Visual analytics for supply network management: system design and evaluation

We propose a visual analytic system to augment and enhance decision-making processes of supply chain managers. Several design requirements drive the development of our integrated architecture and lead to three primary capabilities of our system prototype. First, a visual analytic system must integrate various relevant views and perspectives that highlight different structural aspects of a supply network. Second, the system must deliver required information on-demand and update the visual representation via user-initiated interactions. Third, the system must provide both descriptive and predictive analytic functions for managers to gain contingency intelligence. Based on these capabilities we implement an interactive web-based visual analytic system. Our system enables managers to interactively apply visual encodings based on different node and edge attributes to facilitate mental map matching between abstract attributes and visual elements. Grounded in cognitive fit theory, we demonstrate that an interactive visual system that dynamically adjusts visual representations to the decision environment can significantly enhance decision-making processes in a supply network setting. We conduct multi-stage evaluation sessions with prototypical users that collectively confirm the value of our system. Our results indicate a positive reaction to our system. We conclude with implications and future research opportunities.The authors would like to thank the participants of the 2015 Businessvis Workshop at IEEE VIS, Prof. Benoit Montreuil, and Dr. Driss Hakimi for their valuable feedback on an earlier version of the software; Prof. Manpreet Hora for assisting with and Georgia Tech graduate students for participating in the evaluation sessions; and the two anonymous reviewers for their detailed comments and suggestions. The study was in part supported by the Tennenbaum Institute at Georgia Tech Award # K9305. (K9305 - Tennenbaum Institute at Georgia Tech Award)Accepted manuscrip

GEOCHEMISTRY OF VOLATILES RELEASED BY INCIPIENT CONTINENTAL RIFTING AND SUBDUCTION PROCESSES

Volatiles (N2, CO2, and He) are released by volcanism and hydrothermal activity during continental rifting and subduction processes. Analyses of volatile components have been conducted to obtain gas contents (CO2, SO2, H2S, N2, Ar, He, and so on), stable isotope compositions (δ13C, δ15N, and so on), and noble gas isotopes (3He/4He, 40Ar/36Ar, and so on). This dissertation includes four chapters to report new nitrogen isotope fractionation factors of bubbling gases during gas-water transfer at various water temperatures (Chapter 1), first measurements of massive amounts of CO2 released by incipient continental rifting in the Magadi and Natron Basin, East African Rift (Chapter 2), new results of gas chemistry, stable isotopes, and noble gas isotopes of hot springs in the same area as Chapter 2 (Chapter 3), and new nitrogen isotope compositions of springs at the Costa Rican subduction zone (Chapter 4). Chapter 1 (published in Geochemical Journal) is the first experimental work to acquire nitrogen isotope fractionation factors during N2 gas and water transfer at various temperature to examine nitrogen isotope shift for hydrothermal systems. This work reports measured δ15N values of dissolved N2 gas at 5 to 60°C. We obtained δ15N values of 0.91, 0.73, -0.04, and -0.42‰ at 5, 20, 40, and 60°C, respectively. Nitrogen isotope fractionation depending on temperature is more significant than previously published results, showing an isotopic \u27crossover\u27 at 40°C. A kinetic incorporation of 14N into water is enhanced by rising temperatures could explain the steep temperature dependence. In hydrothermal systems, small negative δ15N values could be attributed to kinetic fractionation between dissolved N2 and N2 in air. Chapter 2 (published in Nature Geoscience) is the first estimation of diffuse CO2 degassing (“Tectonic Degassing”) along faults which are away from active volcanic centers in the East African Rift. We used results of diffuse soil CO2 measurements combined with carbon isotopic compositions to quantify the flux of CO2 and constrain CO2 sources. This study reports that 4.05 mega tons per year of mantle-derived CO2 is released by faults penetrating the lower crust in the Magadi-Natron Basin. Extrapolated CO2 flux (71±33 mega tons per year) of the entire Eastern rift (~3,000 km long from Afar to Mozambique) is comparable to CO2 emission from the entire mid-ocean ridge system (53-97 mega tons per year). Therefore, widespread continental rifting and super-continent breakup could result in massive and long-term CO2 emissions, contributing prolonged greenhouse conditions likely during the Cretaceous. Chapter 3 (published in Journal of Volcanology and Geothermal Research) reports new results of gas compositions, stable isotopes (O, H, N, and C), and noble gas isotopes (He and Ar) of hot spring samples from the Magadi and Natron basin in the East African Rift (EAR). In dissolved gases, CO2 is the most abundant deep and shallow sources are mixed based on the N2-He-Ar abundances. δ18O and δD values of the springs waters indicates that the local meteoric water is dominant with minor evaporation. Most of δ15N and δ13C values and 3He/4He ratios suggest that Subcontinental Lithospheric Mantle (SCLM) is the major mantle source. The 4He flux values, significantly greater than the reported mean of global continental flux values, imply that elevated mantle 4He flux is due to magmatism and related heating, and crustal 4He is released by fracturing of old rocks in the Tanzanian craton and Mozambique belt. SCLM-derived volatiles can be ascribed to that a relatively small volume of lithospheric mantle has been replaced by asthenosphere during incipient rifting (Ma). Chapter 4 (in preparation) shows new results of gas compositions, nitrogen, and helium isotopes of springs at forearc and arc front areas in Costa Rica. Nitrogen isotope compositions (9-11N°) with less pelagic sediment contribution compared to further north (Guatemala and Nicaragua) result in insufficient nitrogen output to the atmosphere. This work supports the subduction erosion model in conjunction with seamount subduction. The overlying forearc crustal materials incorporated into the Costa Rican subduction zone dilute sediment-derived nitrogen signals. These results support the deep recycling of N into the deep mantle

CROSS-LINGUISTIC ACTIVATION IN KOREAN L2 LEARNERS’ PROCESSING OF REMENTION BIAS IN ENGLISH

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2019

On Perfect Subdivision Tilings

For a given graph $H$, we say that a graph $G$ has a perfect $H$-subdivision tiling if $G$ contains a collection of vertex-disjoint subdivisions of $H$ covering all vertices of $G.$ Let $\delta_{sub}(n, H)$ be the smallest integer $k$ such that any $n$-vertex graph $G$ with minimum degree at least $k$ has a perfect $H$-subdivision tiling. For every graph $H$, we asymptotically determined the value of $\delta_{sub}(n, H)$. More precisely, for every graph $H$ with at least one edge, there is a constant $1 < \xi^*(H)\leq 2$ such that $\delta_{sub}(n, H) = \left(1 - \frac{1}{\xi^*(H)} + o(1) \right)n$ if $H$ has a bipartite subdivision with two parts having different parities. Otherwise, the threshold may depend on the parity of $n.

BERT, SHAP, Kano 모델을 기반한 소비자 만족 요소 다이나믹스

학위논문(석사) -- 서울대학교대학원 : 경영대학 경영학과, 2022.2. 오정석 교수.최근 10년 간 온라인 쇼핑 산업의 성장으로 온라인 쇼핑몰 플랫폼에 온라인 리뷰 등 무한한 소비자 반응, 만족도 관련 정보가 생성되고 있다. 이에 많은 기업들과 학계에서 이를 활용하여 VoC (Voice of Customer)를 반영한 소비자 만족도 모델링을 시도하고 있다. 본 논문은 BERT, GBM, SHAP 등을 활용하여 카노 모델 (Kano Model)에 기반한 소비자 만족도 특성 (Customer Satisfaction Dimension)을 분류하고 각 특성의 소비자 요구 충족 여부가 소비자 만족도에 미치는 영향도를 측정한다. 본 논문의 방법론에 활용된 각 빅데이터 모델 성능과 선행 연구들에서 사용된 모델 성능을 직접 구현 및 비교하여, 본 논문에서 활용된 모델들의 정확성과 안정성을 보였다. 또한 해석적 머신러닝 기법인 SHAP를 도입하여, 카노 카테고리를 분류하는 통일된 분류 방식을 제안한다. 본 연구는 제시된 방법론을 통해 스마트폰 및 스마트워치 제품군을 대상으로 실증 연구를 진행하며, 산업계에 제품 개발 및 개선, 고객 세분화 전략 등 기업 의사결정 방향성에 유의미한 제언을 제시함으로써 본 방법론의 실용적 가치를 입증하였다.As a large number of online reviews are loaded on e-commerce platforms in recent days, companies are being able to measure customer satisfaction reflecting VoC (Voice of Customer) with big data analytics. This paper proposes the improved framework for identifying characteristics of customer satisfaction dimensions (CSD) based on Kano model using BERT (Bidirectional Encoder Representations from Transformers), GBM (Gradient Boosting Machine), and SHAP (Shapley Additive eXplanation). We proved each model outperformance by comparing other models which previous studies have used. And this paper suggests the unified rule of Kano model classification using SHAP. Furthermore, we conducted empirical studies regarding smartphone and smartwatch products which suggest the direction of product enhancement/development strategy and multi-product level customer segmentation strategy to product manufacturers. This shows proposed methodology’s effectiveness and usefulness on industrial analysis.1. Introduction 1 2. A framework for modelling customer satisfaction from online review 5 3. Research Method 8 3.1 Mining customer’s sentiments toward CSDs from online reviews 8 3.2 Measuring the effects of customer sentiments toward each CSD on customer satisfaction 11 3.3 Identifying the feature of each CSD from the customer’s perspective 11 3.4 Classifying each CSD into Kano categories 14 4. Empirical Study 17 4.1 Study 1 17 4.2 Study 2 24 5. Conclusion 27 6. Reference 29석