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The purpose of this paper is to activate latent users posts by modeling user behaviors by a transition of clusters that represent particular posting activities. Twitter has rapidly spread and become an easy and convenient microblog that enables users to exchange instant text messages called tweets. There are so many latent users whose posting activities have decreased.

Under this model, two kinds of time-series analysis methods are proposed to clarify the lifecycles of Twitter users. In the first one, all users belong to a cluster consisting of several features at individual time slots and move among the clusters in a time series. In the second one, the posting activities of Twitter users are analyzed by the amount of tweets that vary with time.

This sophisticated evaluation using a large actual tweet-set demonstrated the proposed methods effectiveness. The authors found a big difference in the state transition diagrams between long- and short-term users. Analysis of short-term users introduces effective knowledge for encouraging continued Twitter use.

An the efficient user behavior model, which describes transitions of posting activities, is proposed. Two kinds of time longitudinal analysis method are evaluated using a large amount of actual tweets.

The purpose of this paper is to propose a state dependent stochastic Markov model for availability analysis of process plant instead of traditional time dependent model.

The traditional concepts of system performance measurement and reliability (namely, binary; two-state concepts) are observed to be inadequate to characterize performance of complex system components. Availability analysis considering an intermediate state, such as a degraded state, provides a better alternative mechanism for system performance mapping. The availability model provides a better assessment of failure and repair characteristics for equipment in the sub-system and its overall performance. In addition to availability analysis, this paper also discusses the preventive maintenance (PM) program to achieve target availability. In this model, the degraded state is considered as a PM state. Using Markov analysis the optimum maintenance interval is determined.

Markov process provides an easier way to measure the performance of the process facility. This study also revealed that the maintenance interval has a major influence in the availability of a process facility as well as in maintaining target availability. The developed model is also applicable to the varying target availability as well as having the capability to handle even the reconfigured process systems.

Considering the degraded state as an operative state, a higher availability of the plant is predicted. The consideration of the degraded state of the system makes the availability estimation more realistic and acceptable. Availability quantification, target availability allocation and a PM model are exemplified in a sub-system of an liquefied natural gas facility.

The unique features of the present study are; Markov modeling approach integrating availability and PM; optimum PM interval determination of stochastically degrading components based on target availability; consideration of three-state systems; and consideration of increasing failure rates.

When trying to establish quality management in a service industry one is confronted with a particular set of problems due to the distinctive characteristics of service processes. Describes the assessment procedure for service processes using a case study obtained from the sales department of a company in the computer industry. A slightly modified process modelling technique – usually employed in the field of requirements engineering – is used to analyse and depict the processes. Aims to discover weak points inherent in the business processes and eliminate them in order to pass the ISO 9001 certification audit.

While behaviour sequence analysis (BSA) is popular, it is not without limitations, namely, the level of detail required and time taken to run analyses; therefore, this paper aims to outline a novel method, using 30 serial homicide cases as a worked example.

Temporal analysis methods are becoming increasingly popular in applied forensic and criminological research. In recent years, BSA has become a widely used approach.

Waypoint sequencing provides a streamlined version of the traditional BSA approach, allowing for fewer behaviours to be included and providing a clearer overview of the main behaviours of interest.

Waypoint sequencing is shown in the current paper through serial killer research to show how to conduct the analyses and how it is effective in current investigations by expediting the process and allowing quicker analysis to facilitate current investigations.

The current research provides a novel approach to sequence analysis that is more useful in applied settings as it requires fewer behaviours or events than traditional BSA.

Purpose of this study is to classify the states of Markov Chain for the implementation of Markov Password for effective security. Password confirmation is more often required in all authentication process, as the usage of computing facilities and electronic devices have developed hugely to access networks. Over the years with the increase in numerous Web developments and internet applications, each platform needs ID and password validation for individual users.

In the technological development of cloud computing, in recent times, it is facing security issues. Data theft, data security, denial of service, patch management, encryption management, key management, storage security and authentication are some of the issues and challenges in cloud computing. Validation in user login authentications is generally processed and executed by password. To authenticate universally, alphanumeric passwords are used. One of the promising proposed methodologies in this type of password authentication is Markov password. Markov passwords – a rule-based password formation are created or generated by using Markov chain. Representation of Markov password formation can be done by state space diagram or transition probability matrix. State space classification of Markov chain is one of the basic and significant properties. The objective of this paper is to classify the states of Markov chain to support the practice of this type of password in the direction of effective authentication for secure communication in cloud computing. Conversion of some sample obvious password into Markov password and comparative analysis on their strength is also presented in this paper. Analysis on strength of obvious password of length eight has shown range of 7%–9% although the converted Markov password has shown more than 82%. As an effective methodology, this password authentication can be implemented in cloud portal and password login validation process.

The objective of this paper is to classify the states of Markov chain to support the practice of this type of password in the direction of effective authentication for secure communication in cloud computing. Conversion of some sample obvious password into Markov password and comparative analysis on their strength is also presented in this paper.

Validation in user login authentications is generally processed and executed by password. To authenticate universally, alphanumeric passwords are used. One of the promising proposed methodologies in this type of password authentication is Markov password.

The purpose of this paper is to address the complexity of missing persons cases and highlight the linguistic differences that arise in this type of crime. Missing persons cases are typically very complex investigations. Without a body, crime scene forensics is not possible, and police are often left only with witness and suspect statements. Forensic linguistics methods may help investigators to prioritise or remove suspects. There are many competing approaches in forensic linguistic analysis; however, there is limited empirical research available on emerging methods.

This research investigates Statement Analysis, a recent development in linguistic analysis that has practical applications in criminal investigations. Real-world statements of individuals convicted of or found to be not guilty of their involvement in missing persons cases were used in the analyses. In addition, Behaviour Sequence Analysis was used to map the progressions of language in the suspects' statements.

Results indicated differences between the guilty and innocent individuals based on their language choices, for example, guilty suspects in missing [alive] cases were found more likely to use passive language and vague words because of high levels of cognitive load associated with the several types of guilty knowledge suspects in missing persons cases possess. Of particular interest is the use of untruthful words in the innocent suspects’ statements in missing [murdered] cases. While typically seen in deceptive statements, untruthful words in innocent statements may result because of false acquittals.

This research provides some support for Statement Analysis as a suitable approach to analysing linguistic statements in missing persons cases.

When investigating missing persons cases, witness and suspect statements are often the only available evidence to investigators. As such, forensic linguistics can be useful to police when seeking information from individuals during investigative interviews. The presumption of innocence must be maintained in an investigation, and therefore this study aims to use a method focused on veracity detection, rather than the majority of studies using deception detection approaches.

The current research uses criteria-based content analysis (CBCA), a method that has been applied to a variety of criminal cases. Real-world statements of individuals convicted or found innocent of their involvement in missing persons cases were used in the analyses. Additionally, behaviour sequence analysis (BSA) was used to map language patterns within individuals’ statements.

Results indicated that two individual markers occurred at a high frequency across all four groups (the guilty and innocent statements of both case types); however, differences were noted in the sequences based on an individual’s ability to provide experiential details.

The current research contributes to the growing literature that aims to test CBCA in adult samples across crimes that do not pertain to sexual abuse, in addition to aiding researchers and practitioners to understand better the linguistic differences that occur in missing persons cases.

To the best of the authors’ knowledge, this type of research, using CBCA to assist with missing person's cases with a temporal method (BSA), has never before been tested. BSA has previously been used in forensic linguistics, and shown support for the method. The current research builds on this in terms of missing persons cases.

In this paper we present a roadmap for the elicitation of business rules based on different stakeholders' perspectives, in order to facilitate the processes of structuring, organizing and expressing business tactic and policy in a way that it is close to the business milieu and stakeholders' viewpoints.

This paper has derived from a combined research practice. Initially, the development of a roadmap for understanding different stakeholders' perspectives and for identifying their views on business tactics and policies was based on well‐grounded work on enterprise goal modelling, combined with a theoretical study of business rule – related concepts. The outcome of this work was tested against a real business case dealing with the development of an electronic procurement system in the pre‐fabricated construction sector.

As a conclusion, the paper put forward a comprehensive methodological framework for dealing with rule‐intensive projects. The proposed roadmap can help IT practitioners in collecting and organizing business rule statements that apply within a particular organization, either towards the implementation of change on a business level, or in the context of specifying the (existing or future) functionality of supporting information systems (IS).

The rule roadmap presented here has been coupled with a modelling approach for expressing rules in a structured, consistent manner and for organizing them in a rule repository. Future work includes the extension of this approach to cover design and implementation as part of rule‐centric information systems engineering.

Therefore, the overall contribution of this work relates to the provision of guidance for identifying business policy and tactics at an intentional level (through the investigation of the rationale behind them) and for transforming relevant models to the operational level, where business rules are linked to business processes, information and systems.

Although the business rule concept has been examined from different points of view over the past years, the paper attempts to bridge the gap between approaches that see rules as extensions of business goals, other approaches that consider rules as limitations on the way business activities are performed, and finally, approaches according to which rules constrain the creation, modification and deletion of information entities.

The purpose of this paper is to analyze the usability of a remote learning system in its initial development phase, using a quantitative usability evaluation method through Markov models.

The paper opted for an exploratory study. The data of interest of the research correspond to the possible accesses of users in a learning system's pre‐project. The present research is intended to answer questions of the type “how”, evaluating the usability through Markov models and the interaction of the learning system's users.

The paper provides a study which allowed the generation of a probability matrix among states and actions, which was utilized in the evaluation of usability based on Markov models, where the usability criteria specified were analyzed. Markov models allow a series of measures of interest to be calculated and they have been successfully utilized in the evaluation of computing and communication systems.

This research aimed to investigate the utilization of Markov models in the evaluation of usability in a remote learning system in its pre‐project phase and to help in proposing improvement suggestions.

This research aims to aid product development managers to estimate the expected cost associated with the development of cost-intensive physical prototypes considering transitions associated with pertinent states of quality of the prototype and corresponding decision policies under the Markovian setting.

The authors evolve two types of optimization-based mathematical models under both deterministic and randomized policies. Under the deterministic policy, the product development managers take certain decisions such as “Do nothing,” “Overhaul,” or “Replace” corresponding to different quality states of prototype such as “Good as new,” “Functional with minor deterioration,” “Functional with major deterioration” and “Non-functional.” Under the randomized policy, the product development managers ascertain the probability distribution associated with these decisions corresponding to various states of quality. In both types of mathematical models, i.e. related to deterministic and randomized settings, minimization of the expected cost of the prototype remains the objective function.

Employing an illustrative case of the operator cabin from the construction equipment domain, the authors ascertain that randomized policy provides us with better decision interventions such that the expected cost of the prototype remains lower than that associated with the deterministic policy. The authors also ascertain the steady-state probabilities associated with a prototype remaining in a particular quality state. These findings have implications for product development budget, time to market, product quality, etc.

The authors’ work contributes toward the development of optimization-driven mathematical models that can encapsulate the nuances related to the uncertainty of transition of quality states of a prototype, decision policies at each quality state of the prototype while considering such facets for all constituent subsystems of the prototype. As opposed to a typical prescriptive study, their study captures the inherent uncertainties associated with states of quality in the context of prototype testing, etc.