1,721,411 research outputs found
ANALISIS PENINGKATAN PENJUALAN SHI-DA MELALUI PEMASARAN DIGITAL
Full text linkMaraknya bisnis makanan di Indonesia menyebabkan persaingan menjadi ketat dan masing - masing perusahaan perlu menjaga loyalitas pelanggan sehingga tetap membeli produk makanan yang ditawarkan. SHI-DA Indonesia yang merupakan salah satu bisnis makanan yang menjual jajanan Taiwan. Berdasarkan laporan keuangan SHI-DA Cabang Semarang dapat dilihat bahwa pertumbuhan penjualan tidak setara dengan pertumbuhan pada cabang-cabang lainnya, angka penjualan cenderung stagnan dan menurun. Berbagai jenis pemasaran sudah dilakukan pleh SHI-DA Indonesia. Dari berbagai macam jenis pemasaran yang telah dilakukan oleh SHI-DA Indonesia maka penulis tertarik untuk mengetahui pemasaran mana yang lebih efektif terhadap peningkatan penjualan, maka penulis melakukan analisis dengan judul “ANALISIS PENINGKATAN PENJUALAN SHI-DA MELALUI PEMASARAN DIGITAL”. Tujuan dari penelitian ini adalah untuk mengetahui apakah ada pengaruh dari aplikasi pembayaran digital (e-wallet) terhadap kesadaran merek SHI-DA, dan apakah ada pengaruh pemasaran melalui pemanfaatan Promo Offline (on-site) , Gofood/Grabfood, dan Instagram berpengaruh terhadap peningkatan penjualan SHI-DA.
Metode penelitian yang digunakan adalah metode kuantitatif penelitian tindakan. Untuk analisis menggunakan regresi linear berganda, dengan uji t dan uji F. Penelitian ini dilakukan di SHI-DA Cabang Semarang dengan menggunakan data penjualan periode Desember 2019 sampai Maret 2020.
Hasil dari penelitian ini adalah pemasaran melalui pembayaran digital (e-wallet) memiliki pengaruh terhadap kesadaran merek dan memiliki pengaruh yang signifikan pada peningkatan penjualan SHI-DA Cabang Semarang. Media pemasaran baik yang hanya melalui Promo Offline (on-site) , atau Gofood/Grabfood, atau melalui Instagram hasilnya tidak memiliki pengaruh terhadap peningkatan penjualan SHI-DA Cabang Semarang. Hasil berbeda didapat saat analisa dilakukan secara simultan antara media pemasaran melalui melalui Promo Offline (on-site), Gofood/Grabfood, dan Instagram memiliki pengaruh terhadap peningkatan penjualan SHI-DA Cabang Semarang. Maka adanya media pemasaran melalui Promo Offline (on-site), Gofood/Grabfood, dan Instagram harus dilakukan secara bersamaan agar dapat memberi pengaruh pada peningkatan penjualan SHI-DA Cabang Semarang
Analysis of Glubam Joint Behavior and Truss Model Updating Based on Optimization Algorithms
Full text linkBamboo, as a naturally fast-growing renewable resource, is abundant in China and supported by a wellestablished
industrial foundation, making it a crucial material for promoting green building development.
Modern engineered bamboo structures are typically fabricated using industrialized processes with
engineered bamboo-based panels as raw materials, which reduce environmental impact while enabling
standardization and prefabrication of building components. These structures can effectively meet
performance requirements in terms of safety, economy, and comfort. Glue-Laminated Bamboo (glubam), a
representative type of engineered bamboo, features a high strength-to-weight ratio, low adhesive content,
and stable physical and mechanical properties. As an innovative and sustainable construction material,
glubam has shown great potential for application in modern structural engineering. Compared to traditional
building materials such as timber and steel, glubam offers significant advantages in strength-to-weight
performance, renewability, and environmental friendliness. Despite its excellent material properties,
research on the hysteretic behavior of glubam structural joints and the seismic performance of glubam
composite truss systems remains insufficient. Comprehensive design theories and reliable numerical
modeling approaches are still lacking. Moreover, integrating artificial intelligence (AI) optimization
algorithms into the seismic performance analysis of glubam structures represents a promising yet
underexplored research direction.
In response to these challenges, this study systematically investigates the mechanical behavior of
glubam joints and their corresponding truss assemblies under cyclic loading through a combination of
experimental testing, numerical simulation, and AI-based optimization methods. The main research
contents and findings are summarized as follows: First, according to relevant testing standards, two types
of glubam joints and their corresponding planar truss and roof truss structures were subjected to quasi-static
cyclic loading tests to evaluate their hysteretic behavior and failure modes. Based on the experimental
observations, both high-fidelity three-dimensional finite element models and simplified low-fidelity
hysteresis models were developed to capture the nonlinear mechanical responses of the two joint types. For
the simplified models, two parametric hysteresis constitutive models were proposed to reproduce critical
features observed under cyclic loading, such as pinching effects, asymmetry, and strength degradation.
Three representative AI optimization algorithms—Genetic Algorithm (GA), Bayesian Inference (BI), and
Neural Network (NN)—were introduced to perform parameter identification and model calibration,
significantly improving the accuracy and generalizability of the models. Finally, using the calibrated
hysteresis models, a macro-scale numerical model of the glubam truss structure was constructed by
combining the joint models with beam-column elements. Structural-level model updating was then
performed using AI algorithms, and the optimized model was used to analyze the structural response of
glubam trusses under cyclic loading. The detailed research tasks and contributions of this study are
summarized as follows: This study first conducted axial monotonic and cyclic loading tests on two types of glubam joint
connections with distinct configurations: the steel-insert glubam joint and the steel-plate clamped glubam
joint. The fasteners used in these joints were designed with varying geometric dimensions. Through
systematic experimentation, the mechanical behavior of both joint types under cyclic loading was
comprehensively analyzed, including characteristics of their hysteresis curves, stiffness degradation
patterns, energy dissipation capacity, and typical failure modes. The test results demonstrated that both
types of glubam joints exhibited favorable hysteretic behavior and excellent energy dissipation performance.
Their failure processes were primarily ductile in nature, indicating promising seismic resistance potential.
In addition, the influence of geometric parameters of the fasteners on the mechanical performance of the
joints was further investigated. It was found that these parameters significantly affect the joints' load-bearing
capacity, initial stiffness, and energy dissipation efficiency.
Building upon the joint performance investigation, planar truss and roof truss systems were designed
using the two connection types (steel-insert and steel-plate clamped) and subjected to quasi-static cyclic
loading tests. The study systematically evaluated the global hysteretic performance, energy dissipation
capacity, and seismic behavior of the two types of truss systems under cyclic loads. Test results indicated
that glubam truss systems exhibited good deformation capacity and high energy dissipation efficiency,
meeting the basic requirements of seismic design.
In the numerical simulation component of this study, high-fidelity three-dimensional finite element
(FE) models were developed for both types of glubam joint configurations. A novel modeling approach was
proposed by coupling the "element deletion method" with the Hill yield criterion, enabling simultaneous
characterization of the orthotropic mechanical properties and crack propagation behavior of glubam. These
constitutive mechanisms were implemented via a user-defined material subroutine (UMAT) in Abaqus and
successfully applied to the high-fidelity 3D finite element model of the steel-insert glubam joint. The
simulated load–displacement curves closely matched the experimental results, validating the model’s
accuracy and reliability in capturing the nonlinear hysteretic response of the joints.
To enable more efficient simulation at the structural (macro) scale, two sets of low-fidelity simplified
hysteretic models were further developed for the aforementioned joint configurations. These models
innovatively combined multiple types of spring elements—each representing distinct mechanical behaviors
such as ideal elastoplasticity, pinching, and gap characteristics—through series and parallel arrangements.
This approach significantly reduced computational cost in structural analysis and facilitated subsequent
parameter identification and model updating. The simplified hysteretic models systematically incorporated
key nonlinear features observed during cyclic loading, including stiffness degradation, unloading stiffness
recovery, strength deterioration, and energy dissipation. Comparison with experimental data demonstrated
that the simulated load–displacement curves agreed closely with test results, confirming the proposed
hysteretic models’ accuracy and engineering applicability.
To ensure that the numerical hysteresis models accurately capture the actual cyclic behavior of glubam
joints, it is essential to identify and calibrate multiple key model parameters. However, due to the high dimensionality of these parameter sets, manual tuning is inefficient and often fails to yield stable and reliable
results. To address this issue, this study incorporates three mainstream artificial intelligence (AI)
optimization algorithms—Genetic Algorithm (GA), Bayesian Inference (BI), and Neural Networks (NN)—
into the finite element (FE) simulation workflow, thereby establishing an intelligent parameter identification
framework. By conducting a comparative analysis of the three algorithms in terms of accuracy, convergence
speed, and robustness, the most suitable optimization strategy was selected. The resulting calibrated
numerical hysteresis models exhibit both high accuracy and strong stability, and are capable of faithfully
reproducing the cyclic behavior of the joints under repeated loading, providing a reliable basis for
subsequent structural-level modeling. Building on this foundation, the calibrated simplified joint models
were embedded into macro-scale glubam truss models, enabling simulation of the coupled behavior between
the joints and the overall structural system. To further improve the predictive accuracy of the structural mo
dels under realistic loading conditions, an advanced model updating procedure was implemented using
optimization techniques. The updated models were validated through systematic comparisons between
numerical simulations and experimental results, confirming the accuracy and practical value of the proposed
model updating methodology.
The research findings demonstrate that glubam joints and their corresponding truss systems exhibit
excellent energy dissipation capacity and mechanical stability under cyclic loading, highlighting their
significant potential in seismic design and sustainable construction. This dissertation not only systematically
uncovers the hysteresis evolution characteristics of glubam joints and truss systems but also proposes a
comprehensive modeling and optimization framework—from constitutive joint modeling and parameter
identification to structural-level model integration and updating. These contributions lay a solid theoretical
and technical foundation for the engineering application of glubam-based structural systems in seismic
desig
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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