ppxscal/embedding_network huggingface dataset:
The ongoing challenge: an accurate assessment of supply linked to demand to create an enterprise-wide end to end detailed central supply chain plan
Authors: Ken Fordyce, Alfred Degbotse, John Milne, Robert Orzell, Chi-Tai Wang
Venue: Proceedings of the 40th Conference on Winter Simulation (2008)

Organizations can be viewed as an ongoing sequence of loosely coupled decisions where current and future assets are matched with current and future demand across the demand-supply network at different levels of granularity ranging from a placing a lot on a tool to an aggregate capacity plan across a five year horizon. Since the early 1990s detailed enterprise wide central planning has become a key member of this "decision suite." Despite its importance, most organizations execute central planning with "limited levels of accuracy or intelligence." Early in the evolution of "central planning engines" IBM determined that "extended accuracy" was an important component of supply chain efficiency and customer satisfaction and made a substantial investment to develop a central planning engine which could handle the scope (complexity) and scale (size) of large organizations. This paper covers the value from this investment and the technical details of combining heuristics and optimization.
An Automata-Theoretic Dynamic Completeness Criterion for Bounded Model-Checking
Authors: Rotem Oshman
Venue: Proceedings of the 10th International Conference on Verification, Model Checking, and Abstract Interpretation (2008)

Bounded model-checking is a technique for finding bugs in very large designs. Bounded model-checking by itself is incomplete: it can find bugs, but it cannot prove that a system satisfies a specification. A dynamic completeness criterion can allow bounded model-checking to prove properties. A dynamic completeness criterion typically searches for a "beginning" of a bug or bad behavior; if no such "beginning" can be found, we can conclude that no bug exists, and bounded model-checking can terminate. Dynamic completeness criteria have been suggested for several temporal logics, but most are tied to a specific bounded model-checking encoding, and the ones that are not are based on nondeterministic Büchi automata. In this paper we develop a theoretic framework for dynamic completeness criteria based on alternating Büchi automata. Our criterion generalizes and explains several existing dynamic completeness criteria, and is suitable for both linear-time and universal branching-time logic. We show that using alternating automata rather than nondeterministic automata can lead to much smaller completeness thresholds.
Partitions weighted by the parity of the crank
Authors: Dohoon Choi, Soon-Yi Kang, Jeremy Lovejoy
Venue: Journal of Combinatorial Theory Series A (2009)

The 'crank' is a partition statistic which originally arose to give combinatorial interpretations for Ramanujan's famous partition congruences. In this paper, we establish an asymptotic formula and a family of Ramanujan type congruences satisfied by the number of partitions of n with even crank M"e(n) minus the number of partitions of n with odd crank M"o(n). We also discuss the combinatorial implications of q-series identities involving M"e(n)-M"o(n). Finally, we determine the exact values of M"e(n)-M"o(n) in the case of partitions into distinct parts. These values are at most two, and zero for infinitely many n.
Efficient Polyhedral Modeling from Silhouettes
Authors: Jean-Sébastien Franco, Edmond Boyer
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

Modeling from silhouettes is a popular and useful topic in computer vision. Many methods exist to compute the surface of the visual hull from silhouettes, but few address the problem of ensuring sane topological properties of the surface, such as manifoldness. This article provides an efficient algorithm to compute such a surface in the form of a polyhedral mesh. It relies on a small number of geometric operations to compute a visual hull polyhedron in a single pass. Such simplicity enables the algorithm to combine the advantages of being fast, producing pixel-exact surfaces, and repeatably yield manifold and watertight polyhedra in general experimental conditions with real data, as verified with all datasets tested. The algorithm is fully described, its complexity analyzed and modeling results given.
On-line Signature Verification: An Approach Based on Cluster Representations of Global Features
Authors: D. S. Guru, H. N. Prakash, S. Manjunath
Venue: Proceedings of the 2009 Seventh International Conference on Advances in Pattern Recognition (2009)

In this paper, we propose a new method of representation of on-line signatures by clustering of signatures. Our idea is to provide better representation by clustering of signatures based on global features. Global features of signatures of each cluster are used to form an interval valued feature vector which is a symbolic representation for a cluster. Based on cluster representation, we propose methods of signature verification. We compare the feasibility of the proposed representation scheme for signature verification on a large MCYT_ signature database of 16500 signatures. Unlike other signature verification methods, the proposed method is simple and efficient and in addition, shows a remarkable reduction in EER.
Learning from planner performance
Authors: Mark Roberts, Adele Howe
Venue: Artificial Intelligence (2009)

The planning community has amassed a large body of publicly available problems in a standardized input language and planners that accept the language. We seized this remarkable opportunity to collect data about how some of these planners perform on the benchmark problems. We analyzed the resulting data to learn about the state of the art in Classical planning. Our analyses are retrospective, prescriptive and prospective. The first analyses are retrospective and prescriptive in that they characterize the problems and planners in terms of difficulty, diversity and trends over time. We statistically confirm that problem sets have become more difficult and that new planners are generally more capable. A visualization of planner success on domains shows how the domains distinguish performance. We also assess whether some older planners can be disregarded as out-dated and find that while they are not up to current capabilities, some do provide limited distinct functionality. The second analyses automatically learn models of success and time for each planner. The models are constructed from easily extracted features of problems and domains and use off-the-shelf Machine Learning techniques. We find the models of success to be extremely accurate, but the models of time to be less so. They too are both retrospective and prescriptive in demonstrating the predictability of current planner performance. In a third analysis, we apply the data to an existing explanatory model linking the relationship between the search space and planner performance. Our study validates previous results linking search topology with planner performance on a wider set of planners than the original study. Finally, we fill in some gaps in observed performance of the benchmark problems by constructing new problems; these problems do turn out to be more challenging. This study of existing and new problems and planners is prescriptive and prospective in that the results should help guide researchers in comparatively evaluating their planners and suggest need for additional effort. These analyses highlight the importance of problems in driving research in planning. We show how much can be accomplished with the available resources and point out how much more can be done by broadening the problems available and by learning from what has already been done.
Creative self-efficacy and its factors: An empirical study of information system analysts and programmers
Authors: Heng-Li Yang, Hsiu-Hua Cheng
Venue: Computers in Human Behavior (2009)

Based on a survey of 94 information systems developers, this study explored how personal factors (i.e. computer self-efficacy and domain-specific information technology skills), contextual factors (i.e. strength of ties and degree centrality) and creative self-efficacy are related. Regression analysis results demonstrate that system analysts and programmers differ in terms of influencing factors on creative self-efficacy. Domain-specific skills were the main influence in the system analyst model, followed by degree centrality. In comparison, degree centrality was the only influence in the programmer model. Degree centrality exerted a negative influence in both groups. Additionally, among system analysts, the strength of ties slightly influenced creative self-efficacy, while computer self-efficiency and domain-specific information technology skills exerted only small influences on programmers.
Professional Office Business Application Development: Using Microsoft Office SharePoint Server 2007 and VSTO (Wrox Programmer to Programmer)
Authors: Steve Fox, Bill Sheldon
Venue:  (2008)

Office Business Application (OBA) development is new and growing at a rapid pace as large companies discover its importance. This book provides you with insight into how organizations can leverage OBA. Youll go on an in-depth journey to learning how to use various tools to bridge the gap between business data and the people who need it. Plus, youll gain an extensive understanding on building and deploying OBA via a common scenario and that is broken down so that you can learn each component.
Innovative concept of open source enterprise resource planning (ERP) system
Authors: Svilen Valkov
Venue: Proceedings of the 9th International Conference on Computer Systems and Technologies and Workshop for PhD Students in Computing (2008)

This paper introduces a new concept for open source business software development, collaboration structure, business models and metadata system. The commercial business software models of today are out-dated and although the Enterprise Resource Planning (ERP) market is ruled by a few key players they are facing lots of unresolved problems. The proposed ERP open collaboration concept is a summary of a complete solution based on business models (UML diagrams and metadata) that are saved in database and parsed by business engine to generate data layer, business logic objects and user interfaces.
High Capacity Reversible Data Hiding for 3D Meshes in the PVQ Domain
Authors: Zhe-Ming Lu, Zhen Li
Venue: Proceedings of the 6th International Workshop on Digital Watermarking (2008)

In the digitized world nowadays, digital content (audio, images, video, 3D meshes, etc.) can be easily copied, manipulated and distributed. Copyright protection and integrity verification of digital content have become urgent problems for multimedia owners and distributors. In addition, to alleviate bandwidth requirements, vector quantization (VQ) is an effective and popular vertex data compression technique for triangle meshes. In this paper, we present a new data hiding method for 3D triangle meshes in the predictive VQ domain. The proposed method is reversible and enables the cover mesh data to be completely restored when the payload is removed from the VQ bitstream. The mechanism is embedding the payload by modifying the prediction rules during the VQ process. Besides, the hash of the cover mesh can be hidden for the self authentication purpose. Experimental results demonstrate the high capacity of the proposed data hiding scheme.
Privacy-Preserving Hierarchical-k-means Clustering on Horizontally Partitioned Data
Authors: Anrong Xue, Dongjie Jiang, Shiguang Ju, Weihe Chen, Handa Ma
Venue: International Journal of Distributed Sensor Networks (2009)

Privacy preserving mining of distributed data is an important direction for data mining, and privacy preserving clustering is one of the main researches. Privacy-preserving data mining techniques enable knowledge discovery without requiring disclosure of private data. The existing privacy preserving algorithms mainly concentrated on association rules and classification, only few algorithms on privacy preserving clustering, and these algorithms mainly concentrated on centralized and vertically partitioned data. So we proposed privacy preserving hierarchical k-means clustering algorithm on horizontally partitioned data, denoted as HPPHKC. The complexity on k-means clustering algorithm is only O(n), so most existing privacy preserving clustering algorithms are concentrated on k-means and based on two parties and the trusted third party, these algorithms have the drawbacks of inaccurate results because of choosing initial clustering centers randomly and applying to multi-party difficult and revealing privacy because of depending on the third party excessively. By introduction of three protocols for secure multi-party computation: distance computation, cluster center computation, and standardization and combination of the merits of hierarchical and k-means clustering, we presented a privacy-preserving hierarchical-k-means clustering algorithm on horizontally partitioned data for semi-honest parties using some secure multi-party computation protocols. The algorithm uses the security protocol mentioned above to achieve the protection of the privacy data, and uses the hierarchical clustering algorithm to obtain k cluster centers, then uses the k-means clustering algorithm to obtain the final k clusters. We introduce the clustering feature and the clustering feature tree, which are used to summarize the cluster representations. A clustering feature (CF) is a three-dimensional vector summarizing information about clusters of objects. The ith clustering feature is CFi = (cni,cci,cpi), where cni is the number of ith clusters, denoted as the size of ith cluster, cci is the center of the cni objects, and cpi is the pointer of the list of cni objects. The algorithm has two phases: the first phase, every object can be as a cluster, a secure computation protocol is used to compute the dissimilarity matrix and the most similar clusters will be merged. This process is repeated until we get the assigned clusters number k and get k clustering centers. In the second phase, the semi-honest third party and all data involved parties use the k-means algorithm refine the results of the first phase and get the final clustering results. Finally, we give the proof of security of the algorithm and analysis of communication costs, and we show that our scheme is secure and complete with good efficiency.
Reconfigurable NoC design flow for multiple applications run-time mapping on FPGA devices
Authors: Dario Cozzi, Claudia Farè, Alessandro Meroni, Vincenzo Rana, Marco Domenico Santambrogio, Donatella Sciuto
Venue: Proceedings of the 19th ACM Great Lakes symposium on VLSI (2009)

Dynamic reconfiguration capabilities exploited by modern FPGA devices improve the flexibility and the reliability of embedded systems. The increasing complexity demands for a design-paradigm shift towards a communication-centric approach. Networks-on-Chip are a promising design paradigm for both homogeneous and heterogeneous systems in which communication is represented in a network-like manner, even if they cannot directly be applied to the dynamic reconfiguration scenario. While in literature there are different approaches to design communication infrastructures able to support the reconfiguration of its functionalities, what seems to be neglected is the definition of a complete design flow for a dynamic reconfigurable communication infrastructure able to adapt itself at runtime to the current working scenario. This paper proposes a design flow to automatically create a reconfigurable architecture that consists of a grid of homogeneous tiles that can be filled with either computational (master or slave cores with their network interfaces) or communication (switches) elements.
Efficient and scalable multiprocessor fair scheduling using distributed weighted round-robin
Authors: Tong Li, Dan Baumberger, Scott Hahn
Venue: ACM SIGPLAN Notices (2009)

Fairness is an essential requirement of any operating system scheduler. Unfortunately, existing fair scheduling algorithms are either inaccurate or inefficient and non-scalable for multiprocessors. This problem is becoming increasingly severe as the hardware industry continues to produce larger scale multi-core processors. This paper presents Distributed Weighted Round-Robin (DWRR), a new scheduling algorithm that solves this problem. With distributed thread queues and small additional overhead to the underlying scheduler, DWRR achieves high efficiency and scalability. Besides conventional priorities, DWRR enables users to specify weights to threads and achieve accurate proportional CPU sharing with constant error bounds. DWRR operates in concert with existing scheduler policies targeting other system attributes, such as latency and throughput. As a result, it provides a practical solution for various production OSes. To demonstrate the versatility of DWRR,we have implemented it in Linux kernels 2.6.22.15 and 2.6.24, which represent two vastly different scheduler designs. Our evaluation shows that DWRR achieves accurate proportional fairness and high performance for a diverse set of workloads.
Teaching about threading: where and what?
Authors: Alan D. Fekete
Venue: ACM SIGACT News (2009)

Trends in hardware and software are increasing the importance of concurrent programming, in the skill set expected of graduates. The curriculum is fairly full already, so teachers face complicated trade-offs in deciding how to incorporate additional material related to concurrency. In this paper we discuss some of the different ways to cover thread programming; we also survey the literature on this topic from the Computing Education community.
Embedded lattices tree: An efficient indexing scheme for content based retrieval on image databases
Authors: Mahmoud Mejdoub, Leonardo Fonteles, Chokri BenAmar, Marc Antonini
Venue: Journal of Visual Communication and Image Representation (2009)

One of the challenges in the development of a content-based multimedia indexing and retrieval application is to achieve an efficient indexing scheme. To retrieve a particular image from a large scale image database, users can be frustrated by the long query times. Conventional indexing structures cannot usually cope with the presence of a large amount of feature vectors in high-dimensional space. This paper addresses such problems and presents a novel indexing technique, the embedded lattices tree, which is designed to bring an effective solution especially for realizing the trade off between the retrieval speed up and precision. The embedded lattices tree is based on a lattice vector quantization algorithm that divides the feature vectors progressively into smaller partitions using a finer scaling factor. The efficiency of the similarity queries is significantly improved by using the hierarchy and the good algebraic and geometric properties of the lattice. Furthermore, the dimensionality reduction that we perform on the feature vectors, translating from an upper level to a lower one of the embedded tree, reduces the complexity of measuring similarity between feature vectors. In addition, it enhances the performance on nearest neighbor queries especially for high dimensions. Our experimental results show that the retrieval speed is significantly improved and the indexing structure shows no sign of degradations when the database size is increased.
Design of interpretable fuzzy rule-based classifiers using spectral analysis with structure and parameters optimization
Authors: Alexandre G. Evsukoff, Sylvie Galichet, Beatriz S. L. P. de Lima, Nelson F. F. Ebecken
Venue: Fuzzy Sets and Systems (2009)

This paper presents a design method for fuzzy rule-based systems that performs data modeling consistently according to the symbolic relations expressed by the rules. The focus of the model is the interpretability of the rules and the model's accuracy, such that it can be used as tool for data understanding. The number of rules is defined by the eigenstructure analysis of the similarity matrix, which is computed from data. The rule induction algorithm runs a clustering algorithm on the dataset and associates one rule to each cluster. Each rule is selected among all possible combinations of one-dimensional fuzzy sets, as the one nearest to a cluster's center. The rules are weighted in order to improve the classifier performance and the weights are computed by a bounded quadratic optimization problem. The model complexity is minimized in a structure selection search, performed by a genetic algorithm that selects simultaneously the most representative subset of variables and also the number of fuzzy sets in the fuzzy partition of the selected variables. The resulting model is evaluated on a set of benchmark datasets for classification problems. The results show that the proposed approach produces accurate and yet compact fuzzy classifiers. The resulting model is also evaluated from an interpretability point of view, showing how the rule weights provide additional information to help data understanding and model exploitation.
Design and implementation of video conference system over the hybrid peer-to-peer networks
Authors: Hyen Ki Kim
Venue: Proceedings of the 12th WSEAS international conference on Computers (2008)

This paper describes the design and implementation of video conference system over the hybrid type peer-to-peer networks. The proposed video conference system has hybrid type Peer to Peer networks based on a client-server and peer-to-peer, where client-server is used for exchange of account management, client list and status information and peer-to-peer is used for the real time video conference. The proposed video conference system decreases the traffic of server, and can cuts down the load of a networks. Because the multimedia data is decentralized to client by hybrid peer-to-peer networks. Also, the proposed system is implemented and tested by the multi-party video conference system using communication protocol and application software through high speed networks.
NBTI-aware sleep transistor design for reliable power-gating
Authors: Andrea Calimera, Enrico Macii, Massimo Poncino
Venue: Proceedings of the 19th ACM Great Lakes symposium on VLSI (2009)

Negative Bias Temperature Instability (NBTI) has been regarded as most important source of reliability of CMOS devices, and specifically pMOS transistors. In this work we focus on the NBTI-induced degradation of sleep transistor cells More in details we present a practical SPICE-based analysis framework for evaluating delay degradation of power-gated circuits due to NBTI-induced current capability reducing of pMOS sleep transistor. We also describe three NBTI-tolerant pMOS sleep transistor cell design approaches, in which the V<<sub>i>th</i></sub> increase due to NBTI is compensated through (i) sleep-transistor over-sizing, (ii) forward-body-biasing, (iii) equivalent 0-probability reduction of the sleep-transistor driving signal. Characterization results on a commercial 45nm CMOS technology define fundamental guide-lines to be used during NBTI-aware sleep-transistor design, while experiments on an industrial benchmark highlight the importance of considering NBTI effect on pMOS sleep transistor design, emphasizing the effectiveness of the proposed design methodologies: <i>more than 85% of time-life extension.</i>