• Title/Summary/Keyword: impact trajectory

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Surface-shape Processing Characteristics and Conditions during Trajectory-driven Fine-particle injection Processing (궤적 구동 미세입자 분사가공 시 표면 형상 가공 특성 및 가공 조건)

  • Lee, Hyoung-Tae;Hwang, Chul-Woong;Lee, Sea-Han;Wang, Duck Hyun
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.20 no.10
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    • pp.19-26
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    • 2021
  • In fine-particle injection processing, hard fine particles, such as silicon carbide or aluminum oxide, are injected - using high-pressure air, and a small amount of material is removed by applying an impact to the workpiece by spraying at high speeds. In this study, a two-axis stage device capable of sequence control was developed to spray various shapes, such as circles and squares, on the surface during the micro-particle jetting process to understand the surface-shape micro-particle-processing characteristics. In the experimental device, two stepper motors were used for the linear movement of the two degree-of-freedom mechanism. The signal output from the microcontroller is - converted into a signal with a current sufficient to drive the stepper motor. The stepper motor rotates precisely in synchronization with the pulse-signal input from the outside, eliminating the need for a separate rotation-angle sensor. The major factors of the processing conditions are fine particles (silicon carbide, aluminum oxide), injection pressure, nozzle diameter, feed rate, and number of injection cycles. They were identified using the ANOVA technique on the design of the experimental method. Based on this, the surface roughness of the spraying surface, surface depth of the spraying surface, and radius of the corner of the spraying surface were measured, and depending on the characteristics, the required spraying conditions were studied.

Appraising the Performance of Construction Projects during Implementation in Kenya, 1963-2018: A Literature Review Perspective

  • Ong'ondo, Cyrus Babu;Gwaya, Abednego Oswald;Masu, Sylvester
    • Journal of Construction Engineering and Project Management
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    • v.9 no.2
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    • pp.1-24
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    • 2019
  • Poor project performance has been noted as the bane in the construction industry globally. This paper sought to investigate, by way of literature, the performance patterns of construction projects in Kenya since independence (1963-2018). This was informed by reports of undesirable project performance in the industry. This descriptive study used available studies previously done in this subject area. In sum, literature is replete with evidence on a myriad of challenges facing the execution of projects. The study established that generally, the project performance is poor and has assumed a chronic trajectory spanning over five decades. On average, the findings reveal that 35-60% of projects initiated in Kenya face cost overruns while time overrun is most severe with 35-73% projects overrunning their schedule. In addition, the findings problematize the issue of plurality of performance measurement regimes in the construction industry. Here, it was observed that no singular construct exists to objectively measure the various facets that constitute the 'health' of a project. This paper has contributed to the body of knowledge by examining the performance patterns in Kenya for over fifty years while at the same time identifying the bottlenecks inherent in projects execution. Importantly, the conceptual performance efficiency framework derived in the current study presents a paradigm shift in the monitoring and evaluation of projects. To this end, an in-depth analysis is recommended on the interaction of efficiency enablers in the buildup of performance efficiency index (PEI). Similarly, a further inquiry is recommended on the integration and impact of the proposed framework in the management of projects.

Research on aerodynamic force and structural response of SLCT under wind-rain two-way coupling environment

  • Ke, Shitang;Yu, Wenlin;Ge, Yaojun
    • Wind and Structures
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    • v.29 no.4
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    • pp.247-270
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    • 2019
  • Wind-resistant design of existing cooling tower structures overlooks the impacts of rainfall. However, rainstorm will influence aerodynamic force on the tower surface directly. Under this circumstance, the structural response of the super-large cooling tower (SLCT) will become more complicated, and then the stability and safety of SLCT will receive significant impact. In this paper, surrounding wind fields of the world highest (210 m) cooling tower in Northwest China underthree typical wind velocities were simulated based on the wind-rain two-way coupling algorithm. Next, wind-rain coupling synchronous iteration calculations were conducted under 9 different wind speed-rainfall intensity combinations by adding the discrete phase model (DPM). On this basis, the influencing laws of different wind speed-rainfall intensity combinations on wind-driving rain, adhesive force of rain drops and rain pressure coefficients were discussed. The acting mechanisms of speed line, turbulence energy strength as well as running speed and trajectory of rain drops on structural surface in the wind-rain coupling field were disclosed. Moreover, the fitting formula of wind-rain coupling equivalent pressure coefficient of the cooling tower was proposed. A systematic contrast analysis on its 3D distribution pattern was carried out. Finally, coupling model of SLCT under different working conditions was constructed by combining the finite element method. Structural response, buckling stability and local stability of SLCT under different wind velocities and wind speed-rainfall intensity combinations were compared and analyzed. Major research conclusions can provide references to determine loads of similar SLCT accurately under extremely complicated working conditions.

Contributions of Emissions and Atmospheric Physical and Chemical Processes to High PM2.5 Concentrations on Jeju Island During Spring 2018 (2018년 봄철 제주지역 고농도 PM2.5에 대한 배출량 및 물리·화학적 공정 기여도 분석)

  • Baek, Joo-Yeol;Song, Sang-Keun;Han, Seung-Beom;Cho, Seong-Bin
    • Journal of Environmental Science International
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    • v.31 no.7
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    • pp.637-652
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    • 2022
  • In this study, the contributions of emissions (foreign and domestic) and atmospheric physical and chemical processes to PM2.5 concentrations were evaluated during a high PM2.5 episode (March 24-26, 2018) observed on the Jeju Island in the spring of 2018. These analyses were performed using the community multi-scale air quality (CMAQ) modeling system using the brute-force method and integrated process rate (IPR) analysis, respectively. The contributions of domestic emissions from South Korea (41-45%) to PM2.5 on the Jeju Island were lower than those (81-89%) of long-range transport (LRT) from China. The substantial contribution of LRT was also confirmed in conjunction with the air mass trajectory analysis, indicating that the frequency of airflow from China (58-62% of all trajectories) was higher than from other regions (28-32%) (e.g., South Korea). These results imply that compared to domestic emissions, emissions from China have a stronger impact than domestic emissions on the high PM2.5 concentrations in the study area. From the IPR analysis, horizontal transport contributed substantially to PM2.5 concentrations were dominant in most of the areas of the Jeju Island during the high PM2.5 episode, while the aerosol process and vertical transport in the southern areas largely contributed to higher PM2.5 concentrations.

The Influence of Human Capital on GDP Dynamics: Modeling in the COVID-19 Conditions

  • Derii, Zhanna;Zosymenko, Tetiana;Shaposhnykov, Kostiantyn;Tochylina, Yuliia;Krylov, Denys;Papaika, Oleksandr
    • International Journal of Computer Science & Network Security
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    • v.22 no.3
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    • pp.67-76
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    • 2022
  • COVID-19 struck labor markets around the world, exposing and exacerbating the gender inequalities within the human capital structure. The last, in its turn, jeopardizes the return of the national economies to the growth trajectory undermined by pandemic impact. The authors assume that COVID-19 disproportionately affected the employment rates of women and men, which led to increased gender inequality in the labor market, which, in turn, affected GDP growth rates in the EU. To prove this hypothesis two research questions are discovered: 1) whether there was a different correlation between the number of COVID-19 cases in the EU and indicators of the labor market for women and men; and 2) whether there was a link between the growth of gender inequality in the EU labor market and the GDP dynamics in these countries. The analysis of the correlation between the number of cases of COVID-19 and indicators of the labor market in the EU revealed faster growth of women's unemployment rates compared to men's ones as the COVID-19 incidence unfolded. Multiple linear regression and factor analysis have been used to investigate the influence of gender inequality in the labor market on GDP dynamics. Despite the methodological limitations, the proposed model is both a sound argument and an analytical basis in favor of gender-responsive economic recovery backed by the systematic and consistent gender equality policy of a government.

A semi-supervised interpretable machine learning framework for sensor fault detection

  • Martakis, Panagiotis;Movsessian, Artur;Reuland, Yves;Pai, Sai G.S.;Quqa, Said;Cava, David Garcia;Tcherniak, Dmitri;Chatzi, Eleni
    • Smart Structures and Systems
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    • v.29 no.1
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    • pp.251-266
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    • 2022
  • Structural Health Monitoring (SHM) of critical infrastructure comprises a major pillar of maintenance management, shielding public safety and economic sustainability. Although SHM is usually associated with data-driven metrics and thresholds, expert judgement is essential, especially in cases where erroneous predictions can bear casualties or substantial economic loss. Considering that visual inspections are time consuming and potentially subjective, artificial-intelligence tools may be leveraged in order to minimize the inspection effort and provide objective outcomes. In this context, timely detection of sensor malfunctioning is crucial in preventing inaccurate assessment and false alarms. The present work introduces a sensor-fault detection and interpretation framework, based on the well-established support-vector machine scheme for anomaly detection, combined with a coalitional game-theory approach. The proposed framework is implemented in two datasets, provided along the 1st International Project Competition for Structural Health Monitoring (IPC-SHM 2020), comprising acceleration and cable-load measurements from two real cable-stayed bridges. The results demonstrate good predictive performance and highlight the potential for seamless adaption of the algorithm to intrinsically different data domains. For the first time, the term "decision trajectories", originating from the field of cognitive sciences, is introduced and applied in the context of SHM. This provides an intuitive and comprehensive illustration of the impact of individual features, along with an elaboration on feature dependencies that drive individual model predictions. Overall, the proposed framework provides an easy-to-train, application-agnostic and interpretable anomaly detector, which can be integrated into the preprocessing part of various SHM and condition-monitoring applications, offering a first screening of the sensor health prior to further analysis.

A Longitudinal Analysis of the Number of Checked-out Books Using Latent Growth Model and Growth Mixture Modeling (잠재성장모형과 성장혼합모형을 이용한 도서관 대출권수의 종단적 분석)

  • Heejin Park;Sungjae Park
    • Journal of the Korean Society for Library and Information Science
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    • v.57 no.1
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    • pp.45-68
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    • 2023
  • The purpose of this study is to longitudinally analyze impact factors on library use. One of library use indicators, the number of circulated books was statistically analyzed with latent growth model and growth mixture model. Library data from 2014 to 2019 were collected from the National Library Statistics System, and 846 public libraries were analyzed. As results, the number of circulated books were decreased, but it was tempered. Next, with controlling the factor affecting the dependent variable, the size of collection and the number of participants in reading programs provided by public libraries were statistically significant. Lastly, 5 classes were identified by applying the growth mixture model, and the number of librarians was significantly associated with trajectory class membership.

Analysis of vibration characterization of a multi-stage planetary gear transmission system containing faults

  • Hao Dong;Yue Bi;Bing-Xing Ren;Zhen-Bin Liu;Yue, Li
    • Structural Engineering and Mechanics
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    • v.88 no.4
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    • pp.389-403
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    • 2023
  • In order to explore the influence of tooth root cracks on the dynamic characteristics of multi-stage planetary gear transmission systems, a concentrated parameter method was used to construct a nonlinear dynamic model of the system with 30-DOF in bending and torsion, taking into account factors such as crack depth, length, angle, error, time-varying meshing stiffness (TVMS), and damping. In the model, the energy method was used to establish a TVMS model with cracks, and the influence of cracks on the TVMS of the system was studied. By using the Runge- Kutta method to calculate the differential equations of system dynamics, a series of system vibration diagrams containing cracks were obtained, and the influence of different crack parameters on the vibration of the system was analyzed. And vibration testing experiments were conducted on the system with planetary gear cracks. The results show that when the gear contains cracks, the TVMS of the system will decrease, and as the cracks intensify, the TVMS will decrease. When cracks appear on the II-stage planetary gear, the system will experience impact effects with intervals of rotation cycles of the II-stage planetary gear. There will be obvious sidebands near the meshing frequency doubling, and the vibration trajectory of the gear will also become disordered. These situations will become more and more obvious as the degree of cracks intensifies. Through experiments, the theoretical results are in good agreement with experimental results, verifying the correctness of the theoretical model. This provides a theoretical basis for fault diagnosis and reliability research of the system.

Utilizing the n-back Task to Investigate Working Memory and Extending Gerontological Educational Tools for Applicability in School-aged Children

  • Chih-Chin Liang;Si-Jie Fu
    • Journal of Information Technology Applications and Management
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    • v.31 no.1
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    • pp.177-188
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    • 2024
  • In this research, a cohort of two children, aged 7-8 years, was selected to participate in a specialized three-week training program aimed at enhancing their working memory. The program consisted of three sessions, each lasting approximately 30 minutes. The primary goal was to investigate the impact and developmental trajectory of working memory in school-aged children. Working memory plays a significant role in young children's learning and daily activities. To address the needs of this demographic, products should offer both educational and enjoyable activities that engage working memory. Digital educational tools, known for their flexibility, are suitable for both older individuals and young children. By updating software or modifying content, these tools can be effectively repurposed for young learners without extensive hardware changes, making them both cost-effective and practical. For example, memory training games initially designed for older adults can be adapted for young children by altering images, music, or storylines. Furthermore, incorporating elements familiar to children, like animals, toys, or fairy tales, can increase their engagement in these activities. Historically, working memory capabilities have been assessed predominantly through traditional intelligence tests. However, recent research questions the adequacy of these behavioral measures in accurately detecting changes in working memory. To bridge this gap, the current study utilized electroencephalography (EEG) as a more sophisticated and precise tool for monitoring potential changes in working memory after the training. The research findings were revealing. Participants showed marked improvement in their performance on n-back tasks, a standard measure for evaluating working memory. This improvement post-training strongly supports the effectiveness of the training program. The results indicate that such targeted and structured training programs can significantly enhance the working memory abilities of children in this age group, providing promising implications for educational strategies and cognitive development interventions.

Investigation on a Haze Episode of Fine Particulate Matter using Semi-continuous Chemical Composition Data (준 실시간 화학적 조성자료를 이용한 미세입자 연무 에피소드 규명)

  • Park, Seung-Shik;Kim, Sun-Jung;Gong, Bu-Joo;Lee, Kwon-Ho;Cho, Seog-Yeon;Kim, Jong-Choon;Lee, Suk-Jo
    • Journal of Korean Society for Atmospheric Environment
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    • v.29 no.5
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    • pp.642-655
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    • 2013
  • In this study, semi-continuous measurements of $PM_{2.5}$ mass, organic and elemental carbon (OC and EC), black carbon (BC), and ionic species concentrations were made for the period of April 03~13, 2012, at a South Area Supersite at Gwangju. Possible sources causing the high concentrations of major chemical species in $PM_{2.5}$ observed during a haze episode were investigated. The measurement results, along with meteorological parameters, gaseous pollutants data, air mass back trajectory analyses and PSCF (potential source contribution function) results, were used to study the haze episode. Substantial enhancements of OC, EC, BC, $K^+$, $SO{_4}^{2-}$, $NO{_3}{^-}$, $NH{_4}{^+}$, and CO concentrations were closely associated with air masses coming from regions of forest fires in southeastern China, suggesting likely an impact of the forest fires. Also the PSCF maps for EC, OC, $SO{_4}^{2-}$, and $K^+$ demonstrate further that the long-range transport of smoke plumes of forest fires detected over the southeastern China could be a possible source of haze phenomena observed at the site. Another possible source leading to haze formation was likely from photochemistry of precursor gases such as volatile organic compounds, $SO_2$, and $NO_2$, resulting in accumulation of secondary organic aerosol, $SO{_4}^{2-}$ and $NO{_3}{^-}$. Throughout the episode, local wind directions were between 200 and $230^{\circ}C$, where two industrial areas are situated, with moderate wind speeds of 3~5 m/s, resulting in highly elevated concentration of $SO_2$ with a maximum of 15 ppb. The $SO{_4}^{2-}$ peak occurring in the afternoon hours coincided with maximum ambient temperature ($24^{\circ}C$) and ozone concentration (~100 ppb), and were driven by photochemistry of $SO_2$. As a result, the pattern of $SO{_4}^{2-}$ variations in relation to wind direction, $SO_2$ and $O_3$ concentrations, and the strong correlation between $SO_2$ and $SO{_4}^{2-}$ ($R^2=0.76$) suggests that in addition to the impact of smoke plumes from forest fires in the southeastern China, local $SO_2$ emissions were likely an important source of $SO{_4}^{2-}$ leading to haze formation at the site.