcity

Procedia PDF Downloads 182