ppxscal/embedding_network huggingface dataset:
Particle Swarm Optimization with Adaptive Mutation
Authors: Jun Tang, Xiaojuan Zhao
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

Particle swarm optimization (PSO) has shown its good performance in many optimization problems. However, PSO could often easily fall into local minima because the particles could quickly converge to a position by the attraction of the best particles. Under this circumstance, all the particles could hardly be improved. This paper presents a hybrid PSO (AMPSO) to solve this problem by applying a novel adaptive mutation operator. Experimental results on 8 well-known benchmark functions show that the AMPSO achieves better results than the standard PSO, PSO with Gaussian mutation and PSO with Cauchy mutation on most test cases.
Computing under occupation
Authors: Klaus Kursawe, Stefan Katzenbeisser
Venue: Proceedings of the 2007 Workshop on New Security Paradigms (2008)

Recent investigations have found a massively increasing professionalisation and organization of attacks executed on consumer computing systems. Simultaneously, the systems we are trying to defend are getting more and more complex and networked, while promising security technologies---such as trusted boot and strong process isolation---appear to have troubles finding their way into mainstream devices. This leads us to the conclusion that we may be forced to accept that the security war is lost for now, and that a considerable portion of all consumer PCs is under control of some organized malicious entity. In this work, we investigate the options left to the defenders in this scenario: Assuming that PC World is under control of a hostile force, how can we (a) survive (i.e., work) in a meaningful way, and (b) destroy the economic value for the attacker without severely damaging our own resources.
Coordination and multi-tasking using EMT
Authors: Zinovi Rabinovich, Nir Pochter, Jeffrey S. Rosenschein
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

We introduce a multi-model variant of the EMT-based control algorithm. The new algorithm, MM-EMT, is capable of balancing several control tasks expressed using separate dynamic models with a common action space. Such multiple models are common in both single-agent environments, when the agent has multiple tasks to achieve, and in team activities, when agent actions affect both the local agent's task as well as the overall team's coordination. To demonstrate the behaviour that MM-EMT engenders, several experimental setups were devised. Simulation results support the effectiveness of the approach, which in the multi-agent scenario is expressed in the MM-EMT algorithm's ability to balance local and team-coordinated motion requirements.
A comparison of SNOTEL and AMSR-E snow water equivalent datasets in western U.S. watersheds
Authors: Cody L. Moser, Oubeidillah Aziz, Glenn A. Tootle, Venkat Lakshmi, Greg Kerr
Venue: Proceedings of the Third International Workshop on Knowledge Discovery from Sensor Data (2009)

It is a consensus among earth scientists that climate change will result in an increased frequency of extreme events (e.g., precipitation, snow). Streamflow forecasts and flood/drought analyses, given this high variability in the climatic driver (snowpack), are vital in the western United States. However, the ability to produce accurate forecasts and analyses is dependent upon the quality (accuracy) of these predictors (snowpack). Current snowpack datasets are based upon in-situ telemetry. Recent satellite deployments offer an alternative remote sensing data source of snowpack. The proposed research will investigate (compare) remote sensing datasets in western U.S. watersheds in which snowpack is the primary driver of streamflow. A comparison is made between snow water equivalent (SWE) data from in-situ snowpack telemetry (SNOTEL) sites and the advanced microwave scanning radiometer -- earth observing system (AMSR-E) aboard NASA's Aqua satellite. Principal component techniques and Singular Value Decomposition are applied to determine similarities and differences between the datasets and investigate regional snowpack behaviors. Given the challenges (including costs, operation and maintenance) of deploying SNOTEL stations, the objective of the research is to determine if satellite based remote sensed SWE data provide a comparable option to in-situ datasets. Watersheds investigated include the North Platte River, the Upper Green River, and the Upper Colorado River. The time period analyzed is 2003--2008, due to the recent deployment of the NASA Aqua satellite. Two distinct snow regions were found to behave similarly between both datasets using principal component analysis. Singular Value Decomposition linked both data products with streamflow in the region and found similar behaviors among datasets. However, only 11 of the 84 SNOTEL sites investigated correlated at a significance of 90% or greater with its corresponding AMSR-E cell. Also, when comparing SNOTEL data with the corresponding satellite cell, there was a consistent difference in the magnitude (Snow Water Equivalent) of the datasets. Finally, both datasets were utilized and compared in a statistically based streamflow forecast of several gages.
Some specially formulated axiomizations for IΣ0 manage to evade the Herbrandized version of the Second Incompleteness Theorem
Authors: Dan E. Willard
Venue: Information and Computation (2009)

In 1981, Paris and Wilkie indicated it was an open question whether I@S"0 would satisfy the Second Incompleteness Theorem for Herbrand deduction. We will show that some specially formulated axiomizations for I@S"0 can evade the Herbrandized version of the Second Incompleteness Theorem.
A comparison of rule-based and statistical methods for semantic language modeling and confidence measurement
Authors: Ruhi Sarikaya, Yuqing Gao, Michael Picheny
Venue: Proceedings of HLT-NAACL 2004: Short Papers on XX (2004)

This paper presents a comparison of a rule-based and a statistical semantic information modeling technique. For the rule--based method we employ Embedded Grammar (EG) tagging and for the statistical method we use a previously proposed Semantic Structured Language Modeling (SSLM) technique. Both EG and SSLM achieve around 15% relative improvement in speech recognition performance over the baseline dialog state--based trigram language model in a financial transaction domain. Combining EG and SSLM using linear interpolation results in further improvement. We also use the features obtained from EG and SSLM for confidence measurement. Word level confidence measurement experiments using EG and SSLM--based semantic features combined with posterior probability show over 20% relative improvement in correct acceptance rate (CA) at 5% false alarm (FA) rate over the posterior probability based feature. In both language model rescoring and confidence measurement experiments SSLM outperforms EG by a small margin.
Validation and regression testing for a cross-linguisic grammar resource
Authors: Emily M. Bender, Laurie Poulson, Scott Drellishak, Chris Evans
Venue: Proceedings of the Workshop on Deep Linguistic Processing (2007)

We present a validation methodology for a cross-linguistic grammar resource which produces output in the form of small grammars based on elicited typological descriptions. Evaluating the resource entails sampling from a very large space of language types, the type and range of which preclude the use of standard test suites development techniques. We produce a database from which gold standard test suites for these grammars can be generated on demand, including well-formed strings paired with all of their valid semantic representations as well as a sample of ill-formed strings. These string-semantics pairs are selected from a set of candidates by a system of regular-expression based filters. The filters amount to an alternative grammar building system, whose generative capacity is limited compared to the actual grammars. We perform error analysis of the discrepancies between the test suites and grammars for a range of language types, and update both systems appropriately. The resulting resource serves as a point of comparison for regression testing in future development.
Expressive banner ad auctions and model-based online optimization for clearing
Authors: Craig Boutilier, David C. Parkes, Tuomas Sandholm, William E. Walsh
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

We present the design of a banner advertising auction which is considerably more expressive than current designs. We describe a general model of expressive ad contract/bidding and an allocation model that can be executed in real time through the assignment of fractions of relevant ad channels to specific advertiser contracts. The uncertainty in channel supply and demand is addresscd by the formulation of a stochastic combinatorial optimization problem for channel allocation that is rerun periodically. We solve this in two different ways: fast deterministic optimization with respect to expectations; and a novel online sample-based stochastic optimization method-- that can be applied to continuous decision spaces--which exploits the deterministic optimization as a black box. Experiments demonstrate the importance of expressive bidding and the value of stochastic optimization.
The OPL Access Control Policy Language
Authors: Christopher Alm, Ruben Wolf, Joachim Posegga
Venue: Proceedings of the 6th International Conference on Trust, Privacy and Security in Digital Business (2009)

Existing policy languages suffer from a limited ability of directly and elegantly expressing high-level access control principles such as history-based separation of duty [22], binding of duty [26], context constraints [24], Chinese wall properties [10], and obligations [20]. It is often difficult to extend a language in order to retrofit these features once required or it is necessary to use complicated and complex language constructs to express such concepts. The latter, however, is cumbersome and error-prone for humans dealing with policy administration.We present the flexible policy language OPL that can represent a wide range of access control principles in XML directly, by providing dedicated language constructs for each supported principle. It can be easily extended with further principles if necessary. OPL is based on a module concept, and it can easily cope with the language complexity that usually comes with a growing expressiveness. OPL is suitable to be used in an enterprise environment, since it combines the required expressiveness with the simplicity necessary for an appropriate administration.
Kernel regression with order preferences
Authors: Xiaojin Zhu, Andrew B. Goldberg
Venue: Proceedings of the 22nd national conference on Artificial intelligence - Volume 1 (2007)

We propose a novel kernel regression algorithm which takes into account order preferences on unlabeled data. Such preferences have the form that point x1 has a larger target value than that of x2, although the target values for x1, x2 are unknown. The order preferences can be viewed as side information or a form of weak labels, and our algorithm can be related to semi-supervised learning. Learning consists of formulating the order preferences as additional regularization in a risk minimization framework. We define a linear program to effectively solve the optimization problem. Experiments on benchmark datasets, sentiment analysis, and housing price problems show that the proposed algorithm outperforms standard regression, even when the order preferences are noisy.
Approximation Algebra and Framework
Authors: Davide Ciucci
Venue: Fundamenta Informaticae (2009)

Generalized approximation algebras and approximation algebras are defined as a theoretical counterpart of all the situations where a "lower" and an "upper" mapping are used. Some models of these structures are discusse, among them rough sets, fuzzy rough sets and possibility theory. Generalized approximation framework and approximation framework are also introduced as an abstraction of all those cases where several approximations are possibile on the same element. Also in this case some examples are given.
The achievable rate region of 802.11-scheduled multihop networks
Authors: Apoorva Jindal, Konstantinos Psounis
Venue: IEEE/ACM Transactions on Networking (TON) (2009)

In this paper, we characterize the achievable rate region for any IEEE 802.11-scheduled static multihop network. To do so, we first characterize the achievable edge-rate region, that is, the set of edge rates that are achievable on the given topology. This requires a careful consideration of the interdependence among edges since neighboring edges collide with and affect the idle time perceived by the edge under study. We approach this problem in two steps. First, we consider two-edge topologies and study the fundamental ways they interact. Then, we consider arbitrary multihop topologies, compute the effect that each neighboring edge has on the edge under study in isolation, and combine to get the aggregate effect. We then use the characterization of the achievable edge-rate region to characterize the achievable rate region. We verify the accuracy of our analysis by comparing the achievable rate region derived from simulations with the one derived analytically. We make a couple of interesting and somewhat surprising observations while deriving the rate regions. First, the achievable rate region with 802.11 scheduling is not necessarily convex. Second, the performance of 802.11 is surprisingly good. For example, in all the topologies used for model verification, the max-min allocation under 802.11 is at least 64% of the max-min allocation under a perfect scheduler.
Assessment of Psychophysiological Differences of West Point Cadets and Civilian Controls Immersed within a Virtual Environment
Authors: Thomas D. Parsons, Christopher Courtney, Louise Cosand, Arvind Iyer, Albert A. Rizzo, Kelvin Oie
Venue: Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009 (2009)

An important question for ecologically valid virtual environments is whether cohort characteristics affect immersion. If a method for assessing a certain neurocognitive capacity (e.g. attentional processing) is adapted to a cohort other than the one that was used for the initial normative distribution, data obtained in the new cohort may not be reflective of the neurocognitive capacity in question. We assessed the psychophysiological impact of different levels of immersion upon persons from two cohorts: 1) civilian university students; and 2) West Point Cadets. Cadets were found to have diminished startle eyeblink amplitude compared with civilians, which may reflect that cadets experienced less negative affect during the scenario in general. Further, heart rate data revealed that Cadets had significantly lower heart rates than Civilians in the "low" but not "high" immersion condition. This suggests that "low" immersion conditions may not have the ecological validity necessary to evoke consistent affect across cohorts.
Co-occurrence contexts for noun compound interpretation
Authors: Diarmuid Ó Séaghdha, Ann Copestake
Venue: Proceedings of the Workshop on a Broader Perspective on Multiword Expressions (2007)

Contextual information extracted from corpora is frequently used to model semantic similarity. We discuss distinct classes of context types and compare their effectiveness for compound noun interpretation. Contexts corresponding to word-word similarity perform better than contexts corresponding to relation similarity, even when relational co-occurrences are extracted from a much larger corpus. Combining word-similarity and relation-similarity kernels further improves SVM classification performance.
Multiple Mobile Sinks Positioning in Wireless Sensor Networks for Buildings
Authors: Leila Ben Saad, Bernard Tourancheau
Venue: Proceedings of the 2009 Third International Conference on Sensor Technologies and Applications (2009)

Real deployment of wireless sensor networks inside buildings is a very challenging. In fact, in such networks, a large number of small sensor devices suffer from limited energy supply. These sensors have to observe and monitor their in-door environment, and then to report the data collected to a nearest information collector, referred to as the sink node. Sensor nodes which are far away from the sink relay their data via multiple hops to reach the sink. This way of communication makes the sensors near the sink deplete their energy much faster than distant nodes because they carry heavier traffic. So what is known as a hole appears around the sink and prevents distant nodes to send their data. Consequently the network lifetime ends prematurely. One efficient solution for this problem is to relocate sinks. In this work, we aim to find the best way to relocate sinks by determining their optimal locations and the duration of their sojourn time. So, we propose an Integer Linear Programming for multiple mobile sinks which directly maximizes the network lifetime instead of minimizing the energy consumption or maximizing the residual energy, which is what was done in previous solutions. Simulations results show that with our solution, the network lifetime is extended and the energy depletion is more balanced among the nodes. We also show that relocating mobile sinks inside a whole network is more efficient than relocating mobile sinks inside different clusters and we can achieve almost 52 $\%$ network lifetime improvement in our experiments.
Removing Shadow in Color Images Using a Combined Algorithm
Authors: Zhiqiang Wei, Kang Yao, Xiaopeng Ji, Miao Yang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

This paper is concerned with shadow removal in color images. We propose a combined algorithm which is based on colorimetry and retinex theory. Our method can effectively remove shadow in color images, and meanwhile avoid intrinsic disadvantages of the two algorithms if they are used individually. It can be used as a pre-process step in some computer vision tasks such as image segmentation, motion tracking and objective recognition.
Evaluation of VANET-based advanced intelligent transportation systems
Authors: Yi Yang, Rajive Bagrodia
Venue: Proceedings of the sixth ACM international workshop on VehiculAr InterNETworking (2009)

This paper aims at enabling accurate and efficient evaluation of emerging vehicular network applications such as Intelligent Transportation Systems (ITS). A distributed simulation platform that integrates transportation simulation and wireless network simulation is proposed and implemented, providing a user level simulation environment to evaluate the feasibility and performance limitations of VANETs in supporting ITS. The proposed simulation platform facilitates the dynamic interaction between the two simulation domains, allowing runtime control of vehicles' behavior in the transportation simulation as they react in real time to information exchange in the simulated communication network. Case studies are conducted within the proposed simulation platform to evaluate the performance of Dynamic Route Planning when deployed in VANETs, using metrics collected at the transportation system level such as travel and delay time. The effectiveness of three representative VANET dynamic adaptation protocols in enhancing the application performance in scenarios with high vehicle density are compared in the case studies. The experiment results show that Dynamic Route Planning can be effectively supported by a VANET system with up to 118% increase on the number of vehicles reaching the destination, 36.2% reduction on travel time and 56.1% reduction on delay time.
Text data acquisition for domain-specific language models
Authors: Abhinav Sethy, Panayiotis G. Georgiou, Shrikanth Narayanan
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

The language modeling community is showing a growing interest in using large collections of text mined from the World Wide Web (WWW) to supplement sparse in-domain text resources. However, in most cases the style and content of the text harvested from these corpora differs significantly from the specific nature of these domains. In this paper we present a relative entropy (r.e.) based method to select relevant subsets of sentences whose distribution in an n-gram sense matches the domain of interest. Using simulations, we provide an analysis of how the proposed scheme outperforms filtering techniques proposed in recent language modeling literature on mining text from the web. A comparative study is presented using a text collection of over 800M words collected from the WWW. Experimental results show that by using the proposed subset selection scheme we can get performance improvement in both Word Error Rate (WER) and Perplexity (PPL) over the models built from the entire collection by using just 10% of the data. Improvements in data selection also translated to a significant reduction in the vocabulary size as well as the number of estimated parameters in the adapted language model.
Making the Best Use of Landsat MSS Images for Land Use/Cover Change Analysis
Authors: Yuan Zhang, Xia Chen, Shiliang Su, Jiaping Wu, Jiaguo Qi
Venue: Proceedings of the 2009 International Conference on Environmental Science and Information Application Technology - Volume 01 (2009)

Current land use and cover (LUC) mapping is often made using high resolution images such as those from the Landsat TM/ETM+, SPOT, IKONOS, QuickBird sensors etc. However, the historical LUC information was often extracted from the earlier Landsat MSS images. Resultant land cover classification accuracy is often unsatisfactory for quantitative change analysis due to the limited number of spectral bands and the low spectral sensitivity. In this study, digital elevation model (DEM) data and the normalized difference vegetation index (NDVI) were integrated with MSS images. And also, a supervised spectral angle mapper (SAM) classification method was applied to improve the LUC classifications from the MSS images. The results showed that the MSS images classification accuracy could be improve to achieve a better LUC map with this method with overall accuracy and Kappa statistics of 81.4% and 0.781 respectively.
Security and usability research using a microworld environment
Authors: Noam Ben-Asher, Joachim Meyer, Yisrael Parmet, Sebastian Moeller, Roman Englert
Venue: Proceedings of the 11th International Conference on Human-Computer Interaction with Mobile Devices and Services (2009)

Technological developments and the addition of new features to existing applications or services require the inclusion of security mechanisms to protect the user. When using these mechanisms the user faces a tradeoff between more risky and more efficient or safer and less efficient use of the system. We discuss this tradeoff and present a novel complementary experimental system which provides researchers and corporations the ability to explore and model the usability and security tradeoff in the context of user interaction with security systems and psychological acceptability, even before the actual development and implementation processes have ended.