ppxscal/embedding_network huggingface dataset:
Facial Action Unit Recognition by Exploiting Their Dynamic and Semantic Relationships
Authors: Yan Tong, Wenhui Liao, Qiang Ji
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

A system that could automatically analyze the facial actions in real time has applications in a wide range of different fields. However, developing such a system is always challenging due to the richness, ambiguity, and the dynamic nature of facial actions. Although a number of research groups attempt to recognize facial action units (AUs) by either improving facial feature extraction techniques, or the AU classification techniques, these methods often recognize AUs or certain AU combinations individually and statically, ignoring the semantic relationships among AUs and the dynamics of AUs. Hence, these approaches cannot always recognize AUs reliably, robustly, and consistently.In this paper, we propose a novel approach that systematically accounts for the relationships among AUs and their temporal evolutions for AU recognition. Specifically, we use a dynamic Bayesian network (DBN) to model the relationships among different AUs. The DBN provides a coherent and unified hierarchical probabilistic framework to represent probabilistic relationships among various AUs and to account for the temporal changes in facial action development. Within our system, robust computer vision techniques are used to obtain AU measurements. And such AU measurements are then applied as evidence to the DBN for inferring various AUs. The experiments show that the integration of AU relationships and AU dynamics with AU measurements yields significant improvement of AU recognition, especially for spontaneous facial expressions and under more realistic environment including illumination variation, face pose variation, and occlusion.
Query Relaxing Based on Ontology and Users_ Behavior in Service Discovery
Authors: Li Lian, Jun Ma, JingSheng Lei, Ling Song, DongMei Zhang
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03 (2007)

Relaxing a failing query to the successful one with smallest semantic gap is the goal in Web service discovery. A schema for query relaxing is proposed based on both service ontologies and users' behavior, where the conceptual hierarchies and the conceptual distribution density of the ontologiese are taken into account during query relaxing and the conceptual hierarchies of a ontology are enlarged based on users' behavior. A failing query can be relaxed to a successful one based on service ontologies and users' behavior with progressive processing.
A LBP-based Face Recognition Method with Hamming Distance Constraint
Authors: Hong Yang, Yiding Wang
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

In this paper, we present a new LBP-based face recognition method with Hamming distance constraint. The traditional LBP operator uses a uniform pattern to describe the local features and assort the other nonuniform patterns to one additional class, for images under expression and illumination condition changes, this method could cause more inaccuracy and instability. By assuming that the illumination, pose or expression changes of a face image are some kinds of "noise", we introduce the widely used Hamming distance in channel coding to LBP so as to decrease the error rate caused by these noise disturbances. Experimental results on FRGC show that our method improves the recognition performance obviously than the traditional LBP-based face recognition methods when face images are under uncontrolled circumstances.
Using the Principal Component Analysis and BP Network to Model the Worsted Fore-spinning Working Procedure
Authors: Gui Liu, Wei-dong Yu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

The characteristic of worsted fore-spinning working procedure and the BP neural network modeling technology all have been summarily analyzed. Based on roving craft parameters' relevant characteristic, the principal component analysis method is proposed to pretreat the sample data set, which results are the new sample data of the BP neural network. The input layer node numbers reduce; the relevancies among every input factors are eliminated simultaneously; the network architecture is simplified that the network's study speed and the performance are all enhanced greatly. The relative mean error percent (MEP) between the roving unevenness and weight's prediction value and their mean value, reduce to 3.35% and 1.95% respectively. While the former values respectively are 4.86% and 2.24%. The network precision, the correlation coefficient between the forecast value and the actual value all have the remarkable enhancement.
Lightweight application classification for network management
Authors: Hongbo Jiang, Andrew W. Moore, Zihui Ge, Shudong Jin, Jia Wang
Venue: Proceedings of the 2007 SIGCOMM workshop on Internet network management (2007)

Traffic application classification is an essential step in the network management process to provide high availability of network services. However, network management has seen limited use of traffic classification because of the significant overheads of existing techniques. In this context we explore the feasibility and performance of lightweight traffic classification based on NetFlow records. In our experiments, the NetFlow records are created from packet-trace data and pre-tagged based upon packet content. This provides us with NetFlow records that are tagged with a high accuracy for ground-truth. Our experiments show that NetFlow records can be usefully employed for application classification. We demonstrate that our machine learning technique is able to provide an identification accuracy (&ap; 91%) that, while a little lower than that based upon previous packet-based machine learning work (> 95%), is significantly higher than the commonly used port-based approach (50--70%). Trade-offs such as the complexity of feature selection and packet sampling are also studied. We conclude that a lightweight mechanism of classification can provide application information with a considerably high accuracy, and can be a useful practice towards more effective network management.
Mobile IP and the IETF
Authors: Charles E. Perkins
Venue: ACM SIGMOBILE Mobile Computing and Communications Review (1998)

This is a report from your faithful IETF correspondent, covering some of the relevant events at the 42nd IETF conference in Chicago, IL. Milestones were reached, and promising new developments are taking shape. Chief among the milestones was the passage to Last Call of the mobility support protocol for IP version 6 (IPv6). New developments include accounting protocol extensions for Mobile IP, and interest forming around the possible convening of a BOF for IP and TCP over wireless links at the next IETF conference in December.
A dependability benchmark for OLTP application environments
Authors: Marco Vieira, Henrique Madeira
Venue: Proceedings of the 29th international conference on Very large data bases - Volume 29 (2003)

The ascendance of networked information in our economy and daily lives has increased the awareness of the importance of dependability features. OLTP (On-Line Transaction Processing) systems constitute the kernel of the information systems used today to support the daily operations of most of the business. Although these systems comprise the best examples of complex business-critical systems, no practical way has been proposed so far to characterize the impact of faults in such systems or to compare alternative solutions concerning dependability features. This paper proposes a dependability benchmark for OLTP systems. This dependability benchmark uses the workload of the TPC-C performance benchmark and specifies the measures and all the steps required to evaluate both the performance and key dependability features of OLTP systems, with emphasis on availability. This dependability benchmark is presented through a concrete example of benchmarking the performance and dependability of several different transactional systems configurations. The effort required to run the dependability benchmark is also discussed in detail.
General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
Authors: Dacheng Tao, Xuelong Li, Xindong Wu, Stephen J. Maybank
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2007)

The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem (USP): the dimensionality of the feature space is much higher than the number of training samples. Motivated by the successes of the two dimensional LDA (2DLDA) for face recognition, we develop a general tensor discriminant analysis (GTDA) as a preprocessing step for LDA. The benefits of GTDA compared with existing preprocessing methods, e.g., principal component analysis (PCA) and 2DLDA, include 1) the USP is reduced in subsequent classification by, for example, LDA; 2) the discriminative information in the training tensors is preserved; and 3) GTDA provides stable recognition rates because the alternating projection optimization algorithm to obtain a solution of GTDA converges, while that of 2DLDA does not.We use human gait recognition to validate the proposed GTDA. The averaged gait images are utilized for gait representation. Given the popularity of Gabor function based image decompositions for image understanding and object recognition, we develop three different Gabor function based image representations: 1) the GaborD representation is the sum of Gabor filter responses over directions, 2) GaborS is the sum of Gabor filter responses over scales, and 3) GaborSD is the sum of Gabor filter responses over scales and directions. The GaborD, GaborS and GaborSD representations are applied to the problem of recognizing people from their averaged gait images.A large number of experiments were carried out to evaluate the effectiveness (recognition rate) of gait recognition based on first obtaining a Gabor, GaborD, GaborS or GaborSD image representation, then using GDTA to extract features and finally using LDA for classification. The proposed methods achieved good performance for gait recognition based on image sequences from the USF HumanID Database. Experimental comparisons are made with nine state of the art classification methods in gait recognition.
A Performance Analysis Tool for Scenario-Aware Streaming Applications
Authors: B. D. Theelen
Venue: Proceedings of the Fourth International Conference on Quantitative Evaluation of Systems (2007)

Dataflow models are often used for analysing streaming applications. The recently introduced scenario-aware extension of the synchronous dataflow model can capture the dynamism in computation and communication resource requirements of streaming applications that originates from different modes of operation (scenarios). This scenario-aware dataflow model uses a probabilistic approach to express the order in which scenarios (and different execution times within a scenario) occur. This paper discusses a tool for exhaustive and simulation-based analysis of various important performance metrics for scenario-aware streaming applications.
Applicants' selection applying a fuzzy multicriteria CBR methodology
Authors: Gleiber Fernandes Royes, Rogério Cid Bastos, Golber Fernandes Royes
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2003)

The usual methods applied by enterprises to the selection of high executives involve a set of relevant criteria. These criteria frequently involve subjective and complex characteristics that must be adequately assessed to produce the proper decision about the most suitable profile among the available job applicants. A Fuzzy Multicriteria tool is suggested to help on the choice of the most promising applicant among the available candidates. Fuzzy sets are used to represent and manipulate the uncertain criteria of the problem in a computer system. The Multicriteria technique explores the fuzzy criteria in order to produce a preference ranking order of the applicants for the employment. As an important complement to this proposal, a CBR (Case-Based Reasoning) mechanism is presented as an additional tool for decision aid and as a mechanism of incremental learning. A practical real situation is also presented to illustrate the functional process of this approach.
An Efficient Ad-Hoc Routing Using a Hybrid Clustering Method in a Wireless Sensor Network
Authors: Do-Hyun Nam, Hong-Ki Min
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

The routing methods which used in the wireless sensor network deal with the clustering method to diminish the amount of data transmission from the energy efficiency view. However, the clustering methods cause several problems in energy consumption at the cluster head node. Dynamic clustering is a method which used to supplement a high energy consumption problem by distributing energy consumption through the re-selection of the cluster head node. But, this method changes cluster structure every time the cluster head node is re-selected, which causes energy consumption. Namely, the dynamic clustering method approaches examined in previous researches involve the repetitive processes of cluster head node selection. This consumes a high amount of energy during the set-up process of cluster generation. Consequently, this paper proposes the hybrid clustering method that fixes the cluster and selects the head node in a round-robin method. The hybrid clustering approach is an energy-efficient method that realizes consistent and balanced energy consumption in each node of a generated cluster to prevent repetitious set-up processes as in the LEACH method. The propriety of the proposed method is substantiated with a simulation experiment.
Formal equivalence checking for loop optimization in C programs without unrolling
Authors: Takeshi Matsumoto, Kenshu Seto, Masahiro Fujita
Venue: Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology (2007)

In this paper, we propose an equivalence checking method for loop optimizations. Those optimizations are effective to improve the performance of both hardware and software. In our proposed method, a symbolic simulation based method is used to check the equivalence. Before applying symbolic simulation, loops are usually unrolled by certain number of times. This causes two problems. One is that the equivalence of the whole loop executions is not guaranteed if the number of unrolling is not large enough. The other is that the verification time can be very long if the loops are unrolled many times. To solve the problems, we propose the method to verify the equivalence of programs including loops and array accesses without unrolling. In the method, we extract the relations of array indexes and iterators of loops, and find the symbolic values of the iterators, for which the loops need to be executed to compute the output arrays of arbitrary indexes. Then, symbolic simulation is applied only to the specified iterations by setting the iterators to particular symbolic values. Thus, in most cases, symbolic simulation can complete the task within very small number of iterations. Finally, we show the experimental results on several loop optimizations.
A public transport system based sensor network for road surface condition monitoring
Authors: Kasun De Zoysa, Chamath Keppitiyagama, Gihan P. Seneviratne, W. W. A. T. Shihan
Venue: Proceedings of the 2007 workshop on Networked systems for developing regions (2007)

A well maintained road network is a must for the economic development and the well being of people in any country. Unfortunately, most developing countries do not poses such road networks. While the lack of funds is mainly to blame for not building new road networks and maintaining the existing ones the lack of proper monitoring and reporting system is a major contributory factor for the dilapidated condition of road networks in third world countries. A case in point is the road network in Sri Lanka; Sri Lanka has an extensive road network that spans the country and new roads are being built every day, yet even the roads in the capital city are not maintained properly. The lack of a monitoring and reporting mechanism is apparent in this case. We propose a public transport system based sensor network to monitor road surface condition. We are currently building such a network called BusNet to monitor environmental pollution and that system can be extended for road surface condition monitoring by adding acceleration sensor boards to the system.
OPTIMA: An Ontology-Based PlaTform-specIfic software Migration Approach
Authors: Hong Zhou, Jian Kang, Feng Chen, Hongji Yang
Venue: Proceedings of the Seventh International Conference on Quality Software (2007)

Software migration is an inherently knowledge intensive activity, which requires a great amount of expertise and experience from different sources. Knowledge-based approach to software migration has a great potential for improving traditional approaches. In this paper, an Ontology-based PlaTform-specIfic software Migration Approach (OPTIMA) is proposed. Firstly, the background and the related work are introduced, and the ontology design for platform- specific software migration is discussed. Secondly, the architecture and workflow of OPTIMA are illustrated with a prototype tool. Thirdly, the case study is used for experiments with the approach and the prototype tool, and finally, the conclusion is drawn and further research directions are speculated. Keywords: Knowledge Base, Ontology, Model Driven Architecture (MDA), Software Migration
Managing Wireless Mesh Networks - Analysis and Proposals
Authors: Djohara Benyamina, Abdelhamid Hafid, Michel Gendreau, Nasreddine Hallam
Venue: Proceedings of the Third IEEE International Conference on Wireless and Mobile Computing, Networking and Communications (2007)

A mesh network allows nodes or access points to communicate with each other without being routed through a central switch point, eliminating centralized failure and providing self-healing & self-organization. Although decisions on traffic are made locally, the system can be managed globally. In this paper, a preliminary study on Wireless Mesh Networks (WMNs) management is presented, pointing out the different managements functions required to maintain the network reliability. A decomposition of WMNs management functions into key areas is presented and analyzed. The state-of-the-art management protocols for WMNs are explored and classified according to the proposed key areas.
Speed versus Accuracy Trade-Offs in Microarchitectural Simulations
Authors: Joshua J. Yi, Resit Sendag, David J. Lilja, Douglas M. Hawkins
Venue: IEEE Transactions on Computers (2007)

Due to the long simulation time of the reference input set, computer architects often use reduced time simulation techniques to shorten the simulation time. However, what has not yet been thoroughly evaluated is the accuracy of these techniques relative to the reference input set and with respect to each other. To rectify this deficiency, this paper uses three methods to characterize reduced input set, truncated execution, and sampling-based simulation techniques while also examining their speed vs. accuracy trade-off and configuration dependence. Our results show that the three sampling-based techniques, SimPoint, SMARTS, and random sampling, have the best accuracy, the best speed vs. accuracy trade-off, and the least configuration dependence. On the other hand, the reduced input set and truncated execution simulation techniques had generally poor accuracy, were not significantly faster than the sampling-based techniques, and were severely configuration dependent. The final contribution of this paper is a decision tree which can help architects choose the most appropriate technique for their simulations.
Trustworthily Forwarding Sensor Networks Information to the Internet
Authors: Olivier Powell, Jean-Marc Seigneur, Luminita Moraru
Venue: Proceedings of the The International Conference on Emerging Security Information, Systems, and Technologies (2007)

The Internet is soon going to be extended with the information collected from sensor networks deployed in wild remote regions of the world. For example, sensors may be dispersed in the jungle and forward information about the sensed states of the natural ecosystem, such as, humidity, fire detection However, it is still quite easy for attackers to disconnect the sensors network from the Internet. For example, the sensors usually forward their messages to a base station, the Internet gateway, in a hop-by-hop fashion because they are resource-constrained in terms of energy, the spending of energy dramatically increases with the range of transmission and the attackers may capture intermediate sensors and drop messages rather than forwarding them. In this paper we study how computational trust can be used to mitigate the issue of sinkhole attacks and evaluate our approach on top of the MIX protocol.
Efficient and Dynamic Location-based Event Service for Mobile Computing Environments
Authors: Sun Wook Kim, Kyu Bong Cho, Seungwok Han, Hee Yong Youn
Venue: Proceedings of the The 2007 International Conference Computational Science and its Applications (2007)

In mobile computing the location information of the objects is an important factor in providing customized services to the users. The location-based service(LBS) is one of the technologies providing the services adaptively according to the changed user position. The existing filtering technology employed in the typical pub/mb model has some drawbacks such as useless connection and wasted queue space. In this paper we propose an efficient and dynamic location-based event service solving these problems. It is achieved by employing Location Monitor which dynamically manages the event channel. Performance evaluation shows that the proposed scheme provides much higher performance than the existing scheme when the number of suppliers is larger than six.
Managing and Predicting the Costs of Real-Time Software
Authors: R. D. H. Warburton
Venue: IEEE Transactions on Software Engineering (1983)

The Putnam model can be used to predict and manage software development projects. It is a management tool that takes, as input, easily obtained manpower data and produces cost and schedule estimates. This paper examines data from two real-time software projects and analyzes the applicability of the Putnam model. We propose a variation ation of the model which more reliably follows the staffing curve of real-time software applications. A critical analysis of the assumptions is presented and the parameters are reinterpreted so that they reflect the environment of embedded applications. Two projects are analyzed from actual data. It is shown how management decisions are reflected in the model. Even erratic and incomplete data can yield valuable conclusions. It is also shown that the model is appropriate to software developed with modern practices. We show how valuable management information can be obtained by laying out the data in a systematic manner.
Energy Efficient Broadcasting Based on Ant Colony System Optimization Algorithm in Wireless Sensor Networks
Authors: Fei Ge, Yuanni Wang, Quande Wang, Jian Kang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 04 (2007)

Broadcasting operation is used to distribute the information from one WSNs node to all nodes. In this paper, we develop a protocol for energy efficient Broadcasting based on Ant colony system Optimization Algorithm that is called BAOA. We present the procedure of BAOA including six steps when searching the optimized broadcasting path in WSNs and design BAOA with UML. We also simulate BAOA with C++ language and the results show the lifetime of BAOA is longer and the total energy consumption is less than BIP.