Search results for: performance and emission testing

Authors: Amr Emam, Joseph Victor, Mohamed Abd Elghany

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The paper presents the effect of the orbit inclination on the pointing error of the satellite antenna and consequently on its footprint on earth for a typical Ku- band payload system. The performance assessment is examined both theoretically and by means of practical measurements, taking also into account all additional sources of pointing errors, such as East-West station keeping, orbit eccentricity and actual attitude control performance. An implementation and computation of the sinusoidal biases in satellite roll and pitch used to compensate the pointing error of the satellite antenna coverage is studied and evaluated before and after the pointing corrections performed. A method for evaluation of the performance of the implemented biases has been introduced through measuring satellite received level from a tracking 11m and fixed 4.8m transmitting antenna before and after the implementation of the pointing corrections.

Keywords: satellite, inclined orbit, pointing errors, coverage optimization

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Authors: Hameed Rukayat Opeyemi, Pericles Pilidis, Pagone Emanuele

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An infinitesimal increase in performance can have immense reduction in operating and capital expenses in a power generation system. Therefore, constant studies are being carried out to improve both conventional and novel power cycles. Globally, power producers are constantly researching on ways to minimize emission and to collectively downsize the total cost rate of power plants. A substantial spurt of developmental technologies of low carbon cycles have been suggested and studied, however they all have their limitations and financial implication. In the area of carbon abatement in power plants, three major objectives conflict: The cost rate of the plant, Power output and Environmental impact. Since, an increase in one of this parameter directly affects the other. This poses a multi-objective problem. It is paramount to be able to discern the point where improving one objective affects the other. Hence, the need for a Pareto-based optimization algorithm. Pareto-based optimization algorithm helps to find those points where improving one objective influences another objective negatively and stops there. The application of Pareto-based optimization algorithm helps the user/operator/designer make an informed decision. This paper sheds more light on areas that multi-objective optimization has been applied in carbon abatement technologies in the last five years, developments and prospects.

Keywords: gas turbine, low carbon technology, pareto optimal, multi-objective optimization

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Authors: Jisong Zhang, Yinghua Zhao

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The present study investigated the mechanical properties and microstructure of Ultra-High Performance Concrete (UHPC) containing supplementary cementitious materials (SCMs), such as fly ash (FA) and silica fume (SF), and to verify the synergistic effect in the ternary system. On the basis of 30% fly ash replacement, the incorporation of either 10% SF or 20% SF show a better performance compared to the reference sample. The efficiency factor (k-value) was calculated as a synergistic effect to predict the compressive strength of UHPC with these SCMs. The SEM of micrographs and pore volume from BJH method indicate a high correlation with compressive strength. Further, an artificial neural networks model was constructed for prediction of the compressive strength of UHPC containing these SCMs.

Keywords: artificial neural network, fly ash, mechanical properties, ultra-high performance concrete

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Authors: Andrea L. Arnett, Ann T. Packard, Yolanda I. Garces, Kenneth W. Merrell

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Objective: Pathologic response following neoadjuvant chemoradiation (CRT) has been associated with improved overall survival (OS). Conflicting results have been reported regarding the pathologic predictive value of positron emission tomography (PET) response in patients with stage III lung cancer. The aim of this study was to evaluate the correlation between post-treatment PET response and pathologic response utilizing novel FDG-PET parameters. Methods: This retrospective study included patients with non-metastatic, stage IIIA (N2) NSCLC cancer treated with CRT followed by resection. All patients underwent PET prior to and after neoadjuvant CRT. Univariate analysis was utilized to assess correlations between PET response, nodal clearance, pCR, and near-complete pathologic response (defined as the microscopic residual disease or less). Maximal standard uptake value (SUV), standard uptake ratio (SUR) [normalized independently to the liver (SUR-L) and blood pool (SUR-BP)], metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were measured pre- and post-chemoradiation. Results: A total of 44 patients were included for review. Median age was 61.9 years, and median follow-up was 2.6 years. Histologic subtypes included adenocarcinoma (72.2%) and squamous cell carcinoma (22.7%), and the majority of patients had the T2 disease (59.1%). The rate of pCR and near-complete pathologic response within the primary lesion was 28.9% and 44.4%, respectively. The average reduction in SUVmₐₓ was 9.2 units (range -1.9-32.8), and the majority of patients demonstrated some degree of favorable treatment response. SUR-BP and SUR-L showed a mean reduction of 4.7 units (range -0.1-17.3) and 3.5 units (range –1.7-12.6), respectively. Variation in PET response was not significantly associated with histologic subtype, concurrent chemotherapy type, stage, or radiation dose. No significant correlation was found between pathologic response and absolute change in MTV or TLG. Reduction in SUVmₐₓ and SUR were associated with increased rate of pathologic response (p ≤ 0.02). This correlation was not impacted by normalization of SUR to liver versus mediastinal blood pool. A threshold of > 75% decrease in SUR-L correlated with near-complete response, with a sensitivity of 57.9% and specificity of 85.7%, as well as positive and negative predictive values of 78.6% and 69.2%, respectively (diagnostic odds ratio [DOR]: 5.6, p=0.02). A threshold of >50% decrease in SUR was also significantly associated pathologic response (DOR 12.9, p=0.2), but specificity was substantially lower when utilizing this threshold value. No significant association was found between nodal PET parameters and pathologic nodal clearance. Conclusions: Our results suggest that treatment response to neoadjuvant therapy as assessed on PET imaging can be a predictor of pathologic response when evaluated via SUV and SUR. SUR parameters were associated with higher diagnostic odds ratios, suggesting improved predictive utility compared to SUVmₐₓ. MTV and TLG did not prove to be significant predictors of pathologic response but may warrant further investigation in a larger cohort of patients.

Keywords: lung cancer, positron emission tomography (PET), standard uptake ratio (SUR), standard uptake value (SUV)

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Authors: S. Dhib, S. A. Addouche, T. Loukil, A. Elmhamedi

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In this paper, a reverse supply chain network is investigated for a decision making. This decision is surrounded by complex flows of returned products, due to the increasing quantity, the type of returned products and the variety of recovery option products (reuse, recycling, and refurbishment). The most important problem in the reverse logistic network (RLN) is to orient returned products to the suitable type of recovery option. However, returned products orientations from collect sources to the recovery disposition have not well considered in performance model. In this study, we propose a performance model for designing a network configuration on reverse logistics. Conceptual and analytical models are developed with taking into account operational, economic and environmental factors on designing network.

Keywords: reverse logistics, network design, performance model, open loop configuration

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Authors: Navonil Hazra

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The paper discusses how and why aphasia can be understood as the language of nonverbal communication in musical performance and also looks for the elements that are required to classify it as a nonverbal language. Since music is regarded as a nonverbal medium that cannot be engaged in any language, it is concerned about how aphasia might be called the language of nonverbalization. The paper also talks about how it portrays the magnificence of a performance, and how it expresses its likings or dislikes. Regarding the reasons for aphasia, the paper talks about the seizure factor and elucidates on seizure subjects as well. Furthermore, it discusses collective seizures and individual seizures. It also tries to consider aphasia as a-posteriori rather than a-priori looking at it from the lens of ‘Pure Reason’. Along with aphasia, the paper tries to make a critique of silence and the possibilities of looking at silence differently, also looking at the ontology of silence and sound. This paper also critically examines silence and the significance of gestures in performance. It also investigates whether gestures are accompanied by silence, establishing the notion of agential silence. This paper also talks about the place and role of memory in the formulation and analysis of a performance, as well as the plaguing and reclamation of memory, how memory alters the linear course of time and taunts us to look for alternative models of temporalities. This paper discusses the concept of 'auditory labour', with active and passive listening.

Keywords: aphasia, gestures, memory, silence

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Authors: Somsak Klaysung

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This study aims to investigate the comparison of brands equity between Samsung and Apple from students of Suan Sunandha Rajabhat University. The research method will using quantitative research, data was collected by questionnaires distributed to communication of arts students in the faculty of management science of Suan Sunandha Rajabhat University for 100 samples by purposive sampling method. Data was analyzed by descriptive statistic including percentage, mean, standard deviation and inferential statistic is t-test for hypothesis testing. The results showed that brands equity between Apple and Samsung brand have the ability to recognize brand from the customer by perceived value of the uniqueness of brand and recall when in a situation that must be purchased (Salience), which is the lowest level in branding and consumers can recognize the capacity of the product (Judgment) and opinions about the quality and reliability when it comes to mobile phones Apple and Samsung brand are not different.

Keywords: Apple and Samsung brand, brand equity, judgment, performance, resonance, salience

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Authors: Xueying Zhao, Ke Ma, Hui Li, Yu Cao, Fan Yang, Qingwen Xu, Wenbin Liu

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Massively parallel sequencing (MPS) technologies allow high-throughput sequencing analyses with a relatively affordable price and have gradually been applied to forensic casework. MPS technology identifies short tandem repeat (STR) loci based on sequence so that repeat motif variation within STRs can be detected, which may help one to infer the origin of the mutation in some cases. Here, we report on one case with one three-step mismatch (D18S51) in family trios based on both capillary electrophoresis (CE) and MPS typing. The alleles of the alleged father (AF) are [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₁₅. The mother’s alleles are [AGAA]₁₉ and [AGAA]₉AGGA[AGAA]₃. The questioned child’s (QC) alleles are [AGAA]₁₉ and [AGAA]₁₂. Given that the sequence variants in repeat regions of AF and mother are not observed in QC’s alleles, the QC’s allele [AGAA]₁₂ was likely inherited from the AF’s allele [AGAA]₁₅ by loss of three repeat [AGAA]. Besides, two new alleles of D18S51 in this study, [AGAA]₁₇AGAG[AGAA]₃ and [AGAA]₉AGGA[AGAA]₃, have not been reported before. All the results in this study were verified using Sanger-type sequencing. In summary, the MPS typing method can offer valuable information for forensic genetics research and play a promising role in paternity testing.

Keywords: family trios analysis, forensic casework, ion torrent personal genome machine (PGM), massively parallel sequencing (MPS)

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Authors: Zunaira Zaman, David Bohannon

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This study explores the application of machine learning (ML) for detecting security vulnerabilities in source code. The research aims to assist organizations with large application portfolios and limited security testing capabilities in prioritizing security activities. ML-based approaches offer benefits such as increased confidence scores, false positives and negatives tuning, and automated feedback. The initial approach using natural language processing techniques to extract features achieved 86% accuracy during the training phase but suffered from overfitting and performed poorly on unseen datasets during testing. To address these issues, the study proposes using the abstract syntax tree (AST) for Java and C++ codebases to capture code semantics and structure and generate path-context representations for each function. The Code2Vec model architecture is used to learn distributed representations of source code snippets for training a machine-learning classifier for vulnerability prediction. The study evaluates the performance of the proposed methodology using two datasets and compares the results with existing approaches. The Devign dataset yielded 60% accuracy in predicting vulnerable code snippets and helped resist overfitting, while the Juliet Test Suite predicted specific vulnerabilities such as OS-Command Injection, Cryptographic, and Cross-Site Scripting vulnerabilities. The Code2Vec model achieved 75% accuracy and a 98% recall rate in predicting OS-Command Injection vulnerabilities. The study concludes that even partial AST representations of source code can be useful for vulnerability prediction. The approach has the potential for automated intelligent analysis of source code, including vulnerability prediction on unseen source code. State-of-the-art models using natural language processing techniques and CNN models with ensemble modelling techniques did not generalize well on unseen data and faced overfitting issues. However, predicting vulnerabilities in source code using machine learning poses challenges such as high dimensionality and complexity of source code, imbalanced datasets, and identifying specific types of vulnerabilities. Future work will address these challenges and expand the scope of the research.

Keywords: code embeddings, neural networks, natural language processing, OS command injection, software security, code properties

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Authors: Antonina Semakova, Karim Mynbaev, Nikolai Bazhenov, Anton Chernyaev, Sergei Kizhaev, Nikolai Stoyanov

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At present, heterostructures are used for fabrication of almost all types of optoelectronic devices. Our research focuses on the optoelectronic properties of InAs(Sb) solid solutions that are widely used in fabrication of light emitting diodes (LEDs) operating in middle wavelength infrared range (MWIR). This spectral range (2-6 μm) is relevant for laser diode spectroscopy of gases and molecules, for systems for the detection of explosive substances, medical applications, and for environmental monitoring. The fabrication of MWIR LEDs that operate efficiently at room temperature is mainly hindered by the predominance of non-radiative Auger recombination of charge carriers over the process of radiative recombination, which makes practical application of LEDs difficult. However, non-radiative recombination can be partly suppressed in quantum-well structures. In this regard, studies of such structures are quite topical. In this work, electroluminescence (EL) of LED heterostructures based on InAs(Sb) epitaxial films with the molar fraction of InSb ranging from 0 to 0.09 and multi quantum-well (MQW) structures was studied in the temperature range 4.2-300 K. The growth of the heterostructures was performed by metal-organic chemical vapour deposition on InAs substrates. On top of the active layer, a wide-bandgap InAsSb(Ga,P) barrier was formed. At low temperatures (4.2-100 K) stimulated emission was observed. As the temperature increased, the emission became spontaneous. The transition from stimulated emission to spontaneous one occurred at different temperatures for structures with different InSb contents in the active region. The temperature-dependent carrier lifetime, limited by radiative recombination and the most probable Auger processes (for the materials under consideration, CHHS and CHCC), were calculated within the framework of the Kane model. The effect of various recombination processes on the carrier lifetime was studied, and the dominant role of Auger processes was established. For MQW structures quantization energies for electrons, light and heavy holes were calculated. A characteristic feature of the experimental EL spectra of these structures was the presence of peaks with energy different from that of calculated optical transitions between the first quantization levels for electrons and heavy holes. The obtained results showed strong effect of the specific electronic structure of InAsSb on the energy and intensity of optical transitions in nanostructures based on this material. For the structure with MQWs in the active layer, a very weak temperature dependence of EL peak was observed at high temperatures (>150 K), which makes it attractive for fabricating temperature-resistant gas sensors operating in the middle-infrared range.

Keywords: Electroluminescence, InAsSb, light emitting diode, quantum wells

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Authors: Baladitya Swaika, Rahul Khatry

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Computer Adaptive Tests (CATs) is one of the most efficient ways for testing the cognitive abilities of students. CATs are based on Item Response Theory (IRT) which is based on item selection and ability estimation using statistical methods of maximum information selection/selection from posterior and maximum-likelihood (ML)/maximum a posteriori (MAP) estimators respectively. This study aims at combining both classical and Bayesian approaches to IRT to create a dataset which is then fed to a neural network which automates the process of ability estimation and then comparing it to traditional CAT models designed using IRT. This study uses python as the base coding language, pymc for statistical modelling of the IRT and scikit-learn for neural network implementations. On creation of the model and on comparison, it is found that the Neural Network based model performs 7-10% worse than the IRT model for score estimations. Although performing poorly, compared to the IRT model, the neural network model can be beneficially used in back-ends for reducing time complexity as the IRT model would have to re-calculate the ability every-time it gets a request whereas the prediction from a neural network could be done in a single step for an existing trained Regressor. This study also proposes a new kind of framework whereby the neural network model could be used to incorporate feature sets, other than the normal IRT feature set and use a neural network’s capacity of learning unknown functions to give rise to better CAT models. Categorical features like test type, etc. could be learnt and incorporated in IRT functions with the help of techniques like logistic regression and can be used to learn functions and expressed as models which may not be trivial to be expressed via equations. This kind of a framework, when implemented would be highly advantageous in psychometrics and cognitive assessments. This study gives a brief overview as to how neural networks can be used in adaptive testing, not only by reducing time-complexity but also by being able to incorporate newer and better datasets which would eventually lead to higher quality testing.

Keywords: computer adaptive tests, item response theory, machine learning, neural networks

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Authors: Harshita Raj, Joydeep Ghosh, Rakesh L. Tanna, Prabal K. Chattopadhyay, K. A. Jadeja, Sharvil Patel, Kaushal M. Patel, Narendra C. Patel, S. B. Bhatt, V. K. Panchal, Chhaya Chavda, C. N. Gupta, D. Raju, S. K. Jha, J. Raval, S. Joisa, S. Purohit, C. V. S. Rao, P. K. Atrey, Umesh Nagora, R. Manchanda, M. B. Chowdhuri, Nilam Ramaiya, S. Banerjee, Y. C. Saxena

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Efficient gas fueling is a critical aspect that needs to be mastered in order to maintain plasma density, to carry out fusion. This requires a fair understanding of fuel recycling in order to optimize the gas fueling. In Aditya tokamak, multiple gas puffs are used in a precise and controlled manner, for hydrogen fueling during the flat top of plasma discharge which has been instrumental in achieving discharges with enhanced density as well as energy confinement time. Following each gas puff, we observe peaks in temporal profile of Hα emission, Soft X-ray (SXR) and chord averaged electron density in a number of discharges, indicating efficient gas fueling. Interestingly, Hα temporal profile exhibited an additional peak following the peak corresponding to each gas puff. These additional peak Hα appeared in between the two gas puffs, indicating the presence of a secondary hydrogen source apart from the gas puffs. A thorough investigation revealed that these secondary Hα peaks coincide with Hard X- ray bursts which come from the interaction of runaway electrons with vessel limiters. This leads to consider that the runaway electrons (REs), which hit the wall, in turn, bring out the absorbed hydrogen and oxygen from the wall and makes the interaction of REs with limiter a secondary hydrogen source. These observations suggest that runaway electron induced recycling should also be included in recycling particle source in the particle balance calculations in tokamaks. Observation of two Hα peaks associated with one gas puff and their roles in enhancing and maintaining plasma density in Aditya tokamak will be discussed in this paper.

Keywords: fusion, gas fueling, recycling, Tokamak, Aditya

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Authors: Pedro Dias, Lurdes Verissimo, Maria Joao Baptista, Ana Pinheiro, Patricia Oliveira-Silva, Sofia Serra, Daniela Coimbra

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To achieve a high standard in performance, a musician must be well in all aspects of health (physical, mental and social). Anxiety in performance is related to the high level of coordination and skill needed in performance, as well as to the public evaluation of the performer. It affects some key elements of performance, such as concentration, memory, motor coordination, and relaxation. This work presents two studies focused on the adaptation and evaluation of the psychometric properties of the Music Performance Anxiety Inventory (MPAI-A) in young Portuguese music students. The first study was conducted with a sample of 161 adolescent music students, who responded to the Portuguese version of this instrument, and to the State-Trait Anxiety Inventory for Children (STAIC-c2). Validity and reliability were examined, and this measure revealed robust psychometric properties in this sample. The second study aimed to adapt the MPAI to a younger population (one hundred 8-10 years-old music students). Again, the MPAI and the STAIC c-2 were used in this study. Exploratory factor analysis, correlations, and internal consistency were used to evaluate the final children version of the instrument (MPAI-C), presenting a different factor structure compared to the adolescent version (10 items organized in 2 factors) and high levels of reliability and convergent validity.

Keywords: anxiety, assessment, children and adolescents, music performance

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Authors: A. Yazdanmehr, H. Jahed

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Being made with the lightest commercially available industrial metal, Magnesium (Mg) alloys are of interest for light-weighting. Expanding their application to different material processing methods requires Mg properties at large strains. Several room-temperature processes such as shot and laser peening and hole cold expansion need compressive large strain data. Two methods have been proposed in the literature to obtain the stress-strain curve at high strains: 1) anti-buckling guides and 2) small cubic samples. In this paper, an anti-buckling fixture is used with the help of digital image correlation (DIC) to obtain the compression-tension (C-T) of AZ31B-H24 rolled sheet at large strain values of up to 10.5%. The effect of the anti-bucking fixture on stress-strain curves is evaluated experimentally by comparing the results with those of the compression tests of cubic samples. For testing cubic samples, a new fixture has been designed to increase the accuracy of testing cubic samples with DIC strain measurements. Results show a negligible effect of anti-buckling on stress-strain curves, specifically at high strain values.

Keywords: large strain, compression-tension, loading-unloading, Mg alloys

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Authors: Aissa Hanifi

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People across different world societies are using information and communication technology (ICT) for different purposes. Unfortunately, in contemporary societies, some people have little access to ICT and thus cannot have effective participation in society compared with those who have better access. The purpose of this study is to test the impact of ICTs on university life in general and students' performance in particular. The study relied on an online survey questionnaire that was administered to 30 undergraduate students at Chef University. The findings of the survey revealed that there is still an important number of students who do not have easy access to ICT. Such limited access to ICTs is attributed to varied factors. Some students live in rural areas, where due to the poor internet coverage, they face difficulties in competing with students who live in urban areas with better ICT access. The lack of ICT access has hindered the students' university performance in general and their language skills, and the exchange of information with teachers and classmates.

Keywords: access, communication, ICT, performance, technology

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Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

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Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

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Authors: L. Chiriatti, H. Hafid, H. R. Mercado-Mendoza, K. L. Apedo, C. Fond, F. Feugeas

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Substituting natural aggregate with recycled aggregate coming from concrete demolition represents a promising alternative to face the issues of both the depletion of natural resources and the congestion of waste storage facilities. However, the crushing process of concrete demolition waste, currently in use to produce recycled concrete aggregate, does not allow the complete separation of natural aggregate from a variable amount of adhered mortar. Given the physicochemical characteristics of the latter, the introduction of recycled concrete aggregate into a concrete mix modifies, to a certain extent, both fresh and hardened concrete properties. As a consequence, the behavior of recycled reinforced concrete members could likely be influenced by the specificities of recycled concrete aggregates. Beyond the mechanical properties of concrete, and as a result of the composite character of reinforced concrete, the bond characteristics at the rebar/concrete interface have to be taken into account in an attempt to describe accurately the mechanical response of recycled reinforced concrete members. Hence, a comparative experimental campaign, including 16 pull-out tests, was carried out. Four concrete mixes with different recycled concrete aggregate content were tested. The main mechanical properties (compressive strength, tensile strength, Young’s modulus) of each concrete mix were measured through standard procedures. A single 14-mm-diameter ribbed rebar, representative of the diameters commonly used in the domain of civil engineering, was embedded into a 200-mm-side concrete cube. The resulting concrete cover is intended to ensure a pull-out type failure (i.e. exceedance of the rebar/concrete interface shear strength). A pull-out test carried out on the 100% recycled concrete specimen was enriched with exploratory acoustic emission measurements. Acoustic event location was performed by means of eight piezoelectric transducers distributed over the whole surface of the specimen. The resulting map was compared to existing data related to natural aggregate concrete. Damage distribution around the reinforcement and main features of the characteristic bond stress/free-end slip curve appeared to be similar to previous results obtained through comparable studies carried out on natural aggregate concrete. This seems to show that the usual bond mechanism sequence (‘chemical adhesion’, mechanical interlocking and friction) remains unchanged despite the addition of recycled concrete aggregate. However, the results also suggest that bond efficiency seems somewhat improved through the use of recycled concrete aggregate. This observation appears to be counter-intuitive with regard to the diminution of the main concrete mechanical properties with the recycled concrete aggregate content. As a consequence, the impact of recycled concrete aggregate content on bond characteristics seemingly represents an important factor which should be taken into account and likely to be further explored in order to determine flexural parameters such as deflection or crack distribution.

Keywords: acoustic emission monitoring, high-bond steel rebar, pull-out test, recycled aggregate concrete

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Authors: Byungmin Cho, Dongchul Lee, Taejin Kim, Minhee Lee

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The procedure for the seismic retrofit of existing buildings includes the seismic evaluation. In the evaluation step, it is assessed whether the buildings have satisfactory performance against seismic load. Based on the results of that, the buildings are upgraded. To evaluate seismic performance of the buildings, it usually goes through the model transformation from elastic analysis to inelastic analysis. However, when the data is not delivered through the interwork, engineers should manually input the data. In this process, since it leads to inaccuracy and loss of information, the results of the analysis become less accurate. Therefore, in this study, the process for the seismic evaluation of existing buildings using structural information modeling is suggested. This structural information modeling makes the work economic and accurate. To this end, it is determined which part of the process could be computerized through the investigation of the process for the seismic evaluation based on ASCE 41. The structural information modeling process is developed to apply to the seismic evaluation using Perform 3D program usually used for the nonlinear response history analysis. To validate this process, the seismic performance of an existing building is investigated.

Keywords: existing building, nonlinear analysis, seismic performance, structural information modeling

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Authors: Mohsen Goodarzi, George Berghorn

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Despite the rapid growth in the number of green building and community development projects, the long-term performance of these projects has not yet been sufficiently evaluated from the users’ points of view. This is partially due to the lack of post-occupancy evaluation tools available for this type of project. In this study, a post-construction evaluation model is developed to evaluate the relationship between the perceived performance and satisfaction of residents in LEED-certified residential buildings and communities. To develop this evaluation model, a primary five-factor model was developed based on the existing models and residential satisfaction theories. Each factor of the model included several measures that were adopted from LEED certification systems such as LEED-BD+C New Construction, LEED-BD+C Multifamily Midrise, LEED-ND, as well as the UC Berkeley’s Center for the Built Environment survey tool. The model included four predictor variables (factors), including perceived building performance (8 measures), perceived infrastructure performance (9 measures), perceived neighborhood design (6 measures), and perceived economic performance (4 measures), and one dependent variable (factor), which was residential satisfaction (6 measures). An online survey was then conducted to collect the data from the residents of LEED-certified residential communities (n=192) and the validity of the model was tested through Confirmatory Factor Analysis (CFA). After modifying the CFA model, 26 measures, out of the initial 33 measures, were retained to enter into a Structural Equation Model (SEM) and to find the relationships between the perceived buildings performance, infrastructure performance, neighborhood design, economic performance and residential Satisfaction. The results of the SEM showed that the perceived building performance was the most influential factor in determining residential satisfaction in LEED-certified communities, followed by the perceived neighborhood design. On the other hand, perceived infrastructure performance and perceived economic performance did not show any significant relationship with residential satisfaction in these communities. This study can benefit green building researchers by providing a model for the evaluation of the long-term performance of these projects. It can also provide opportunities for green building practitioners to determine priorities for future residential development projects.

Keywords: green building, residential satisfaction, perceived performance, confirmatory factor analysis, structural equation modeling

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Authors: Igor Miňo, Lenka Lešková

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Over the past 80 years, open-field method has evolved as a commonly used tool for the analysis of animal behaviour. The study was carried out using 50 kennel-reared purebred puppies of the German Shepherd dog breed. All dogs were tested in 5^th, 7^th, and 9^th week of age. For the purpose of behavioural analysis, an open-field evaluation report was designed prior to testing to ensure the most convenient, rapid, and suitable way to assess selected behavioural patterns in field conditions. Onset of vocalisation, intensity of vocalisation, level of physical activity, response to sound, and overall behaviour was monitored in the study. Correlations between measures of height, weight and chest circumference, and behavioural characteristics in the 5^th, 7^th, and 9^th week of age were not statistically significant. Onset of vocalisation, intensity of vocalisation, level of physical activity and response to sound differed on statistically significant level between 5^th, 7^th, and 9^th week of age. Results suggest that our practical assessment report may be used as an applicable method to evaluate the suitability of service dog puppies for future working roles.

Keywords: dog, behaviour, open-field, testing

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Authors: E. Irankhah, M. Zarif, E. Mazrooei Rad, K. Ghandehari

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Alzheimer's prevalence is on the rise, and the disease comes with problems like cessation of treatment, high cost of treatment, and the lack of early detection methods. The pathology of this disease causes the formation of protein deposits in the brain of patients called plaque amyloid. Generally, the diagnosis of this disease is done by performing tests such as a cerebrospinal fluid, CT scan, MRI, and spinal cord fluid testing, or mental testing tests and eye tracing tests. In this paper, we tried to use the Medial Temporal Atrophy (MTA) method and the Leave One Out (LOO) cycle to extract the statistical properties of the three Fz, Pz, and Cz channels of ERP signals for early diagnosis of this disease. In the process of CT scan images, the accuracy of the results is 81% for the healthy person and 88% for the severe patient. After the process of ERP signaling, the accuracy of the results for a healthy person in the delta band in the Cz channel is 81% and in the alpha band the Pz channel is 90%. In the results obtained from the signal processing, the results of the severe patient in the delta band of the Cz channel were 89% and in the alpha band Pz channel 92%.

Keywords: Alzheimer's disease, image and signal processing, LOO cycle, medial temporal atrophy

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Authors: Daodu Joshua Rotimi

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This study investigated the Efficacy of Self-Assessment Metacognitive Strategy on Academic performance in Energy Concepts among Upper Basic Science Students in Ankpa, Kogi State, Nigeria. The research design adopted for the study was a Quasi-experimental control group design which employed a pretest, posttest of the experimental and control groups. The population of the study consisted of one hundred and twenty-four (124) JSSII Students; sixty-five (65) for the experimental group and (59) for the control group. The instrument used for the study was the Energy Concept Performance Test (ECPT), with a reliability coefficient of 0.80. Two research questions were answered using descriptive statistics of mean and standard deviation, while two hypotheses were tested using a t-test at P≤0.05 level of significance. The findings of the study revealed that the use of the Self-Assessment Metacognitive Strategy has a positive effect on students’ performance in energy concepts among upper Basic Science Students leading to high academic performance; also, there is no significant difference in the mean Academic Performance scores between Male and Female students taught Energy Concept using Self-Assessment Metacognitive Strategy. Based on the research findings, recommendations were made, which include that Secondary school teachers should be encouraged the use Self-Assessment Metacognitive strategy so as to make the learning process attractive, interactive and enriching to the learners.

Keywords: metacognition, self-assessment, performance, efficacy

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Authors: Huilan Yao, Huaixin Zhang

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Simulations of the transition flow of model propellers are important for predicting hydrodynamic performance and studying scale effects. In this paper, the transition flow of a model propeller under different loadings are simulated using a transition model provided by STAR-CCM+, and the influence of turbulence intensity (TI) on the transition, especially friction and pressure components of propeller performance, was studied. Before that, the transition model was applied to simulate the transition flow of a flat plate and an airfoil. Predicted transitions agree well with experimental results. Then, the transition model was applied for propeller simulations in open water, and the influence of TI was studied. Under the heavy and moderate loadings, thrust and torque of the propeller predicted by the transition model (different TI) and two turbulence models are very close and agree well with measurements. However, under the light loading, only the transition model with low TI predicts the most accurate results. Above all, the friction components of propeller performance predicted by the transition model with different TI have obvious difference.

Keywords: transition flow, model propellers, hydrodynamic performance, numerical simulation

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Authors: Prem Singh, Jagdeep Singh

Abstract:

In an attempt to investigate the performance of single basin solar still for climate conditions of Ludhiana a single basin solar still was designed, fabricated and tested. The energy balance equations for various parts of the still are solved by Gauss-Seidel iteration method. Computer model was made and experimentally validated. The validated computer model was used to estimate the annual distillation yield and performance ratio of the still for Ludhiana. The Theoretical and experimental distillation yield were 4318.79 ml and 3850 ml, respectively for the typical day. The predicted distillation yield was 12.5% higher than the experimental yield. The annual distillation yield per square meter aperture area and annual performance ratio for single basin solar still is 1095 liters and 0.43 liters, respectively. The payback period for micro-stepped solar still is 2.5 years.

Keywords: solar distillation, solar still, single basin, still

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Authors: Melake Kuflom

Abstract:

European power networks involve the use of multiple overhead transmission lines to construct a highly duplicated system that delivers reliable and stable electrical energy to the distribution level. The transmission line protection applied in the existing GB transmission network are normally independent unit differential and time stepped distance protection schemes, referred to as main-1 & main-2 respectively, with overcurrent protection as a backup. The increasing penetration of renewable energy sources, commonly referred as “weak sources,” into the power network resulted in the decline of fault level. Traditionally, the fault level of the GB transmission network has been strong; hence the fault current contribution is more than sufficient to ensure the correct operation of the protection schemes. However, numerous conventional coal and nuclear generators have been or about to shut down due to the societal requirement for CO2 emission reduction, and this has resulted in a reduction in the fault level on some transmission lines, and therefore an adaptive transmission line protection is required. Generally, greater utilization of renewable energy sources generated from wind or direct solar energy results in a reduction of CO2 carbon emission and can increase the system security and reliability but reduces the fault level, which has an adverse effect on protection. Consequently, the effectiveness of conventional protection schemes under low fault levels needs to be reviewed, particularly for future GB transmission network operating scenarios. The proposed paper will evaluate the transmission line challenges under high penetration of renewable energy sources andprovides alternative viable protection solutions based on the problem observed. The paper will consider the assessment ofrenewable energy sources (RES) based on a fully rated converter technology. The DIgSILENT Power Factory software tool will be used to model the network.

Keywords: fault level, protection schemes, relay settings, relay coordination, renewable energy sources

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Authors: Shima Soltanzadeh, Mohammad Hosain Fazel Zarandi, Mojtaba Barzegar Astanjin

Abstract:

Diagnosis of male infertility by the laboratory tests is expensive and, sometimes it is intolerable for patients. Filling out the questionnaire and then using classification method can be the first step in decision-making process, so only in the cases with a high probability of infertility we can use the laboratory tests. In this paper, we evaluated the performance of four classification methods including naive Bayesian, neural network, logistic regression and fuzzy c-means clustering as a classification, in the diagnosis of male infertility due to environmental factors. Since the data are unbalanced, the ROC curves are most suitable method for the comparison. In this paper, we also have selected the more important features using a filtering method and examined the impact of this feature reduction on the performance of each methods; generally, most of the methods had better performance after applying the filter. We have showed that using fuzzy c-means clustering as a classification has a good performance according to the ROC curves and its performance is comparable to other classification methods like logistic regression.

Keywords: classification, fuzzy c-means, logistic regression, Naive Bayesian, neural network, ROC curve

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Authors: Sherine Farouk, Fauzia Jabeen

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The purpose of this study is to examine the role played by ethical climate and CSR on organizational performance in public sector organizations. In particular, the research will shed light on the link between formalized ethical procedures and employee responses including corporate social responsibility, and organizational performance among public sector employees. Data was collected from 425 employees working in public sector organizations in Abu Dhabi, the capital of United Arab Emirates. Structural Equation Modeling will be used to test the proposed hypotheses. The paper contributes to the literature by being one of the first to study CSR and ethical climate within a Middle Eastern context, and will offer important implications for theory and practice.

Keywords: corporate social responsibility, ethical climate, organizational performance, United Arab Emirates

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Authors: Ibrahim Bashir, Yahaya Y. Yusuf

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The ongoing shift towards Industry 4.0 represents a critical growth factor in the industrial enterprise, where the digital transformation of industries is increasingly seen as a crucial element for competitiveness. This transformation holds substantial potential, yet its full benefits have yet to be realized due to the fragmented approach to introducing Industry 4.0 technologies. Therefore, this pilot study aims to explore the individual and collective impact of Industry 4.0 technologies and digital transformation on organizational performance. Data were collected through a questionnaire-based survey across 51 companies in the manufacturing industry in the United Kingdom. The correlations and multiple linear regression analyses were conducted to assess the relationship and impact between the variables in the study. The results show that Industry 4.0 and digital transformation positively influence organizational performance and that Industry 4.0 technologies positively influence digital transformation. The results of this pilot study indicate that the implementation of Industry 4.0 technology is vital for increasing organizational performance; however, their roles differ largely. The differences are manifest in how the types of Industry 4.0 technologies correlate with how organizations integrate digital technologies into their operations. Hence, there is a clear indication of a strong correlation between Industry 4.0 technology, digital transformation, and organizational performance. Consequently, our study presents numerous pertinent implications that propel the theory of I4.0, digital business transformation (DBT), and organizational performance forward, as well as guide managers in the manufacturing sector.

Keywords: industry 4.0 technologies, digital transformation, digital integration, organizational performance

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Authors: Hasnizan Aksah, Adi Irfan Che Ani

Abstract:

Refurbished historic government buildings should perform as intended to support the organization’s goals that enhance occupant satisfaction. However, these buildings may have issues associated with functional performance evaluation. The aim of this study is to develop a Post Occupancy Evaluation (POE) sustainability assessment tool for functional performance evaluation of refurbished historic government buildings. Developing an assessment tool requires a strategic methodology for a logical and cohesive tool that incorporating relevant theories and practical experiences. In this study, mixed method approaches use to collect all necessary data to achieve the objectives of this study. The design of sampling involves are interviews and survey questionnaires to relevant professionals in order to evaluate the criteria and problem encircled in functional performance evaluation. Then, the involvement of expert panels is required in establishing the assessment tool. During the process of investigation on the functional performance criteria, it was discovered that is seen to be critical in aspects of comfort, safety, and services. The proposed assessment tool has a significant role in providing opportunities for the improvement of building performance especially on functional performance for the future historic government building refurbishment project. It is hoped that the tool developed from this study will give benefits to related professionals, public agencies, local municipality, and relevant interested parties in historic building management.

Keywords: refurbished historic government buildings, functional performance, Post Occupancy Evaluation, sustainability

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Authors: Ayesha Anjum, Arbaz Basha

Abstract:

Active Galactic Nuclei (AGN) are the actively accreting centers of the galaxies that host supermassive black holes. AGN emits radiation in all wavelengths and also shows variability across all the wavelength bands. The analysis of flux variability tells us about the morphology of the site of emission radiation. Some of the major classifications of AGN are (a) Blazars, with featureless spectra. They are subclassified as BLLacertae objects, Flat Spectrum Radio Quasars (FSRQs), and others; (b) Seyferts with prominent emission line features are classified into Broad Line, Narrow Line Seyferts of Type 1 and Type 2 (c) quasars, and other types. Sloan Digital Sky Survey (SDSS) is an optical telescope based in Mexico that has observed and classified billions of objects based on automated photometric and spectroscopic methods. A sample of blazars is obtained from the third Fermi catalog. For variability analysis, we searched for light curves for these objects in Wide-Field Infrared Survey Explorer (WISE) and Near Earth Orbit WISE (NEOWISE) in two bands: W1 (3.4 microns) and W2 (4.6 microns), reducing the final sample to 256 objects. These objects are also classified into 155 BLLacs, 99 FSRQs, and 2 Narrow Line Seyferts, namely, PMNJ0948+0022 and PKS1502+036. Mid-infrared variability studies of these objects would be a contribution to the literature. With this as motivation, the present work is focused on studying a final sample of 256 objects in general and the Seyferts in particular. Owing to the fact that the classification is automated, SDSS has miclassified these objects into quasars, galaxies, and stars. Reasons for the misclassification are explained in this work. The variability analysis of these objects is done using the method of flux amplitude variability and excess variance. The sample consists of observations in both W1 and W2 bands. PMN J0948+0022 is observed between MJD from 57154.79 to 58810.57. PKS 1502+036 is observed between MJD from 57232.42 to 58517.11, which amounts to a period of over six years. The data is divided into different epochs spanning not more than 1.2 days. In all the epochs, the sources are found to be variable in both W1 and W2 bands. This confirms that the object is variable in mid-infrared wavebands in both long and short timescales. Also, the sources are observed for color variability. Objects either show a bluer when brighter trend (BWB) or a redder when brighter trend (RWB). The possible claim for the object to be BWB (present objects) is that the longer wavelength radiation emitted by the source can be suppressed by the high-energy radiation from the central source. Another result is that the smallest radius of the emission source is one day since the epoch span used in this work is one day. The mass of the black holes at the centers of these sources is found to be less than or equal to 108 solar masses, respectively.

Keywords: active galaxies, variability, Seyfert galaxies, SDSS, WISE

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