ppxscal/embedding_network huggingface dataset:
RELATIONAL DATA MINING AND ILP FOR DOCUMENT IMAGE UNDERSTANDING
Authors: Michelangelo Ceci, Margherita Berardi, Donato Malerba
Venue: Applied Artificial Intelligence (2007)

Document image understanding denotes the recognition of semantically relevant components in the layout extracted from a document image. This recognition process is based on domain-specific knowledge that can be acquired automatically by applying data mining techniques. The spatial dimension of page layout makes classification methods developed in inductive logic programming (ILP) and multi-relational data mining (MRDM) the most suitable candidates for this specific task. In this paper, both approaches are considered and empirically compared on three different data sets consisting of multi-page articles published in an international journal and historical documents. The ILP method is able to learn recursive logical theories that express dependencies between logical components, while the MRDM method extends the naïve Bayesian classifier to data stored in multiple tables of a relational database. Experimental results confirm the importance of the spatial dimension for this application and show that the ILP method tends to be conservative with a high (low) percentage of omission (commission) errors, while the probabilistic nature of the MRDM method allows us to tradeoff between the two types of error.
Adaptive optimization of join trees for multi-join queries over sensor streams
Authors: Joseph Gomes, Hyeong-Ah Choi
Venue: Information Fusion (2008)

Data processing applications for sensor streams have to deal with multiple continuous data streams with inputs arriving at highly variable and unpredictable rates from various sources. These applications perform various operations (e.g. filter, aggregate, join, etc.) on incoming data streams in real-time according to predefined queries or rules. Since the data rate and data distribution fluctuate over time, an appropriate join tree for processing join queries must be adaptively maintained in response to dynamic changes to prevent rapid degradation of the system performance. In this paper, we address the problem of finding an optimal join tree that maximizes throughput for sliding window based multi-join queries over continuous data streams and prove its NP-Hardness. We present a dynamic programming algorithm, OptDP, which produces the optimal tree but runs in an exponential time in the number of input streams. We then present a polynomial time greedy algorithm, XGreedyJoin. We tested these algorithms in ARES, an adaptively re-optimizing engine for stream queries, which we developed by extending Jess (Jess is a popular RETE-based, forward chaining rule engine written in java). For almost all instances, trees from XGreedyJoin perform close to the optimal trees from OptDP, and significantly better than common heuristics-based XJoin algorithms.
Quality of Service Routing for Real-Time Applications Using the Analytical Hierarchy Process (Invited Paper)
Authors: Albara Awajan, Khalid Al-Begain, Paula Thomas
Venue: Proceedings of the Tenth International Conference on Computer Modeling and Simulation (2008)

Multimedia and real-time applications applied on the Internet require Quality of Service (QoS) routing algorithms; however, QoS routing is considered an NP-complete problem. This paper proposes an enhanced source based QoS routing algorithm that aims at reducing the complexity of route selection for services with multi QoS metrics. The algorithm uses the Analytic Hierarchy Process to find the best path between the service provider and the client that meets a list of constraints stored in a QoS profile; these constraints are specific for that particular service. Simulation results show that the algorithm finds a path with multiple metrics in scalable time; also the algorithm shows high ability to handle various types of multimedia and real-time applications
Path-quality monitoring in the presence of adversaries
Authors: Sharon Goldberg, David Xiao, Eran Tromer, Boaz Barak, Jennifer Rexford
Venue: ACM SIGMETRICS Performance Evaluation Review (2008)

Edge networks connected to the Internet need effective monitoring techniques to drive routing decisions and detect violations of Service Level Agreements (SLAs). However, existing measurement tools, like ping, traceroute, and trajectory sampling, are vulnerable to attacks that can make a path look better than it really is. In this paper, we design and analyze path-quality monitoring protocols that reliably raise an alarm when the packet-loss rate and delay exceed a threshold, even when an adversary tries to bias monitoring results by selectively delaying, dropping, modifying, injecting, or preferentially treating packets. Despite the strong threat model we consider in this paper, our protocols are efficient enough to run at line rate on high-speed routers. We present a secure sketching protocol for identifying when packet loss and delay degrade beyond a threshold. This protocol is extremely lightweight, requiring only 250-600 bytes of storage and periodic transmission of a comparably sized IP packet to monitor billions of packets. We also present secure sampling protocols that provide faster feedback and accurate round-trip delay estimates, at the expense of somewhat higher storage and communication costs. We prove that all our protocols satisfy a precise definition of secure path-quality monitoring and derive analytic expressions for the trade-off between statistical accuracy and system overhead. We also compare how our protocols perform in the client-server setting, when paths are asymmetric, and when packet marking is not permitted.
Active forest fire monitoring in Uttaranchal State, India using multi-temporal DMSP-OLS and MODIS data
Authors: T. R. Kiran Chand, K. V. S. Badarinath, M. S. R. Murthy, G. Rajshekhar, C. D. Elvidge, B. T. Tuttle
Venue: International Journal of Remote Sensing (2007)

This paper gives an account of day-night active forest fire monitoring conducted over the sub-tropical and moist temperate forests of the Uttaranchal State, India, during 2005 using the Defence Meteorological Satellite Program-Operational Line Scan system (DMSP-OLS) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. The state experienced heavy fire episodes during May-June 2005 and daily datasets of DMSP-OLS (night-time) and selected cloud-free MODIS (daytime) datasets were used in mapping active fire locations. DMSP-OLS collects data in visible (0.5 to 0.9 µm) and thermal (10.5 to 12.5 µm) bands and detects dim sources of lighting on the earth's surface, including fires. The enhanced fire algorithm for active fire detection (version 4) was used in deriving fire products from MODIS datasets. Fire locations derived from DMSP-OLS and MODIS data were validated with limited ground data from forest department and media reports. Results of the study indicated that the state experienced heavy fire episodes, most of them occurring during night-time rather than daytime. Validation of satellite-derived fires with ground data showed a high degree of spatial correlation.
Study of Multi-Agent Task Model Based on Product Structure Breakdown
Authors: Hao Yongping, Zeng Pengfei, Shao Weiping
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

From the view of task modeling of project process in Product Data Management (PDM) system, a User-Task Allocation Model is put forward based-on product breakdown structure for distributed collaborative product design. The constraints model of function mapping was established between product structure and task breakdown structure. The Colored Petri Net was introduced into PDM system as the modeling tool to realize product structure model- driven project task management mode and to execute dynamic visible design task scheduling. It is explored to apply Multi-agent system to carry out intelligent task management and dispatching. The Agent communication and task dispatching framework were implemented.
Low-power high-accuracy timing systems for efficient duty cycling
Authors: Thomas Schmid, Jonathan Friedman, Zainul Charbiwala, Young H. Cho, Mani B. Srivastava
Venue: Proceeding of the 13th international symposium on Low power electronics and design (2008)

Time keeping and synchronization are important services for networked and embedded systems. High quality timing information allows embedded network nodes to provide accurate time-stamping, fast localization, efficient duty cycling schedules, and other basic but essential functions - all of which are required for low power operation. In this paper we present a new type of local clock source called Crystal Compensated Crystal based Timer (XCXT) and a number of novel algorithms that effectively utilize it to achieve low power consumption in wireless sensor networks. The XCXT has timing accuracies similar to timers based on temperature compensated crystal oscillators (TCXO) but has a lower implementation cost and requires less power. Our initial 8MHz prototype unit, using the simplest algorithm, achieves an effective frequency stability of ±1.2ppm and consumes only 1.27mW. On the other hand, commercially available TCXOs with similar stability can cost over 10 times as much and consume over 20mW. In addition to the prototype, we will present algorithms that will improve the XCXT's power consumption by at least 48%, depending on application and environmental conditions. We will also show how XCXT's power efficiency can be improved even further by employing clocks at different frequency when different time granularities are required by an application.
Modelling of the mitochondrial apoptosis network
Authors: J. Cui, C. Chen, H. Lu, P. Shen
Venue: International Journal of Bioinformatics Research and Applications (2008)

In this paper, we performed an experimental observation-based computer simulation of the regulatory network of mitochondrial apoptosis. By modelling we obtained dynamical understandings of various apoptosis-related proteins, including cytochrome c (cyt c) release and caspase activation. Through parameter analysis, we examined the role of Bcl-2 family proteins and the natural inhibitors of apoptosis in the regulatory network of apoptosis. Furthermore, the effects of several amplified loops in the network were found to enhance caspase activation and make the decision of apoptosis switch like. Consistent with most available experimental evidences, our results yield insights into the complex regulatory mechanism of mitochondrial apoptosis.
Anomaly Detection Using LibSVM Training Tools
Authors: Chu-Hsing Lin, Jung-Chun Liu, Chia-Han Ho
Venue: Proceedings of the 2008 International Conference on Information Security and Assurance (isa 2008) (2008)

Intrusion detection is the means to identify the intrusive behaviors and provides useful information to intruded systems to respond fast and to avoid or reduce damages. In recent years, learning machine technology is often used as a detection method in anomaly detection. In this research, we use support vector machine as a learning method for anomaly detection, and use LibSVM as the support vector machine tool. By using this tool, we get rid of numerous and complex operation and do not have to use external tools for finding parameters as need by using other algorithms such as the genetic algorithm. Experimental results show that high average detection rates and low average false positive rates in anomaly detection are achieved by our proposed approach.
Privacy-MaxEnt: integrating background knowledge in privacy quantification
Authors: Wenliang Du, Zhouxuan Teng, Zutao Zhu
Venue: Proceedings of the 2008 ACM SIGMOD international conference on Management of data (2008)

Privacy-Preserving Data Publishing (PPDP) deals with the publication of microdata while preserving people' private information in the data. To measure how much private information can be preserved, privacy metrics is needed. An essential element for privacy metrics is the measure of how much adversaries can know about an individual's sensitive attributes (SA) if they know the individual's quasi-identifiers (QI), i.e., we need to measure P(SA|QI). Such a measure is hard to derive when adversaries' background knowledge has to be considered. We propose a systematic approach, Privacy-MaxEnt, to integrate background knowledge in privacy quantification. Our approach is based on the maximum entropy principle. We treat all the conditional probabilities P(SA|QI) as unknown variables; we treat the background knowledge as the constraints of these variables; in addition, we also formulate constraints from the published data. Our goal becomes finding a solution to those variables (the probabilities) that satisfy all these constraints. Although many solutions may exist, the most unbiased estimate of P(SA|QI) is the one that achieves the maximum entropy.
On the Construction of a Super-Peer Topology underneath Middleware for Distributed Computing
Authors: Peter Merz, Jan Ubben, Matthias Priebe
Venue: Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid (2008)

Scalability constitutes a key property of Peer-to-Peer overlay networks. Recent advances that improve scalability include super-peer infrastructures and network coordinates.As an integral part of an upcoming middleware for distributed computing, we have developed a mechanism that builds and maintains a super-peer overlay network in a decentralized, self-organized way, using network coordinates to facilitate inter-peer distance estimation.We discuss the benefits of super-peer infrastructures in the context of Desktop Grids and present the outcome of experiments conducted on PlanetLab to observe the constructed topology's behavior in a practical environment.
Instructional efficiency of integrated and separated text with animated presentations in computer-based science instruction
Authors: Zeynel Kablan, Münire Erden
Venue: Computers Education (2008)

This study deals with the instructional efficiency of integrating text and animation into computer-based science instruction. The participants were 84 seventh-grade students in a private primary school in Istanbul. The efficiency of instruction was measured by mental effort and performance level of the learners. The results of the study showed that processing integrated text and animation format in computer-based science instruction requires less mental effort than the separated format, and that the performance of the students in the group with integrated presentation format group is higher than that of students in the group with separated presentation format. Instructional efficiency of the integrated presentation group was found to be higher than that of the separated presentation group. Finally, there was no difference between the two groups for instructional time.
Gains in activation energy from quasi Fermi splitting, in selectively doped MQW solar cells
Authors: Argyrios C. Varonides, Robert A. Spalletta, Andrew W. Berger
Venue: Proceedings of the 9th International Conference on Circuits (2005)

Illumination of a Multiple Quantum Well (MQW) solar cell, affects the Fermi level position in the gap, directly under the conduction band of the narrow gap layer. In this communication, we explore Fermi level shifting and splitting in these structures. The neutrality condition is examined in terms of (a) availability of carriers (b) carrier confinement (c) escaping carriers (d) doping levels (e) layer width and (f) Fermi level dependence on doping and illumination. We conclude that short circuit currents and open circuit voltage are seriously affected.
Validation of Alternating Kernel Mixture Method Based Segmentation of the Human Brain
Authors: Nayoung A. Lee, Carey E. Priebe, J. Tilak Ratnanather, Michael I. Miller
Venue: Proceedings of the 2007 Frontiers in the Convergence of Bioscience and Information Technologies (2007)

This paper describes the application of a novel segmentation method in high resolution MRI subvolumes containing hippocampus in five subjects and occipital lobe in five subjects. The alternating kernel mixture (AKM) algorithm is used to segment the MRI subvolumes into cerebrospinal fluid, gray matter, and white matter. The segmentation is validated by comparison with manual segmentation. The misclassification errors are 0.10-0.17 (n=10). When compared with Bayesian segmentation method, AKM yields smaller errors. By generating multiple mixtures for each tissue compartment, AKM mimics the increasing variance in the manual segmentation in partial volumes between the highly folded tissues. AKM's superior performance makes it useful for automated segmentation of sub-cortical and cortical structures in neuro-imaging studies.
Conserved Domain Combination Identification in Human Proteins
Authors: Suk Hoon Jung, Desok Kim, Dong-Soo Han
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

In this paper, we propose a method for the analysis of conservation of domain combinations in proteins. Using the method, we extract conserved domain combinations in Homo sapience proteome and examine their GO term annotations in order to understand the co-evolution of domains in a proteome. Unlike conventional methods, which use co-occurrence frequency for evolutionary analysis of domains, the proposed method measures mutual dependency of domains in proteins as well. According to the results, domains in Homo sapience proteome turn out to form patterns whose members are highly affiliated to one another. Besides, GO term analysis shows that extracted patterns have a tendency of being associated with molecular functions, and molecular functions are more related with mutual dependency than co-occurrence frequency of domains. Those results indicate that the proposed method adopting mutual dependency outperforms conventional methods in terms of finding domain combinations conserved through evolution for molecular functional collaboration.
Sliding-mode variable structure control for the position tracking servo system
Authors: Jiang Jing
Venue: Proceedings of the 5th WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing (2006)

This paper mainly discusses a control algorithm basing on the principle of the sliding mode variable structure control for the position tracking servo system. The original control strategy of the system is classical control. It neglects the backlash nonlinear characteristics and the parameters uncertainties of the system, and it regards the system as a linear one, so the dynamic and static control properties of the system are not excellent. Simulation results show that the new control algorithm exhibits the better control effects than the classical control method, and the rapidness and robustness of the system are improved. Moreover, this control system realization is simple and convenient.
A flexible dual frequency testbed for RFID
Authors: Christoph Angerer, Martin Holzer, Bastian Knerr, Markus Rupp
Venue: Proceedings of the 4th International Conference on Testbeds and research infrastructures for the development of networks & communities (2008)

This paper presents the setup of a testbed developed for the fast evaluation of RFID systems in two frequency domains. At the one hand the 13.56 MHz and at the other hand the 868 MHz frequency domain are supported. The suggested design flow for configuring the testbed is highly automated and supports rapid evaluations of different designs and implementations within shortest time. Several layers of abstraction for rating existing and future RFID standards are provided, from abstract simulation models down to the implementation on the rapid prototype. This includes a fast setup for measuring and rating existing RFID standards, or running them side by side, as well as the rapid exploration of future RFID designs and various aspects of those prototypes. It allows for verifying both protocol stack- and signal processing of RFID systems. In order to demonstrate this concept, we briefly describe an implemented example system, and our overall hardware layout in detail. Measurement results on two existing RFID standards corroborate the concept.
Privacy and Islam: From the Quran to data protection in Pakistan
Authors: Muhammad Aslam Hayat
Venue: Information and Communications Technology Law (2007)

Islam gives great importance to the fundamental human right to privacy. This is evident from the some of the verses of the Holy Quran: 'Do not spy on one another' (49:12); 'Do not enter any houses except your own homes unless you are sure of their occupants' consent' (24:27). The Prophet has gone to the extent of instructing his followers that a man should not enter even his own house suddenly or surreptitiously. This article attempts to explore the extent of the sanctity given to the right to privacy by Islam and the kinds of privacy it recognizes. It will also explore the extent to which this right has been recognized in the laws of certain key Islamic Countries. The article includes a case study of Pakistan, an Islamic state that recognizes the Quran and Sunnah as sources of law. Under the Pakistani Constitution, there cannot be a law in violation of the injunctions of Islam. In fact, various laws have been declared to be in violation of the injunctions of Islam by the Federal Shariah Court. The Constitution of Pakistan, as well as the Pakistani law on Freedom of Information, recognizes the right to privacy. Despite this, the main objective of the draft Pakistani Data Protection Law is not to enshrine the principles of Islam, but to satisfy the requirements of European Union Directive 95/46, in particular Article 25 thereof, with the hope of ensuring that data will be allowed to flow freely between the European Union and Pakistan, thus making Pakistan an attractive market for outsourcing.
Hybrid Content-Based Trademark Retrieval Using Region and Contour Features
Authors: Zhiling Hong, Qingshan Jiang
Venue: Proceedings of the 22nd International Conference on Advanced Information Networking and Applications - Workshops (2008)

The number of registered trademarks is increasing tremendously in recent years. In order to retrieve a similar looking trademark from a large trademark database, we propose a hybrid content based trademark retrieval method using region and contour features. Experiments have been conducted on the MPEG-7 Core Experiment CE-Shape-1 database of 1400 images and a collected trademark database of 2000 images. The retrieval results are very encouraging.
Optimal algorithms and inapproximability results for every CSP?
Authors: Prasad Raghavendra
Venue: Proceedings of the 40th annual ACM symposium on Theory of computing (2008)

Semidefinite Programming(SDP) is one of the strongest algorithmic techniques used in the design of approximation algorithms. In recent years, Unique Games Conjecture(UGC) has proved to be intimately connected to the limitations of Semidefinite Programming. Making this connection precise, we show the following result : If UGC is true, then for every constraint satisfaction problem(CSP) the best approximation ratio is given by a certain simple SDP. Specifically, we show a generic conversion from SDP integrality gaps to UGC hardness results for every CSP. This result holds both for maximization and minimization problems over arbitrary finite domains. Using this connection between integrality gaps and hardness results we obtain a generic polynomial-time algorithm for all CSPs. Assuming the Unique Games Conjecture, this algorithm achieves the optimal approximation ratio for every CSP. Unconditionally, for all 2-CSPs the algorithm achieves an approximation ratio equal to the integrality gap of a natural SDP used in literature. Further the algorithm achieves at least as good an approximation ratio as the best known algorithms for several problems like MaxCut, Max2Sat, MaxDiCut and Unique Games.