ppxscal/embedding_network huggingface dataset:
A Look at Typical Difficulties in Practical Software Development from the Developer Perspective--A Field Study and a First Solution Proposal with UPEX
Authors: Ivonne Erfurth, Wilhelm R. Rossak
Venue: Proceedings of the 14th Annual IEEE International Conference and Workshops on the Engineering of Computer-Based Systems (2007)

In the first part of this paper we summarize the results of a questionnaire for software professionals which we, the Software Engineering Group at Friedrich-Schiller- University Jena, handed out to (local) small and medium-sized IT businesses. The questionnaire targeted the true state of the art in practical software development with a focus on questions regarding the benefits and drawbacks of standard methodologies and all forms of user participation in such an environment. Especially interesting for us was the degree of customer integration into the development process, the understandability of used notations from the developer and user perspective, and the possible reasons for difficulties in the interaction between customer and developer teams. In the second part we present a first look at the UPEX methodology which takes into account the results of the questionnaire.
Constructing optimal wavelet basis for image compression
Authors: Yan Zhuang
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

We study the problem of choosing an image based optimal wavelet basis with compact support for image data compression and provide a general algorithm for computing the optimal wavelet basis. We parameterize the mother wavelet and scaling function of wavelet systems through a set of real coefficients of the relevant quadrature mirror filter (QMF) banks. We further introduce decomposition entropy as an information measure to describe the distance between a given digital image and its projection into the subspace spanned by the wavelet basis. The optimal basis for the given image is obtained through minimizing this information measure. The resulting subspace is used for image analysis and synthesis. Experiments show improved compression ratios due to the application of the optimal wavelet basis and demonstrate the potential applications of our methodology in image compression. This method is also useful for constructing efficient wavelet based image coding systems.
Event-driven rules for sensing and responding to business situations
Authors: Josef Schiefer, Szabolcs Rozsnyai, Christian Rauscher, Gerd Saurer
Venue: Proceedings of the 2007 inaugural international conference on Distributed event-based systems (2007)

Event-based systems have been developed and used to implement networked and adaptive business environments based on loosely coupled systems in order to respond faster to critical business events. In this paper, we introduce a rule management system which is able to sense and evaluate events in order to respond to changes in a business environment or customer needs. It enables users to graphically compose comprehensive event-triggered rules, which can be used to control the processing of services. For the definition of a rule set, users can independently define event conditions, event patterns and correlation-related information which can be combined for modeling complex business situations. We have fully implemented the proposed system with a service-oriented approach and illustrate our approach with an order management business case.
Hierarchical Agent System for Web-Based Sensor Network
Authors: Tokihiro Fukatsu, Takuji Kiura, Kei Tanaka, Masayuki Hirafuji
Venue: Proceedings of the 2007 International Symposium on Applications and the Internet Workshops (2007)

To achieve a smart sensor network with Web-based sensor nodes such as Field Servers, we propose a hierarchical agent system that manages sensor nodes autonomously and flexibly, and acts as an intelligent module of the sensor network. Our agent can treat Web applications in addition to sensor nodes and is a Web application itself; thus, it can control other agents hierarchically. This hierarchical structure provides the Web-based sensor network with high scalability and robustness. The leaf node of our agent system, called the Field Server Agent Box, is equipped with an agent system, a Web interface, a storage function, and data viewers. It can be used with Web-based sensor nodes at sites where an Internet connection is not available. In this study, we also examine the leaf node's scalability.
Antipatterns in the Creation of Intelligent Systems
Authors: Phil Laplante, Robert R. Hoffman, Gary Klein
Venue: IEEE Intelligent Systems (2007)

Shortly after the notion of design patterns emerged, practitioners began discussing problem-solution pairs in which the solution did more harm than good. These have come to be known as antipatterns. The authors describe two existing classes of antipatterns related to human-centered computing: programming development and architecture. They then propose two new classes: procurement and unintelligent systems.
SISC: providing efficient XML-based service-orientation for core OS functionality
Authors: Hermann Schloss, Ingo Scholtes, Peter Sturm
Venue: Proceedings of the 2007 workshop on Service-oriented computing performance: aspects, issues, and approaches (2007)

Dependability, lucidity of design and ease-of-administration are more and more outrivaling performance as the top priority in Operating System design. These endeavors have led to a new generation of Operating Systems that abolish physical address space separation by the restriction to type-safe languages and memory-managed runtime environments. Provided that adequately efficient XML-message representations are used, this paper argues that these novel approaches to OS design are well-suited to make XML-Message-based communication sufficiently fast to introduce it along with the notion of services into the very heart of Operating Systems. By these means a truly homogeneous communication scheme can be offered in which services provided by the Operating System, applications and remote entities can be consumed alike. This paper will present motivation and implementation of SISC, a SOAP-based and service-oriented middleware prototype facilitating shared DOM communication in next-generation Operating Systems. It also presents some preliminary performance measurements that suggest the viability of the underlying approach.
PMQS: scalable Linux scheduling for high end servers
Authors: Hubertus Franke, Shailabh Nagar, Mike Kravetz, Rajan Ravindran
Venue: Proceedings of the 5th annual Linux Showcase & Conference - Volume 5 (2001)

The Linux Kernel scheduler for large SMP and NUMA systems needs to address conflicting requirements of system throughput and application response times. This paper pesents a pooled multiqueue scheduler (PMQS) designed for such high-end SMP and NUMA systems. PMQS is based on MQS, a multiqueue schduler that has previously been shown to significantly improve upon the scalability of the current Linux 2.4 scheduler. Load imbalances introduced by the pooling approach are reduced by a load balancing module. The paper presents different kinds of load balances and compares their efficacy. The Performance evaluation of PMQS and the load balancer is carried out using application and microbenchmarks with mixed results. Pooling is shown to have potential for further improving MQS' perfomance though more work needs to be done on the load balancers.
Models and algorithms: applications to satisfiability and genome rearrangement problems
Authors: Richard Durrett, Bart Selman
Venue:  (2006)

This thesis has two parts. The first part talks about problems related to Boolean Satisfiability. The second part discusses work related to the Genome Median Problem. In Chapter 2 we consider a model for generating random k-SAT formulas, in which each literal occurs approximately the same number of times in the formula clauses (regular random k-SAT). We study properties of these formulas related to the phase transition phenomena. Chapter 3 defines and studies a general model for generating random quantified boolean formula (QBF) instances. We exhibit experimental results showing that our model bears certain desirable similarities to the random SAT model, as well as a number of theoretical results concerning our model. In Chapter 4 we present a new approach for solving unsatisfiable two-alternation QBFs. Our approach is able to solve hard random QBF formulas that other current algorithms cannot handle. We finish the first part of the thesis discussing the MIN-SAT problem. Specifically, in Chapter 5 we develop stochastic local search techniques for MIN-SAT. We compare our results to those obtained by encoding MIN-SAT problems as instances of MAX-SAT and running the widely used WaIkSAT algorithm on these instances. We find much better solutions with our MIN-SAT algorithms than the solutions obtained from running WaIkSAT on the encoded problems. Chapters 6 and 7 present our work on the Genomic Median Problem. We propose a new algorithm for the genomic median problem that combines greedy and stochastic search. Our computational experiments suggest that for more complex problems our algorithm finds better solutions than previous approaches. In particular we find an improved midpoint for a human-mouse-rat comparison with 424 markers. In order to understand why such problems are hard, we explore a phase transition in the complexity of the median problem for random data, associated with the emergence of a giant component in the breakpoint graph.
A new data reduction algorithm for pattern classification
Authors: H. Tahani
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06 (1996)

The design of pattern classifiers such as multiprototype classifiers and neural network classifiers such as learning vector quantization and radial basis function neural networks requires reducing the size of the training data sets. In addition, memory storage, computation complexity and time, and data redundancy demand many pattern classifiers to use a smaller subset of a training data set. In this paper, we present a data reduction algorithm which automatically selects the subset of training data that faithfully represents the training data set for pattern classification. The applicability of this algorithm is demonstrated through k-nearest neighbor and learning vector quantization neural networks classifiers using both speech and synthetic data sets.
Evaluating the impact of cache interferences on numerical codes
Authors: 0. Temam, C. Fricker, W. Jalby
Venue: Proceedings of the 1993 International Conference on Parallel Processing - Volume 01 (1993)

In numerical codes, the regular interleaved accesses that occur within do-loop nests induce cache interference phe nomena that can severely degrade program performance. Cache interferences can significantly increase the volume of memory traffic and the amount of communication in uniprocessors and multiprocessors. In this paper, we iden tify cache interference phenomena, determine their causes and the conditions under which they occur. Based on these results, we derive a methodology for computing an analyt ical expression of cache misses for most classic loop nests, which can be used for precise performance analysis and prediction. We show that cache performance is unstable, because some unexpected parameters such as arrays base address can play a significant role in interference phenom ena. We also show that the impact of cache interferences can be so high, that the benefits of current data local ity optimization techniques can be partially, if not totally, eradicated.
Towards Interactive Generation of "Ground-truth" in Background Subtraction from Partially Labeled Examples
Authors: E. Grossmann, A. Kale, C. Jaynes
Venue: Proceedings of the 14th International Conference on Computer Communications and Networks (2005)

Ground truth segmentation of foreground and background is important for performance evaluation of existing techniques and can guide principled development of video analysis algorithms. Unfortunately, generating ground truth data is a cumbersome and incurs a high cost in human labor. In this paper, we propose an interactive method to produce foreground/background segmentation of video sequences captured by a stationary camera, that requires comparatively little human labor, while still producing high quality results. Given a sequence, the user indicates, with a few clicks in a GUI, a few rectangular regions that contain only foreground or background pixels. Adaboost then builds a classifier that combines the output of a set of weak classifiers. The resulting classifier is run on the remainder of the sequence. Based on the results and the accuracy requirements, the user can then select more example regions for training. This cycle of hand-labeling, training and automatic classification steps leads to a high-quality segmentation with little effort. Our experiments show promising results, raise new issues and provide some insight on possible improvements.
Reliability issues in deep deep sub-micron technologies: time-dependent variability and its impact on embedded system design
Authors: Antonis Papanikolaou, Hua Wang, Miguel Miranda, Francky Catthoor
Venue: Proceedings of the 13th IEEE International On-Line Testing Symposium (2007)

Embedded system design is especially demanding in terms of requirements that need to be satisfied, e.g. real-time processing, cost effectiveness, low energy consumption and reliable operation. These requirements have to be properly balanced until a financially viable global solution is found. Novel mobile multimedia and communication applications pose extremely severe requirements on the amount of storage, processing and functionality capabilities of the system. Near future embedded systems will have to combine interactive gaming with advanced 3D and video codecs together with leading edge wireless connectivity standards, like software defined radio front-ends and protocol stacks for cognitive radio. This will increase the platform requirements by at least a factor of 10. Meanwhile, battery capacity is only increasing by about 7% per year and users demand longer times between battery recharges. Optimizing any one of these requirements by compromising on another is a rather straightforward design task. In embedded system design the solution must obey the constraints in all four requirement axes.
Compromising Location Privacy inWireless Networks Using Sensors with Limited Information
Authors: Ye Zhu, Riccardo Bettati
Venue: Proceedings of the 27th International Conference on Distributed Computing Systems (2007)

We propose a methodology to identify nodes in fully anonymizedwireless networks using collections of very simple sensors. Based on time series of counts of anonymous packets provided by the sensors, we estimate the number of nodes using Principal Component Analysis. We then proceed to separate the collected packet data into traffic flows that, with help of the spatial diversity in the available sensors, can be used to estimate the location of the wireless nodes. Our simulation experiments indicate that the estimators show high accuracy and high confidence for anonymized TCP traffic. Additional experiments indicate that the estimators perform very well in anonymous wireless networks that use traffic padding.
Vandermonde invariance transformation
Authors: T. R. Kurpjuhn
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05 (2001)

In this article we introduce a novel multiple-input-multiple-output (MIMO) spatial filter (SF) which can be applied as a preprocessing scheme to uniform linear arrays in mobile communications, preserving the Vandermonde structure of the steering vectors while changing the amplitude and the phase gradient of the steering vector in a nonlinear fashion. The new scheme is therefore titled Vandermonde invariance transformation. The introduced degrees of freedom due to this preprocessing transformation can be used to beneficially influence the properties of the channel to achieve an enhanced performance of the subsequent signal processing algorithm.
An undergraduate course in object-oriented software design
Authors: C. Bishop-Clark
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 01 (1998)

Many software development organizations are adopting object-oriented methodologies as their primary paradigm for software development. The object-oriented method appears to increase programmer productivity, reduce the overall cost of the software and, perhaps most importantly, creates software that promotes reuse and subsequently is easier to modify. Consistent with the change in industry, many universities and industry training organizations are currently in the process of integrating object orientation into their curriculum. There are several approaches including horizontal integration (integrating a small dose of the object orientation into many courses) and vertical integration (having a large dose of the concepts in a single course). In 1996, the Systems Analysis department of Miami University, USA, opted for the latter approach and added a new course to its curriculum. It is a course that is intended to provide some in-depth exposure to object-oriented design and implementation. It should be of particular value to faculty in computer science and information systems departments (both at the 4-year and 2-year institutions) as well as those in industry training organizations who are looking for ways to incorporate the object orientation into their curriculum. In this paper, the authors describe the choices their department made, what worked well, and what needs to be improved.
A data management framework for secure and dependable data grid
Authors: I-Ling Yen
Venue:  (2006)

Data grid enables the sharing and coordinated use of data from various sources and provides various services to fit the needs of high-performance distributed and data-intensive computing. In many data grid applications, security, availability, and access efficiency are important issues that need to be addressed. Also, some data grid applications involve mobile clients where mobile users access the information from hand held devices. Thus, how to minimize the communication cost for the mobile clients accessing the data in data grids should also be investigated. The goal of this dissertation research is to develop a data management framework to facilitate secure, highly available, and highly efficient accesses in data grids, considering both mobile and wired clients. Replication is used as the basic approach to achieve high availability and efficient accesses. Data are replicated on storage servers that are close to the clients so that the communication cost is minimized. In the case of mobile environment, data are also replicated on the mobile clients themselves to improve the access efficiency. To achieve security protection in data grids, secret sharing and erasure coding (with encryption) schemes are used to partition the data into data shares and distribute them on different storage servers. Thus, the security of the data can be assured even if some storage servers in the data grids are malicious or compromised. To improve the access performance of the partitioned data, data shares are further replicated and placed close to the clients. In both cases, how to place the data objects is the key issue in performance improvement and availability and security enhancement. Thus, this dissertation focuses on the data placement issues for correlated data due to transaction accesses and due to data partitioning. In this dissertation research, several data placement algorithms for correlated data have been developed. Some of these algorithms determine the data placement solutions that can optimize the access efficiency. Some algorithms further consider the conflicting security, availability, and access efficiency objectives and aiming at satisfying security, availability, and efficiency constraints while optimizing these objectives. Assessment approaches have also been developed so that the security, availability, and performance objectives can be quantitatively measured to guide the placement decisions. These data placement algorithms and assessment approaches servers as the core of the data management framework. Future research efforts will focus on the development of innovative techniques for the remaining parts of the framework and building an ecological data grid using these techniques. The research results from this dissertation provide the technologies for developing secure, highly available, and highly efficient data grid applications. This is especially beneficial for critical data grid applications that have stringent dependability requirements.
Two additive-constrained path selection in the presence of inaccurate state information
Authors: Yanxing Zheng, Turgay Korkmaz, Wenhua Dou
Venue: Computer Communications (2007)

We study quality-of-service (QoS) routing, particularly two additive-constrained path selection problem, in the presence of inaccurate state information. We formulate this problem as Most-Probable Two-Additive-Constrained Path (MP-TACP) problem. To solve it, we follow a probabilistic approach and propose an algorithm called MP-TACPA. In general, MP-TACPA uses pre- and on-demand computation along with both linear and nonlinear search techniques. In contrast to previous algorithms using similar techniques, MP-TACPA takes into account the inaccuracies along with new bounds and heuristics including look ahead and dominance probability. Extensive simulations show that MP-TACPA behaves very well in the presence of inaccurate state information. Specifically, it gives higher success rate in finding feasible paths than existing solutions that assume the availability of exact state information. In addition, its average computational cost and thus response time is better than typical on-demand path selection algorithms.
Performance Comparison of Two Algorithms for Task Assignment
Authors: Anup Kumar, Sub Ramakrishnan, Chinar Deshpande, Larry Dunning
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 03 (1994)

In this paper we investigate a new algorithm for solving the optimal task assignment problem. The assignment is based on Stone's [11] "throughput" metric with the optimality criteria being the total cost for execution and interprocess communication. Two approaches studied are a new approach based on genetic algorithms and A*, a well known tree search algorithm for solving the same problem. We use the algorithm execution time as a performance criteria for the two algorithms. It is shown that the genetic algorithm techniques are more favorable than A* for larger search spaces while for smaller search spaces A* is preferred.
An additional projection step to He and Liao's method for solving variational inequalities
Authors: Abdellah Bnouhachem
Venue: Journal of Computational and Applied Mathematics (2007)

In this paper, we proposed a modified extragradient method for solving variational inequalities. The method can be viewed as an extension of the method proposed by He and Liao [Improvement of some projection methods for monotone variational inequalities, J. Optim. Theory Appl. 112 (2002) 111-128], by performing an additional projection step at each iteration and another optimal step length is employed to reach substantial progress in each iteration. We used a self-adaptive technique to adjust parameter @r at each iteration. Under certain conditions, the global convergence of the proposed method is proved. Preliminary numerical experiments are included to compare our method with some known methods.