Query: Identification of Design Elements for a Maturity Model for Interorganizational Integration: A Comparative Analysis

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Capability Maturity Model for Software <=SEP=> This paper provides an overview of the latest version of the Capability Maturity Model for Software, CMM v1.1. Based on over six years of experience with software process improvement and the contributions of hundreds of reviewers, CMM v1.1 describes the software engineering and management practices that characterize organizations as they mature their processes for developing and maintaining software. This paper stresses the need for a process maturity framework to prioritize improvement actions, describes the process maturity framework of five maturity levels and the associated structural components, and discusses future directions for the CMM.

The Levels of Conceptual Interoperability Model <=SEP=> Interoperability of systems is not a cookie-cutter-function. There are various levels of interoperability between two systems ranging from no interoperability to full interoperability. In the technical domain, various models for levels of interoperability already exist and are used successfully to determine the degree of interoperability between information technology systems. However, such models are not yet established in the domain of conceptual modeling. This paper introduces a general model dealing with various levels of conceptual interoperability that goes beyond the technical reference models for interoperable solutions. The model is intended to become a bridge between the conceptual design and the technical design for implementation, integration, or federation. It should also contribute to the standardization of V&V procedures as well as to the documentation of systems that are designed to be federated. It is furthermore a framework to determine in the early stages of the federation development process whether meaningful interoperability between systems is possible. To this end, the scope of the model goes beyond the implementation level of actual standards, which focus on the exchange of data using standardized formats and interfaces. Another practical application of the model is, that it enhances the only recently published DoD Net-Centric Data Strategy for the Global Information Grid (GIG) and is directly applicable to derive necessary metadata to reach the DoD Data Goal to “enable Data to be understandable.”

Electronic Data Interchange and Small Organizations: Adoption and Impact of Technology <=SEP=> Many EDI researchers and practitioners have recognized the importance of high penetration levels for the success of EDI. Unfortunately, such penetration is partly impeded by the resistance of small companies to become EDI capable. To investigate this issue, three major factors are identified that influence the EDI adoption practices of small firms. These factors are: organizational readiness (because of the low levels of IT sophistication and resource availability of small firms), external pressures to adopt (because of the weak market positions of small firms and the network nature of the technology), and perceived benefits (because of the limited impact that IT has on small firms due to under-utilization and lack of integration). By combining the anticipated effects of these factom, we developed a framework of EDI adoption by small businesses. The applicability of this framework is empirically demonstrated using the results of seven case studies. Finally, recommendations are made for the development of successful EDI partner expansion plans. These include the development of a long-term EDI partner expansion plan from the very beginning, the individual assessment of each partner’s EDI preparedness level, and the selection of appropriate influence tactics to expedite adoption by small partners. Specifically, it is suggested that EDI initiators pursue promotional efforts to improve partners’ perceptions of EDI benefits, provide financial and technological assistance to partners with low organizational readiness, and carefully select and enact influence strategies to reduce resistance.

The Modeling Process for Stage Models <=SEP=> The purpose of this paper is to present and test a modeling procedure because researchers have struggled for decades to develop stages-of-growth models that are both theoretically founded and empirically validated. This article presents the concept and hypothesis of stages, the history of stage models, and a procedure that may serve as a useful tool in modeling stages of growth. Based on previous research and lessons learned from case study experience of the government sector in Norway, a procedure for the stages of growth modeling process is suggested and demonstrated. The procedure is used for developing a stage model for e-government interoperability. This article provides new insight into issues and challenges faced when engaging in stages of growth research. The paper proposes a new approach to stages of growth modeling. The utility of the suggested procedure is to improve theory building and empirical validation. The contribution to academia is the modeling process that can be applied in future developments of stages of growth. The contribution to practice lies in the stage hypothesis of organizational development over time.

The Case Research Strategy in Studies of Information Systems <=SEP=> This article defines and discusses one of these qualitative methods--the case research strategy. Suggestions are provided for researchers who wish to undertake research employing this approach. Criteria for the evaluation of case research are established and several characteristics useful for categorizing the studies are identified. A sample of papers drawn from information systems journals is reviewed. The paper concludes with examples of research areas that are particularly wellsuited to investigation using the case research approach. ACM categories: H.O., J.O.

Does a Water Protocol Improve the Hydration and Health Status of Individuals with Thin Liquid Aspiration Following Stroke? A Randomized Controlled Trial <=SEP=> The benefit of water protocols for individuals with thin liquid aspiration remains controversial, with mixed findings from a small number of randomized controlled trials (RCTs). This study aimed to contribute to the evidence of the effectiveness of water protocols with a particular emphasis on health outcomes, especially hydration. An RCT was conducted with patients with known thin liquid aspiration post stroke randomized to receiving thickened liquids only or a water protocol. For the 14 participants in rehabilitation facilities whose data proceeded to analysis, there was no difference in the total amount of beverages consumed between the water protocol group (mean = 1103 ml per day, SD = 215 ml) and the thickened liquids only group (mean = 1103 ml, SD = 247 ml). Participants in the water protocol group drank on average 299 ml (SD 274) of water but offset this by drinking less of the thickened liquids. Their hydration improved over time compared with participants in the thickened liquids only group, but differences between groups were not significant. Twenty-one percent of the total sample was diagnosed with dehydration, and no participants in either group were diagnosed with pneumonia. There were significantly more diagnoses of urinary tract infection in the thickened liquids only group compared to the water protocol group (χ 2 = 5.091, p = 0.024), but no differences between groups with regard to diagnoses of dehydration (χ 2 = 0.884, p = 0.347) or constipation (χ 2 = 0.117, p = 0.733). The findings reinforce evidence about the relative safety of water protocols for patients in rehabilitation post stroke and provide impetus for future research into the potential benefits for hydration status and minimizing adverse health outcomes.

A comparative study between RadViz and Star Coordinates <=SEP=> RadViz and star coordinates are two of the most popular projection-based multivariate visualization techniques that arrange variables in radial layouts. Formally, the main difference between them consists of a nonlinear normalization step inherent in RadViz. In this paper we show that, although RadViz can be useful when analyzing sparse data, in general this design choice limits its applicability and introduces several drawbacks for exploratory data analysis. In particular, we observe that the normalization step introduces nonlinear distortions, can encumber outlier detection, prevents associating the plots with useful linear mappings, and impedes estimating original data attributes accurately. In addition, users have greater flexibility when choosing different layouts and views of the data in star coordinates. Therefore, we suggest that analysts and researchers should carefully consider whether RadViz's normalization step is beneficial regarding the data sets' characteristics and analysis tasks.

The Role of Chatbots in Formal Education <=SEP=> Chatbots appeared in large numbers at the beginning of the current decade. Interactive technology, often combined with artificial intelligence, has rapidly invaded and occupied the world of online chat. Chatbots are not just elements of virtual assistants, but are used by organizations and governments on websites, in applications, and instant messaging platforms to promote products, ideas or services. In this paper, the authors firstly present a theoretical and historical background, then discuss the issues of using chatbots as educational assistants, and finally describe the basic steps and challenges of programming a bot.

Health data integration with Secured Record Linkage: A practical solution for Bangladesh and other developing countries <=SEP=> Knowledge discovery from various health data repositories requires the incorporation of healthcare data from diversified sources. Maintaining record linkage during the integration of medical data is an important research issue. Researchers have given different solutions to this problem that are applicable for developed countries where electronic health record of patients are maintained with identifiers like social security number (SSN), universal patient identifier (UPI), health insurance number, etc. These solutions cannot be used correctly for record linkage of health data of developing countries because of missing data, ambiguity in patient identification, and high amount of noise in patient information. Also, identifiable health data in electronic health repositories may produce a significant risk to patient privacy and also make the health information systems security vulnerable to hackers. In this paper, we have analyzed the practical problems of collecting and integrating healthcare data in Bangladesh for developing national health data warehouse. We have proposed a privacy preserved secured record linkage architecture that can support constrained health data of developing countries such as Bangladesh. Our technique can anonymize identifiable private data of the patients while maintaining record linkage in integrated health repositories to facilitate knowledge discovery process. Experimental results show that our proposed method successfully linked records with acceptable accuracy for noisy data in the absence of any standard ID like SSN.

with Emphasis to the Computer and Internet <=SEP=> This article discusses the Roles of ICT in education. Information communication technologies (ICT) at present are influencing every aspect of human life. They are playing salient roles in work places, business, education, and entertainment. Moreover, many people recognize ICTs as catalysts for change; change in working conditions, handling and exchanging information, teaching methods, learning approaches, scientific research, and in accessing information. Therefore, this review article discusses the roles of ICTs, the promises, limitations and key challenges of integration to education systems. The review attempts in answering the following questions: (1) What are the benefits of ICTs in education? (2) What are the existing promises of ICT use in education systems of some developing countries? (3) What are the limitations and key challenges of ICTs integration to education systems? The review concludes that regardless of all the limitations characterizing it, ICT benefits education systems to provide quality education in alignment with constructivism, which is a contemporary paradigm of learning.

Linear feedback control : analysis and design with MATLAB <=SEP=> 

Adversarial Deep Structural Networks for Mammographic Mass Segmentation <=SEP=> Mass segmentation is an important task in mammogram analysis, providing effective morphological features and regions of interest (ROI) for mass detection and classification. Inspired by the success of using deep convolutional features for natural image analysis and conditional random fields (CRF) for structural learning, we propose an end-to-end network for mammographic mass segmentation. The network employs a fully convolutional network (FCN) to model a potential function, followed by a CRF to perform structured learning. Because the mass distribution varies greatly with pixel position, the FCN is combined with a position priori. Due to the small size of mammogram datasets, we use adversarial training to control over-fitting. Four models with different convolutional kernels are further fused to improve the segmentation results. Experimental results on two public datasets, INBreast and DDSM-BCRP, demonstrate that our end-to-end network achieves the state-of-the-art results. 1

Home, habits, and energy: examining domestic interactions and energy consumption <=SEP=> This paper presents findings from a qualitative study of people's everyday interactions with energy-consuming products and systems in the home. Initial results from a large online survey are also considered. This research focuses not only on "conservation behavior" but importantly investigates interactions with technology that may be characterized as "normal consumption" or "over-consumption." A novel vocabulary for analyzing and designing energy-conserving interactions is proposed based on our findings, including: cutting, trimming, switching, upgrading, and shifting. Using the proposed vocabulary, and informed by theoretical developments from various literatures, this paper demonstrates ways in which everyday interactions with technology in the home are performed without conscious consideration of energy consumption but rather are unconscious, habitual, and irrational. Implications for the design of energy-conserving interactions with technology and broader challenges for HCI research are proposed.

A new vector evaluated PBIL algorithm for reinsurance analytics <=SEP=> The purpose of this paper is to evaluate the performance of a new multiobjective algorithm called Vector Evaluated Population Based Incremental Learning (VEPBIL). The new algorithm was applied in solving a real world application named Reinsurance Contract Optimization (RCO), which is a multiobjective problem consisting of maximizing two conflicting functions: expected return and risk. The VEPBIL was tested on two instances of the problem composed by 7 and 15 layers of real anonymized data. In order to evaluate the algorithm, metrics such as hyper volume, number of solutions and coverage were used. A comparisons against Vector Evaluated Differential evolution (VEDE) is also carried out. The comparison has shown that VEPBIL can dominate about 70% and 50% of solutions from VEDE using 7 and 15 layers respectively, whereas VEDE dominates about 10% and 30% of solutions in the way around.

A service orchestration architecture for Fog-enabled infrastructures <=SEP=> The development of Fog Computing technology is crucial to address the challenges to come with the mass adoption of Internet Of Things technology, where the generation of data tends to grow at an unprecedented pace. The technology brings computing power to the surrounds of devices, to offer local processing, filtering, storage and analysis of data and control over actuators. Orchestration is a requirement of Fog Computing technology to deliver services, based on the composition of microservices. It must take into consideration the heterogeneity of the IoT environment and device's capabilities and constraints. This heterogeneity requires a different approach for orchestration, be it regarding infrastructure management, node selection and/or service placement. Orchestrations shall be manually or automatically started through event triggers. Also, the Orchestrator must be flexible enough to work in a centralized or distributed fashion. Orchestration is still a hot topic and can be seen in different areas, especially in the Service Oriented Architectures, hardware virtualization, in the Cloud, and in Network Virtualization Function. However, the architecture of these solutions is not enough to handle Fog Requirements, specially Fog's heterogeneity, and dynamics. In this paper, we propose an architecture for Orchestration for the Fog Computing environment. We developed a prototype to prof some concepts. We discuss in this paper the implementation, and the tools chose, and their roles. We end the paper with a discussion on performance indicators and future direction on the evaluation of non-functional aspects of the Architecture.

Design of a new counter-balancing stackable mechanism <=SEP=> This paper describes design and application of a novel counter-balancing stackable parallel mechanism. The stackable mechanism is designed by combining a five-bar and a couple of parallelograms. This design allows a compact design and wide workspace as compared to prior parallel type counter-balancing mechanisms. A linear geometry of this mechanism guarantees static balancing in the whole workspace. This mechanism was successfully applied to otologic.

A Language Modeling Approach to Predicting Reading Difficulty <=SEP=> We demonstrate a new research approach to the problem of predicting the reading difficulty of a text passage, by recasting readability in terms of statistical language modeling. We derive a measure based on an extension of multinomial naïve Bayes classification that combines multiple language models to estimate the most likely grade level for a given passage. The resulting classifier is not specific to any particular subject and can be trained with relatively little labeled data. We perform predictions for individual Web pages in English and compare our performance to widely-used semantic variables from traditional readability measures. We show that with minimal changes, the classifier may be retrained for use with French Web documents. For both English and French, the classifier maintains consistently good correlation with labeled grade level (0.63 to 0.79) across all test sets. Some traditional semantic variables such as type-token ratio gave the best performance on commercial calibrated test passages, while our language modeling approach gave better accuracy for Web documents and very short passages (less than 10 words).

Adopting a Digital Business Operating System <=SEP=> The role of software in society and in industry in particular continues to grow exponentially. Most companies either have or are in the process of adoption continuous deployment of their software at products in the field and collect data concerning the performance of their systems. The continuous, fast feedback loops that companies now have available allow for a fundamentally different way of organizing. In fact, based on our work with dozens of companies, we have come to the conclusion that companies are moving towards a new, digital operating system. In this paper, we first present the key elements of the digital operating system and then discuss some of the challenges companies experience during the transformation.

Preliminary Guidelines for Empirical Research in Software Engineering <=SEP=> Empirical software engineering research needs research guidelines to improve the research and reporting processes. We propose a preliminary set of research guidelines aimed at stimulating discussion among software researchers. They are based on a review of research guidelines developed for medical researchers and on our own experience in doing and reviewing software engineering research. The guidelines are intended to assist researchers, reviewers and meta-analysts in designing, conducting and evaluating empirical studies. Editorial boards of software engineering journals may wish to use our recommendations as a basis for developing guidelines for reviewers and for framing policies for dealing with the design, data collection and analysis and reporting of empirical studies.

The Multidimensional Work Motivation Scale : Validation evidence in seven languages and nine countries <=SEP=> The Multidimensional Work Motivation Scale: Validation evidence in seven languages and nine countries Marylène Gagné, Jacques Forest, Maarten Vansteenkiste, Laurence Crevier-Braud, Anja Van den Broeck, Ann Kristin Aspeli, Jenny Bellerose, Charles Benabou, Emanuela Chemolli, Stefan Tomas Güntert, Hallgeir Halvari, Devani Laksmi Indiyastuti, Peter A. Johnson, Marianne Hauan Molstad, Mathias Naudin, Assane Ndao, Anja Hagen Olafsen, Patrice Roussel, Zheni Wang & Cathrine Westbye a School of Psychology, University of Western Australia, Perth, Australia b Department of Organization and Human Resource Management, UQAM School of Management Sciences, Université du Québec à Montréal, Montréal, Canada c Department of Developmental, Personality and Social Psychology, University of Gent, Gent, Belgium d Department of Psychology, Université du Québec à Montréal, Montréal, Canada e Department of Economy and Management, Hogeschool Universiteit Brussel, Brussels, and KU Leuven, Leuven, Belgium f Faculty of Economics and Social Science, Høgskolen i Buskerud og Vestfold, Kongsberg, Norway g Department of Psychology, Université de Montréal, Montréal, Canada h Psychology of Work in Organization and Society Research Group, Swiss Federal Institute of Technology, Zurich, Switzerland i Faculty of Economics and Business, Universitas Gadjah Mada, Yogyakarta, Indonesia j Institute of Work Psychology, University of Sheffield, Sheffield, United Kingdom k International Institute of Commerce and Development, Université Panthéon Assas — Paris II, Paris, France l Faculty of Economics and Management Sciences, Université Cheikh Anta DIOP, Dakkar, Sénégal m Department of Management and Human Resources, Université Toulouse 1, Toulouse, France Published online: 05 Feb 2014.

Repeatable texture sampling with interchangeable patches <=SEP=> Rendering textures in real-time environments is a key task in computer graphics. This paper presents a new parallel patch-based method which allows repeatable sampling without cache, and does not create visual repetitions. Interchangeable patches of arbitrary shape are prepared in a preprocessing step, such that patches may lie over the boundary of other patches in a repeating tile. This compresses the example texture into an infinite texture map with small memory requirements, suitable for GPU and ray-tracing applications. The quality of textures rendered with this method can be tuned in the offline preprocessing step, and they can then be rendered in times comparable to Wang tiles. Experimental results demonstrate combined benefits in speed, memory requirements, and quality of randomisation when compared to previous methods.

Social Sentiment Sensor in Twitter for Predicting Cyber-Attacks Using ℓ1 Regularization <=SEP=> In recent years, online social media information has been the subject of study in several data science fields due to its impact on users as a communication and expression channel. Data gathered from online platforms such as Twitter has the potential to facilitate research over social phenomena based on sentiment analysis, which usually employs Natural Language Processing and Machine Learning techniques to interpret sentimental tendencies related to users’ opinions and make predictions about real events. Cyber-attacks are not isolated from opinion subjectivity on online social networks. Various security attacks are performed by hacker activists motivated by reactions from polemic social events. In this paper, a methodology for tracking social data that can trigger cyber-attacks is developed. Our main contribution lies in the monthly prediction of tweets with content related to security attacks and the incidents detected based on ℓ 1 regularization.

The orbital angular momentum (OAM) multiplexing controversy: OAM as a subset of MIMO <=SEP=> Recently the orbital angular momentum (OAM) multiplexing scheme has been proposed to increase without limit the channel capacity between a transmitter and a receiver node communicating in line of sight. A controversy arose about the far-field effectiveness of this method and about it being or not a subset of MIMO communication schemes. In this contribution we first illustrate that OAM multiplexing can be completely understood as line of sight MIMO, and hence that the technique cannot bring additional advantages in far field communications. Secondly, we show that it is possible to build similar line of sight near field MIMO systems based on lenses with similar or better performance than their OAM counterparts.

Semantic Labeling: A Domain-Independent Approach <=SEP=> Semantic labeling is the process of mapping attributes in data sources to classes in an ontology and is a necessary step in heterogeneous data integration. Variations in data formats, attribute names and even ranges of values of data make this a very challenging task. In this paper, we present a novel domain-independent approach to automatic semantic labeling that uses machine learning techniques. Previous approaches use machine learning to learn a model that extracts features related to the data of a domain, which requires the model to be re-trained for every new domain. Our solution uses similarity metrics as features to compare against labeled domain data and learns a matching function to infer the correct semantic labels for data. Since our approach depends on the learned similarity metrics but not the data itself, it is domainindependent and only needs to be trained once to work effectively across multiple domains. In our evaluation, our approach achieves higher accuracy than other approaches, even when the learned models are trained on domains other than the test domain.

Internal Uniplanar Antenna for LTE/WWAN/GPS/GLONASS Applications in Tablet/Laptop Computers <=SEP=> This letter presents an internal uniplanar small size multiband antenna for tablet/laptop computer applications. The proposed antenna in addition to common LTE/WWAN channels covers commercial GPS/GLONASS frequency bands. The antenna is comprised of three sections: coupled-fed, shorting and low frequency spiral strips with the size of 50 ×11 ×0.8 mm2. With the aid of spiral strip, lower band operation at 900 MHz is achieved. Two operating frequency bands cover 870-965 and 1556-2480 MHz. In order to validate simulation results, a prototype of the proposed printed antenna is fabricated and tested. Good agreement between the simulation and measurement results is obtained.

A Novel Term Weighting Scheme Model <=SEP=> The use of textual data has increased exponentially in recent years due to the networking infrastructure such as Facebook, Twitter, Wikipedia, Blogs, and so one. Analysis of this massive textual data can help to automatically categorize and label new content. Before classification process, term weighting scheme is the crucial step for representing the documents in a way suitable for classification algorithms. In this paper, we are conducting a survey on the term weighting schemes and we propose an efficient term weighting scheme that provide a better classification accuracy than those obtained with the famous TF-IDF, the recent IF-IGM and the others term weighting schemes in the literature.

Cloud Data Patterns for Confidentiality <=SEP=> Cloud computing enables cost-effective, self-service, and elastic hosting of applications in the Cloud. Applications may be partially or completely moved to the Cloud. When hosting or moving the database layer to the Cloud, challenges such as avoidance of disclosure of critical data have to be faced. The main challenges are handling different levels of confidentiality and satisfying security and privacy requirements. We provide reusable solutions in the form of patterns.

Localization & Segmentation of Indian Car Number Plate system : A Projection based Multistage Approach <=SEP=> Enormous incorporation of information technologies into all aspects of recent life caused demand for processing vehicles as conceptual resources in information systems. This can be achieved by a human agent, or by special intelligent equipment which is be able to recognize vehicles by their number plates in a real environment and reflect it into conceptual resources. Because of this, various recognition techniques have been developed and number plate recognition systems are today used in various traffic and security applications, such as parking, access and border control, or tracking of stolen cars. This work deals with problematic from field of artificial intelligence, machine vision and neural networks in construction of an automatic car number plate Recognition (ACNPR). This techniques deals with enhanced shadow removal algorithm, along with horizontal and vertical projection method for number plate localization & segmentation..Work comparatively deals with methods achieving invariance of systems towards image illumination, translations and various light conditions during the capture.

The development of cross-language plagiarism detection tool utilising fuzzy swarm-based summarisation <=SEP=> This work presents the design and development of a web-based system that supports cross-language similarity analysis and plagiarism detection. A suspicious document dq in a language Lq is to be submitted to the system via a PHP web-based interface. The system will accept the text through either uploading or pasting it directly to a text-area. In order to lighten large texts and provide an ideal set of queries, we introduce the idea of query document reduction via summarisation. Our proposed system utilised a fuzzy swarm-based summarisation tool originally built in Java. Then, the summary is used as a query to find similar web resources in languages Lx other than Lq via a dictionary-based translation. Thereafter, a detailed similarity analysis across the languages Lq and Lx is performed and friendly report of results is produced. Such report has global similarity score on the whole document, which assures high flexibility of utilisation.

Revisiting Taxonomy Induction over Wikipedia <=SEP=> Guided by multiple heuristics, a unified taxonomy of entities and categories is distilled from the Wikipedia category network. A comprehensive evaluation, based on the analysis of upward generalization paths, demonstrates that the taxonomy supports generalizations which are more than twice as accurate as the state of the art. The taxonomy is available at http://headstaxonomy.com.