An operational approach to object-oriented software development

The traditional waterfall software life cycle model has several weaknesses. One problem is that a working version of a system is unavailable until a late stage in the development; any omissions and mistakes in the specification undetected until that stage can be costly to maintain. The operational approach which emphasises the construction of executable specifications can help to remedy this problem. An operational specification may be exercised to generate the behaviours of the specified system, thereby serving as a prototype to facilitate early validation of the system's functional requirements. Recent ideas have centred on using an existing operational method such as JSD in the specification phase of object-oriented development. An explicit transformation phase following specification is necessary in this approach because differences in abstractions between the two domains need to be bridged. This research explores an alternative approach of developing an operational specification method specifically for object-oriented development. By incorporating object-oriented concepts in operational specifications, the specifications have the advantage of directly facilitating implementation in an object-oriented language without requiring further significant transformations. In addition, object-oriented concepts can help the developer manage the complexity of the problem domain specification, whilst providing the user with a specification that closely reflects the real world and so the specification and its execution can be readily understood and validated. A graphical notation has been developed for the specification method which can capture the dynamic properties of an object-oriented system. A tool has also been implemented comprising an editor to facilitate the input of specifications, and an interpreter which can execute the specifications and graphically animate the behaviours of the specified systems.

An investigation of managerial skills:Implications for personnel policy

This research explores the conceptual basis in adopting a skills approach to management development. The literature reveals a number of development approaches but only a limited appreciation of how the manager does his job i.e. of the skills that he needs. An investigation of managerial skills was conducted with 10 manager s mainly occupying middle and senior positions. The principal source of evidence was the manager's thoughts on what he did and how he did it, although the interviews were supplemented by formal and informal observation. There was also a dialectic value from discussions with other analysts/managers and empathy between analyst and practitioner also played a part. Each manager was invited to comment upon his own skills analysis as a check upon validity. The study supports the view that the manager similar to other skilled practitioners, is conceptually a model builder and operationally a navigator (Singleton 1978b) . The manager variously holds enactive, pictorial, symbolic and hybrid models that enable him to understand his world and act in it. The universal managerial function is decision making and the study presents a preliminary nomenclature in classifying decision processes or perceptual skills. Managerial skills are also reflected in interpersonal interaction where the hallmark is mutual construction and attribution and in 'self-management’ where the requirement is to cope with the inner rather than the outer world. Differences between the managers are most evident in perceptual skills, the more senior manager requiring increasing ability to process abstract information and take account of environmental uncertainty. He will also make greater use of 'off- line’ information. The practical purpose in studying managerial skills is to facilitate the improvement of managerial performance and the implications of the research for training, selection and appraisal are explored.

Extracting protein-protein interactions from MEDLINE using the hidden vector state model

A major challenge in text mining for biomedicine is automatically extracting protein-protein interactions from the vast amount of biomedical literature. We have constructed an information extraction system based on the Hidden Vector State (HVS) model for protein-protein interactions. The HVS model can be trained using only lightly annotated data whilst simultaneously retaining sufficient ability to capture the hierarchical structure. When applied in extracting protein-protein interactions, we found that it performed better than other established statistical methods and achieved 61.5% in F-score with balanced recall and precision values. Moreover, the statistical nature of the pure data-driven HVS model makes it intrinsically robust and it can be easily adapted to other domains.

Extracting interactions between proteins from the literature

During the last decade, biomedicine has witnessed a tremendous development. Large amounts of experimental and computational biomedical data have been generated along with new discoveries, which are accompanied by an exponential increase in the number of biomedical publications describing these discoveries. In the meantime, there has been a great interest with scientific communities in text mining tools to find knowledge such as protein-protein interactions, which is most relevant and useful for specific analysis tasks. This paper provides a outline of the various information extraction methods in biomedical domain, especially for discovery of protein-protein interactions. It surveys methodologies involved in plain texts analyzing and processing, categorizes current work in biomedical information extraction, and provides examples of these methods. Challenges in the field are also presented and possible solutions are discussed.

Joint sentiment/topic model for sentiment analysis

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

Semantic annotation for knowledge management:requirements and a survey of the state of the art

While much of a company's knowledge can be found in text repositories, current content management systems have limited capabilities for structuring and interpreting documents. In the emerging Semantic Web, search, interpretation and aggregation can be addressed by ontology-based semantic mark-up. In this paper, we examine semantic annotation, identify a number of requirements, and review the current generation of semantic annotation systems. This analysis shows that, while there is still some way to go before semantic annotation tools will be able to address fully all the knowledge management needs, research in the area is active and making good progress.

Strategic marketing and e-business

The dramatic growth in e-business is manifest in phenomena such as the surge in internet retailing, the boom in social media based marketing communications, and the centrality of e-commerce to many organizations’ core strategies. Despite this the precise implications of e-business for marketing strategy remain little-understood. In order to guide theory development and practice in the marketing strategy domain, it is of fundamental importance to take stock of the impact that e-business has had upon strategic marketing. Therefore, this chapter develops a conceptual framework in order to explicate the implications of e-business for strategic marketing theory and practice. We find that the impact of e-business on strategic marketing is far-reaching; influencing not only isolated departments, but the organization as a whole. Finally, we conclude that whilst organizations should be alert to the dynamic opportunities and threats posed by e-business, the guiding principle of value creation should not be forgotten.

Dynamic joint sentiment-topic model

Social media data are produced continuously by a large and uncontrolled number of users. The dynamic nature of such data requires the sentiment and topic analysis model to be also dynamically updated, capturing the most recent language use of sentiments and topics in text. We propose a dynamic Joint Sentiment-Topic model (dJST) which allows the detection and tracking of views of current and recurrent interests and shifts in topic and sentiment. Both topic and sentiment dynamics are captured by assuming that the current sentiment-topic-specific word distributions are generated according to the word distributions at previous epochs. We study three different ways of accounting for such dependency information: (1) Sliding window where the current sentiment-topic word distributions are dependent on the previous sentiment-topic-specific word distributions in the last S epochs; (2) skip model where history sentiment topic word distributions are considered by skipping some epochs in between; and (3) multiscale model where previous long- and shorttimescale distributions are taken into consideration. We derive efficient online inference procedures to sequentially update the model with newly arrived data and show the effectiveness of our proposed model on the Mozilla add-on reviews crawled between 2007 and 2011. © 2013 ACM 2157-6904/2013/12-ART5 $ 15.00.

A Stochastic Approach for Finding of Semantically Related Words

2000 Mathematics Subject Classification: 62P99, 68T50

Business statistics using EXCEL and SPSS

'Takes the challenging and makes it understandable. The book contains useful advice on the application of statistics to a variety of contexts and shows how statistics can be used by managers in their work.' - Dr Terri Byers, Assistant Professor, University Of New Brunswick, Canada A book about introductory quantitative analysis for business students designed to be read by first- and second-year students on a business studies degree course that assumes little or no background in mathematics or statistics. Based on extensive knowledge and experience in how people learn and in particular how people learn mathematics, the authors show both how and why quantitative analysis is useful in the context of business and management studies, encouraging readers to not only memorise the content but to apply learning to typical problems. Fully up-to-date with comprehensive coverage of IBM SPSS and Microsoft Excel software, the tailored examples illustrate how the programmes can be used, and include step-by-step figures and tables throughout. A range of ‘real world’ and fictional examples, including "The Ballad of Eddie the Easily Distracted" and "Esha's Story" help bring the study of statistics alive. A number of in-text boxouts can be found throughout the book aimed at readers at varying levels of study and understanding •Back to Basics for those struggling to understand, explain concepts in the most basic way possible - often relating to interesting or humorous examples •Above and Beyond for those racing ahead and who want to be introduced to more interesting or advanced concepts that are a little bit outside of what they may need to know •Think it over get students to stop, engage and reflect upon the different connections between topics A range of online resources including a set of data files and templates for the reader following in-text examples, downloadable worksheets and instructor materials, answers to in-text exercises and video content compliment the book.

The Mismanagement of Environmental Conflicts

During the Communist regime, companies' conflicts with the public were hidden. The public did not have the right to express their objection. Recent Hungarian law, however, supports people's right to influence decisions that have an impact on their lives, but attitudes change slowly. In this article, I show the typical methods of companies' mismanagement of environmental conflicts. The first part of the article concentrates on strategic issues, and the second one emphasizes mistakes in communication with local communities. There are signs that Hungarian companies have already started to learn their lesson, but they also need help to face the new situation of the post-Communist era. Conflict theory and conflict resolution techniques may help them to deal with communication problems and to reach win-win solutions. Although not unknown, facilitation is not a common technique in Hungary yet. This means that there is potential for its development.

The effect of reciprocal mapping on high-risk sixth-grade students' social studies achievement

Reading deficits in students in Grades 4 to 12 are evident in American schools. Informational text is particularly difficult for students. This quasi-experimental study (N=138) investigated sixth-grade students' achievement in social studies using the Reciprocal Mapping instructional routine, compared to sixth-grade students' achievement taught with a traditional approach. The Reciprocal Mapping instructional routine incorporated explicit instruction in text structure using graphic organizers. Students created their own graphic organizers and used them to write about social studies content. The comparison group used a traditional approach, students' reading the textbook and answering questions. Students for this study included sixth-graders in the seven sixth-grade classrooms in two public schools in a small, rural south Florida school district. A focus of this study was to determine the helpfulness of the intervention for at-risk readers. To determine students considered to be at-risk, the researcher used data from the reading portion of the Florida Comprehensive Assessment Test (FCAT), 2011-2012, that considers Level 1 and 2 as at-risk readers. The quasi-experimental study used a pretest-posttest control group design, with students assigned to treatment groups by class. Two teachers at the two rural sites were trained on the Reciprocal Mapping instructional routine and taught students in both the experimental and control groups for an equivalent amount of time over a 5-week period. Results of the 3 x 2 factorial ANCOVA found a significant positive difference favoring the experimental group's social studies achievement as compared to that of the comparison group as measured by the pre/post unit test from the social studies series (McGraw-Hill, 2013), when controlling for initial differences in students' reading FCAT scores. Interactions for high-risk struggling readers were investigated using the significance level p < .05. Due to no significant interaction the main effects of treatment were interpreted. The pretest was used as a covariate and the multivariate analysis was found to be significant. Therefore, analysis of covariance was run on each of the dependent variable as a follow-up. Reciprocal Mapping was found to be significant in posttest scores, independent of gender and level of risk, and while holding the pretest scores constant. Findings showed there was a significant difference in the performance of the high-risk reading students taught with the Reciprocal Mapping intervention who scored statistically better than students in the control group. Further study findings showed that teacher fidelity of implementation of the treatment had a statistically significant relationship in predicting posttest scores when controlling for pretest scores. Study results indicated that improving students' use of text structure through the Reciprocal Mapping instructional routine positively supported sixth-grade students' social studies achievement.