Rapid flipping of parametric phase states

Since the invention of the solid-state transistor, the overwhelming majority of computers followed the von Neumann architecture that strictly separates logic operations and memory. Today, there is a revived interest in alternative computation models accompanied by the necessity to develop corresponding hardware architectures. The Ising machine, for example, is a variant of the celebrated Hopfield network based on the Ising model. It can be realized with artifcial spins such as the `parametron' that arises in driven nonlinear resonators. The parametron encodes binary information in the phase state of its oscillation. It enables, in principle, logic operations without energy transfer and the corresponding speed limitations. In this work, we experimentally demonstrate flipping of parametron phase states on a timescale of an oscillation period, much faster than the ringdown time \tau that is often (erroneously) deemed a fundamental limit for resonator operations. Our work establishes a new paradigm for resonator-based logic architectures.Comment: 6 pages, 3 figure

Controlling services in a mobile context-aware infrastructure

Context-aware application behaviors can be described as logic rules following the Event-Control-Action (ECA) pattern. In this pattern, an Event models an occurrence of interest (e.g., a change in context); Control specifies a condition that must hold prior to the execution of the action; and an Action represents the invocation of arbitrary services. We have defined a Controlling service aiming at facilitating the dynamic configuration of ECA rule specifications by means of a mobile rule engine and a mechanism that distributes context reasoning activities to a network of context processing nodes. In this paper we present a novel context modeling approach that provides application developers and users with more appropriate means to define context information and ECA rules. Our approach makes use of ontologies to model context information and has been developed on top of web services technology

Neuro-Symbolic Recommendation Model based on Logic Query

A recommendation system assists users in finding items that are relevant to them. Existing recommendation models are primarily based on predicting relationships between users and items and use complex matching models or incorporate extensive external information to capture association patterns in data. However, recommendation is not only a problem of inductive statistics using data; it is also a cognitive task of reasoning decisions based on knowledge extracted from information. Hence, a logic system could naturally be incorporated for the reasoning in a recommendation task. However, although hard-rule approaches based on logic systems can provide powerful reasoning ability, they struggle to cope with inconsistent and incomplete knowledge in real-world tasks, especially for complex tasks such as recommendation. Therefore, in this paper, we propose a neuro-symbolic recommendation model, which transforms the user history interactions into a logic expression and then transforms the recommendation prediction into a query task based on this logic expression. The logic expressions are then computed based on the modular logic operations of the neural network. We also construct an implicit logic encoder to reasonably reduce the complexity of the logic computation. Finally, a user's interest items can be queried in the vector space based on the computation results. Experiments on three well-known datasets verified that our method performs better compared to state of the art shallow, deep, session, and reasoning models.Comment: 17 pages, 6 figure

Security information management with frame-based attack presentation and first-order reasoning

Internet has grown by several orders of magnitude in recent years, and this growth has escalated the importance of computer security. Intrusion Detection System (IDS) is used to protect computer networks. However, the overwhelming flow of log data generated by IDS hamper security administrators from uncovering new insights and hidden attack scenarios. Security Information Management (SIM) is a new growing area of interest for intrusion detection. The research work in this dissertation explores the semantics of attack behaviors and designs Frame-based Attack Representation and First-order logic Automatic Reasoning (FAR-FAR) using linguistics and First-order Logic (FOL) based approaches. Techniques based on linguistics can provide efficient solutions to acquire semantic information from alert contexts, while FOL can tackle a wide variety of problems in attack scenario reasoning and querying. In FAR-FAR, the modified case grammar PCTCG is used to convert raw alerts into frame-structured alert streams and the alert semantic network 2-AASN is used to generate the attack scenarios, which can then inform the security administrator. Based on the alert contexts and attack ontology, Space Vector Model (SVM) is applied to categorize the intrusion stages. Furthermore, a robust Variant Packet Sending-interval Link Padding algorithm (VPSLP) is proposed to prevent links between the IDS sensors and the FAR-FAR agents from traffic analysis attacks. Recent measurements and studies demonstrated that real network traffic exhibits statistical self-similarity over several time scales. The bursty traffic anomaly detection method, Multi-Time scaling Detection (MTD), is proposed to statistically analyze network traffic\u27s Histogram Feature Vector to detect traffic anomalies

Exact likelihood computation in Boolean networks with probabilistic time delays, and its application in signal network reconstruction

Motivation: For biological pathways, it is common to measure a gene expression time series after various knockdowns of genes that are putatively involved in the process of interest. These interventional time-resolved data are most suitable for the elucidation of dynamic causal relationships in signaling networks. Even with this kind of data it is still a major and largely unsolved challenge to infer the topology and interaction logic of the underlying regulatory network. Results: In this work, we present a novel model-based approach involving Boolean networks to reconstruct small to medium-sized regulatory networks. In particular, we solve the problem of exact likelihood computation in Boolean networks with probabilistic exponential time delays. Simulations demonstrate the high accuracy of our approach. We apply our method to data of Ivanova et al. (2006), where RNA interference knockdown experiments were used to build a network of the key regulatory genes governing mouse stem cell maintenance and differentiation. In contrast to previous analyses of that data set, our method can identify feedback loops and provides new insights into the interplay of some master regulators in embryonic stem cell development. Availability and implementation: The algorithm is implemented in the statistical language R. Code and documentation are available at Bioinformatics online. Contact: [email protected] or [email protected] Supplementary information: Supplementary Materials are available at Bioinfomatics onlin

A SMART DATA APPROACH TO ANALYZE VEHICLE FLOWS

Abstract. In the logic of Smart Cities it is of fundamental importance to analyze the traffic situation through dedicated sensors and networks. According to this approach and through the potential of smart data is based this study. Improve prediction of traffic patterns by analyzing and counting vehicles in a virtualized scene in real time. In the past, the technique of hardware inductive coils was used that were dropped in the asphalt to exploit the principle of magnetic induction in order to verify the transit of vehicles. This technique is not able to classify vehicles or estimate their speed, unless using multiple inductive coils. The proposed system provides for the virtualization of an area of interest which requires a selection and mapping of the areas where the control areas are to be included. The "image detection" techniques allow us to classify the vehicles in transit. With the techniques of "machine learning" can to able to verify the flow, count the vehicles present in the scene and classify them by vehicle type in real time. The vehicle counting and classification data available in the cloud platform allow to model and update the main nodes of the network in order to improve the prediction and estimates of the best routes of the road network according to the degree of saturation of the flows and the length of the line of the graph. The model can also indicate additional information of an environmental nature in an ITS system present in the cloud

The balanced scorecard logic in the management control and reporting of small business company networks: a case study

The purpose of this paper is to assess and integrate the application of the balance scorecard (BSC) logic into business networks identifying functions and use that such performance measuring tool may undertake for SME’s collaborative development. Thus, the paper analyses a successful case study regarding an Italian network of small companies, evaluating how the multidimensional perspective of BSC can support strategic and operational network management as well as communication of financial and extra financial performance to stakeholders. The study consists of a qualitative method, proposing the application of BSC model for business networks from international literature. Several meetings and interviews as well as triangulation with primary and secondary documents have been conducted. The case study allows to recognize how BSC network logic can play a fundamental role on defining network mission, supporting management control as well as measuring and reporting the intangible assets formation along the network development lifecycle. This is the first time application of a BSC integrated framework for business networks composed of SMEs. The case study demonstrates operational value of BSC for SME’s collaborative development and success

Value proposition as a framework for value co-creation in crowd-funding ecosystem

The present paper suggests that crowd-funding in the arts and cultural sector occurs within a complex service ecosystem, where six categories of value propositions frame eight value co-creation processes, namely through ideation, evaluation, design, testing, launch, financing and authorship. Managerial contributions include the development of a crowd-funding service ecosystem model for arts managers, which offers not only a method of financing or economic value, but which also offers opportunities for strengthening bonds with customers and other stakeholders. Our paper is innovative in that we integrate value propositions categories with the micro – meso and macro contexts and analyse the different kind of co-creation are framed in the crowdfunding contextUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Applying Formal Methods to Networking: Theory, Techniques and Applications

Despite its great importance, modern network infrastructure is remarkable for the lack of rigor in its engineering. The Internet which began as a research experiment was never designed to handle the users and applications it hosts today. The lack of formalization of the Internet architecture meant limited abstractions and modularity, especially for the control and management planes, thus requiring for every new need a new protocol built from scratch. This led to an unwieldy ossified Internet architecture resistant to any attempts at formal verification, and an Internet culture where expediency and pragmatism are favored over formal correctness. Fortunately, recent work in the space of clean slate Internet design---especially, the software defined networking (SDN) paradigm---offers the Internet community another chance to develop the right kind of architecture and abstractions. This has also led to a great resurgence in interest of applying formal methods to specification, verification, and synthesis of networking protocols and applications. In this paper, we present a self-contained tutorial of the formidable amount of work that has been done in formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial