Identification and Check of Inconsistencies between UML Diagrams

Relationships between Unified Modeling Language (UML) diagrams are complex. The complexity leads to inconsistencies between UML diagrams easily. This paper focus on how to identify and check inconsistencies between UML diagrams. 13 consistency rules are given to identify inconsistencies between the most frequent 6 types of UML diagrams in the domain of information systems analysis and design. These diagrams are as follows: Use Case Diagrams, Class Diagrams, Activity Diagrams, State Machine Diagrams, Sequence Diagrams and Communication Diagrams. 4 methods are given to check inconsistencies between UML diagrams as follows: manual check, compulsory restriction, automatic maintenance, dynamic check. These rules and methods are helpful for developers to model information systems.

A Solution of Data Inconsistencies in Data Integration——Designed for Pervasive Computing Environment

New challenges including how to share information on heterogeneous devices appear in data-intensive pervasive computing environments. Data integration is a practical approach to these applications. Dealing with inconsistencies is one of the important problems in data integration. In this paper we motivate the problem of data inconsistency solution for data integration in pervasive environments. We define data qualit~ criteria and expense quality criteria for data sources to solve data inconsistency. In our solution, firstly, data sources needing high expense to obtain data from them are discarded by using expense quality criteria and utility function. Since it is difficult to obtain the actual quality of data sources in pervasive computing environment, we introduce fuzzy multi-attribute group decision making approach to selecting the appropriate data sources. The experimental results show that our solution has ideal effectiveness.

A Component-Based Debugging Approach for Detecting Structural Inconsistencies in Declarative Equation Based Models

Object-oriented modeling with declarative equation based languages often unconsciously leads to structural inconsistencies. Component-based debugging is a new structural analysis approach that addresses this problem by analyzing the structure of each component in a model to separately locate faulty components. The analysis procedure is performed recursively based on the depth-first rule. It first generates fictitious equations for a component to establish a debugging environment, and then detects structural defects by using graph theoretical approaches to analyzing the structure of the system of equations resulting from the component. The proposed method can automatically locate components that cause the structural inconsistencies, and show the user detailed error messages. This information can be a great help in finding and localizing structural inconsistencies, and in some cases pinpoints them immediately.

A PRIORITY-BASED NEGOTIATIONS APPROACH FOR HANDLING INCONSISTENCIES IN MULTI-PERSPECTIVE SOFTWARE REQUIREMENTS

Inconsistency of multi-perspective requirements specifications is a pervasive issue during the requirements process. However, managing inconsistency is not just a pure technical problem. It is always associated with a process of interactions and competitions among corresponding stakeholders. The main contribution of this paper is to present a negotiations approach to handling inconsistencies in multi-perspective software requirements. In particular, the priority of requirements relative to each perspective plays an important role in proceeding negotiation over resolving inconsistencies among different stakeholders. An algorithm of generating negotiation proposals and an approach to evaluating proposals are also presented in this paper, respectively.

Dialectical Thermodynamics’Solution to the Conceptual Imbroglio That Is the Reversible Path

According to the second law of thermodynamics, as currently understood, any given transit of a system along the reversible path proceeds with a total entropy change equal to zero. The fact that this condition is also the identifier of thermodynamic equilibrium, makes each and every point along the reversible path a state of equilibrium, and the reversible path, as expressed by a noted thermodynamic author, “a dense succession of equilibrium states”. The difficulties with these notions are plural. The fact, for example, that systems need to be forced out of equilibrium via the expenditure of work, would make any spontaneous reversible process a consumer of work, this in opposition to common thermodynamic wisdom that makes spontaneous reversible processes the most efficient transformers of work-producing-potential into actual work. The solution to this and other related impasses is provided by Dialectical Thermodynamics via its previously proved notion assigning a negative entropy change to the energy upgrading process represented by the transformation of heat into work. The said solution is here exemplified with the ideal-gas phase isomerization of butane into isobutane.

Interaction between Surface Acoustic Wave and Quantum Hall Effects

Surface acoustic wave(SAW)is a powerful technique for investigating quantum phases appearing in twodimensional electron systems.The electrons respond to the piezoelectric field of SAW through screening,attenuating its amplitude,and shifting its velocity,which is described by the relaxation model.In this work,we systematically study this interaction using orders of magnitude lower SAW amplitude than those in previous studies.At high magnetic fields,when electrons form highly correlated states such as the quantum Hall effect,we observe an anomalously large attenuation of SAW,while the acoustic speed remains considerably high,inconsistent with the conventional relaxation model.This anomaly exists only when the SAW power is sufficiently low.

RESTlogic: Detecting Logic Vulnerabilities in Cloud REST APIs

logical testing model and resource lifecycle information,generate test cases and complete parameters,and alleviate inconsistency issues through parameter inference.Once again,we propose a method of analyzing test results using joint state codes and call stack information,which compensates for the shortcomings of traditional analysis methods.We will apply our method to testing REST services,including OpenStack,an open source cloud operating platform for experimental evaluation.We have found a series of inconsistencies,known vulnerabilities,and new unknown logical defects.

Agricultural Investment Project Decisions Based on an Interactive Preference Disaggregation Model Considering Inconsistency

Agricultural investment project selection is a complex multi-criteria decision-making problem,as agricultural projects are easily influenced by various risk factors,and the evaluation information provided by decisionmakers usually involves uncertainty and inconsistency.Existing literature primarily employed direct preference elicitation methods to address such issues,necessitating a great cognitive effort on the part of decision-makers during evaluation,specifically,determining the weights of criteria.In this study,we propose an indirect preference elicitation method,known as a preference disaggregation method,to learn decision-maker preference models fromdecision examples.To enhance evaluation ease,decision-makers merely need to compare pairs of alternatives with which they are familiar,also known as reference alternatives.Probabilistic linguistic preference relations are employed to account for the presence of incomplete and uncertain information in such pairwise comparisons.To address the inconsistency among a group of decision-makers,we develop a pair of 0-1mixed integer programming models that consider both the semantics of linguistic terms and the belief degrees of decision-makers.Finally,we conduct a case study and comparative analysis.Results reveal the effectiveness of the proposed model in solving agricultural investment project selection problems with uncertain and inconsistent decision information.

On the Proof of the Contradiction of Set Theory

The article is devoted to proving the inconsistency of set theory arising from the existence of strange trees. All steps of the proof rely on common informal set-theoretic reasoning, but they take into account the prohibitions that were introduced into axiomatic set theories in order to overcome the difficulties encountered by the naive Cantor set theory. Therefore, in fact, the article is about proving the inconsistency of existing axiomatic set theories, in particular, the ZFC theory.

Mathematical Modeling of the Co-Infection Dynamics of HIV and Tuberculosis Incorporating Inconsistency in HIV Treatment

A non-linear HIV-TB co-infection has been formulated and analyzed. The positivity and invariant region has been established. The disease free equilibrium and its stability has been determined. The local stability was determined and found to be stable under given conditions. The basic reproduction number was obtained and according to findings, co-infection diminishes when this number is less than unity, and persists when the number is greater than unity. The global stability of the endemic equilibrium was calculated. The impact of HIV on TB was established as well as the impact of TB on HIV. Numerical solution was also done and the findings indicate that when the rate of HIV treatment increases the latent TB increases while the co-infected population decreases. When the rate of HIV treatment decreases the latent TB population decreases and the co-infected population increases. Encouraging communities to prioritize the consistent treatment of HIV infected individuals must be emphasized in order to reduce the scourge of HIV-TB co-infection.

Mathematical Modeling of HIV Investigating the Effect of Inconsistent Treatment

HIV is a retrovirus that infects and impairs the cells and functions of the immune system. It has caused a great challenge to global public health systems and leads to Acquired Immunodeficiency Syndrome (AIDS), if not attended to in good time. Antiretroviral therapy is used for managing the virus in a patient’s lifetime. Some of the symptoms of the disease include lean body mass and many opportunistic infections. This study has developed a SIAT mathematical model to investigate the impact of inconsistency in treatment of the disease. The arising non-linear differential equations have been obtained and analyzed. The DFE and its stability have been obtained and the study found that it is locally asymptotically stable when the basic reproduction number is less than unity. The endemic equilibrium has been obtained and found to be globally asymptotically stable when the basic reproduction number is greater than unity. Numerical solutions have been obtained and analyzed to give the trends in the spread dynamics. The inconsistency in treatment uptake has been analyzed through the numerical solutions. The study found that when the treatment rate of those infected increases, it leads to an increase in treatment population, which slows down the spread of HIV and vice versa. An increase in the rate of treatment of those with AIDS leads to a decrease in the AIDS population, the reverse happens when this rate decreases. The study recommends that the community involvement in advocating for consistent treatment of HIV to curb the spread of the disease.

Recycling a Scarce Resource

Caleb Munyao,a 48-year-old middle-scale farmer from Kenya’s eastern region,understands the importance of water better than most.On his 13-hectare farm,where he grows maize,yellow beans,and mangoes,every drop of water is precious.Kenya,like many countries in Africa,faces significant challenges in managing its water resources.The country’s water scarcity issues are exacerbated by climate change,rapid urbanisation,and inconsistent rainfall patterns.

Research on Agricultural Ontology and Fusion Rules Based Knowledge Fusion Framework

Currently, knowledge-based sharing and service system has been a hot issue and knowledge fusion, especially for implicit knowledge discovery, becomes the core of knowledge processing and optimization in the system. In the research, a knowledge fusion framework based on agricultural ontology and fusion rules was pro- posed, including knowledge extraction, clearing and annotation modules based on a- gricultural ontology, fusion rule construction, choosing and evaluation modules based on agricultural ontology and knowledge fusion module for users＇ demands. Finally, the significance of the framework to system of agricultural knowledge services was proved with the help of a case.

Big Data Flow Adjustment Using Knapsack Problem

The advancements of mobile devices, public networks and the Internet of creature huge amounts of complex data, both construct & unstructured are being captured in trust to allow organizations to produce better business decisions as data is now pivotal for an organizations success. These enormous amounts of data are referred to as Big Data, which enables a competitive advantage over rivals when processed and analyzed appropriately. However Big Data Analytics has a few concerns including Management of Data, Privacy & Security, getting optimal path for transport data, and Data Representation. However, the structure of network does not completely match transportation demand, i.e., there still exist a few bottlenecks in the network. This paper presents a new approach to get the optimal path of valuable data movement through a given network based on the knapsack problem. This paper will give value for each piece of data, it depends on the importance of this data (each piece of data defined by two arguments size and value), and the approach tries to find the optimal path from source to destination, a mathematical models are developed to adjust data flows between their shortest paths based on the 0 - 1 knapsack problem. We also take out computational experience using the commercial software Gurobi and a greedy algorithm (GA), respectively. The outcome indicates that the suggest models are active and workable. This paper introduced two different algorithms to study the shortest path problems: the first algorithm studies the shortest path problems when stochastic activates and activities does not depend on weights. The second algorithm studies the shortest path problems depends on weights.

New Composite Equalization Strategy for Lithium Battery Packs

In order to improve the working efficiency of the power battery pack and prolong the service life, there is a problem of inconsistency among the individual cells. Based on the centralized equalization structure of the multi-output winding transformer, a three-stage hybrid equalization control strategy is designed for equalization. The equalization scheme realizes that the high voltage single battery transfers the energy to the low voltage battery cell during the charging of the battery pack, improving not only charging efficiency and energy use loss, but also the high voltage battery transferring the power to the low voltage battery cell when the pressure difference is greater than 10 mv during the discharge. Between 5 mv and 10 mv, it performs passive equalization, reducing the output fluctuation of the power battery pack and achieving the balance purpose. During the standing time, the maximum active balancing operation within the battery pack is performed in order to achieve intra-group optimum consistency. It is proved by experiments that the equalization control method can realize the quick and effective equalization in the battery pack, and the energy balance of each single battery.

Is inconsistency of α-fetoprotein level a good prognosticator for hepatocellular carcinoma recurrence?

AIM: To identify the clinical outcomes of hepato-cellular carcinoma (HCC) patients with inconsistent α-fetoprotein (AFP) levels which were initially high and then low at recurrence.METHODS: We retrospectively included 178 patients who underwent liver resection with high preoperative AFP levels (≥ 200 ng/dL). Sixty-nine HCC patients had recurrence during follow-up and were grouped by their AFP levels at recurrence: group Ⅰ, AFP ≤ 20 ng/dL (n = 16); group Ⅱ, AFP 20-200 ng/dL (n = 24); and group Ⅲ, AFP ≥ 200 ng/dL (n = 29). Their preoperative clinical characteristics, accumulated recurrence rate, and recurrence-to-death survival rate were compared. Three patients, one in each group, underwentliver resection twice for primary and recurrent HCC. AFP immunohistochemistry of primary and recurrent HCC specimens were examined.RESULTS: In this study, 23% of patients demon-strated normal AFP levels at HCC recurrence. The AFP levels in these patients were initially high. There were no significant differences in clinical characteristics between the three groups except for the mean recur-rence interval (21.8 ± 14.6, 12.3 ± 7.7, 8.3 ± 6.6 mo, respectively, P < 0.001) and survival time (40.2 ± 19.9, 36.1 ± 22.4, 21.9 ± 22.0 mo, respectively, P = 0.013). Tumor size > 5 cm, total bilirubin > 1.2 mg/dL, vessel invasion, Child classification B, group Ⅲ, and recurrence interval < 12 mo, were risk factors for survival rate. Cox regression analysis was performed and vessel invasion, group Ⅲ, and recurrence interval were independent risk factors. The recurrence inter-val was significant longer in group Ⅰ (P < 0.001). The recurrence-to-death survival rate was significantly bet-ter in group Ⅱ (P = 0.016). AFP staining was strong in the primary HCC specimens and was reduced at recur-rence in group Ⅰ specimens.CONCLUSION: Patients in group Ⅰ with inconsistent AFP levels had a longer recurrence interval and worse recurrence-to-death survival rate than those in group Ⅱ. This clinical presentation may be caused by a delay in the detection of HCC recurrence.

Updating ontologies and general rules

Inconsistencies or conflicts appearing in the integration of ontologies and general rules are handled by applying prioritizing and updating. First, a prioritized knowledge base is obtained by weighting information weight. Then, based on the idea ＂abandoning the old for the new＂, the weight of each rule is greater than that of the information in ontologies. If ontologies conflict with general rules, then a new knowledge-base without any inconsistency or conflict is obtained by using rules with big weight updating information in ontologies with small weight. Thus, current logic programming solvers and description logic reasoners are employed to implement the reasoning services, such as querying etc. Updating based on prioritizing is more suitable for handling inconsistencies than other approaches to introducing non-standard semantics if knowledge bases are dynamically evolving. Moreover, a consistent knowledge base can be always maintained in the dynamical environment by updating outdated information with new information based on weighting. Finally, this approach to dealing with inconsistencies is feasibly exemplified.

Discrete Event System Framework for Fault Diagnosis with Measurement Inconsistency:Case Study of Rogue DHCP Attack

Fault detection and diagnosis(FDD) facilitates reliable operation of systems. Various approaches have been proposed for FDD like Analytical redundancy(AR), Principal component analysis(PCA), Discrete event system(DES) model etc., in the literature. Performance of FDD schemes greatly depends on accuracy of the sensors which measure the system parameters.Due to various reasons like faults, communication errors etc.,sensors may occasionally miss or report erroneous values of some system parameters to FDD engine, resulting in measurement inconsistency of these parameters. Schemes like AR, PCA etc.,have mechanisms to handle measurement inconsistency, however,they are computationally heavy. DES based FDD techniques are widely used because of computational simplicity, but they cannot handle measurement inconsistency efficiently. Existing DES based schemes do not use Measurement inconsistent(MI)parameters for FDD. These parameters are not permanently unmeasurable or erroneous, so ignoring them may lead to weak diagnosis. To address this issue, we propose a Measurement inconsistent discrete event system(MIDES) framework, which uses MI parameters for FDD at the instances they are measured by the sensors. Otherwise, when they are unmeasurable or erroneously reported, the MIDES invokes an estimator diagnoser that predicts the state(s) the system is expected to be in, using the subsequent parameters measured by the other sensors. The efficacy of the proposed method is illustrated using a pumpvalve system. In addition, an MIDES based intrusion detection system has been developed for detection of rogue dynamic host configuration protocol(DHCP) server attack by mapping the attack to a fault in the DES framework.

Reliability and Availability Models of Belt Drive Systems Considering Failure Dependence

Conventional reliability models of belt drive systems in the failure mode of fatigue are mainly based on the static stress strength interference model and its extended models, which cannot consider dynamic factors in the operational duration and be used for further availability analysis. In this paper, time-dependent reliability models, failure rate models and availability models of belt drive systems are developed based on the system dynamic equations with the dynamic stress and the material property degradation taken into account. In the proposed models, dynamic failure dependence and imperfect maintenance are taken into consideration. Furthermore, the issue of time scale inconsistency between system failure rate and system availability is proposed and addressed in the proposed system availability models. Besides, Monte Carlo simulations are carried out to validate the established models. The results from the proposed models and those from the Monte Carlo simulations show a consistency. Furthermore, the case studies show that the failure dependence, imperfect maintenance and the time scale inconsistency have significant influences on system availability. The independence assumption about the belt drive systems results in underestimations of both reliability and availability. Moreover, the neglect of the time scale inconsistency causes the underestimate of the system availability. Meanwhile, these influences show obvious time-dependent characteristics.

A consistency improving method in the analytic hierarchy process based on directed circuit analysis

Test of consistency is critical for the analytic hierarchy process(AHP) methodology. When a pairwise comparison matrix(PCM) fails the consistency test, the decision maker(DM) needs to make revisions. The state of the art focuses on changing a single entry or creating a new matrix based on the original inconsistent matrix so that the modified matrix can satisfy the consistency requirement. However, we have noticed that the reason that causes inconsistency is not only numerical inconsistency, but also logical inconsistency, which may play a more important role in the whole inconsistency. Therefore, to realize satisfactory consistency, first of all, we should change some entries that form a directed circuit to make the matrix logically consistent, and then adjust other entries within acceptable deviations to make the matrix numerically consistent while preserving most of the original comparison information. In this paper, we firstly present some definitions and theories, based on which two effective methods are provided to identify directed circuits. Four optimization models are proposed to adjust the original inconsistent matrix. Finally, illustrative examples and comparison studies show the effectiveness and feasibility of our method.