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Software vulnerabilities have been the greatest threat to the software industry for a long time. Many detection techniques have been developed to address this kind of issue, such as Fuzzing, but mere Fuzz Testing is not good enough, because the Fuzzing only alters the input of program randomly, and does not consider the basic semantics of the target software. The purpose of this paper is to introduce a new vulnerability exploring system, called “SEVE” to explore the target software more deeply and to generate more test cases with more accuracy.

Symbolic execution is the core technique of SEVE. The user can just input a standard input, and the SEVE system will record the execution path, alter the critical branches of it, and generate a totally different test case which will make the software under test execute a different path. In this way, some potential bugs or defects, even the exploitable vulnerabilities will be discovered. To alleviate path explosion, the authors propose heuristic method and function abstraction, which in turn improve the performance of SEVE even further.

We evaluate SEVE system to record critical data about its efficiency and performance. We have tested some real‐world vulnerabilities, from which the underlying file‐input programs suffer. After that, the results show that SEVE is not only re‐creating the discovery of these vulnerabilities, but also at a higher performance level than traditional techniques.

The paper proposes a new vulnerability exploring system, called “SEVE” to explore the target software and generate test cases automatically and also heuristic method and function abstraction to handle path explosion.

In this chapter, we explore uses of corpus linguistics within higher education research. Corpus linguistic approaches enable examination of large bodies of language data based on computing power. These bodies of data, or corpora, facilitate investigation of the meaning of words in context. The semiautomated nature of such investigation helps researchers to identify and interpret language patterns that might otherwise be inaccessible through manual analysis. We illustrate potential uses of corpus linguistic approaches through four short case studies by higher education researchers, spanning educational contexts, disciplines and genres. These case studies are underpinned by discussion of the development of corpus linguistics as a field of investigation, including existing open corpora and corpus analysis tools. We give a flavour of how corpus linguistic techniques, in isolation or as part of a wider research approach, can be particularly helpful to higher education researchers who wish to investigate language data and its context.

The role of conventional contracts in achieving sustainability goals in public–private partnership (PPP) projects has been questioned. From the multifunctional perspective of contract theory, joint-contract functions that combine contractual control, coordination and adaptation may be a potential approach for improving PPP project sustainability performance. This research intends to investigate the link between the joint-contract functions and PPP project sustainability performance, and their underlying mechanism, by analyzing the mediating role of relationship quality and moderating roles of environmental uncertainty and behavioral uncertainty.

Based on 170 valid survey data collected from the Chinese PPP professionals, partial least squares structural equation modeling (PLS-SEM) was adopted to test the hypothesis.

The results reveal that joint-contract functions are positively associated with the PPP project sustainability performance. This relationship is strengthened by environmental and behavioral uncertainty. Moreover, the relationship between the joint-contract functions and PPP project sustainability performance is mediated by relationship quality.

This research extends contract governance theory and sustainability research in PPP projects. The research implications are as follows: (1) joint-contract functions are a second-order construct consisting of three first-order dimensions: control, coordination and adaptation and are positively associated with PPP project sustainability performance; (2) joint-contract functions enhance the sustainable benefits of PPP projects during environmental uncertainty and behavioral uncertainty; (3) informal relationships are a critical bridge connecting formal institutions with the sustainability performance of PPP projects.

In general, these findings guide project participants who aim to achieve sustainable outcomes in PPP projects. (1) Project participants should consider the process of contract design and sign contracts that focus on joint-contract functions. (2) Project participants should investigate the degree of uncertainty of a PPP project before designing contracts, and design the contracts with corresponding complexity. (3) Project participants should work to enhance PPP sustainable benefits by improving the relationship between partners, such as encouraging mutual trust and joint problem-solving.

This research verifies the relationship between joint-contract functions and PPP project sustainability performance, and the boundary and intermediary conditions between them.

The Brandeis serials collection of 3,550 periodicals and 1,950 annuals and irregulars, in two libraries, are maintained on Faxon's LINX online system. At a cost of $26,500 per year, Brandeis has been able to save resources and increase performance through the use of LINX. This article provides an evaluation of the system after one full year of use.

To provide an overview of how a number of frequently used smoothing‐based forecasting techniques can be modelled for use in dynamic analysis of production‐inventory systems.

The smoothing techniques are modelled using transfer functions and state space representation. Basic control theory is used for analysing the dynamic properties.

A set of expressions are derived for the smoothing techniques and dynamic properties are identified.

Dynamic properties are important in many applications. It is shown that the different smoothing techniques can have very different influences on the dynamic behaviour and therefore should be considered as a factor when smoothing parameters are decided on.

Dynamic behaviour of production‐inventory systems can be analysed using control theory based on, e.g. transfer functions or state space models. In this paper a set of models for five common smoothing techniques are analysed and their respective dynamic properties are highlighted.

The purpose of this paper is to examine the grain production implications of alternative designs for China’s grain subsidy policy. In particular, the authors examine three subsidy designs including area-based subsidy, quantity-based subsidy and production-cost-based subsidy.

To carry out the analysis, the authors develop a Chinese agricultural sector model (CASM) and an econometric, policy action–farmer response summary model. The CASM is used under a wide variety of subsidy level and basis experiments to generate pseudo data on farmer reactions to subsidies. Then a summary function model was estimated over those pseudo data that quantitatively summarized modeled farmer responses to different grain subsidy schemes. In turn, the summary functions were used to optimize the subsidy level such that it maximized grain production both within and across the area-based, quantity-based and cost-based subsidies. Regional implications were also developed.

The authors found that the production-quantity-based subsidy is the most cost-effective in stimulating grain production among the subsidy schemes. The authors also argue that scheme complies with WTO regulations regarding product-specific support. The authors found that the areas where grain production was most affected were the traditional grain-producing regions.

To the authors’ knowledge the authors have not seen a study of the Chinese grain subsidy program context that examined the effects of alternative subsidy schemes, nor one that developed estimates of the optimal subsidy level. In addition, the methodology is unique employing bottom-up, regionally disaggregated, sector modeling coupled with an aggregate pseudo data based summary function approach providing a new, original approach for analyzing agricultural policy design.

Query-based summarization approaches might not be able to provide summaries compatible with the user’s information need, as they mostly rely on a limited source of information, usually represented as a single query by the user. This issue becomes even more challenging when dealing with scientific documents, as they contain more specific subject-related terms, while the user may not be able to express his/her specific information need in a query with limited terms. This study aims to propose an interactive multi-document text summarization approach that generates an eligible summary that is more compatible with the user’s information need. This approach allows the user to interactively specify the composition of a multi-document summary.

This approach exploits the user’s opinion in two stages. The initial query is refined by user-selected keywords/keyphrases and complete sentences extracted from the set of retrieved documents. It is followed by a novel method for sentence expansion using the genetic algorithm, and ranking the final set of sentences using the maximal marginal relevance method. Basically, for implementation, the Web of Science data set in the artificial intelligence (AI) category is considered.

The proposed approach receives feedback from the user in terms of favorable keywords and sentences. The feedback eventually improves the summary as the end. To assess the performance of the proposed system, this paper has asked 45 users who were graduate students in the field of AI to fill out a questionnaire. The quality of the final summary has been also evaluated from the user’s perspective and information redundancy. It has been investigated that the proposed approach leads to higher degrees of user satisfaction compared to the ones with no or only one step of the interaction.

The interactive summarization approach goes beyond the initial user’s query, while it includes the user’s preferred keywords/keyphrases and sentences through a systematic interaction. With respect to these interactions, the system gives the user a more clear idea of the information he/she is looking for and consequently adjusting the final result to the ultimate information need. Such interaction allows the summarization system to achieve a comprehensive understanding of the user’s information needs while expanding context-based knowledge and guiding the user toward his/her information journey.

Many attempts have been made to integrate communication with other properties of organisations. Frameworks and models have been developed by Galbraith (1977, 1973), Tushman (1979), Tushman and Nadler (1978), and Penley (1982). This study proposes to continue the line of research by considering additional aspects of the organisational environment in addition to various communication variables.

The purpose of this paper is to present an extended version of the Elaboration Likelihood Model (ELM‐model) to explain and predict which of the four cognitive processes that are distinguished in the literature, with respect to Country of Origin (CoO), can be expected to occur: the halo‐effect, the summary construct‐effect, the product attribute‐effect or the default heuristic‐effect.

Contrary to most of the previous theoretically‐oriented work on cognitive CoO‐effects, the epistemological background of the CoO‐ELM model proposed in this paper is of an inductive nature with theoretical propositions being derived from empirical data already gathered in the existing studies.

The outcome of this paper is a flow chart model leading to a set of theoretical propositions on which cognitive CoO‐effects can be expected to occur under different situational contexts.

This paper only focuses on the explanation of cognitive CoO‐effects, not on affective or conative/normative effects. Also, the CoO‐ELM model applies only to the processing of consumers' prior knowledge about a country's products and not about the country itself. Finally, the CoO‐ELM model still needs to be subjected to empirical verification. An important implication of this paper is that the CoO‐ELM framework makes the bulk of empirical data become more transparent given the four effects of cognitive CoO‐processes.

The CoO‐ELM model provides marketing practitioners with an easy and practical tool for the management of CoO‐cues.

This paper is the first attempt trying to catch all the cognitive CoO‐effects previously identified within a theoretically solid framework.

An aerodynamic shape optimization algorithm is presented, which includes all aspects of the design process: parameterization, flow computation and optimization. The purpose of this paper is to show that the Class‐Shape‐Refinement‐Transformation method in combination with an Euler/adjoint solver provides an efficient and intuitive way of optimizing aircraft shapes.

The Class‐Shape‐Transformation method was used to parameterize the aircraft shape and the flow was computed using an in‐house Euler code. An adjoint solver implemented into the Euler code was used to compute the required gradients and a trust‐region reflective algorithm was employed to perform the actual optimization.

The results of two aerodynamic shape optimization test cases are presented. Both cases used a blended‐wing‐body reference geometry as their initial input. It was shown that using a two‐step approach, a considerable improvement of the lift‐to‐drag ratio in the order of 20‐30 per cent could be achieved. The work presented in this paper proves that the CSRT method is a very intuitive and effective way of parameterizating aircraft shapes. It was also shown that using an adjoint algorithm provides the computational efficiency necessary to perform true three‐dimensional shape optimization.

The novelty of the algorithm lies in the use of the Class‐Shape‐Refinement‐Transformation method for parameterization and its coupling to the Euler and adjoint codes.