Enabling the evolution of J2EE applications through reverse engineering and quality assurance

Enterprise Applications are complex software systems that manipulate much persistent data and interact with the user through a vast and complex user interface. In particular applications written for the Java 2 Platform, Enterprise Edition (J2EE) are composed using various technologies such as Enterprise Java Beans (EJB) or Java Server Pages (JSP) that in turn rely on languages other than Java, such as XML or SQL. In this heterogeneous context applying existing reverse engineering and quality assurance techniques developed for object-oriented systems is not enough. Because those techniques have been created to measure quality or provide information about one aspect of J2EE applications, they cannot properly measure the quality of the entire system. We intend to devise techniques and metrics to measure quality in J2EE applications considering all their aspects and to aid their evolution. Using software visualization we also intend to inspect to structure of J2EE applications and all other aspects that can be investigate through this technique. In order to do that we also need to create a unified meta-model including all elements composing a J2EE application.

NodePM: A Remote Monitoring Alert System for Energy Consumption Using Probabilistic Techniques

In this paper, we propose an intelligent method, named the Novelty Detection Power Meter (NodePM), to detect novelties in electronic equipment monitored by a smart grid. Considering the entropy of each device monitored, which is calculated based on a Markov chain model, the proposed method identifies novelties through a machine learning algorithm. To this end, the NodePM is integrated into a platform for the remote monitoring of energy consumption, which consists of a wireless sensors network (WSN). It thus should be stressed that the experiments were conducted in real environments different from many related works, which are evaluated in simulated environments. In this sense, the results show that the NodePM reduces by 13.7% the power consumption of the equipment we monitored. In addition, the NodePM provides better efficiency to detect novelties when compared to an approach from the literature, surpassing it in different scenarios in all evaluations that were carried out.

Software Engineering for Self-Adaptive Systems: A Second Research Roadmap

The goal of this roadmap paper is to summarize the state-of-the-art and identify research challenges when developing, deploying and managing self-adaptive software systems. Instead of dealing with a wide range of topics associated with the field, we focus on four essential topics of self-adaptation: design space for self-adaptive solutions, software engineering processes for self-adaptive systems, from centralized to decentralized control, and practical run-time verification & validation for self-adaptive systems. For each topic, we present an overview, suggest future directions, and focus on selected challenges. This paper complements and extends a previous roadmap on software engineering for self-adaptive systems published in 2009 covering a different set of topics, and reflecting in part on the previous paper. This roadmap is one of the many results of the Dagstuhl Seminar 10431 on Software Engineering for Self-Adaptive Systems, which took place in October 2010.

Geo-Locating the Knowledge Transfer in StackOverflow

By analyzing the transactions in Stack Overflow we can get a glimpse of the way in which the different geographical regions in the world contribute to the knowledge market represented by the website. In this paper we aggregate the knowledge transfer from the level of the users to the level of geographical regions and learn that Europe and North America are the principal and virtually equal contributors; Asia comes as a distant third, mainly represented by India; and Oceania contributes less than Asia but more than South America and Africa together.

An OMNeT++ Framework to Evaluate Video Transmission in Mobile Wireless Multimedia Sensor Networks

The development and evaluation of new algorithms and protocols for Wireless Multimedia Sensor Networks (WMSNs) are usually supported by means of a discrete event network simulator, where OMNeT++ is one of the most important ones. However, experiments involving multimedia transmission, video flows with different characteristics, genres, group of pictures lengths, and coding techniques must be evaluated based also on Quality of Experience (QoE) metrics to reflect the user's perception. Such experiments require the evaluation of video-related information, i.e., frame type, received/lost, delay, jitter, decoding errors, as well as inter and intra-frame dependency of received/distorted videos. However, existing OMNeT++ frameworks for WMSNs do not support video transmissions with QoE-awareness, neither a large set of mobility traces to enable evaluations under different multimedia/mobile situations. In this paper, we propose a Mobile MultiMedia Wireless Sensor Network OMNeT++ framework (M3WSN) to support transmission, control and evaluation of real video sequences in mobile WMSNs.

Terrorists Among Us: Effects of a Suspect's Group Membership, Terrorist Past, and Knowledge on Lay Persons' Interrogation Severity Recommendations

Support among US citizens for severe interrogation has been recognized as drawing upon utilitarian as well as on retributive motivation (Carlsmith & Sood, 2009). Two studies were conducted to expand on these findings in a Swiss sample. In Study 1, participants rated the severity of different interrogation techniques, which were scaled to provide an alternative measure of interrogation severity. In Study 2, retributive motivation was manipulated by varying the terrorist past of a male suspect, and utilitarian motivation was manipulated by varying the probability that the suspect could provide valuable information. Additionally, we manipulated the suspect’s group membership. The results of the vignette study suggest that the number and severity of recommended interrogation techniques is mainly influenced by whether the suspect might provide valuable information. Whether the suspect had a terrorist past was an additional influence that, however, was primarily attributable to the suspect’s group membership: If the suspect belonged to the ingroup, participants’ harsher interrogation recommendations were affected by that person’s past, whereas recommendations were not significantly influenced by a terrorist past if the suspect was an outgroup member.

Fuzzy Web Knowledge Aggregation, Representation, and Reasoning for Online Privacy and Reputation Management

A social Semantic Web empowers its users to have access to collective Web knowledge in a simple manner, and for that reason, controlling online privacy and reputation becomes increasingly important, and must be taken seriously. This chapter presents Fuzzy Cognitive Maps (FCM) as a vehicle for Web knowledge aggregation, representation, and reasoning. With this in mind, a conceptual framework for Web knowledge aggregation, representation, and reasoning is introduced along with a use case, in which the importance of investigative searching for online privacy and reputation is highlighted. Thereby it is demonstrated how a user can establish a positive online presence.

Emergency stabilization of the pelvic ring: Clinical comparison between three different techniques

Background: Emergency devices for pelvic ring stabilization include circumferential sheets, pelvic binders, and c-clamps. Our knowledge of the outcome of these techniques is currently based on limited information. Methods: Using the dataset of the German Pelvic Trauma Registry, demographic and injury-associated characteristics as well as the outcome of pelvic fracture patients after sheet, binder, and c-clamp treatment was compared. Outcome parameters included transfusion requirement of packed red blood cells, length of hospital stay, mortality, and incidence of lethal pelvic bleeding. Results: Two hundred seven of 6137 (3.4%) patients documented in the German Pelvic Trauma Registry between April 30th 2004 and January 19th 2012 were treated by sheets, binders, or c-clamps. In most cases, c-clamps (69%) were used, followed by sheets (16%), and binders (15%). The median age was significantly lower in patients treated with binders than in patients treated with sheets or c-clamps (26 vs. 47 vs. 42 years, p = 0.01). Sheet wrapping was associated with a significantly higher incidence of lethal pelvic bleeding compared to binder or c-clamp stabilization (23% vs. 4% vs. 8%). No significant differences between the study groups were found in sex, fracture type, blood haemoglobin concentration, arterial blood pressure, Injury Severity Score, the incidence of additional pelvic packing and arterial embolization, need of red blood cell transfusion, length of hospitalisation, and mortality. Conclusions: The data suggest that emergency stabilization of the pelvic ring by binders and c-clamps is associated with a lower incidence of lethal pelvic bleeding compared to sheet wrapping.

Combining Bottom-up and Top-down Generation of Interactive Knowledge Maps for Enterprise Search

Our research project develops an intranet search engine with concept- browsing functionality, where the user is able to navigate the conceptual level in an interactive, automatically generated knowledge map. This knowledge map visualizes tacit, implicit knowledge, extracted from the intranet, as a network of semantic concepts. Inductive and deductive methods are combined; a text ana- lytics engine extracts knowledge structures from data inductively, and the en- terprise ontology provides a backbone structure to the process deductively. In addition to performing conventional keyword search, the user can browse the semantic network of concepts and associations to find documents and data rec- ords. Also, the user can expand and edit the knowledge network directly. As a vision, we propose a knowledge-management system that provides concept- browsing, based on a knowledge warehouse layer on top of a heterogeneous knowledge base with various systems interfaces. Such a concept browser will empower knowledge workers to interact with knowledge structures.

Shaping the PSF to nearly top-hat profile: CHEOPS laboratory results

Spreading the PSF over a quite large amount of pixels is an increasingly used observing technique in order to reach extremely precise photometry, such as in the case of exoplanets searching and characterization via transits observations. A PSF top-hat profile helps to minimize the errors contribution due to the uncertainty on the knowledge of the detector flat field. This work has been carried out during the recent design study in the framework of the ESA small mission CHEOPS. Because of lack of perfect flat-fielding information, in the CHEOPS optics it is required to spread the light of a source into a well defined angular area, in a manner as uniform as possible. Furthermore this should be accomplished still retaining the features of a true focal plane onto the detector. In this way, for instance, the angular displacement on the focal plane is fully retained and in case of several stars in a field these look as separated as their distance is larger than the spreading size. An obvious way is to apply a defocus, while the presence of an intermediate pupil plane in the Back End Optics makes attractive to introduce here an optical device that is able to spread the light in a well defined manner, still retaining the direction of the chief ray hitting it. This can be accomplished through an holographic diffuser or through a lenslet array. Both techniques implement the concept of segmenting the pupil into several sub-zones where light is spread to a well defined angle. We present experimental results on how to deliver such PSF profile by mean of holographic diffuser and lenslet array. Both the devices are located in an intermediate pupil plane of a properly scaled laboratory setup mimicking the CHEOPS optical design configuration. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

Index Tracking Using Data-Mining Techniques and Mixed-Binary Linear Programming

Index tracking has become one of the most common strategies in asset management. The index-tracking problem consists of constructing a portfolio that replicates the future performance of an index by including only a subset of the index constituents in the portfolio. Finding the most representative subset is challenging when the number of stocks in the index is large. We introduce a new three-stage approach that at first identifies promising subsets by employing data-mining techniques, then determines the stock weights in the subsets using mixed-binary linear programming, and finally evaluates the subsets based on cross validation. The best subset is returned as the tracking portfolio. Our approach outperforms state-of-the-art methods in terms of out-of-sample performance and running times.

Systematic literature review of digital three-dimensional superimposition techniques to create virtual dental patients

PURPOSE Digital developments have led to the opportunity to compose simulated patient models based on three-dimensional (3D) skeletal, facial, and dental imaging. The aim of this systematic review is to provide an update on the current knowledge, to report on the technical progress in the field of 3D virtual patient science, and to identify further research needs to accomplish clinical translation. MATERIALS AND METHODS Searches were performed electronically (MEDLINE and OVID) and manually up to March 2014 for studies of 3D fusion imaging to create a virtual dental patient. Inclusion criteria were limited to human studies reporting on the technical protocol for superimposition of at least two different 3D data sets and medical field of interest. RESULTS Of the 403 titles originally retrieved, 51 abstracts and, subsequently, 21 full texts were selected for review. Of the 21 full texts, 18 studies were included in the systematic review. Most of the investigations were designed as feasibility studies. Three different types of 3D data were identified for simulation: facial skeleton, extraoral soft tissue, and dentition. A total of 112 patients were investigated in the development of 3D virtual models. CONCLUSION Superimposition of data on the facial skeleton, soft tissue, and/or dentition is a feasible technique to create a virtual patient under static conditions. Three-dimensional image fusion is of interest and importance in all fields of dental medicine. Future research should focus on the real-time replication of a human head, including dynamic movements, capturing data in a single step.

Forecasting Intraday Stock Price Trends with Text Mining Techniques

In this paper, we describe NewsCATS (news categorization and trading system), a system implemented to predict stock price trends for the time immediately after the publication of press releases. NewsCATS consists mainly of three components. The first component retrieves relevant information from press releases through the application of text preprocessing techniques. The second component sorts the press releases into predefined categories. Finally, appropriate trading strategies are derived by the third component by means of the earlier categorization. The findings indicate that a categorization of press releases is able to provide additional information that can be used to forecast stock price trends, but that an adequate trading strategy is essential for the results of the categorization to be fully exploited.