The Local Volume Mapper (LVM), for the Sloan Digital Sky Survey V, consists of four 16 cm telescopes with three fiber spectrographs in the Las Campanas Observatory in Chile. With the fixed telescopes on optical tables, the Alt-Alt mounted siderostats point and guide targets during spectrograph exposures. We are developing the integrated LVM instrument control software. Considering international travel restrictions caused by the COVID-19 pandemic in 2021, we decided to make a simplified version of siderostat to test the LVM telescope control system in Korea. The prototype siderostat consists of two aluminum flat mirrors, optomechanical housing structures made by aluminum profiles, and the Planewave L-350 mount. We designed the optical mirrors and the optomechanical structure of the siderostat. From structural analysis at various pointing cases, we estimated the tilt misalignments of mirrors within 4 arcsec, which would affect the telescope pointing errors.
Determining the properties of pile from cone penetration test (CPT) is costly, and need several in-situ tests. At the present study, two novel hybrid learning models, namely PSO-RF and HHO-RF, which are an amalgamation of random forest (RF) with particle swarm optimization (PSO) and Harris hawks optimization (HHO) were developed and applied to predict the pile set-up parameter "A" from CPT for the design aim of the projects. To forecast the "A," CPT data along were collected from different sites in Louisiana, where the selected variables as input were plasticity index (PI), undrained shear strength (Su), and over consolidation ratio (OCR). Results show that both PSO-RF and HHO-RF models have acceptable performance in predicting the set-up parameter "A," with R2 larger than 0.9094, representing the admissible correlation between observed and predicted values. HHO-RF has better proficiency than the PSO-RF model, with R2 and RMSE equal to 0.9328 and 0.0292 for the training phase and 0.9729 and 0.024 for testing data, respectively. Moreover, PI and OBJ indices are considered, in which the HHO-RF model has lower results which leads to outperforming this hybrid algorithm with respect to PSO-RF for predicting the pile set-up parameter "A," consequently being specified as the proposed model. Therefore, the results demonstrate the ability of the HHO algorithm in determining the optimal value of RF hyperparameters than PSO.
Sports activities, including playing tennis, are popular with many people. As this industry has become more professionalized, investors and those involved in sports are sure to pay attention to any tool that improves athletes' performance Tennis requires perfect coordination between hands, eyes, and the whole body. Consequently, to perform long-term sports, athletes must have enough muscle strength, flexibility, and endurance. Tennis rackets with new frames were manufactured because tennis players' performance depends on their rackets. These rackets are distinguished by their lighter weight. Composite rackets are available in many types, most of which are made from the latest composite materials. During physical exercise with a tennis racket, nanocomposite materials have a significant effect on reducing injuries. Materials as strong as graphite and thermoplastic can be used to produce these composites that include both fiber and filament. Polyamide is a thermoplastic typically used in composites as a matrix. In today's manufacturing process, materials are made more flexible, structurally more vital, and lighter. This paper discusses the production, testing, and structural analysis of a new polyamide/Multi-walled carbon nanotube nanocomposite. This polyamide can be a suitable substitute for other composite materials in the tennis racket frame. By compression polymerization, polyamide was synthesized. The functionalization of Multi-walled carbon nanotube (MWCNT) was achieved using sulfuric acid and nitric acid, followed by ultrasonic preparation of nanocomposite materials with weight percentages of 5, 10, and 15. Fourier transform infrared (FTIR) and Nuclear magnetic resonance (NMR) confirmed a synthesized nanocomposite structure. Nanocomposites were tested for thermal resistance using the simultaneous thermal analysis (DTA-TG) method. scanning electron microscopy (SEM) analysis was used to determine pores' size, structure, and surface area. An X-ray diffraction analysis (XRD) analysis was used to determine their amorphous nature.
The Journal of Economics, Marketing and Management
/
v.6
no.4
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pp.1-16
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2018
Purpose - This study will investigate and identify the relationship between brand image, brand attitude and intent to purchase based on subjects that have remembered or watched more than one storytelling marketing ad related to airlines. The purpose of the project is to secure market competitiveness by presenting the basis for and use of the marketing strategy using storytelling, which can capture the goodwill of the aerospace competition market in the future. Research, design, data, and methodology - Prior to the research model and hypothesis testing phase, a verification factor analysis was conducted to assess internal consistency among each measurement item and to ensure reliability and validity of the measurement tool. Further, the organization was assessed for validity by calculating the mean variance estimation (AVE) and the construction concept reliability (CCR) through a positive factor analysis. Hypothesis verification was analyzed through a structural equation model, and each concept set in the hypothesis was entered as a potential variable, and each measurement item was entered as an observation variable. Results - Airline's storytelling marketing has a significant impact on the brand image and two emotional and cognitive responses have been shown to influence the brand image. In addition, airline storytelling marketing has a significant impact on brand attitudes and airline storytelling marketing derived from factor analysis has shown two emotional and cognitive responses to brand attitudes. Conclusions - The parts derived based on the research results show that storytelling marketing has a strong influence on the airline's brand image and attitude, and that it is necessary for airlines to have a brand image and attitude. Also, forming a favorable brand image has a significant impact on brand attitudes. We believe that by presenting basic data to the aviation industry in future research on airline storytelling, we will be able to increase understanding and contribution to development of storytelling marketing in aviation.
Purpose - Competitive industry structure and recent economic depression challenge a survival of Korean small- and medium-sized food franchising companies (SMFCs), albeit the explosive growth of the Korean food service industry for last few decades. Against this backdrop, it examines how these SMFCs overcome liabilities of smallness and resource scarcity to strengthen competitive advantage in the market. To tackle this, in this article we focus on corporate entrepreneurship and human resources as a knowledge-based asset for these SMFCs. Furthermore, the ratio of employee turnover is high in SMFCs. We view that such brain-drain may result in poor performance of the Korean SMFCs. As such, we pay attention to the role of organizational commitment to an organization as a solution for enhancing individual-level employees' loyalty toward their organization. Research design, data, and methodology - Our research question is to what extent corporate entrepreneurship (i.e., innovative organizational culture, organizational autonomy, and administrative innovation) affects an individual-level attitude toward the organization and, in turn, employee creativity and satisfaction in the Korean SMFCs context. We collected data from employees in SMFCs for three months. A total of 126 valid questionnaires were collected, and analyzed the data using partial least squares path modeling. Results - The reliable and valid measurement model feed into testing the structural model. Our findings suggest that innovative organizational culture and organizational autonomy positively affect employee commitment. Particularly, organizational autonomy has a greater effect than innovative culture on employee commitment. However, the relationship between administrative innovation and employee commitment is not significant. We also find that employee commitment positively affects both employee creativity and satisfaction. Conclusions - Our contribution to the existing franchising business and management literature is twofold. First, the conceptual model includes three antecedents in the organizational entrepreneurship dimension to organizational commitment. Second, we conceptualize organizational commitment as employee commitment, and validate its impact on employee creativity and job satisfaction at an individual performance level. Overall, this article suggests that it is critically important for the Korean SMFCs to develop corporate entrepreneurship in order to facilitate employees' positive attitudes toward their organizations.
A deep recursive bidirectional Cuda Deep Neural Network Long Short Term Memory (Bi-CuDNNLSTM) layer is recruited in this paper to predict the entire force time histories, and the corresponding hysteresis and backbone curves of reinforced concrete (RC) bridge piers using experimental fast and slow cyclic tests. The proposed stacked Bi-CuDNNLSTM layers involve multiple uncertain input variables, including horizontal actuator displacements, vertical actuators axial loads, the effective height of the bridge pier, the moment of inertia, and mass. The functional application programming interface in the Keras Python library is utilized to develop a deep learning model considering all the above various input attributes. To have a robust and reliable prediction, the dataset for both the fast and slow cyclic tests is split into three mutually exclusive subsets of training, validation, and testing (unseen). The whole datasets include 17 RC bridge piers tested experimentally ten for fast and seven for slow cyclic tests. The results bring to light that the mean absolute error, as a loss function, is monotonically decreased to zero for both the training and validation datasets after 5000 epochs, and a high level of correlation is observed between the predicted and the experimentally measured values of the force time histories for all the datasets, more than 90%. It can be concluded that the maximum mean of the normalized error, obtained through Box-Whisker plot and Gaussian distribution of normalized error, associated with unseen data is about 10% and 3% for the fast and slow cyclic tests, respectively. In recapitulation, it brings to an end that the stacked Bi-CuDNNLSTM layer implemented in this study has a myriad of benefits in reducing the time and experimental costs for conducting new fast and slow cyclic tests in the future and results in a fast and accurate insight into hysteretic behavior of bridge piers.
Assessment of the compressive strength of concrete plays a major role during formwork removal and in the prestressing process. In concrete, temperature changes occur due to hydration which is an influencing factor that decides the compressive strength of concrete. Many methods are available to find the compressive strength of concrete, but the maturity method has the advantage of prognosticating strength without destruction. The temperature-time factor is found using a LM35 temperature sensor through the IoT technique. An experimental investigation was carried out with 56 concrete cubes, where 35 cubes were for obtaining the compressive strength of concrete using a universal testing machine while 21 concrete cubes monitored concrete's temperature by embedding a temperature sensor in each grade of M25, M30, M35, and M40 concrete. The mathematical prediction model equation was developed based on the temperature-time factor during the early age compressive strength on the 1st, 2nd, 3rd and 7th days in the M25, M30, M35, and M40 grades of concrete with their temperature. The 14th, 21st and 28th day's compressive strength was predicted with the mathematical predicted equation and compared with conventional results which fall within a 2% difference. The compressive strength of concrete at any desired age (day) before reaching 28 days results in the discovery of the prediction coefficient. Comparative analysis of the results found by the predicted mathematical model show that, it was very close to the results of the conventional method.
S. Sivakumar;R. Prakash;S. Srividhya;A.S. Vijay Vikram
Structural Engineering and Mechanics
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v.87
no.3
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pp.221-229
/
2023
Urbanization and industrialization have significantly increased the amount of solid waste produced in recent decades, posing considerable disposal problems and environmental burdens. The practice of waste utilization in concrete has gained popularity among construction practitioners and researchers for the efficient use of resources and the transition to the circular economy in construction. This study employed Lytag aggregate, an environmentally friendly pulverized fuel ash-based lightweight aggregate, as a substitute for natural coarse aggregate. At the same time, fly ash, an industrial by-product, was used as a partial substitute for cement. Concrete mix M20 was experimented with using fly ash and Lytag lightweight aggregate. The percentages of fly ash that make up the replacements were 5%, 10%, 15%, 20%, and 25%. The Compressive Strength (CS), Split Tensile Strength (STS), and deflection were discovered at these percentages after 56 days of testing. The concrete cube, cylinder, and beam specimens were examined in the explorations, as mentioned earlier. The results indicate that a 10% substitution of cement with fly ash and a replacement of coarse aggregate with Lytag lightweight aggregate produced concrete that performed well in terms of mechanical properties and deflection. The cementitious composites have varying characteristics as the environment changes. Therefore, understanding their mechanical properties are crucial for safety reasons. CS, STS, and deflection are the essential property of concrete. Machine learning (ML) approaches have been necessary to predict the CS of concrete. The Artificial Fish Swarm Optimization (AFSO), Particle Swarm Optimization (PSO), and Harmony Search (HS) algorithms were investigated for the prediction of outcomes. This work deftly explains the tremendous AFSO technique, which achieves the precise ideal values of the weights in the model to crown the mathematical modeling technique. This has been proved by the minimum, maximum, and sample median, and the first and third quartiles were used as the basis for a boxplot through the standardized method of showing the dataset. It graphically displays the quantitative value distribution of a field. The correlation matrix and confidence interval were represented graphically using the corrupt method.
This study is for analyzing the management performances of Korean tourism firms, operating as preparing strategically against FTA which is one of the most importantly external environment in international management since in the middle of 1990s. The main purpose is to test empirically some relations between the management performances and the levels of ownership-specifics advantages of Korean tourism ones. To be exact, the dependent variables of management performances are classified with sales, profits and management satisfaction, while the independent ones of the competitive advantages are sorted with the 5 following factors like marketing, product development, service supply, finance and organization culture. The survey of Korean tourism enterprises engaging in management activities in Korea is implemented by collecting questionnaires. And for testing the hypothesis, the analyzing tools are being used for correlation, reliability, validity, multi regression and the path analysis of structural equation modeling. As a result, Marketing is certified as only common factor to influence three dependent variables of sales, profit and management satisfaction positively.
Tara L. Cavalline;David C. Weggel;Dallas E. Schwerin
International conference on construction engineering and project management
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2013.01a
/
pp.390-390
/
2013
Use of recycled aggregates in portland cement concrete construction can offer benefits associated with both economy and sustainability. Testing performed to date indicates that RBMA can be used as a 100% replacement for conventional coarse aggregate in concrete that exhibits acceptable mechanical properties for use in structural and pavement elements, including satisfactory performance in some durability tests. RBMAC is currently not used in any type of construction in the United States. However, use of RBMAC could become a viable construction strategy as sustainable building practices become the norm. Rating systems such as LEED offer points for reuse of building materials (particularly on-site) and use of recycled materials. If renovations at an existing facility call for the demolition of existing brick masonry constructions, the rubble could be included as RBMA in new concrete pavement, sidewalks, or curb and gutter. Other potential uses for RBMAC could include those in the precast concrete industry, particularly in architectural precast concrete applications. In addition to providing acceptable strength and economy, the color of RBMA could be an attractive component of architectural precast concrete panels or other façade components. This paper explores the feasibility of use of RBMAC in several types of sustainable construction initiatives, based upon the findings of previous work with RBMAC produced from construction and demolition waste from a case study site. Guidance for obtaining and using RBMA is presented, along with a summary of material properties of RBMAC that will be useful to construction professionals.
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