ppxscal/embedding_network huggingface dataset:
An approaching genetic algorithm for automatic beam angle selection in IMRT planning
Authors: Jie Lei, Yongjie Li
Venue: Computer Methods and Programs in Biomedicine (2009)

A method named approaching genetic algorithm (AGA) is introduced to automatically select the beam angles for intensity-modulated radiotherapy (IMRT) planning. In AGA, the best individual of the current population is found at first, and the rest of the normal individuals approach the current best one according to some specially designed rules. In the course of approaching, some better individuals may be obtained. Then, the current best individual is updated to try to approach the real best one. The approaching and updating operations of AGA replace the selection, crossover and mutation operations of the genetic algorithm (GA) completely. Using the specially designed updating strategies, AGA can recover the varieties of the population to a certain extent and retain the powerful ability of evolution, compared to GA. The beam angles are selected using AGA, followed by a beam intensity map optimization using conjugate gradient (CG). A simulated case and a clinical case with nasopharynx cancer are employed to demonstrate the feasibility of AGA. For the case investigated, AGA was feasible for the beam angle optimization (BAO) problem in IMRT planning and converged faster than GA.
Topology agnostic hot-spot avoidance with InfiniBand
Authors: Abhinav Vishnu, Matthew Koop, Adam Moody, Amith Mamidala, Sundeep Narravula, Dhabaleswar K. Panda
Venue: Concurrency and Computation: Practice Experience (2009)

InfiniBand has become a very popular interconnect due to its advanced features and open standard. Large-scale InfiniBand clusters are becoming very popular, as reflected by the TOP 500 supercomputer rankings. However, even with popular topologies such as constant bi-section bandwidth Fat Tree, hot-spots may occur with InfiniBand due to inappropriate configuration of network paths, presence of other jobs in the network and un-availability of adaptive routing. In this paper, we present a hot-spot avoidance layer (HSAL) for InfiniBand, which provides hot-spot avoidance using path bandwidth estimation and multi-pathing using LMC mechanism, without taking the network topology into account. We propose an adaptive striping policy with batch-based striping and sorting approach, for efficient utilization of disjoint network paths. Integration of HSAL with MPI, the de facto programming model of clusters, shows promising results with collective communication primitives and MPI applications. Copyright &copy; 2008 John Wiley & Sons, Ltd.
Effective temporal data classification by integrating sequential pattern mining and probabilistic induction
Authors: Vincent S. Tseng, Chao-Hui Lee
Venue: Expert Systems with Applications: An International Journal (2009)

Data classification is an important topic in the field of data mining due to its wide applications. A number of related methods have been proposed based on the well-known learning models such as decision tree or neural network. Although data classification was widely discussed, relatively few studies explored the topic of temporal data classification. Most of the existing researches focused on improving the accuracy of classification by using statistical models, neural network, or distance-based methods. However, they cannot interpret the results of classification to users. In many research cases, such as gene expression of microarray, users prefer the classification information above a classifier only with a high accuracy. In this paper, we propose a novel pattern-based data mining method, namely classify-by-sequence (CBS), for classifying large temporal datasets. The main methodology behind the CBS is integrating sequential pattern mining with probabilistic induction. The CBS has the merit of simplicity in implementation and its pattern-based architecture can supply clear classification information to users. Through experimental evaluation, the CBS was shown to deliver classification results with high accuracy under two real time series datasets. In addition, we designed a simulator to evaluate the performance of CBS under datasets with different characteristics. The experimental results show that CBS can discover the hidden patterns and classify data effectively by utilizing the mined sequential patterns.
Learning goes global
Authors: Samuel Greengard
Venue: Communications of the ACM (2009)

In a world that's increasingly global and interconnected, international education is growing, changing, and evolving.
An Improved Differential Evolution Based on Triple Evolutionary Strategy
Authors: Yichao He, Yingzhan Kou, Chunpu Shen
Venue: Proceedings of the 3rd International Symposium on Advances in Computation and Intelligence (2008)

Differential Evolution (DE) is an evolution algorithm that was proposed by Storn and Price in 1997, which has already succeeded in applying to solve optimization questions in a lot of fields. This paper discusses various kinds of characteristics that DE demonstrates at first, then propose an improved differential evolution algorithm (TSDE) which has three kinds of efficiently evolutionary strategies, and proves its global convergence property use the finite Markov chain theory. Through the compare result of calculation of 5 classics testing functions, it shows that TSDE has the obvious advantage in the quality of solution, adaptability, robustness etc. than original DE and DEfirDE.
Does Quantum Mechanics Need Interpretation?
Authors: Louis Marchildon
Venue: Proceedings of the 2009 Third International Conference on Quantum, Nano and Micro Technologies (2009)

Since the beginning, quantum mechanics has raised major foundational and interpretative problems. Foundational research has been an important factor in the development of quantum cryptography, quantum information theory and, perhaps one day, practical quantum computers. Many believe that, in turn, quantum information theory has bearing on foundational research. This is largely related to the so-called epistemic view of quantum states, which maintains that the state vector represents information on a system and has led to the suggestion that quantum theory needs no interpretation. I will argue that this and related approaches fail to take into consideration two different explanatory functions of quantum mechanics, namely that of accounting for classically unexplainable correlations between classical phenomena and that of explaining the microscopic structure of classical objects. If interpreting quantum mechanics means answering the question, "How can the world be for quantum mechanics to be true?", there seems to be no way around it.
New lower bounds based on column generation and constraint programming for the pattern minimization problem
Authors: Cláudio Alves, Rita Macedo, José Valério de Carvalho
Venue: Computers and Operations Research (2009)

The pattern minimization problem is a cutting and packing problem that consists in finding a cutting plan with the minimum number of different patterns. This objective may be relevant when changing from one pattern to another involves a cost for setting up the cutting machine. When the minimization of the number of different patterns is done by assuming that no more than the minimum number of rolls can be used, the problem is also referred to as the cutting stock problem with setup costs. Most of the approaches described in the literature are based on heuristics. Solving the problem exactly has been a real challenge, and only very few exact solution methods have been reported so far in the literature. In this paper, we intend to contribute to the resolution of the pattern minimization problem with new results. We explore a different integer programming model that can be solved using column generation, and we describe different strategies to strengthen it, among which are constraint programming and new families of valid inequalities. Lower bounds for the pattern minimization problem are derived from the new integer programming model, and also from a constraint programming model. Our approaches were tested on a set of real instances, and on a set of random instances from the literature. For these instances, the computational experiments show a clear improvement on the quality of the lower bounds.
Using video and static pictures to improve learning of procedural contents
Authors: Amaël Arguel, Eric Jamet
Venue: Computers in Human Behavior (2009)

Animations and videos are often designed to present information that involves change over time, in such a way as to aid understanding and facilitate learning. However, in many studies, static displays have been found to be just as beneficial and sometimes better. In this study, we investigated the impact of presenting together both a video recording and a series of static pictures. In experiment 1, we compared 3 conditions (1) video shown alone, (2) static pictures displayed alone, and (3) video plus static pictures. On average the best learning scores were found for the 3rd condition. In experiment 2 we investigated how best to present the static pictures, by examining the number of pictures required (low vs. high frequency) and their appearance type (static vs. dynamic). We found that the dynamic presentation of pictures was superior to the static pictures mode; and showing fewer pictures (low frequency) was more beneficial. Overall the findings support the effectiveness of a combination of instructional animation with static pictures. However, the number of static pictures, which are used, is an important moderating factor.
Customizable Business Process Composition with Query Optimization
Authors: Krishna Raman, Yue Zhang, Mark Panahi, Kwei-Jay Lin
Venue: Proceedings of the 2008 10th IEEE Conference on E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services (2008)

One of the challenges in SOA is to provide an efficient and effective way to select compatible Web service(s) and compose them into a functional service process that satisfies a user's needs. Moreover, the Web services(s) selected may be integrated with structures such as branches and merges to fulfill a task. This paper describes our system architecture and strategies on Web services composition based on semantic matching. Our strategies include customizable and adaptive composition strategy, query optimization, and heuristic prioritization.
Local PTAS for Dominating and Connected Dominating Set in Location Aware Unit Disk Graphs
Authors: Andreas Wiese, Evangelos Kranakis
Venue: Approximation and Online Algorithms: 6th International Workshop, WAOA 2008, Karlsruhe, Germany, September 18-19, 2008. Revised Papers (2009)

We present local 1&thinsp;+&thinsp;&epsilon; approximation algorithms for the minimum dominating and the connected dominating set problems in location aware Unit Disk Graphs (UDGs). Our algorithms are local in the sense that the status of a vertex v in the output (i.e. whether or not v is part of the set to be computed) depends only on the vertices which are a constant number of edges (hops) away from v. This constant is independent of the size of the network. In our graph model we assume that each vertex knows its geographic coordinates in the plane (location aware nodes). Our algorithms give the best approximation ratios known for this setting. Moreover, the processing time that each vertex needs to determine whether or not it is part of the computed set is bounded by a polynomial in the number of vertices which are a constant number of hops away from it. We employ a new method for constructing the connected dominating set and we give the first analysis of trade-offs between approximation ratio and locality distance.
Impact of media richness and flow on e-learning technology acceptance
Authors: Su-Houn Liu, Hsiu-Li Liao, Jean A. Pratt
Venue: Computers Education (2009)

Advances in e-learning technologies parallels a general increase in sophistication by computer users. The use of just one theory or model, such as the technology acceptance model, is no longer sufficient to study the intended use of e-learning systems. Rather, a combination of theories must be integrated in order to fully capture the complexity of e-learners, who are both system users and learners. The current research presents an integrated theoretical framework to study users' acceptance of streaming media for e-learning. Three streams of research provide the basis for this integrated framework: the technology acceptance model, flow theory and media richness theory. Students enrolled in an online section of an information systems course used one of three different combinations of text, streamed audio and streamed video. Regression analysis was used to test the hypotheses in this field experiment. Perceived ease of use was a predictor of perceived usefulness; both the perceived usefulness and the attitude of the user were predictors of intention to use. Richer content-presentation types were positively correlated with higher concentration levels but showed mixed results when correlated with perceived usefulness. Results from this study have practical implications for those interested in integrating streaming media into e-learning.
VIFI-CMP: variability-tolerant chip-multiprocessors for throughput and power
Authors: Wan-Yu Lee, Iris Hui-Ru Jiang
Venue: Proceedings of the 19th ACM Great Lakes symposium on VLSI (2009)

This paper proposes a new architecture of variability-tolerant chip-multiprocessor. To mitigate the impact of process variability on throughput and power, voltage and frequency islands are introduced into chip-multiprocessors. Thus, voltage island frequency island chip-multiprocessors enable per-core scaling on the supply voltage and operating frequency. It can naturally collaborate with dynamic voltage frequency scaling. The process variations are characterized through an analytical model, and are quantified through Monte Carlo analysis. Compared with the design without process variations, when 70 threads are run on a chip of 70 small cores, our results show throughput degradation is 0.06%, while power reduction is 36.27%.
A traffic load-aware energy efficient protocol for wireless sensor networks
Authors: I-Hui Li, I-En Liao, Feng-Nien Wu
Venue: Proceedings of the International Conference on Mobile Technology, Applications, and Systems (2008)

With the improvement of miniaturized fabrication and battery technologies, the topic of deploying a wireless sensor network which uses tiny sensors with the abilities of detecting environmental factors and processing data is getting more and more important for different environments and applications. However, the resource limitation in a sensor brings out an important issue. The challenges for saving energy and thus extending the lifespan of a sensor are conceivable. This paper proposes a protocol involving multi-hops and self-organization of routing paths. The method, using time division with reservation scheduling, reduces energy consumption and prevents packet collisions. The routing decision takes the transmission cost, the battery status and the traffic load into consideration. This yields efficient routings and results in energy savings in sensors. The experimental results show the system's lifespan is extended dramatically and the system is quite robust under different environmental parameters.
Career education in business data processing teacher education
Authors: Joe M. Kinzer,  Jr.
Venue: Proceedings of the May 6-10, 1974, national computer conference and exposition (1974)

The career path for teachers of business data processing has virtually been non-existent in the State of Oklahoma. Higher education institutions, however, have offered some coursework in data processing since 1958. Most of these courses were designed for scientific applications oriented toward the physicist and engineer. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Efficient RFID authentication protocols based on pseudorandom sequence generators
Authors: Jooyoung Lee, Yongjin Yeom
Venue: Designs, Codes and Cryptography (2009)

In this paper, we introduce a new class of PRSGs, called partitioned pseudorandom sequence generators(PPRSGs), and propose an RFID authentication protocol using a PPRSG, called S-protocol. Since most existing stream ciphers can be regarded as secure PPRSGs, and stream ciphers outperform other types of symmetric key primitives such as block ciphers and hash functions in terms of power, performance and gate size, S-protocol is expected to be suitable for use in highly constrained environments such as RFID systems. We present a formal proof that guarantees resistance of S-protocol to desynchronization and tag-impersonation attacks. Specifically, we reduce the availability of S-protocol to pseudorandomness of the underlying PPRSG, and the security of the protocol to the availability. Finally, we give a modification of S-protocol, called S*-protocol, that provides mutual authentication of tag and reader.
The Symbiotic Relationship between Coal Mining Machinery Enterprises and Coal Mining Enterprises in China
Authors: Fei Wang
Venue: Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining (2009)

This article used VAR model to analyze and verify the symbiosis between Chinese coal mining machinery enterprises and coal mining enterprises from the perspective of static state and dynamic state, it concluded that: there is a co-integration relationship between the actual output value of Chinese coal mining machinery enterprises and the actual value of Chinese coal mining enterprises, namely, there is a long-term and stable equilibrium; Chinese coal mining machinery enterprises have advanced the development of Chinese coal mining enterprises, while the development of Chinese coal mining enterprises also have played a significant role in promoting Chinese coal mining machinery enterprises; in the short term, the changes of the actual output value of Chinese coal mining machinery enterprises are due to themselves as well as the actual output value of Chinese coal mining enterprises, and the changes of actual output value of Chinese coal mining enterprises are also due to themselves and the actual output value of Chinese coal mining machinery enterprises.
State-dependent computation using coupled recurrent networks
Authors: Ueli Rutishauser, Rodney J. Douglas
Venue: Neural Computation (2009)

Although conditional branching between possible behavioral states is a hallmark of intelligent behavior, very little is known about the neuronal mechanisms that support this processing. In a step toward solving this problem, we demonstrate by theoretical analysis and simulation how networks of richly interconnected neurons, such as those observed in the superficial layers of the neocortex, can embed reliable, robust finite state machines. We show how a multistable neuronal network containing a number of states can be created very simply by coupling two recurrent networks whose synaptic weights have been configured for soft winner-take-all (sWTA) performance. These two sWTAs have simple, homogeneous, locally recurrent connectivity except for a small fraction of recurrent cross-connections between them, which are used to embed the required states. This coupling between the maps allows the network to continue to express the current state even after the input that elicited that state is withdrawn. In addition, a small number of transition neurons implement the necessary input-driven transitions between the embedded states. We provide simple rules to systematically design and construct neuronal state machines of this kind. The significance of our finding is that it offers a method whereby the cortex could construct networks supporting a broad range of sophisticated processing by applying only small specializations to the same generic neuronal circuit.
Building a terminology network for search: the KoMoHe project
Authors: Philipp Mayr, Vivien Petras
Venue: Proceedings of the 2008 International Conference on Dublin Core and Metadata Applications (2008)

The paper reports about results on the GESIS-IZ project "Competence Center Modeling and Treatment of Semantic Heterogeneity" (KoMoHe). KoMoHe supervised a terminology mapping effort, in which 'cross-concordances' between major controlled vocabularies were organized, created and managed. In this paper we describe the establishment and implementation of cross-concordances for search in a digital library (DL).
A low-order markov model integrating long-distance histories for collaborative recommender systems
Authors: Geoffray Bonnin, Armelle Brun, Anne Boyer
Venue: Proceedings of the 13th international conference on Intelligent user interfaces (2009)

Recommender systems provide users with pertinent resources according to their context and their profiles, by applying statistical and knowledge discovery techniques. This paper describes a new approach of generating suitable recommendations based on the active user's navigation stream, by considering long and short-distance resources in the history with a tractable model. The Skipping Based Recommender we propose uses Markov models inspired from the ones used in language modeling while integrating skipping techniques to handle noise during navigation. Weighting schemes are also used to alleviate the importance of distant resources. This recommender has also the characteristic to be anytime. It has been tested on a browsing dataset extracted from Intranet logs provided by a French bank. Results show that the use of exponential decay weighting schemes when taking into account non contiguous resources to compute recommendations enhances the accuracy. Moreover, the skipping variant we propose provides a high accuracy while being less complex than state of the art variants.
Level-4 SaaS applications for healthcare industry
Authors: Anand V. Hudli, Balasubrahmanya Shivaradhya, Raghu V. Hudli
Venue: Proceedings of the 2nd Bangalore Annual Compute Conference (2009)

Software applications and solutions as Software as a Service (SaaS) has been gaining momentum all over the world in recent times. In the SaaS context, applications are hosted by the vendor using the vendor's IT infrastructure. Most SaaS applications are web-based. What separates SaaS application from multi-user web-based applications are SaaS is not just a web-front to a back-end application as in a bank's application. SaaS is not just a multi-user application, but multi-tenant application. Each customer organization is a tenant in a SaaS application. Multiple customer organizations may use the same application and each organization may have multiple users. Four levels of SaaS application maturity have been defined in the literature. A Level 4 SaaS application supports multiple tenants with a multiple but identical instances of the application and a metadata configuration of the application and offers superior ability to scale and handle large volumes of traffic and transactions. In this paper we present a SaaS application, addressing all issues involved in a Level 4 SaaS application. We have chosen the healthcare industry as a business context, as it has multiple players. Multi-tenant is a natural phenomenon on such a context. We have recognized that while SaaS may offer a business solution to a customer, it still needs to integrate with other business applications and workflows. We provide integration case studies in a SaaS Context. We also discuss security issues in a SaaS context. We present a multi-key secure encryption model to secure user data and a fully user defined Role Based Access Control model.