Coordination of Purchasing and Bidding Activities Across Markets

In both consumer purchasing and industrial procurement, combinatorial interdependencies among the items to be purchased are commonplace. E-commerce compounds the problem by providing more opportunities for switching suppliers at low costs, but also potentially eases the problem by enabling automated market decision-making systems, commonly referred to as trading agents, to make purchasing decisions in an integrated manner across markets. Most of the existing research related to trading agents assumes that there exists a combinatorial market mechanism in which buyers (or sellers) can bid (or sell) service or merchant bundles. Todayâ??s prevailing e-commerce practice, however, does not support this assumption in general and thus limits the practical applicability of these approaches. We are investigating a new approach to deal with the combinatorial interdependency challenges for online markets. This approach relies on existing commercial online market institutions such as posted-price markets and various online auctions that sell single items. It uses trading agents to coordinate a buyerâ??s purchasing and bidding activities across multiple online markets simultaneously to achieve the best overall procurement effectiveness. This paper presents two sets of models related to this approach. The first set of models formalizes optimal purchasing decisions across posted-price markets with fixed transaction costs. Flat shipping costs, a common e-tailing practice, are captured in these models. We observe that making optimal purchasing decisions in this context is NP-hard in the strong sense and suggest several efficient computational methods based on discrete location theory. The second set of models is concerned with the coordination of bidding activities across multiple online auctions. We study the underlying coordination problem for a collection of first or second-price sealed-bid auctions and derive the optimal coordination and bidding policies.

Clustering Customer Shopping Trips With Network Structure

Moving objects can be tracked with sensors such as RFID tags or GPS devices. Their movement can be represented as sequences of time-stamped locations. Studying such spatio-temporal movement sequences to discover spatial sequential patterns holds promises in many real-world settings. A few interesting applications are customer shopping traverse pattern discovery, vehicle traveling pattern discovery, and route prediction. Traditional spatial data mining algorithms suitable for the Euclidean space are not directly applicable in these settings. We propose a new algorithm to cluster movement paths such as shopping trips for pattern discovery. In our work, we represent the spatio-temporal series as sequences of discrete locations following a pre-defined network. We incorporate a modified version of the Longest Common Subsequence (LCS) algorithm with the network structure to measure the similarity of movement paths. With such spatial networks we implicitly address the existence of spatial obstructs as well. Experiments were performed on both hand-collected real-life trips and simulated trips in grocery shopping. The initial evaluation results show that our proposed approach, called Net-LCSS, can be used to support effective and efficient clustering for shopping trip pattern discovery

A Cooporative Analysis Framework for Investment Decisions in Community Source Partnerships

Community source development has emerged as a new way of developing enterprise applications, leading to a unique type of open source practice involving partnership and investments from multiple organizations. A critical research question in community source development is concerned with the rationale and the economic incentives behind investments from partnering organizations. In this paper, we examine a real world case, the Kuali community source project, and propose a cooperative decision framework to analyze investment decisions made by various types of organizations involved in community source. We analyze joint investment decisions and adopt the Black-Scholes model to capture individual organizations’ decision-making in risky environments. Our analytical results are able to explain an array of observed investment behavior from community-source partners and reveal useful insights to help these organizations make decisions. Our results also facilitate a general understanding of the emerging community source development landscape

Metastatic model of HPV+ oropharyngeal squamous cell carcinoma demonstrates heterogeneity in tumor metastasis

Human papillomavirus induced (HPV+) cancer incidence is rapidly rising, comprising 60–80% of oropharyngeal squamous cell carcinomas (OPSCCs); while rare, recurrent/metastatic disease accounts for nearly all related deaths. An in vivo pre-clinical model for these invasive cancers is necessary for testing new therapies. We characterize an immune competent recurrent/metastatic HPV+ murine model of OPSSC which consists of four lung metastatic (MLM) cell lines isolated from an animal with HPV+ OPSCC that failed cisplatin/radiation treatment. These individual metastatic clonal cell lines were tested to verify their origin (parental transgene expression and define their physiological properties: proliferation, metastatic potential, heterogeneity and sensitivity/resistance to cisplatin and radiation. All MLMs retain expression of parental HPV16 E6 and E7 and degrade P53 yet are heterogeneous from one another and from the parental cell line as defined by Illumina expression microarray. Consistent with this, reverse phase protein array defines differences in protein expression/activation between MLMs as well as the parental line. While in vitro growth rates of MLMs are slower than the parental line, in vivo growth of MLM clones is greatly enhanced. Moreover, in vivo resistance to standard therapies is dramatically increased in 3 of the 4 MLMs. Lymphatic and/or lung metastasis occurs 100% of the time in one MLM line. This recurrent/metastatic model of HPV+ OPSCC retains the characteristics evident in refractory human disease (heterogeneity, resistance to therapy, metastasis in lymph nodes/lungs) thus serving as an ideal translational system to test novel therapeutics. Moreover, this system may provide insights into the molecular mechanisms of metastasis

CFUI: Collaborative Filtering With Unlabeled Items

As opposed to Web search, social tagging can be considered an alternative technique tapping into the wisdom of the crowd for organizing and discovering information on the Web. Effective tag-based recommendation of information items is critical to the success of this social information discovery mechanism. Over the past few years, there have been a growing number of studies aiming at improving the item recommendation quality of collaborative filtering (CF) methods by leveraging tagging information. However, a critical problem that often severely undermines the performance of tag-based CF methods, i.e., sparsity of user-item and user-tag interactions, is still yet to be adequately addressed. In this paper, we propose a novel learning framework, which deals with this data sparsity problem by making effective use of unlabeled items and propagating users’ preference information between the item space and the tag space. Empirical evaluation using real-world tagging data demonstrates the utility of the proposed framework

A Random Walk Model for Item Recommendation in Social Tagging Systems

Social tagging, as a novel approach to information organization and discovery, has been widely adopted in many Web 2.0 applications. Tags contributed by users to annotate a variety of Web resources or items provide a new type of information that can be exploited by recommender systems. Nevertheless, the sparsity of the ternary interaction data among users, items, and tags limits the performance of tag-based recommendation algorithms. In this article, we propose to deal with the sparsity problem in social tagging by applying random walks on ternary interaction graphs to explore transitive associations between users and items. The transitive associations in this article refer to the path of the link between any two nodes whose length is greater than one. Taking advantage of these transitive associations can allow more accurate measurement of the relevance between two entities (e.g., user-item, user-user, and item-item). A PageRank-like algorithm has been developed to explore these transitive associations by spreading users\u27 preferences on an item similarity graph and spreading items\u27 influences on a user similarity graph. Empirical evaluation on three real-world datasets demonstrates that our approach can effectively alleviate the sparsity problem and improve the quality of item recommendation

Absence of Two-Dimensional Bragg Glasses

The stability to dislocations of the elastic phase, or ``Bragg glass'', of a randomly pinned elastic medium in two dimensions is studied using the minimum-cost-flow algorithm for a disordered fully-packed loop model. The elastic phase is found to be unstable to dislocations due to the quenched disorder. The energetics of dislocations are discussed within the framework of renormalization group predictions as well as in terms of a domain wall picture.Comment: 5 pages, REVTEX, 3 figures included. Further information can be obtained from [email protected]

State of Charge Estimation of Parallel Connected Battery Cells via Descriptor System Theory

This manuscript presents an algorithm for individual Lithium-ion (Li-ion) battery cell state of charge (SOC) estimation when multiple cells are connected in parallel, using only terminal voltage and total current measurements. For battery packs consisting of thousands of cells, it is desirable to estimate individual SOCs by only monitoring the total current in order to reduce sensing cost. Mathematically, series connected cells yield dynamics given by ordinary differential equations under classical full voltage sensing. In contrast, parallel connected cells are evidently more challenging because the dynamics are governed by a nonlinear descriptor system, including differential equations and algebraic equations arising from voltage and current balance across cells. An observer with linear output error injection is formulated, where the individual cell SOCs and local currents are locally observable from the total current and voltage measurements. The asymptotic convergence of differential and algebraic states is established by considering local Lipschitz continuity property of system nonlinearities. Simulation results on LiNiMnCoO$_2$/Graphite (NMC) cells illustrate convergence for SOCs, local currents, and terminal voltage.Comment: 7 pages, 4 figures, 1 table, accepted by 2020 American Control Conferenc

htof::A New Open-source Tool for Analyzing Hipparcos, Gaia, and Future Astrometric Missions

We present htof, an open-source tool for interpreting and fitting the intermediate astrometric data (IAD) from both the 1997 and 2007 reductions of Hipparcos, the scanning-law of Gaia, and future missions such as the Nancy Grace Roman Space Telescope (NGRST). htof solves for the astrometric parameters of any system for any arbitrary combination of absolute astrometric missions. In preparation for later Gaia data releases, htof supports arbitrarily high-order astrometric solutions (e.g. five-, seven-, nine-parameter fits). Using htof, we find that the IAD of 6617 sources in Hipparcos 2007 might have been affected by a data corruption issue. htof integrates an ad-hoc correction that reconciles the IAD of these sources with their published catalog solutions. We developed htof to study masses and orbital parameters of sub-stellar companions, and we outline its implementation in one orbit fitting code (orvara, https://github.com/t-brandt/orvara). We use htof to predict a range of hypothetical additional planets in the $\beta$~Pic system, which could be detected by coupling NGRST astrometry with Gaia and Hipparcos. htof is pip installable and available at https://github.com/gmbrandt/htof .Comment: Accepted to AJ. References updated in version 2. The Hipparcos 2007 Re-reduction Java Tool Intermediate Astrometric Data are available at , via the "zip file" link at https://www.cosmos.esa.int/web/hipparcos/hipparcos-2 : "...human readable version of the IAD of the Java tool in a zip file [warning: ~350 MB]...