ppxscal/embedding_network huggingface dataset:
Honey@home: a new approach to large-scale threat monitoring
Authors: Spiros Antonatos, Kostas Anagnostakis, Evangelos Markatos
Venue: Proceedings of the 2007 ACM workshop on Recurring malcode (2007)

Honeypots have been shown to be very useful for accurately detecting attacks, including zero-day threats, at a reasonable cost and without false positives. However, there are two pressing problems with existing approaches. The first problem is that timely detection requires deployment of honeypots in a large fraction of the network address space, many organizations cannot afford. The second problem is that attackers are evolving, and it has been shown that it is not difficult for them to identify honeypots and develop blacklists to avoid them when launching an attack In response to these problems, we propose a new architecture that enables large-scale deploymentat low cost, while making it harder for attackers to maintain accurate blacklists. The Honey@home architecture relies on communities of regular users installing a lightweight honeypot that monitors unused addresses and ports. Because it does not require the static allocation of valuable chunks of network address space, and considering the success of other community-based approaches such as seti@home, our approach is well-suited for creating a large-scale honeypot infrastructure at low cost. Since participation in the system is dynamic as users come and go, it becomes harder for attackers to maintain accurate blacklists In this paper we discuss the current design of the Honey@home architecture, a preliminary implementation and describe the design issues that we faced especially with respect to infrastructure robustness, the challenges we have to deal with and the effectiveness of our approach.
Strength Induction in a Haskell Program Verifier
Authors: Richard B. Kieburtz
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2007)

Haskell employs a melange of strict and non-strict evaluation semantics, hence a Haskell verifier should be capable of checking assumptions that program variables may or may not denote well-defined values. The paper introduces a new strategy, called strength induction, that supports automatic checking of definedness assumptions. Strength induction has been implemented in Plover, an automated property-verifier for Haskell programs that has been under development for the past three years as a component of the Programatica project. In Programatica, predicate definitions and property assertions written in P-logic, a programming logic for Haskell, can be embedded in the text of a Haskell program module. Properties refine the type system of Haskell but cannot be verified by type-checking alone; a more powerful logical verifier is required. Plover codes the proof rules of P-logic, and additionally, embeds strategies and decision procedures for their application and discharge. It integrates a reduction system that implements a rewriting semantics for Haskell terms with a congruence-closure algorithm that supports reasoning with equality.
On the experience of love: the underlying principles
Authors: Beatriz Russo, Paul Hekkert
Venue: Proceedings of the 2007 conference on Designing pleasurable products and interfaces (2007)

In design research, general theories on experiential concepts have been accessed, conceptual models of experiences have been developed, and design strategies for experience have been presented. However, due to the complex nature of experiences and the multidisciplinary nature of design, we argue that designers may not be fully equipped with information to design for particular experiences. In our previous study, we adopted general theories of interpersonal love to conceptualize the 'experience of love' in person-product interaction. In this paper, we complete this conceptualization and present the underlying principles of love. The principles of love are fixed and predetermined 'modes of action' that trigger what is experienced as 'love' in the interaction with consumer products. We believe that, equipped with a complete and clear set of information over experiential concepts, designers and developers would be free to develop their own creativity and, consequently, have more control over their work.
World wide web: online core concept thesaucratic database development to improve information seeking
Authors: Victoria Redfern
Venue: Proceedings of the sixth conference on IASTED International Conference Web-Based Education - Volume 2 (2007)

Information seeking by undergraduate and postgraduate students who are either new to academic research or are from a non-English speaking background is sometimes fraught with difficulties and obstacles for the unwary. Because of personal habits in a home or personal setting Computer users often resort to using the www and Google® to find academic materials. Whilst this is not necessarily an unwise method of finding academic information, those users still experience similar problems because they are related to the establishment of effective search terms. Rootza®TM is an information seeking tool I developed in an attempt to make online searching easier for either the novice or non-novice information seeker. Rootza was researched, developed and experiments conducted with student participants as a PhD project. Rootza's core function is to teach information seekers The Big 61 steps of information seeking as well as the 6 elements that form the basis for the evaluation of online materials acceptable to academic standards. The resulting research and statistical analysis shows a marked improvement in the online information seeking skills for the students who participated in the experiment. This data suggests that the online core concept thesaucratic database which informs the user of the steps of information seeking and the elements which constitute online academically acceptable information does indeed assist students and information seekers.
Fault Diagnosis Method Based on Hybrid Immune Learning Algorithm
Authors: Cunjie Wang, Yuhong Zhao
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

A new fault diagnosis method is proposed, which combines negative selection algorithm and conventional classification algorithm. All the available training samples, including normal samples and known anomaly, are treated as positive samples (self). The real-valued negative selection algorithm is adopted to generate the negative samples (non-self), which distribute among the rest of the detected space. Both the positive and negative samples are used to train a feed forward artificial neural network classifier, whose output neurons are assigned to fault indicators. The simulation result demonstrates that the performance of the proposed approach is satisfactory.
Simulation and Research of the PCB Vias Effects
Authors: Qiu Tang, Yaonan Wang, C. Christopoulos
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

Through-hole vias is the essential element of modern multilayer PCB to connect the signal paths, power planes and ground planes on different layers of the board. The via in the signal path results in the discontinuity and a possible source of signal degradation and EMI. This paper presents the 3D Transmission-Line Modelling(TLM) method to model the vias and PCB trace and simulate the signal transmission process. The aim is to forecast the signal degradation by means of comparing the pulses propagation in the microstrip traces with and without via.
Referential integrity quality metrics
Authors: Carlos Ordonez, Javier García-García
Venue: Decision Support Systems (2008)

Referential integrity is an essential global constraint in a relational database, that maintains it in a complete and consistent state. In this work, we assume the database may violate referential integrity and relations may be denormalized. We propose a set of quality metrics, defined at four granularity levels: database, relation, attribute and value, that measure referential completeness and consistency. Quality metrics are efficiently computed with standard SQL queries, that incorporate two query optimizations: left outer joins on foreign keys and early foreign key grouping. Experiments evaluate our proposed metrics and SQL query optimizations on real and synthetic databases, showing they can help in detecting and explaining referential errors.
An HDL-Based Platform for High Level NoC Switch Testing
Authors: Mahshid Sedghi, Armin Alaghi, Elnaz Koopahi, Zainalabedin Navabi
Venue: Proceedings of the 16th Asian Test Symposium (2007)

This paper presents a non-scan method of NoC switch testing. The method requires addition of testmode hardware for NoC switches and processing elements which is much less than what is required for most scan methods. Associated with our proposed testmode of an NoC, we have developed a test environment based on high-level switch faults. The test environment applies test packets to the NoC-Under-Test in its testmode and generates an NoC fault dictionary to be used for error detection of an NoC running in the test-mode. Proposed fault models and test strategy will be discussed in this paper.
Fuzzy assignment of customers for a parallel queueing system with two heterogeneous servers
Authors: Runtong Zhang, Yannis A. Phillis
Venue: Journal of Intelligent Fuzzy Systems: Applications in Engineering and Technology (2001)

We consider a queueing system with two parallel heterogeneous servers. Each exponential server has its own queue and customers arrive at each queue according to independent Poisson processes. When a customer arrives at queue 1, the customer can be transferred to queue 2 by paying an assignment cost. Each customer in queue pays a holding cost per unit time. The objective is to dynamically determine the optimal assignment policy, based on the state of the system, so as to minimize the average cost. In this paper, a novel approach is presented using fuzzy control to solve the problem. Simulation shows that the approach is efficient and promising.
Extrapolation methods based on the algorithm of continuous process restoration by the finite number of equidistant samples
Authors: D. B. Rozhdestvenskii
Venue: Automation and Remote Control (2008)

Algorithms are obtained for the calculation of a derivative and extrapolation of a continuous process bounded in the spectrum and prescribed in the form of a finite number of discrete equidistant counts.
A Statistical and Instant Information Combined Handoff Target Prediction Scheme in NGI
Authors: Xingwei Wang, Ye Tian, Min Huang
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 02 (2007)

In this paper, a target prediction scheme for handoff in NGI is presented based on both statistical and instant information. At first, it adopts a statistical prediction scheme to predict handoff target, using fuzzy decision tree which is established based on the prior handoff historical records. If there exist several predicted handoff targets, an instant prediction scheme is initiated to compute the probability for each predicted handoff target being visited based on the user's current position, movement rate, direction and the average call duration time, choosing the one with the maximum visited probability as the handoff target. Simulation results have shown that the proposed scheme has higher prediction hitting rates under different user movement rates compared with those schemes simply based on statistical or instant information.
Synthesis of synchronous assertions with guarded atomic actions
Authors: M. Pellauer
Venue: Proceedings of the 2nd ACM/IEEE International Conference on Formal Methods and Models for Co-Design (2005)

The SystemVerilog standard introduces SystemVerilog Assertions (SVA), a synchronous assertion package based on the temporal-logic semantics of PSL. Traditionally assertions are checked in software simulation. We introduce a method for synthesizing SVA directly into hardware modules in Bluespec SystemVerilog. This opens up new possibilities for FPGA-accelerated testbenches, hardware/software co-emulation, dynamic verification and fault-tolerance. We describe adding synthesizable assertions to a cache controller, and investigate their hardware cost.
A Multi-agent Supported Adaptive Mobile Collaborative Service Platform
Authors: Yuhui Cao, Weihong Wang, Zheng Qin
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 05 (2007)

In order to support multiple mobile users cooperate with others and provide them an integrated services, which including multiple services, a novel platform SMCSP (the platform supporting mobile collaboration services), was constructed. Firstly, it adopted the flexible layered configuration structure to adapt the dynamic complex mobile environment. Then, the mobile collaboration was depicted by the different cooperative semantic granularity of cooperative group. After that, the multi-agent supported architecture was given based on the cooperative process of multi-Agent. In order to strengthen the Adaptation of the platform, a context awareness module was added to the platform. Finally, the prototype system of the SMCSP was displayed. The practice indicates the SMCSP platform can support the mobile collaboration work of multiple mobile users well.
A linear-time algorithm for the k-fixed-endpoint path cover problem on cographs
Authors: Katerina Asdre, Stavros D. Nikolopoulos
Venue: Networks (2007)

In this paper, we study a variant of the path cover problem, namely, the k-fixed-endpoint path cover problem. Given a graph G and a subset {\cal T} of k vertices of V(G), a k-fixed-endpoint path cover of G with respect to {\cal T} is a set of vertex-disjoint paths {\cal P} that covers the vertices of G such that the k vertices of {\cal T} are all endpoints of the paths in {\cal P}. The k-fixed-endpoint path cover problem is to find a k-fixed-endpoint path cover of G of minimum cardinality; note that, if {\cal T} is empty, that is, k = 0, the stated problem coincides with the classical path cover problem. We show that the k-fixed-endpoint path cover problem can be solved in linear time on the class of cographs. More precisely, we first establish a lower bound on the size of a minimum k-fixed-endpoint path cover of a cograph and prove structural properties for the paths of such a path cover. Then, based on these properties, we describe an algorithm which, for a cograph G on n vertices and m edges, computes a minimum k-fixed-endpoint path cover of G in linear time, that is, in O(n+m) time. The proposed algorithm is simple, requires linear space, and also enables us to solve some path cover related problems, such as the 1HP and 2HP, on cographs within the same time and space complexity. &copy; 2007 Wiley Periodicals, Inc. NETWORKS, Vol. 50(4), 231240 2007
Multi-relational Association Rule Mining with Guidance of User
Authors: Jingfeng Guo, Weifeng Bian, Jing Li
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

1 A multi-relational association rule mining algorithm with guidance of the user is proposed in this paper. A tuple ID propagation approach is used to solve the association rule mining with multiple database relations directly, and introduces the concept of the user's guidance in this paper. The approach has improved user's satisfaction with the mining result. Compared with the traditional algorithms, it improves the accuracy and supports multi-relational databases directly, so its running time is less than that of the multi-relational association rule mining methods based on ILP.
Intuitionistic computability logic
Authors: Giorgi Japaridze
Venue: Acta Cybernetica (2007)

Computability logic (CL) is a systematic formal theory of computational tasks and resources, which, in a sense, can be seen as a semantics-based alternative to (the syntactically introduced) linear logic. With its expressive and flexible language, where formulas represent computational problems and "truth" is understood as algorithmic solvability, CL potentially offers a comprehensive logical basis for constructive applied theories and computing systems inherently requiring constructive and computationally meaningful underlying logics. Among the best known constructivistic logics is Heyting's intuitionistic calculus INT, whose language can be seen as a special fragment of that of CL. The constructivistic philosophy of INT, however, just like the resource philosophy of linear logic, has never really found an intuitively convincing and mathematically strict semantical justification. CL has good claims to provide such a justification and hence a materialization of Kolmogorov's known thesis "INT = logic of problems". The present paper contains a soundness proof for INT with respect to the CL semantics.
An Improved Genetic Algorithm for the P-wave AVO Inversion
Authors: Haiyan Zhang, Xin Li
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

An improved genetic algorithm (IGA) is presented for geophysical P-wave amplitude variation with offset (AVO) inversion. The optimization method includes two phases: a new real coded GA with hybrid selection operator and hybrid crossover operator serves as a base level search. It makes a quick decision to direct the search towards the optimal region. In phase-2, the diversity of the population is maintained by creating new population and the particular parent with the best fitness is preserved in the next generation. The elitism method increases the probability of finding the global optimum. The experimental results show that the IGA not only improves the solution accuracy but also increases the convergence speed. Applying the IGA to P-wave AVO inversion, four elastic parameter contrasts are extracted. The proposed algorithm presents good stability in noisy condition.
What is Ada?
Authors: R. F. Brender
Venue: Computer (1981)

This introduction to the principal features of Ada emphasizes those aspects expected to offer significant advantage in large-scale program development.
Cluster Analysis Based on Artificial Immune System and Ant Algorithm
Authors: Chui-Yu Chiu, Chia-Hao Lin
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

Ant algorithm is a meta-heuristic approach successfully applied to solve hard combinatorial optimization problems. It is also feasible for clustering analysis in data mining. Many researches use ant algorithms for clustering analysis and the result is better than other heuristic methods. In order to improve the performance of the algorithm, the artificial immune system is utilized to strengthen the ant algorithm for clustering analysis. In this paper, we proposes a new algorithm for clustering problem, the immunity-based Ant Clustering Algorithm (IACA). IACA using the artificial immune system and ant algorithm is an auto-clustering method which can decide the number of the clusters and its centroids. In this research, the proposed algorithm and these two clustering methods will be verified by 243 data sets are generated by Monte Carlo method to evaluate the performance of our proposed method and other methods.
LDA-Based Retrieval Framework for Semantic News Video Retrieval
Authors: Juan Cao, Jintao Li, Yongdong Zhang, Sheng Tang
Venue: Proceedings of the International Conference on Semantic Computing (2007)

Topic-based language model has attracted much attention as the propounding of semantic retrieval in recent years. Especially for the ASR text with errors, the topic representation is more reasonable than the exact term representation. Among these models, Latent Dirichlet Allocation(LDA) has been noted for its ability to discover the latent topic structure, and is broadly applied in many text-related tasks. But up to now its application in information retrieval(IR) is still limited to be a supplement to the standard document models, and furthermore, it has been pointed out that directly employing the basic LDA model will hurt retrieval performance. In this paper, we propose a lexicon-guided two-level LDA retrieval framework. It uses the HowNet to guide the first-level LDA model's parameter estimation, and further construct the second-level LDA models based on the first-level's inference results. We use TRECVID 2005 ASR collection to evaluate it, and compare it with the vector space model(VSM) and latent semantic Indexing(LSI). Our experiments show the proposed method is very competitive.
Distributed Management of a Software Database
Authors: M. A. Linton
Venue: IEEE Software (1987)

The Allegro model demonstrates that communication among objects in different spaces can be implemented efficiently in a software-development database.
Domain-Analysis in Software Reuse - Application in Warehouse Management
Authors: Youxin Meng, Aiguang Young, Xianwei Wang, Kun Shao
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 01 (2007)

A domain-analysis based process was developed to facilitate software reuse. This process starts with analyzing domain common features/differences systematically based on software architectural considerations. The end result of domain-analysis is a domain model with a collection of well-defined and well-developed packages/components ready for reuse. The advantages of domain-analysis were demonstrated in warehouse management software system development process. Furthermore, a number of systems integrated with this domain model were successfully applied to various industries, such as electronics, chemical, and rubber industries. The results in this paper supported the notion that domain-analysis is an effective way to develop efficient component-based software system with maximized code reuse, minimized code duplication, and enhanced software quality in a substantially reduced development timeframe.
Ensemble methods for classification of patients for personalized medicine with high-dimensional data
Authors: Hojin Moon, Hongshik Ahn, Ralph L. Kodell, Songjoon Baek, Chien-Ju Lin, James J. Chen
Venue: Artificial Intelligence in Medicine (2007)

Objective: Personalized medicine is defined by the use of genomic signatures of patients in a target population for assignment of more effective therapies as well as better diagnosis and earlier interventions that might prevent or delay disease. An objective is to find a novel classification algorithm that can be used for prediction of response to therapy in order to help individualize clinical assignment of treatment. Methods and materials: Classification algorithms are required to be highly accurate for optimal treatment on each patient. Typically, there are numerous genomic and clinical variables over a relatively small number of patients, which presents challenges for most traditional classification algorithms to avoid over-fitting the data. We developed a robust classification algorithm for high-dimensional data based on ensembles of classifiers built from the optimal number of random partitions of the feature space. The software is available on request from the authors. Results: The proposed algorithm is applied to genomic data sets on lymphoma patients and lung cancer patients to distinguish disease subtypes for optimal treatment and to genomic data on breast cancer patients to identify patients most likely to benefit from adjuvant chemotherapy after surgery. The performance of the proposed algorithm is consistently ranked highly compared to the other classification algorithms. Conclusion: The statistical classification method for individualized treatment of diseases developed in this study is expected to play a critical role in developing safer and more effective therapies that replace one-size-fits-all drugs with treatments that focus on specific patient needs.