ppxscal/embedding_network huggingface dataset:
Real-time Detection for Anomaly Data in Microseismic Monitoring System
Authors: Liu Li-li, Ji Chang-peng
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

Microseismic monitoring means to records microseismic activities caused by the changes of the rock physical properties continuously through the high sensitivity seismic sensor placed in mine. How to make real-time detection of abnormal data in mine microseisms positioning system is a extremely important task. Forecast model and mechanism of data stream in the mine microcosmic monitoring system are given through the linear self-regression analysis. Based on this prediction model, a detection method of abnormal data is proposed. This method detects whether real-time data is abnormal by calculating the ratio of real-time forecast error and average forecast error and making a comparison between the ratio and predefined threshold. Experimental results verified correctness and effectiveness of the prediction model to show that the model can realize real-time detection of abnormal event in mine earthquake.
Understanding cross-band interference in unsynchronized spectrum access
Authors: Wei Hou, Lei Yang, Lin Zhang, Xiuming Shan, Heather Zheng
Venue: Proceedings of the 2009 ACM workshop on Cognitive radio networks (2009)

We consider the problem of cross-band interference when devices from the same or different networks share radio spectrum. Cross-band interference occurs when unsynchronized transmissions create harmful interference among each other although they use non-overlapping frequency bands. We perform an in-depth study to analytically quantify the degree of interference and its impact on OFDMA-based packet transmissions. The analysis also takes into account practical artifacts including temporal sampling mismatch, frequency offset and power heterogeneity. Using insights from the analysis, we build and compare three methods that apply temporal and frequency redundancy to reduce the interference and add robustness against it. Experimental and analytical results show that adding frequency guardband is the most efficient solution to tackle cross-band interference.
Facial Gender Classification Using LUT-Based Sub-images and DIE
Authors: Jong-Bae Jeon, Sang-Hyeon Jin, Dong-Ju Kim, Kwang-Seok Hong
Venue: Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009 (2009)

This paper presents a gender classification method using LUT-based sub-images and DIE (Difference Image Entropy). The proposed method consists of three major steps; extraction of facial sub-images, construction of a LUT (Look-Up table), and calculation of DIE. Firstly, extraction of sub-images of the face, right eye, and mouth from face images is conducted using Haar-like features and AdaBoost proposed by Viola and Jones. Secondly, sub-images are converted using LUT. LUT-based sub-regions are constructed by calculation of one pixel and near pixels. Finally, sub-images are classified male or female using DIE. The DIE value is computed with histogram levels of a grayscale difference image which has peak positions from -255 to +255, to prevent information sweeping. The performance evaluation is conducted using five standard databases, i.e., PAL, BioID, FERET, PIC, and Caltech facial databases. The experimental results show good performance in comparison with earlier methods.
Agent-based negotiation and decision making for dynamic supply chain formation
Authors: Minhong Wang, Huaiqing Wang, Doug Vogel, Kuldeep Kumar, Dickson K. W. Chiu
Venue: Engineering Applications of Artificial Intelligence (2009)

Modern businesses are facing the challenge of effectively coordinating their supply chains from upstream to downstream services. It is a complex problem to search, schedule, and coordinate a set of services from a large number of service resources under various constraints and uncertainties. Existing approaches to this problem have relied on complete information regarding service requirements and resources, without adequately addressing the dynamics and uncertainties of the environments. The real-world situations are complicated as a result of ambiguity in the requirements of the services, the uncertainty of solutions from service providers, and the interdependencies among the services to be composed. This paper investigates the complexity of supply chain formation and proposes an agent-mediated coordination approach. Each agent works as a broker for each service type, dedicated to selecting solutions for each service as well as interacting with other agents in refining the decision making to achieve compatibility among the solutions. The coordination among agents concerns decision making at strategic, tactical, and operational level. At the strategic level, agents communicate and negotiate for supply chain formation; at the tactical level, argumentation is used by agents to communicate and understand the preferences and constraints of each other; at the operational level, different strategies are used for selecting the preferences. Based on this approach, a prototype has been implemented with simulated experiments highlighting the effectiveness of the approach.
Contextual Metadata in Practice
Authors: Martin Svensson
Venue: Proceedings of the 2009 First International Conference on Advances in Multimedia (2009)

This article aims to survey the scene of contextual metadata annotation of digital content. This is performed through a literature review of current research, looking closer at formal context models, contextual metadata gathering and contextual metadata formalisation respectively. The findings of these efforts indicate that the reviewed context models have three elements of context in common. However, these formal models are inconsistent with the contextual metadata gathered in approaches described in the reviewed literature, in which location metadata are the most common. Furthermore, contextual metadata gathered in these initiatives end up in a variety of data structures. One reason for the dominance of location metadata might be the clear understanding of their ontological dimension. Therefore, the author introduces the notion of ontological dimensions in the area of contextual metadata. The proposed notion of conceiving contextual metadata as a set of ontological dimensions makes it possible to divide the endeavour of formalising elements of context into manageable information chunks. Through identifying and reaching a consensus of the constituent parts of these dimensions, it is the belief of the author that we are well on our way towards improved interoperability, metadata interpretability and digital content reusability facilitated by contextual metadata.
Cryptoanlaysis of a Self-Certified Partially Blind Signature and a Proxy Blind Signature
Authors: Jianhong Zhang, Shengnan Gao
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 02 (2009)

As a special digital signature, blind signature allowsallows a user to get a signature without giving the signerany information about the actual message or the resultingsignature. Unforgeability is an important property of blindsignature, it assures that any one cannot produce a forgedsignature on a message in a blind signature except thesigner. Recently, Lin et.al gave a provably secure selfcertifiedpartilally blind signature scheme in ICC2008 andYang et.al gave a proxy blind signature scheme basedon DLP in ICESS2008. They claimed that their schemeswere secure in their security model, respectively. In thepaper, we analyze the two blind signature schemes and theresult shows that the two blind signature schemes are notsecure. They are universally forgeable in that any one canforge a blind signature on arbitrary a message. Finally, wegive the corresponding attack and the improved discussion,respectively.
Hybridization of very large neighborhood search for ready-mixed concrete delivery problems
Authors: Verena Schmid, Karl F. Doerner, Richard F. Hartl, Juan-José Salazar-González
Venue: Computers and Operations Research (2010)

Companies in the concrete industry are facing the following scheduling problem on a daily basis: concrete produced at several plants has to be delivered at customers' construction sites using a heterogeneous fleet of vehicles in a timely, but cost-effective manner. The distribution of ready-mixed concrete (RMC) is a highly complex problem in logistics and combinatorial optimization. This paper proposes two hybrid solution procedures for dealing with this problem. They are based on a combination of an exact algorithm and a variable neighborhood search (VNS) approach. The VNS is used at first to generate feasible solutions and is trying to further improve them. The exact method is based on a mixed integer linear programming (MILP) formulation, which is solved (after an appropriated variable fixing phase) by using a general-purpose MILP solver. An approach based on very large neighborhood search (VLNS) determines which variables are supposed to be fixed. In a sense, the approaches follows a local branching scheme. The hybrid metaheuristics are compared with the pure VNS approach and the conclusion is that the new metaheuristics outperform the VNS if applied solely.
Diverse Applications of an Automated Argument System Based on the Logic of Multiple-Valued Argumentation
Authors: Gowun Jeong, Hajime Sawamura
Venue: Multi-Agent Systems for Society: 8th Pacific Rim International Workshop on Multi-Agents, PRIMA 2005, Kuala Lumpur, Malaysia, September 26-28, 2005, Revised Selected Papers (2009)

A Logic of Multiple-valued Argumentation (LMA) was formalized by Takahashi and Sawamura on an expressive knowledge representation language, Extended Annotated Logic Programming (EALP). LMA allows agents to construct arguments under uncertain knowledge and to argue with other agents on uncertain issues in the open networked heterogeneous environment. In this paper, we demonstrate its expressiveness and applicability through implementing it in a networked environment and applying it to diverse uncertain domains in which decision-making is sought in an argumentative way. We then show that it is the diversity of truth values in LMA that allows for an extensive applicability of it.
The measurement of user satisfaction with question answering systems
Authors: Chorng-Shyong Ong, Min-Yuh Day, Wen-Lian Hsu
Venue: Information and Management (2009)

Question Answering Systems (QAS) are receiving increasing attention from IS researchers, particularly those in the information retrieval and natural language processing communities. Evaluation of an IS's success and user satisfaction are important issues, especially for emerging online service systems using the Internet. Although many QAS have been implemented, little work has been done on the development of an evaluation model for them. Our purpose was to develop a validated instrument to measure user satisfaction with QAS (USQAS). The proposed validated instrument was intended as a reference for the design of QAS from a user's perspective.
A Schrödinger Wave Equation Approach to the Eikonal Equation: Application to Image Analysis
Authors: Anand Rangarajan, Karthik S. Gurumoorthy
Venue: Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition (2009)

As Planck's constant $\hbar$ (treated as a free parameter) tends to zero, the solution to the eikonal equation $|\nabla S(X)|=f(X)$ can be increasingly closely approximated by the solution to the corresponding Schrödinger equation. When the forcing function f(X) is set to one, we get the Euclidean distance function problem. We show that the corresponding Schrödinger equation has a closed form solution which can be expressed as a discrete convolution and efficiently computed using a Fast Fourier Transform (FFT). The eikonal equation has several applications in image analysis, viz. signed distance functions for shape silhouettes, surface reconstruction from point clouds and image segmentation being a few. We show that the sign of the distance function, its gradients and curvature can all be written in closed form, expressed as discrete convolutions and efficiently computed using FFTs. Of note here is that the sign of the distance function in 2D is expressed as a winding number computation. For the general eikonal problem, we present a perturbation series approach which results in a sequence of discrete convolutions once again efficiently computed using FFTs. We compare the results of our approach with those obtained using the fast sweeping method, closed-form solutions (when available) and Dijkstra's shortest path algorithm.
A cyborg beetle: wireless neural flight control of a free-flying insect
Authors: M. M. Maharbiz
Venue: Proceedings of the 22nd Annual Symposium on Integrated Circuits and System Design: Chip on the Dunes (2009)

We recently demonstrated the remote control of insects in free flight via an implantable radio-equipped miniature neural stimulating system. The system consisted of neural stimulators, muscular stimulators, a radio transceiverequipped microcontroller and a microbattery. Flight initiation, cessation and elevation control were accomplished through neural stimulus of the brain which elicited, suppressed or modulated wing oscillation. Turns were triggered through the direct muscular stimulus of either of the basalar muscles. We believe this type of technology will open the door to in-flight perturbation and recording of insect flight responses.
Broad-coverage sense disambiguation and information extraction with a supersense sequence tagger
Authors: Massimiliano Ciaramita, Yasemin Altun
Venue: Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing (2006)

In this paper we approach word sense disambiguation and information extraction as a unified tagging problem. The task consists of annotating text with the tagset defined by the 41 Wordnet supersense classes for nouns and verbs. Since the tagset is directly related to Wordnet synsets, the tagger returns partial word sense disambiguation. Furthermore, since the noun tags include the standard named entity detection classes -- person, location, organization, time, etc. -- the tagger, as a by-product, returns extended named entity information. We cast the problem of supersense tagging as a sequential labeling task and investigate it empirically with a discriminatively-trained Hidden Markov Model. Experimental evaluation on the main sense-annotated datasets available, i.e., Semcor and Senseval, shows considerable improvements over the best known "first-sense" baseline.
Cryptanalysis of the random number generator of the Windows operating system
Authors: Leo Dorrendorf, Zvi Gutterman, Benny Pinkas
Venue: ACM Transactions on Information and System Security (TISSEC) (2009)

The PseudoRandom Number Generator (PRNG) used by the Windows operating system is the most commonly used PRNG. The pseudorandomness of the output of this generator is crucial for the security of almost any application running in Windows. Nevertheless, its exact algorithm was never published. We examined the binary code of a distribution of Windows 2000. This investigation was done without any help from Microsoft. We reconstructed the algorithm used by the pseudorandom number generator (namely, the function CryptGenRandom). We analyzed the security of the algorithm and found a nontrivial attack: Given the internal state of the generator, the previous state can be computed in 223 steps. This attack on forward security demonstrates that the design of the generator is flawed, since it is well known how to prevent such attacks. After our analysis was published, Microsoft acknowledged that Windows XP is vulnerable to the same attack. We also analyzed the way in which the generator is used by the operating system and found that it amplifies the effect of the attack: The generator is run in user mode rather than in kernel mode; therefore, it is easy to access its state even without administrator privileges. The initial values of part of the state of the generator are not set explicitly, but rather are defined by whatever values are present on the stack when the generator is called. Furthermore, each process runs a different copy of the generator, and the state of the generator is refreshed with system-generated entropy only after generating 128KB of output for the process running it. The result of combining this observation with our attack is that learning a single state may reveal 128KB of the past and future output of the generator. The implication of these findings is that a buffer overflow attack or a similar attack can be used to learn a single state of the generator, which can then be used to predict all random values, such as SSL keys, used by a process in all its past and future operations. This attack is more severe and more efficient than known attacks in which an attacker can only learn SSL keys if it is controlling the attacked machine at the time the keys are used.
The Social Network Induced by the Common Knowledge of Proverbs
Authors: Matthias Funk, Armando Mendes
Venue: Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining (2009)

In a series of interviews, we collected a heterogeneous set of several million relations of positive and negative knowledge that a group of thousands of people has about a set of circa twenty-two thousand Portuguese Proverbs. One of the interesting questions was if we could find a minimum base of proverbs as an indicator to decide from which place a person came due to their specific profile of proverbial knowledge. Before trying this challenge, we will analyse, in this article, the probability of achieving such an idea by trying to find out if a homomorphism between the proverbial knowledge and the geographical location of a person could exist.To solve this question, we chose an approach based on the analysis of social networks where the broadcast of oral culture, at least historically, could be interpreted as a trace of direct social contact between some of their users. We found, in the present pilot-project based on small data sets, that there are clusters where the neighbourhood relation inducted by the minimum Hamming Distance could be a reflex of the geographical distribution and of some migration flux of the population.
Modeling human behavior for virtual training systems
Authors: Yohei Murakami, Yuki Sugimoto, Toru Ishida
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

Constructing highly realistic agents is essential if agents are to be employed in virtual training systems. In training for collaboration based on face-to-face interaction, the generation of emotional expressions is one key. In training for guidance based on one-to-many interaction such as direction giving for evacuations, emotional expressions must be supplemented by diverse agent behaviors to make the training realistic. To reproduce diverse behavior, we characterize agents by using a various combinations of operation rules instantiated by the user operating the agent. To accomplish this goal, we introduce a user modeling method based on participatory simulations. These simulations enable us to acquire information observed by each user in the simulation and the operating history. Using these data and the domain knowledge including known operation rules, we can generate an explanation for each behavior. Moreover, the application of hypothetical reasoning, which offers consistent selection of hypotheses, to the generation of explanations allows us to use otherwise incompatible operation rules as domain knowledge. In order to validate the proposed modeling method, we apply it to the acquisition of an evacuee's model in a fire-drill experiment. We successfully acquire a subject's model corresponding to the results of an interview with the subject.
Multi-core Implementations of Geometric Algorithms
Authors: Stefan Näher, Daniel Schmitt
Venue: Efficient Algorithms: Essays Dedicated to Kurt Mehlhorn on the Occasion of His 60th Birthday (2009)

This paper presents a framework for multi-core implementations of divide and conquer algorithms and shows its efficiency and ease of use by applying it to some fundamental problems in computational geometry. The framework supports automatic parallelization of any D C algorithm. It is only required that the algorithm is implemented by a C++ class implementing a so-called job-interface. We also report on experimental results and discuss some aspects of the automatic parallelization of randomized incremental algorithms. Some results of this paper have been presented in the 20th Annual Canadian Conference on Computational Geometry ([13]).
Precise Analysis of Spectral Reflectance Properties of Cosmetic Foundation
Authors: Yusuke Moriuchi, Shoji Tominaga, Takahiko Horiuchi
Venue: Proceedings of the 16th Scandinavian Conference on Image Analysis (2009)

The present paper describes the detailed analysis of the spectral reflection properties of skin surface with make-up foundation, based on two approaches of a physical model using the Cook-Torrance model and a statistical approach using the PCA. First, we show how the surface-spectral reflectances changed with the observation conditions of light incidence and viewing, and also the material compositions. Second, the Cook-Torrance model is used for describing the complicated reflectance curves by a small number of parameters, and rendering images of 3D object surfaces. Third, the PCA method is presented the observed spectral reflectances analysis. The PCA shows that all skin surfaces have the property of the standard dichromatic reflection, so that the observed reflectances are represented by two components of the diffuse reflectance and a constant reflectance. The spectral estimation is then reduced to a simple computation using the diffuse reflectance, some principal components, and the weighting coefficients. Finally, the feasibility of the two methods is examined in experiments. The PCA method performs reliable spectral reflectance estimation for the skin surface from a global point of view, compared with the model-based method.
A hybrid of Nested Partition, Binary Ant System, and Linear Programming for the multidimensional knapsack problem
Authors: S. Al-Shihabi, S. ílafsson
Venue: Computers and Operations Research (2010)

This work presents a hybrid algorithm of Nested Partition (NP), Binary Ant System (BAS), and Linear Programming (LP) to solve the multidimensional knapsack problem (MKP). The hybrid NP+BAS+LP algorithm takes advantage of the global search strategies of the NP algorithm; the ability of BAS to quickly generate good solutions and incorporates information obtained from solving a LP relaxation of the MKP to help guide the search. It thus incorporates both the lower bounds (LB), found by the BAS, and the upper bounds (UB), found by solving the relaxed LP, into the search by embedding both in the NP framework. An adjustable computation budget is implemented where the number of samples increases if the LB and the UB point to different promising subregions. The proposed hybrid is compared to state-of-the-art solution techniques and is found to be one of the best algorithms in terms of the quality of solutions obtained and CPU time requirements.