The framework proposes legal and enterprise models , a governance analysis method - called GAM - , in addition to a governance analysis language - called GAL - , and an implemented governance analysis tool - called GAT . The method consists in extracting requirements into GAL statements by using patterns and translating them into a logic model for consistency checking . The models , language , and tool proposed in this thesis evolved as a result of their application to governance laws ( privacy and financial ) . Our approach implements triple graph grammars which are declarative and brings them together with OMG ’s MOF standard . From a set of declarative triple graph grammar rules we (semi−)automatically derive operational graph grammar rules that can be used for consistency checking , consistency recovery , and model transformation using rule application mechanisms . Thus , triple graph grammar are suitable for model integration in general and model transformation in particular . Model-based applications in engineering , such as configuration , diagnosis or interactive decision-support systems , require embedded constraint solvers with challenging capabilities . They do not only demand classical services as consistency checking and solving , but also the computation of minimal conflicts and explanations . Moreover , modelling engineered systems makes often use of expressive constraint languages , which mix continuous and discrete variable domains , linear and non-linear equations , inequalities , and even procedural constraints . The resulting specifications are modular , compositional and evolvable . Using ontologies we can apply an ontology reasoner to implement consistency checks . Our method integrates previously separate checks such as checking for allowed dependencies and coding style into a single framework and enables more powerful and flexible analyses . Instead , I propose that requirements be maintained in a knowledge base which supports knowledge-level operations for asserting new knowledge and updating existing knowledge . Consistency checks and entailment of new specifications is done automatically by answering simple queries . Maintaining a requirements knowledge base in parallel with running code means that changes precipitated by evolution are always addressed relative to the ultimate purpose of the system . For the completeness analysis , we use data profiling information from consecutive knowledge base releases to estimate completeness measures that allow predicting quality issues . Then , we perform consistency checks to validate the results of the completeness analysis using integrity constraints and learning models . The approach has been tested both quantitatively and qualitatively by using a subset of datasets from both DBpedia and 3cixty knowledge bases . In order to improve the reliability of the system , it is necessary in privacy-aware Web services collaboration systems to verify whether the implementation of a set of services satisfies the requirement specification of the system . This paper proposes a role-based privacy-aware Web services collaborative model , which delegates the privacy authorization based on trust relationships of services and then presents algorithms to make the consistency verification between the requirement specification and the implementation services . Finally , this paper verifies the correctness and efficiency of the role-based approach through an application example . Then , in order to check requirements consistency , a graph-based algorithm has been elaborated . To our best knowledge , this is the first study which formalizes the consistency checking problem as a graph exploration . The whole of the developed mechanisms have been implemented in a prototype tool with an intuitive graphical interface that offers interesting facilities in terms of requirements ' specification and consistency-checking . The SysMLC extension of SysML has been defined using UML stereotypes . The definition is accompanied by an informal overview , a formal abstract syntax and static semantics definition , enabling consistency checking of models defined in the language . SysMLC is at the earliest stages of development , but it appears to : provide a basis for increasing confidence in the substitutability of SoS constituent systems ; allow rich contract-based descriptions of functional interfaces to be defined for the provided and required services of constituent systems and SoSs ; allow SoS designers to record non-functional properties of system interfaces and services ; and provide a means for SoS designers to record contract agreements at the required levels of rigour from informal notes to formal refinement proofs . This work provides an enhancement to the UML metamodel specification . The formalization proposed should be used as a formal foundation for the construction of case tools performing consistency checking of models . Support offered by tools will improve the quality of software development process . There is no general procedure for determining whether a given belief is consistent with a set of beliefs . This is the consistency check problem . Step-logic was developed in [ Elgot-Drapkin , 1988 ] as a formal mechanism for modeling the ongoing process of reasoning . XML , although not being considered a SWT in itself , stands at the syntactic level of the Semantic Web stack , and is more suitable for efficient information structure and retrieval in interactive software applications . OWL language , on the other hand , is more suitable for background reasoning and consistency checking purposes . In this paper , we introduce a mixed approach for the information representation and knowledge sharing in the nutritional domain , aiming to explode XML and OWL benefits . In order to produce a quality product that fulfills the user requirements , designs are usually therefore proposed through the creation of models to cover the various aspects of the system design criteria . Consistency property checking among design models and their components is one of the software design serious issues since the conflict may occur among design models which may bring an incorrect result . This research presents a consistency verification method based on the proposed rules constructed from the relationship among design models ; functional model , structural model , window navigation diagram and user interface design . Spatio-relational DBMSs are used to implement geographic information systems ( GIS ) and are fit to manage large amounts of data and geographic objects such as points , lines , polygons , etc . In this paper , we extend the Description Logic DL-Lite with spatial objects and show how to answer spatial conjunctive queries ( SCQs ) over ontologies — that is , conjunctive queries with point-set topological relations such as next and within — expressed in this language . The goal of this extension is to enable an off-the-shelf use of spatio-relational DBMSs to answer SCQs using rewriting techniques , where data sources and geographic objects are stored in a database and spatial conjunctive queries are rewritten to SQL statements with spatial functions . In this paper , we address the problem of containment of schema mappings for data exchange , which has been recently proposed in this framework as a step towards the optimization of data exchange settings . We refer to a natural notion of containment that relies on the behaviour of schema mappings with respect to conjunctive query answering , in the presence of so-called LAV TGDs as target constraints . Our contribution is a practical technique for testing the containment based on the existence of a homomorphism between special " dummy " instances , which can be easily built from schema mappings . Enhancing Datalog with existential quantification gives rise to Datalog∃ , a powerful knowledge representation language widely used in ontology-based query answering . In this setting , a conjunctive query is evaluated over a Datalog∃ program consisting of extensional data paired with so-called “ existential ” rules . Owing to their high expressiveness , such rules make the evaluation of queries undecidable , even when the latter are atomic . We provide a precise syntactic characterization of separable ER+schemata by means of a necessary and sufficient condition . We present a complete complexity analysis of the conjunctive query answering problem under separable ER+schemata , and also under several sublanguages of ER+ . We show that the addition of so-called negative constraintsdoes not increase the complexity of query answering . Most modern web search engines employ a two-phase ranking strategy : a candidate list of documents is generated using a " cheap " but low-quality scoring function , which is then reranked by an " expensive " but high-quality method ( usually machine-learned ) . This paper focuses on the problem of candidate generation for conjunctive query processing in this context . We describe and evaluate a fast , approximate postings list intersection algorithms based on Bloom filters . A conjunctive query problem in relational database theory is a problem to determine whether or not a tuple belongs to the answer of a conjunctive query over a database . Here , a tuple and a conjunctive query are regarded as a ground atom and a nonrecursive function-free definite clause , respectively . To this effect , we introduce the concept of data-exchange equivalence and the concept of conjunctive-query equivalence . These two concepts of equivalence are natural relaxations of the classical notion of logical equivalence ; the first captures indistinguishability for data-exchange purposes , while the second captures indistinguishability for conjunctive-query-answering purposes . Moreover , they coincide with logical equivalence on schema mappings specified by source-to-target tuple-generating dependencies ( s-t tgds ) , but differ on richer classes of dependencies , such as second-order tuple-generating dependencies ( SO tgds ) and sets of s-t tgds and target tuple-generating dependencies ( target tgds ) . A popular technique for reasoning in fuzzy DL ontologies is by providing a reduction to crisp DLs and then employ reasoning in the crisp DL . In this paper we adopt this approach to solve conjunctive query ( CQ ) answering problems for fuzzy DLs . We give reductions for Godel , and Łukasiewicz variants of fuzzy Open image in new window and two kinds of fuzzy CQs . The University of Illinois at Urbana-Champaign ( UIUC ) participated in TREC 2007 Genomics Track . Our general goal of participation is to apply language modelbased approaches to the genomics retrieval task and study how we may extend the standard language models to accommodate two special needs for this year ’s genomics retrieval task : ( 1 ) gene synonym expansion and ( 2 ) conjunctive query interpretation . We also tested user relevance feedback . Our purpose in this article is to explore these trade-offs , by investigating intersection techniques that make use of both uncompressed “ integer ” representations , as well as compressed arrangements . We also propose a simple hybrid method that provides both compact storage , and also faster intersection computations for conjunctive querying than is possible even with uncompressed representations . The past decade has produced a range of techniques for assessing the correctness of software systems . These techniques , such as various forms of static analysis , automated verification , and test generation , are capable of producing a variety of forms of evidence showing that the software behavior meets its specified properties . Software testing , also known as an important part of software development life cycle , will continue to be a primary approach for ensuring correctness of software systems . On the basis of two developed testing tools for the Visual Basic and C/C++ language respectively , the architecture of testing tools is extended to cover any context free language . ion and Refinenent in RIM D. L. Boyd , A. Pizzarello , W. T. Wood . 111 Hierarchical Specification of Abstract Data Types H. K. Berg , W. K. Giloi 150 An Approach to the Specification of Distributed Software W. R. Franta , W. E. Boebert , H. K. Berg 197 Correctness of Software An OVerview H. K. Berg , W. R. Franta , T. G. Moher 237 Interactive Design and Verification : A Message Switching Network Example It is a well-known fact that precise definitions play significant role in the development of correct and robust software . It has been recognized and emphasized that appropriately defined formal conceptual framework of the context/problem domain proves quite useful in ensuring precise definitions , including those for software metrics , which are consistent , unambiguous and language independent . Static program analysis has shown tremendous surge from basic compiler optimization technique to becoming a major role player in correctness and verification of software . Because of its rich theoretical background , static analysis is in a good position to help produce quality software . With the rapid development of information technology , software quality has become one of the users ' most concerns . However , due to the difficulties of correctness proof of software products , software quality problems do not have a convincing evaluation method . Especially , evaluation methods in different areas are based on the same kind of indices but lack individuality . For a satisfactory user experience , there are stringent requirements in the real-time response of smartphone applications . In order to meet the performance expectations for DL , numerous deep learning accelerators ( DLA ) have been proposed for DL inference on the edge devices [2]–[5 ] . As depicted in Fig. 7.1.1 , the major challenge in designing a DLA for smartphones is achieving the required computing efficiency , while limited by the power budget and memory bandwidth ( BW ) . With appropriate network retuning , reduced precision networks can achieve accuracy close or equal to that of full-precision floating-point models . Given the wide spectrum of precisions used in DL inference , FPGAs ' ability to create custom bit-width datapaths gives them an advantage over other acceleration platforms in this domain . However , the embedded DSP blocks in the latest Intel and Xilinx FPGAs do not natively support precisions below 18-bit and thus can not efficiently pack low-precision multiplications , leaving the DSP blocks under-utilized . The Compute Library for Deep Neural Networks [ 1 ] ( clDNN ) is an open source performance library for Deep Learning ( DL ) applications intended for acceleration of DL inference on Intel ® Processor Graphics . It was released in 2017 and was recently coupled with Neo [ 2 ] , which is the open source OpenCL [ 3 ] driver for Intel Processor Graphics . Although state-of-the-art description logic ( DL ) reasoners are equipped with a comprehensive set of optimizations , reasoning performance is still a major bottleneck in both research and real world applications . In this paper , we propose a sound and complete algorithm called the intelligent tableau algorithm by incorporating comprehensive learning techniques to tackle all DL reasoning tasks . We also provide a reference implementation reasoner called LIGHT for the DL \({\cal ALC}\ ) dialect based on the algorithm we developed . Reasoning here means not only computing subsumption between concepts and checking satisfiability of the whole knowledge base , but also answering complex queries ( in particular , unions of conjunctive queries ) over the instance level ( ABox ) of the DL knowledge base . We show that , for the DLs of the DL-Lite family , the usual DL reasoning tasks are polynomial in the size of the TBox , and query answering is LogSpace in the size of the ABox ( i.e. , in data complexity ) . To the best of our knowledge , this is the first result of polynomial-time data complexity for query answering over DL knowledge bases . However , we should not discard reasoners from being used on mobile devices such as smartphones or tablets , as the increasing number of applications run on wireless environments demands that many intelligent tasks should be performed on mobile devices rather than on desktop or server computers . Although less powerful that their fixed counterparts , mobile devices are becoming more and more capable of running complex tasks , such as DL reasoning . In this paper we introduce the framework of a competition for reasoners on mobile devices , based on the OWL Reasoner Evaluation , with the main goal of promoting the development of reasoners adapted to mobile environments . Abstract A human expert utilizes various pieces of diagnostic knowledge very dynamically in problem solving . Recently a few integrated reasoning systems have been proposed to use various types of knowledge in an integrated way , but they have shortcomings in reasoning control and reasoning interactions . To overcome these shortcomings , a diagnostic reasoning system with dynamic interactions that uses diverse types of knowledge with cooperation is proposed . This paper presents an implementation of a cognitive model of a complex real-world task in the cognitive architecture Soar . During the implementation process there were lessons learned on various aspects , such as the retrieval of working memory elements with relative values , alternative approaches to reasoning , and reasoning control . Additionally , the implementation is compared to an earlier implementation of the model in the ACT-R architecture and both implementations are discussed in terms of cognitive theories . However , previous ontology literature has paid limited attention to the representation of specific relationships among metadata and the design of reasoning procedures that would allow some information not explicitly specified in the databases or ontologies to be inferred . This article proposes a methodological approach for the definition of relationships and reasoning tasks for patent analysis by using patent ontologies , and provides a real illustration of its potential in the context of international flows of research knowledge . This declarative method is based on the formal definition of key patent analysis indicators ( KPAIs ) . And descriptions of devices can be simplified by cloaking parts thereof or by bypassing in them references to some of the key-concepts , as is done in , for instance , the design methodologies of Stone and Wood , of Lind and of Gero . It is shown that in these simplifications engineers adjust the meaning of the term function in such a way that the simplified descriptions are indeed useful for engineering reasoning about devices . In the proposed overall account technical functions of devices are taken as the desired effects of the behaviour of the devices . This paper presents a study on the computational complexity of qualitative change . More precisely , we discuss the reasoning task of finding a solution to a temporal sequence of static reasoning problems where this sequence is subject to additional transition constraints . Our focus is primarily on smoothness and continuity constraints : we show how such transitions can be defined as relations and expressed within qualitative constraint formalisms . A fact apparently not observed earlier in the literature of n onmonotonic reasoning is that Reiter , in his default logic paper , did not directly formalize informal defaults . Instead , he translated a default into a certain na tural language proposition and provided a formalization of the latter . In this paper we describe the design of the Knowledge Store , a scalable , fault-tolerant , and Semantic Web grounded storage system for interlinking structured and unstructured data . We discuss its capability to adapt to new types of content and application scenarios , and to provide reasoning and semantic queries services on top of stored contents . We also comment on its envisaged use in the News Reader EU project to manage large amounts of economical-financial data . The intention-based model assumes that people categorize an objects ’ by reasoning the creator ’s intent . Evidence for this model are about “ intended function ” effect in categorization , naming , and reasoning studies . However , the utility-based model assumes that using-goal is determining how people categorize an object . Some educators have argued that improvement in students ’ quantitative reasoning ability would improve higher-order math skills — such as algebra — and reduce the growing need for remedial college math . The personal finance problems given for teaching quantitative reasoning are examples of “ obvious benefit/hidden cost ” problems . These are based on studies in the interdisciplinary field of behavioural finance of consumer responses to “ framing ” of financial propositions . We present a simple characterization of definable quotient types as being induced by idempotent functions , and an encoding of this in Cedille ( a dependently typed programming language ) in which both equational constraints and the packaging that associates these with elements of the carrier type are irrelevant , facilitating equational reasoning in proofs . We provide several concrete examples of definable quotients using this encoding and give combinators for function lifting ( with one variant having zero run-time cost ) . We show how the ontology is used to describe real-world network traffic and also serve as a basis for higher level ontologies of cyber operation , threat and risk . Second , we demonstrate how the combination of the packet-centric ontology with an adaptive cognitive agent with learning capabilities , can be used to understand the human defender reasoning processes when monitoring network traffic . Through simulation experiments we evaluated the proposed hybrid computational architecture and demonstrate its ability to successfully detect malicious port scanning within legitimate network traffic . The number of turns in the inference is dynamically modeled by both a document and a query , and is generally related to the complexity of the document and the query . section : REASONING NETWORKS ReasoNets are devised to mimic the inference process of human readers . Recent analysis and results [ reference ] on the cloze - style machine comprehension tasks have suggested some simple models without multiturn reasoning can achieve reasonable performance . Based on these results , we construct a synthetic structured Graph Reachability dataset [ reference ] to evaluate longer range machine inference and reasoning capability , since we anticipate ReasoNets to have the capability to handle long range relationships . We generate two synthetic datasets : a small graph dataset and a large graph dataset . This paper proposes to improve visual question answering ( VQA ) with structured representations of both scene contents and questions . A key challenge in VQA is to require joint reasoning over the visual and text domains . The predominant CNN / LSTM - based approach to VQA is limited by monolithic vector representations that largely ignore structure in the scene and in the question . Since our tree pooling approach involves a tree structure in its learning , we observe an analogy to “ logic - type ” approaches such as decision trees or “ logical operators ” . Such approaches have played a central role in artificial intelligence for applications that require “ discrete ” reasoning , and are often intuitively appealing . Unfortunately , despite the appeal of such logic - type approaches , there is a disconnect between the functioning of decision trees and the functioning of CNNs — the output of a standard decision tree is non - continuous with respect to its input ( and thus nondifferentiable ) . Stacked Attention Networks ( SAN ) explicitly learns the weights of visual feature vectors to select a small portion of visual information for a given question vector . Furthermore , this model stacks the attention networks for multi - step reasoning narrowing down the selection of visual information . For example , if the attention networks are asked to find a pink handbag in a scene , they try to find pink objects first , and then , narrow down to the pink handbag . A standard tool for modeling two sequences with recurrent networks is the encoder - decoder architecture where the second sequence ( also known as the target ) is being processed conditioned on the first one ( also known as the source ) . In this section we explain how to combine the LSTMN which applies attention for intra - relation reasoning , with the encoder - decoder network whose attention module learns the inter - alignment between two sequences . Figures [ reference ] a and [ reference ] b illustrate two types of combination . Execution traces capture information on a software system ’s runtime behavior , including data on system-internal software control flows , performance , as well as request parameters and values . In research and industrial practice , execution traces serve as an important basis for model-based and measurement-based performance evaluation , e.g. , for application performance monitoring ( APM ) , extraction of descriptive and prescriptive models , as well as problem detection and diagnosis . A number of commercial and open-source APM tools that allow the capturing of execution traces within distributed software systems is available . However , particularly problem diagnosis is currently often performed manually with little guidance by APM tools . After a brief introduction into application performance problem detection and diagnosis , I will present what we have done in this area in the context of our open-source APM framework Kieker ( http://kieker-monitoring.net/ ) and outline our plans for the recently started collaborative research project diagnoseIT on expert-guided automatic diagnosis of performance problems in enterprise applications . In this paper we show that aliasing is a very rare occurrence . We then present a simple polynomial-time diagnosis algorithm which takes advantage of this result to run much more efficiently compared to the conventional method of diagnosis . We introduce the concept of NC-detectability and NC-locatability to measure the fault tolerance of the system when check invalidation does not occur and show how to design systems with specified error detectability/NC-detectability and locatability/NC-locatability . One difficulty encountered with any multivariate process control is the diagnosis or interpretation of an out-of-control signal to determine which variable is responsible for the signal . In this paper , the diagnosis of out-of-control signal is formulated as a classification problem . The proposed system includes a shift detector and a classifier . Multivariate process control often encounters with the diagnosis or interpretation difficulty of an out-of-control signal to determine which variable is responsible for the signal . In this article , we formulate the diagnosis of out-of-control signal as a classification problem . The proposed system includes a shift detector and a classifier . Several approaches to identifying the out-of-control variables after the detection of abnormal pattern has been most intensively studied and used in practice . One of the several approaches is the Artificial Neural Network ( ANN ) based model for diagnosis of out-of-control signal of multivariate process mean shift . In spite of the number of years of research in neural network , limited research ( if any ) have been done on the effect of dataset allocations in percentages for training and testing on the performance of ANN . BizTalk Server , working as data transmission and middleware of system integration , and its applications in data integration of legacy systems and new application are researched , after understanding the theory of data integration based on BizTalk Server . Put the theory to the enterprises ’ diagnosis , then design the solution on data integration for enterprises ’ diagnosis , the arithmetic of data connecting and the arithmetic of polling . Finally , implement the data integration for enterprise ’s diagnosing system . Areas under ROC curve were 0.997 + 0.004 and 0.959 + 0.016 respectively , and the difference between the two was significant statistically ( P=0.009 ) . NN showed high performance in diagnosis of SPN on HRCT images . It was worthy of further study Results Total vector ultramicrotomy reconstruction got significantly richer quantitative data than unidirectional(axial ) ultramicrotomy . Conclusions Total vector ultramicrotomy can reveal more comprehensive and more specific SPN imaging detailes such as morphology , edge , intrinsic features and enhancement features , which provides more detailed basis and quantitative data for diagnosis of SPN . For each of the detected oscillatory control loops , the root cause of the oscillation is diagnosed by the analysis of input-output characteristics of a valve . Finally , the combination of the Wavelet tool and the analysis of MV-PV plots is shown to be a powerful practical method for the detection and diagnosis of oscillations in process plants . The paper discusses the special properties of oscillations caused by controller tuning and proposes a method to distinguish it from sinusoidal disturbances . The method is based on analyzing the auto correlation function of the signals for both detection and diagnosis of oscillations in the presence of multiple oscillations . This paper deals with study and development of Architecture to develop an initial phase expert system to provide secure diagnosis to the infectious patient and also propose some protocols using RMPJ2-RSA cryptosystem and signature scheme to provide confidentiality to the patient details . A novel method based on the mathematical morphological gradient transformation and the revised SVM for Doppler weather radar machinery fault diagnosis is proposed . Firstly use the mathematical morphological gradient to remove the noise . Unlike many literature studies , the proposed method does not manually extract features from EEG recordings , instead it transforms the raw EEG into 2D by using Short-time Fourier Transform ( STFT ) in order to have a useful representation of frequency-time features . This work is the first in the relevant literature in using 2D timefrequency features for the purpose of automatic diagnosis of SZ patients . In order to extract most useful features out of all present in the 2D space and classify samples with high accuracy , a state-of-art Convolutional Neural Network architecture , namely VGG-16 , is trained . Abstract We are proposing in this paper a new methodology named FNAD ( Filtrage Numerique et Analyse Discriminante ) methodology , for the on-line detection and diagnosis of multivariate processes . Our methodology is mainly based on the use of the digital filtering and discriminant analysis .
The framework proposes legal and enterprise models , a governance analysis method - called GAM - , in addition to a governance analysis language - called GAL - , and an implemented governance analysis tool - called GAT . The method consists in extracting requirements into GAL statements by using patterns and translating them into a logic model for consistency checking . The models , language , and tool proposed in this thesis evolved as a result of their application to governance laws ( privacy and financial ) .
Our approach implements triple graph grammars which are declarative and brings them together with OMG ’s MOF standard . From a set of declarative triple graph grammar rules we (semi−)automatically derive operational graph grammar rules that can be used for consistency checking , consistency recovery , and model transformation using rule application mechanisms . Thus , triple graph grammar are suitable for model integration in general and model transformation in particular .
Model-based applications in engineering , such as configuration , diagnosis or interactive decision-support systems , require embedded constraint solvers with challenging capabilities . They do not only demand classical services as consistency checking and solving , but also the computation of minimal conflicts and explanations . Moreover , modelling engineered systems makes often use of expressive constraint languages , which mix continuous and discrete variable domains , linear and non-linear equations , inequalities , and even procedural constraints .
The resulting specifications are modular , compositional and evolvable . Using ontologies we can apply an ontology reasoner to implement consistency checks . Our method integrates previously separate checks such as checking for allowed dependencies and coding style into a single framework and enables more powerful and flexible analyses .
Instead , I propose that requirements be maintained in a knowledge base which supports knowledge-level operations for asserting new knowledge and updating existing knowledge . Consistency checks and entailment of new specifications is done automatically by answering simple queries . Maintaining a requirements knowledge base in parallel with running code means that changes precipitated by evolution are always addressed relative to the ultimate purpose of the system .
For the completeness analysis , we use data profiling information from consecutive knowledge base releases to estimate completeness measures that allow predicting quality issues . Then , we perform consistency checks to validate the results of the completeness analysis using integrity constraints and learning models . The approach has been tested both quantitatively and qualitatively by using a subset of datasets from both DBpedia and 3cixty knowledge bases .
In order to improve the reliability of the system , it is necessary in privacy-aware Web services collaboration systems to verify whether the implementation of a set of services satisfies the requirement specification of the system . This paper proposes a role-based privacy-aware Web services collaborative model , which delegates the privacy authorization based on trust relationships of services and then presents algorithms to make the consistency verification between the requirement specification and the implementation services . Finally , this paper verifies the correctness and efficiency of the role-based approach through an application example .
Then , in order to check requirements consistency , a graph-based algorithm has been elaborated . To our best knowledge , this is the first study which formalizes the consistency checking problem as a graph exploration . The whole of the developed mechanisms have been implemented in a prototype tool with an intuitive graphical interface that offers interesting facilities in terms of requirements ' specification and consistency-checking .
The SysMLC extension of SysML has been defined using UML stereotypes . The definition is accompanied by an informal overview , a formal abstract syntax and static semantics definition , enabling consistency checking of models defined in the language . SysMLC is at the earliest stages of development , but it appears to : provide a basis for increasing confidence in the substitutability of SoS constituent systems ; allow rich contract-based descriptions of functional interfaces to be defined for the provided and required services of constituent systems and SoSs ; allow SoS designers to record non-functional properties of system interfaces and services ; and provide a means for SoS designers to record contract agreements at the required levels of rigour from informal notes to formal refinement proofs .
This work provides an enhancement to the UML metamodel specification . The formalization proposed should be used as a formal foundation for the construction of case tools performing consistency checking of models . Support offered by tools will improve the quality of software development process .
There is no general procedure for determining whether a given belief is consistent with a set of beliefs . This is the consistency check problem . Step-logic was developed in [ Elgot-Drapkin , 1988 ] as a formal mechanism for modeling the ongoing process of reasoning .
XML , although not being considered a SWT in itself , stands at the syntactic level of the Semantic Web stack , and is more suitable for efficient information structure and retrieval in interactive software applications . OWL language , on the other hand , is more suitable for background reasoning and consistency checking purposes . In this paper , we introduce a mixed approach for the information representation and knowledge sharing in the nutritional domain , aiming to explode XML and OWL benefits .
In order to produce a quality product that fulfills the user requirements , designs are usually therefore proposed through the creation of models to cover the various aspects of the system design criteria . Consistency property checking among design models and their components is one of the software design serious issues since the conflict may occur among design models which may bring an incorrect result . This research presents a consistency verification method based on the proposed rules constructed from the relationship among design models ; functional model , structural model , window navigation diagram and user interface design .
Spatio-relational DBMSs are used to implement geographic information systems ( GIS ) and are fit to manage large amounts of data and geographic objects such as points , lines , polygons , etc . In this paper , we extend the Description Logic DL-Lite with spatial objects and show how to answer spatial conjunctive queries ( SCQs ) over ontologies — that is , conjunctive queries with point-set topological relations such as next and within — expressed in this language . The goal of this extension is to enable an off-the-shelf use of spatio-relational DBMSs to answer SCQs using rewriting techniques , where data sources and geographic objects are stored in a database and spatial conjunctive queries are rewritten to SQL statements with spatial functions .
In this paper , we address the problem of containment of schema mappings for data exchange , which has been recently proposed in this framework as a step towards the optimization of data exchange settings . We refer to a natural notion of containment that relies on the behaviour of schema mappings with respect to conjunctive query answering , in the presence of so-called LAV TGDs as target constraints . Our contribution is a practical technique for testing the containment based on the existence of a homomorphism between special " dummy " instances , which can be easily built from schema mappings .
Enhancing Datalog with existential quantification gives rise to Datalog∃ , a powerful knowledge representation language widely used in ontology-based query answering . In this setting , a conjunctive query is evaluated over a Datalog∃ program consisting of extensional data paired with so-called “ existential ” rules . Owing to their high expressiveness , such rules make the evaluation of queries undecidable , even when the latter are atomic .
We provide a precise syntactic characterization of separable ER+schemata by means of a necessary and sufficient condition . We present a complete complexity analysis of the conjunctive query answering problem under separable ER+schemata , and also under several sublanguages of ER+ . We show that the addition of so-called negative constraintsdoes not increase the complexity of query answering .
Most modern web search engines employ a two-phase ranking strategy : a candidate list of documents is generated using a " cheap " but low-quality scoring function , which is then reranked by an " expensive " but high-quality method ( usually machine-learned ) . This paper focuses on the problem of candidate generation for conjunctive query processing in this context . We describe and evaluate a fast , approximate postings list intersection algorithms based on Bloom filters .
A conjunctive query problem in relational database theory is a problem to determine whether or not a tuple belongs to the answer of a conjunctive query over a database . Here , a tuple and a conjunctive query are regarded as a ground atom and a nonrecursive function-free definite clause , respectively .
To this effect , we introduce the concept of data-exchange equivalence and the concept of conjunctive-query equivalence . These two concepts of equivalence are natural relaxations of the classical notion of logical equivalence ; the first captures indistinguishability for data-exchange purposes , while the second captures indistinguishability for conjunctive-query-answering purposes . Moreover , they coincide with logical equivalence on schema mappings specified by source-to-target tuple-generating dependencies ( s-t tgds ) , but differ on richer classes of dependencies , such as second-order tuple-generating dependencies ( SO tgds ) and sets of s-t tgds and target tuple-generating dependencies ( target tgds ) .
A popular technique for reasoning in fuzzy DL ontologies is by providing a reduction to crisp DLs and then employ reasoning in the crisp DL . In this paper we adopt this approach to solve conjunctive query ( CQ ) answering problems for fuzzy DLs . We give reductions for Godel , and Łukasiewicz variants of fuzzy Open image in new window and two kinds of fuzzy CQs .
The University of Illinois at Urbana-Champaign ( UIUC ) participated in TREC 2007 Genomics Track . Our general goal of participation is to apply language modelbased approaches to the genomics retrieval task and study how we may extend the standard language models to accommodate two special needs for this year ’s genomics retrieval task : ( 1 ) gene synonym expansion and ( 2 ) conjunctive query interpretation . We also tested user relevance feedback .
Our purpose in this article is to explore these trade-offs , by investigating intersection techniques that make use of both uncompressed “ integer ” representations , as well as compressed arrangements . We also propose a simple hybrid method that provides both compact storage , and also faster intersection computations for conjunctive querying than is possible even with uncompressed representations .
The past decade has produced a range of techniques for assessing the correctness of software systems . These techniques , such as various forms of static analysis , automated verification , and test generation , are capable of producing a variety of forms of evidence showing that the software behavior meets its specified properties .
Software testing , also known as an important part of software development life cycle , will continue to be a primary approach for ensuring correctness of software systems . On the basis of two developed testing tools for the Visual Basic and C/C++ language respectively , the architecture of testing tools is extended to cover any context free language .
ion and Refinenent in RIM D. L. Boyd , A. Pizzarello , W. T. Wood . 111 Hierarchical Specification of Abstract Data Types H. K. Berg , W. K. Giloi 150 An Approach to the Specification of Distributed Software W. R. Franta , W. E. Boebert , H. K. Berg 197 Correctness of Software An OVerview H. K. Berg , W. R. Franta , T. G. Moher 237 Interactive Design and Verification : A Message Switching Network Example
It is a well-known fact that precise definitions play significant role in the development of correct and robust software . It has been recognized and emphasized that appropriately defined formal conceptual framework of the context/problem domain proves quite useful in ensuring precise definitions , including those for software metrics , which are consistent , unambiguous and language independent .
Static program analysis has shown tremendous surge from basic compiler optimization technique to becoming a major role player in correctness and verification of software . Because of its rich theoretical background , static analysis is in a good position to help produce quality software .
With the rapid development of information technology , software quality has become one of the users ' most concerns . However , due to the difficulties of correctness proof of software products , software quality problems do not have a convincing evaluation method . Especially , evaluation methods in different areas are based on the same kind of indices but lack individuality .
For a satisfactory user experience , there are stringent requirements in the real-time response of smartphone applications . In order to meet the performance expectations for DL , numerous deep learning accelerators ( DLA ) have been proposed for DL inference on the edge devices [2]–[5 ] . As depicted in Fig. 7.1.1 , the major challenge in designing a DLA for smartphones is achieving the required computing efficiency , while limited by the power budget and memory bandwidth ( BW ) .
With appropriate network retuning , reduced precision networks can achieve accuracy close or equal to that of full-precision floating-point models . Given the wide spectrum of precisions used in DL inference , FPGAs ' ability to create custom bit-width datapaths gives them an advantage over other acceleration platforms in this domain . However , the embedded DSP blocks in the latest Intel and Xilinx FPGAs do not natively support precisions below 18-bit and thus can not efficiently pack low-precision multiplications , leaving the DSP blocks under-utilized .
The Compute Library for Deep Neural Networks [ 1 ] ( clDNN ) is an open source performance library for Deep Learning ( DL ) applications intended for acceleration of DL inference on Intel ® Processor Graphics . It was released in 2017 and was recently coupled with Neo [ 2 ] , which is the open source OpenCL [ 3 ] driver for Intel Processor Graphics .
Although state-of-the-art description logic ( DL ) reasoners are equipped with a comprehensive set of optimizations , reasoning performance is still a major bottleneck in both research and real world applications . In this paper , we propose a sound and complete algorithm called the intelligent tableau algorithm by incorporating comprehensive learning techniques to tackle all DL reasoning tasks . We also provide a reference implementation reasoner called LIGHT for the DL \({\cal ALC}\ ) dialect based on the algorithm we developed .
Reasoning here means not only computing subsumption between concepts and checking satisfiability of the whole knowledge base , but also answering complex queries ( in particular , unions of conjunctive queries ) over the instance level ( ABox ) of the DL knowledge base . We show that , for the DLs of the DL-Lite family , the usual DL reasoning tasks are polynomial in the size of the TBox , and query answering is LogSpace in the size of the ABox ( i.e. , in data complexity ) . To the best of our knowledge , this is the first result of polynomial-time data complexity for query answering over DL knowledge bases .
However , we should not discard reasoners from being used on mobile devices such as smartphones or tablets , as the increasing number of applications run on wireless environments demands that many intelligent tasks should be performed on mobile devices rather than on desktop or server computers . Although less powerful that their fixed counterparts , mobile devices are becoming more and more capable of running complex tasks , such as DL reasoning . In this paper we introduce the framework of a competition for reasoners on mobile devices , based on the OWL Reasoner Evaluation , with the main goal of promoting the development of reasoners adapted to mobile environments .
Abstract A human expert utilizes various pieces of diagnostic knowledge very dynamically in problem solving . Recently a few integrated reasoning systems have been proposed to use various types of knowledge in an integrated way , but they have shortcomings in reasoning control and reasoning interactions . To overcome these shortcomings , a diagnostic reasoning system with dynamic interactions that uses diverse types of knowledge with cooperation is proposed .
This paper presents an implementation of a cognitive model of a complex real-world task in the cognitive architecture Soar . During the implementation process there were lessons learned on various aspects , such as the retrieval of working memory elements with relative values , alternative approaches to reasoning , and reasoning control . Additionally , the implementation is compared to an earlier implementation of the model in the ACT-R architecture and both implementations are discussed in terms of cognitive theories .
However , previous ontology literature has paid limited attention to the representation of specific relationships among metadata and the design of reasoning procedures that would allow some information not explicitly specified in the databases or ontologies to be inferred . This article proposes a methodological approach for the definition of relationships and reasoning tasks for patent analysis by using patent ontologies , and provides a real illustration of its potential in the context of international flows of research knowledge . This declarative method is based on the formal definition of key patent analysis indicators ( KPAIs ) .
And descriptions of devices can be simplified by cloaking parts thereof or by bypassing in them references to some of the key-concepts , as is done in , for instance , the design methodologies of Stone and Wood , of Lind and of Gero . It is shown that in these simplifications engineers adjust the meaning of the term function in such a way that the simplified descriptions are indeed useful for engineering reasoning about devices . In the proposed overall account technical functions of devices are taken as the desired effects of the behaviour of the devices .
This paper presents a study on the computational complexity of qualitative change . More precisely , we discuss the reasoning task of finding a solution to a temporal sequence of static reasoning problems where this sequence is subject to additional transition constraints . Our focus is primarily on smoothness and continuity constraints : we show how such transitions can be defined as relations and expressed within qualitative constraint formalisms .
A fact apparently not observed earlier in the literature of n onmonotonic reasoning is that Reiter , in his default logic paper , did not directly formalize informal defaults . Instead , he translated a default into a certain na tural language proposition and provided a formalization of the latter .
In this paper we describe the design of the Knowledge Store , a scalable , fault-tolerant , and Semantic Web grounded storage system for interlinking structured and unstructured data . We discuss its capability to adapt to new types of content and application scenarios , and to provide reasoning and semantic queries services on top of stored contents . We also comment on its envisaged use in the News Reader EU project to manage large amounts of economical-financial data .
The intention-based model assumes that people categorize an objects ’ by reasoning the creator ’s intent . Evidence for this model are about “ intended function ” effect in categorization , naming , and reasoning studies . However , the utility-based model assumes that using-goal is determining how people categorize an object .
Some educators have argued that improvement in students ’ quantitative reasoning ability would improve higher-order math skills — such as algebra — and reduce the growing need for remedial college math . The personal finance problems given for teaching quantitative reasoning are examples of “ obvious benefit/hidden cost ” problems . These are based on studies in the interdisciplinary field of behavioural finance of consumer responses to “ framing ” of financial propositions .
We present a simple characterization of definable quotient types as being induced by idempotent functions , and an encoding of this in Cedille ( a dependently typed programming language ) in which both equational constraints and the packaging that associates these with elements of the carrier type are irrelevant , facilitating equational reasoning in proofs . We provide several concrete examples of definable quotients using this encoding and give combinators for function lifting ( with one variant having zero run-time cost ) .
We show how the ontology is used to describe real-world network traffic and also serve as a basis for higher level ontologies of cyber operation , threat and risk . Second , we demonstrate how the combination of the packet-centric ontology with an adaptive cognitive agent with learning capabilities , can be used to understand the human defender reasoning processes when monitoring network traffic . Through simulation experiments we evaluated the proposed hybrid computational architecture and demonstrate its ability to successfully detect malicious port scanning within legitimate network traffic .
The number of turns in the inference is dynamically modeled by both a document and a query , and is generally related to the complexity of the document and the query . section : REASONING NETWORKS ReasoNets are devised to mimic the inference process of human readers .
Recent analysis and results [ reference ] on the cloze - style machine comprehension tasks have suggested some simple models without multiturn reasoning can achieve reasonable performance . Based on these results , we construct a synthetic structured Graph Reachability dataset [ reference ] to evaluate longer range machine inference and reasoning capability , since we anticipate ReasoNets to have the capability to handle long range relationships . We generate two synthetic datasets : a small graph dataset and a large graph dataset .
This paper proposes to improve visual question answering ( VQA ) with structured representations of both scene contents and questions . A key challenge in VQA is to require joint reasoning over the visual and text domains . The predominant CNN / LSTM - based approach to VQA is limited by monolithic vector representations that largely ignore structure in the scene and in the question .
Since our tree pooling approach involves a tree structure in its learning , we observe an analogy to “ logic - type ” approaches such as decision trees or “ logical operators ” . Such approaches have played a central role in artificial intelligence for applications that require “ discrete ” reasoning , and are often intuitively appealing . Unfortunately , despite the appeal of such logic - type approaches , there is a disconnect between the functioning of decision trees and the functioning of CNNs — the output of a standard decision tree is non - continuous with respect to its input ( and thus nondifferentiable ) .
Stacked Attention Networks ( SAN ) explicitly learns the weights of visual feature vectors to select a small portion of visual information for a given question vector . Furthermore , this model stacks the attention networks for multi - step reasoning narrowing down the selection of visual information . For example , if the attention networks are asked to find a pink handbag in a scene , they try to find pink objects first , and then , narrow down to the pink handbag .
A standard tool for modeling two sequences with recurrent networks is the encoder - decoder architecture where the second sequence ( also known as the target ) is being processed conditioned on the first one ( also known as the source ) . In this section we explain how to combine the LSTMN which applies attention for intra - relation reasoning , with the encoder - decoder network whose attention module learns the inter - alignment between two sequences . Figures [ reference ] a and [ reference ] b illustrate two types of combination .
Execution traces capture information on a software system ’s runtime behavior , including data on system-internal software control flows , performance , as well as request parameters and values . In research and industrial practice , execution traces serve as an important basis for model-based and measurement-based performance evaluation , e.g. , for application performance monitoring ( APM ) , extraction of descriptive and prescriptive models , as well as problem detection and diagnosis . A number of commercial and open-source APM tools that allow the capturing of execution traces within distributed software systems is available .
However , particularly problem diagnosis is currently often performed manually with little guidance by APM tools . After a brief introduction into application performance problem detection and diagnosis , I will present what we have done in this area in the context of our open-source APM framework Kieker ( http://kieker-monitoring.net/ ) and outline our plans for the recently started collaborative research project diagnoseIT on expert-guided automatic diagnosis of performance problems in enterprise applications .
In this paper we show that aliasing is a very rare occurrence . We then present a simple polynomial-time diagnosis algorithm which takes advantage of this result to run much more efficiently compared to the conventional method of diagnosis . We introduce the concept of NC-detectability and NC-locatability to measure the fault tolerance of the system when check invalidation does not occur and show how to design systems with specified error detectability/NC-detectability and locatability/NC-locatability .
One difficulty encountered with any multivariate process control is the diagnosis or interpretation of an out-of-control signal to determine which variable is responsible for the signal . In this paper , the diagnosis of out-of-control signal is formulated as a classification problem . The proposed system includes a shift detector and a classifier .
Multivariate process control often encounters with the diagnosis or interpretation difficulty of an out-of-control signal to determine which variable is responsible for the signal . In this article , we formulate the diagnosis of out-of-control signal as a classification problem . The proposed system includes a shift detector and a classifier .
Several approaches to identifying the out-of-control variables after the detection of abnormal pattern has been most intensively studied and used in practice . One of the several approaches is the Artificial Neural Network ( ANN ) based model for diagnosis of out-of-control signal of multivariate process mean shift . In spite of the number of years of research in neural network , limited research ( if any ) have been done on the effect of dataset allocations in percentages for training and testing on the performance of ANN .
BizTalk Server , working as data transmission and middleware of system integration , and its applications in data integration of legacy systems and new application are researched , after understanding the theory of data integration based on BizTalk Server . Put the theory to the enterprises ’ diagnosis , then design the solution on data integration for enterprises ’ diagnosis , the arithmetic of data connecting and the arithmetic of polling . Finally , implement the data integration for enterprise ’s diagnosing system .
Areas under ROC curve were 0.997 + 0.004 and 0.959 + 0.016 respectively , and the difference between the two was significant statistically ( P=0.009 ) . NN showed high performance in diagnosis of SPN on HRCT images . It was worthy of further study
Results Total vector ultramicrotomy reconstruction got significantly richer quantitative data than unidirectional(axial ) ultramicrotomy . Conclusions Total vector ultramicrotomy can reveal more comprehensive and more specific SPN imaging detailes such as morphology , edge , intrinsic features and enhancement features , which provides more detailed basis and quantitative data for diagnosis of SPN .
For each of the detected oscillatory control loops , the root cause of the oscillation is diagnosed by the analysis of input-output characteristics of a valve . Finally , the combination of the Wavelet tool and the analysis of MV-PV plots is shown to be a powerful practical method for the detection and diagnosis of oscillations in process plants .
The paper discusses the special properties of oscillations caused by controller tuning and proposes a method to distinguish it from sinusoidal disturbances . The method is based on analyzing the auto correlation function of the signals for both detection and diagnosis of oscillations in the presence of multiple oscillations .
This paper deals with study and development of Architecture to develop an initial phase expert system to provide secure diagnosis to the infectious patient and also propose some protocols using RMPJ2-RSA cryptosystem and signature scheme to provide confidentiality to the patient details .
A novel method based on the mathematical morphological gradient transformation and the revised SVM for Doppler weather radar machinery fault diagnosis is proposed . Firstly use the mathematical morphological gradient to remove the noise .
Unlike many literature studies , the proposed method does not manually extract features from EEG recordings , instead it transforms the raw EEG into 2D by using Short-time Fourier Transform ( STFT ) in order to have a useful representation of frequency-time features . This work is the first in the relevant literature in using 2D timefrequency features for the purpose of automatic diagnosis of SZ patients . In order to extract most useful features out of all present in the 2D space and classify samples with high accuracy , a state-of-art Convolutional Neural Network architecture , namely VGG-16 , is trained .
Abstract We are proposing in this paper a new methodology named FNAD ( Filtrage Numerique et Analyse Discriminante ) methodology , for the on-line detection and diagnosis of multivariate processes . Our methodology is mainly based on the use of the digital filtering and discriminant analysis .
Validating legal compliance: governance analysis method Model transformation with triple graph grammars A constraint solver for model-based engineering Towards Managing Software Architectures with Ontologies Software evolution: a requirements engineering approach Completeness and Consistency Analysis for Evolving Knowledge Bases Role-based consistency verification for privacy-aware Web services Using graph-based techniques for temporal requirements engineering Contract-Based Interface Specification Language for Functional and Non-Functional Properties Use Case Refinements in the Object Oriented Software Development Process USING STEP-LOGIC FOR TRACTABLE NON-MONOTONIC INFERENCE---RESEARCH SUMMARY A Mixed Approach for the Representation of Nutritional Information Through XML-to-OWL Mappings Consistency Verification between Software Design Models and User Interface Design Based on Components Relationships Lightweight Spatial Conjunctive Query Answering Using Keywords Containment of Schema Mappings for Data Exchange (Preliminary Report) Fast Query Answering over Existential Rules The Return of the Entity-Relationship Model: Ontological Query Answering Fast candidate generation for two-phase document ranking: postings list intersection with bloom filters On the Hardness of Learning Acyclic Conjunctive Queries Towards a theory of schema-mapping optimization Conjunctive Query Answering in Finitely-Valued Fuzzy Description Logics Language Models for Genomics Information Retrieval: UIUC at TREC 2007 Genomics Track Efficient set intersection for inverted indexing Unifying verification and validation techniques: relating behavior and properties through partial evidence DESIGN AND IMPLEMENTATION OF TESTING TOOLS FOR CONTEXT FREE LANGUAGES The Use of Formal Specification of Software A FORMAL CONCEPTUAL FRAMEWORK FOR DYNAMICS WITHIN CONTEXT OF COMPONENT-BASED SYSTEM FOR DESIGNING ROBUST SOFTWARE SYSTEMS & METRICS Static Analysis: A Survey of Techniques and Tools Domain-Oriented Analysis of Software Quality Features 7.1 A 3.4-to-13.3TOPS/W 3.6TOPS Dual-Core Deep-Learning Accelerator for Versatile AI Applications in 7nm 5G Smartphone SoC Embracing Diversity: Enhanced DSP Blocks for Low-Precision Deep Learning on FPGAs Shaping Open Source Compute ecosystem with Neo and clDNN Intelligent Tableau Algorithm for DL Reasoning Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family The OWL Reasoner Evaluation Goes Mobile An integration of heuristic and model-based reasoning in fault diagnosis Implementing a Cognitive Model in Soar and ACT-R: A Comparison Analyzing a firm's international portfolio of technological knowledge: A declarative ontology-based OWL approach for patent documents TECHNICAL FUNCTIONS: TOWARDS ACCEPTING DIFFERENT ENGINEERING MEANINGS WITH ONE OVERALL ACCOUNT Transition Constraints: A Study on the Computational Complexity of Qualitative Change Reiter's Default Logic Is a Logic of Autoepistemic Reasoning And a Good One, Too Interlinking Unstructured and Structured Knowledge in an Integrated Framework The semantic component of the short functional depiction affects categorization of the ambiguous naturally formed object Integrating Quantitative And Financial Literacy Quotients by Idempotent Functions in Cedille Ontology-based Adaptive Systems of Cyber Defense ReasoNet: Learning to Stop Reading in Machine Comprehension Graph-Structured Representations for Visual Question Answering Generalizing Pooling Functions in Convolutional Neural Networks: Mixed, Gated, and Tree Multimodal Residual Learning for Visual QA Long Short-Term Memory-Networks for Machine Reading Towards Performance Tooling Interoperability: An Open Format for Representing Execution Traces Tool-Supported Application Performance Problem Detection and Diagnosis Efficient diagnosis in algorithm-based fault tolerant multiprocessor systems Interpreting the mean shift signals in multivariate control charts using support vector machine-based classifier Identifying the out-of-control variables of multivariate control chart using ensemble SVM classifiers Performance Analysis of ANN on Dataset Allocations for Pattern Recognition of Bivariate Process Implementation of Data Integration for the Enterprises’ Diagnosis Based on BizTalk Server Preliminary Application of Neural Network in Differentiating Benign from Malignant Solitary Pulmonary Nodule on HRCT Total Vector Ultramicrotomy of MSCT Applied in the Dignosis of SPN Detection and Diagnosis of Oscillations in Process Plants Diagnosis between sinusoidal oscillations and oscillatory colored noise Design and development of secured diagnostic expert system for HIV and AIDS Doppler weather radar machinery fault diagnosis based on the mathematical morphological gradient transformation and the revised SVM Automatic Detection of Schizophrenia by Applying Deep Learning over Spectrogram Images of EEG Signals Multivariate Process Control Using the FNAD Methodology
2e4af992a8ab876fcf945c14dc182acc99babfd0 f60840351e4f18c6513465956361b99a0eabb148 dcf68572b16be52abf5e8391b224f8eb98cabe0f 7c0a686c1786fb3b7b3646be955567b35a157a8d 1dc4061c535587cded94daa4e8b08637433bd3c4 3347500b621c52fcb02c5c64d4bf81ed433ef0a4 7258b2dcbb0cf06228c44c9e83c5a8a7c7653258 90d0d0d67d9de49bb48c46c83b048fa4c0437877 86cdecceaaf476bc7541b9a2b0ecaea46e0d87bd 108482b60be9adfebf83ee5076de2d4009618354 4a64a42652436e2a797cd5618a75cd93ddb03b8f 28022bd9602c77638dcc21d835bde28ecf7edc6d 8174cbb90a3b0fc0fc2f18bbc3d417676e0a7274 e3072f559b3d4a6786062c492cdbd9bf1a04b53c 028c8e917edd99b229441b6c68af8f5cac0505a0 e809e60fc0f03f1a13d8f9e5612b7ddd8222baa3 c9c92264d54cbe23f92b4ee4306570f09537c8c3 db6eedd560aa2c55f6c2f8ea80d19bd083192190 6a95af4027feaf177837de186eaaa9b19adfd734 21830af2853df6b23ecf2072d92fd81aa75082dd 218e039598d88449fa347f16005f23b50b1d1968 14e483d4fa6c7f5fac660cfc2e9e23b9abcaf535 763af1194f82ce48f01634716ac7cb16445b11df 273496c60762758c35a8f7908d378d7ee0f6188f a2fe2d68e385143dfeb719e88ef661d918bde7d9 efb2ad6e339f97364a493f03c20728bb2d68ff83 8dce808d80db21a49d6ede08ea6820769bef4a70 0ed643d2fd6dc186885f08f6ba90efed44c8e713 7bc60052b83d3d18f69682f3eb7d471e922f6006 9f2d7e980f3daef0d7ef84c9176616e56fb9cd74 21f9fdf8570af62970b57dbfacdba900ca7396b6 26c3541f5f0acfe8e06b75adea5f8c6f3b714b96 b416c440bfa3054134ab7b23cac6b05607fbbd31 0d07b93cb2ee53cdfa27b116102f38c8e8b921f7 11eeb9fab79444c213d9fbb008f72c79d22531b5 593c8e03e0958d512be4a2eeb4d96dba7882a139 d8d3fec1f48f97f2eb32517da3e4a07cc0b15d00 99caf45e325864e33d91967ed2cd578dbcf87398 c23725ae5058f34647f041a8cb4cf0802aef3d88 8ae44bf96f1a28fda2ee80031cc05d6399791e0a 62eac623c65b6dfa3f16c79a609cbbbe1b27f613 ded4955fdbc7ccf528a7ac13c795d28ade845b66 fac72c2e17357009480a2c663ef2d9ac50acd95c 4e8a1dda073425024092b783f8ffa99e75a7662b 6cb03502cb9268db8a8bfcf09a99ad14061128c1 3d95191e5d24cdf0c96875139d025ccc5af56786 e8b89be69af162e4f11cfcae34084be302583cd7 c3d7f3727c58d4f757f82aef94f4c9a7d2643aeb 5c766e5282d614593b3a4311ba206ba43f8b678e 836402050fbab02b9bf7c243cefd2739890cebb7 20d5ddbab6a0c26f28edfc94f54b8fb8b54b2077 b578a0e157ce1806252842d93d75289138917389 fec73a06f5c50ac395c7951de493130c6b0ad5ca 89305e033ac0dec229c49b3f950d7fceb1c9497e ce56d695c6c90b3c5775ce66635b0ae698a950ce 91dd2c3aa4eff5ad10c8ac53dc2d92837d1b9341 719ba4f91d4a9b3647e175805adb6554efcfa01a 3ad56f776767a5d566c82b6d6abe3809bd5cd937 ce95bafffb442af8293f00aeea1c20629f7611d0 d3443eaeaf21401a8889cd75db66217990e63464 891c6f6a4d01f9db9e48a1fd2c7e98f500ed3947
["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science","Mathematics"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Chemistry"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Engineering","Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science","Medicine"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science"] ["Computer Science","Mathematics"] ["Computer Science"]
2009 2005 2004 2010 2012 2019 2009 2011 2011 2002 2015 2015 2013 2013 2019 2012 2012 2000 2008 2014 2007 2010 2010 2000 1979 2015 2015 2013 2020 2018 2018 2013 2007 2015 1993 2008 2013 2010 2013 2011 2013 2017 2011 2019 2015 2016 2017 2016 2016 2016 2016 2015 1993 2012 2012 2009 2005 2013 2003 2014 2011 2013 2020 2003
Graph Transformations and Model-Driven Engineering CTS SLATE ESWC Semantic Search over the Web CIKM ALT PODS RR TREC FoSER The Use of Formal Specification of Software ISSCC FPL IWOCL TABLEAUX ORE IJCAI ICSC TFP STIDS CoCo@NIPS 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) AISTATS NIPS EMNLP EPEW ICCD KES ACC
https://api.semanticscholar.org/2e4af992a8ab876fcf945c14dc182acc99babfd0 https://api.semanticscholar.org/f60840351e4f18c6513465956361b99a0eabb148 https://api.semanticscholar.org/dcf68572b16be52abf5e8391b224f8eb98cabe0f https://api.semanticscholar.org/7c0a686c1786fb3b7b3646be955567b35a157a8d https://api.semanticscholar.org/1dc4061c535587cded94daa4e8b08637433bd3c4 https://api.semanticscholar.org/3347500b621c52fcb02c5c64d4bf81ed433ef0a4 https://api.semanticscholar.org/7258b2dcbb0cf06228c44c9e83c5a8a7c7653258 https://api.semanticscholar.org/90d0d0d67d9de49bb48c46c83b048fa4c0437877 https://api.semanticscholar.org/86cdecceaaf476bc7541b9a2b0ecaea46e0d87bd https://api.semanticscholar.org/108482b60be9adfebf83ee5076de2d4009618354 https://api.semanticscholar.org/4a64a42652436e2a797cd5618a75cd93ddb03b8f https://api.semanticscholar.org/28022bd9602c77638dcc21d835bde28ecf7edc6d https://api.semanticscholar.org/8174cbb90a3b0fc0fc2f18bbc3d417676e0a7274 https://api.semanticscholar.org/e3072f559b3d4a6786062c492cdbd9bf1a04b53c https://api.semanticscholar.org/028c8e917edd99b229441b6c68af8f5cac0505a0 https://api.semanticscholar.org/e809e60fc0f03f1a13d8f9e5612b7ddd8222baa3 https://api.semanticscholar.org/c9c92264d54cbe23f92b4ee4306570f09537c8c3 https://api.semanticscholar.org/db6eedd560aa2c55f6c2f8ea80d19bd083192190 https://api.semanticscholar.org/6a95af4027feaf177837de186eaaa9b19adfd734 https://api.semanticscholar.org/21830af2853df6b23ecf2072d92fd81aa75082dd https://api.semanticscholar.org/218e039598d88449fa347f16005f23b50b1d1968 https://api.semanticscholar.org/14e483d4fa6c7f5fac660cfc2e9e23b9abcaf535 https://api.semanticscholar.org/763af1194f82ce48f01634716ac7cb16445b11df https://api.semanticscholar.org/273496c60762758c35a8f7908d378d7ee0f6188f https://api.semanticscholar.org/a2fe2d68e385143dfeb719e88ef661d918bde7d9 https://api.semanticscholar.org/efb2ad6e339f97364a493f03c20728bb2d68ff83 https://api.semanticscholar.org/8dce808d80db21a49d6ede08ea6820769bef4a70 https://api.semanticscholar.org/0ed643d2fd6dc186885f08f6ba90efed44c8e713 https://api.semanticscholar.org/7bc60052b83d3d18f69682f3eb7d471e922f6006 https://api.semanticscholar.org/9f2d7e980f3daef0d7ef84c9176616e56fb9cd74 https://api.semanticscholar.org/21f9fdf8570af62970b57dbfacdba900ca7396b6 https://api.semanticscholar.org/26c3541f5f0acfe8e06b75adea5f8c6f3b714b96 https://api.semanticscholar.org/b416c440bfa3054134ab7b23cac6b05607fbbd31 https://api.semanticscholar.org/0d07b93cb2ee53cdfa27b116102f38c8e8b921f7 https://api.semanticscholar.org/11eeb9fab79444c213d9fbb008f72c79d22531b5 https://api.semanticscholar.org/593c8e03e0958d512be4a2eeb4d96dba7882a139 https://api.semanticscholar.org/d8d3fec1f48f97f2eb32517da3e4a07cc0b15d00 https://api.semanticscholar.org/99caf45e325864e33d91967ed2cd578dbcf87398 https://api.semanticscholar.org/c23725ae5058f34647f041a8cb4cf0802aef3d88 https://api.semanticscholar.org/8ae44bf96f1a28fda2ee80031cc05d6399791e0a https://api.semanticscholar.org/62eac623c65b6dfa3f16c79a609cbbbe1b27f613 https://api.semanticscholar.org/ded4955fdbc7ccf528a7ac13c795d28ade845b66 https://api.semanticscholar.org/fac72c2e17357009480a2c663ef2d9ac50acd95c https://api.semanticscholar.org/4e8a1dda073425024092b783f8ffa99e75a7662b https://api.semanticscholar.org/6cb03502cb9268db8a8bfcf09a99ad14061128c1 https://api.semanticscholar.org/3d95191e5d24cdf0c96875139d025ccc5af56786 https://www.semanticscholar.org/paper/c636a2dd242908fe2e598a1077c0c57bfdea8633 https://www.semanticscholar.org/paper/c7d007ba376faddf0046930ea7375ed59600cee9 https://www.semanticscholar.org/paper/4b88e948121a87f00fb5aa0081d2044dde51ee36 https://www.semanticscholar.org/paper/1afb710a5b35a2352a6495e4bf6eef66808daf1b https://www.semanticscholar.org/paper/13fe71da009484f240c46f14d9330e932f8de210 https://api.semanticscholar.org/e8b89be69af162e4f11cfcae34084be302583cd7 https://api.semanticscholar.org/c3d7f3727c58d4f757f82aef94f4c9a7d2643aeb https://api.semanticscholar.org/5c766e5282d614593b3a4311ba206ba43f8b678e https://api.semanticscholar.org/836402050fbab02b9bf7c243cefd2739890cebb7 https://api.semanticscholar.org/20d5ddbab6a0c26f28edfc94f54b8fb8b54b2077 https://api.semanticscholar.org/b578a0e157ce1806252842d93d75289138917389 https://api.semanticscholar.org/fec73a06f5c50ac395c7951de493130c6b0ad5ca https://api.semanticscholar.org/89305e033ac0dec229c49b3f950d7fceb1c9497e https://api.semanticscholar.org/ce56d695c6c90b3c5775ce66635b0ae698a950ce https://api.semanticscholar.org/91dd2c3aa4eff5ad10c8ac53dc2d92837d1b9341 https://api.semanticscholar.org/719ba4f91d4a9b3647e175805adb6554efcfa01a https://api.semanticscholar.org/3ad56f776767a5d566c82b6d6abe3809bd5cd937 https://api.semanticscholar.org/ce95bafffb442af8293f00aeea1c20629f7611d0 https://api.semanticscholar.org/d3443eaeaf21401a8889cd75db66217990e63464 https://api.semanticscholar.org/891c6f6a4d01f9db9e48a1fd2c7e98f500ed3947