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Leveraging Web 2.0 in New Product Development: Lessons Learned from a Cross-company Study

The paper explores the application of Web 2.0 technologies to support product development efforts in a global, virtual and cross-functional setting. It analyses the dichotomy between the prevailing hierarchical structure of CAD/PLM/PDM systems and the principles of the Social Web under the light of the emerging product development trends. Further it introduces the concept of Engineering 2.0, intended as a more bottom up and lightweight knowledge sharing approach to support early stage design decisions within virtual and cross-functional product development teams. The lessons learned collected from a cross-company study highlight how to further developblogs, wikis, forums and tags for the benefit of new product development teams, highlighting opportunities, challenges and no-go areas.




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Modeling Quality Attributes with Aspect-Oriented Architectural Templates

The quality attributes of a software system are, to a large extent, determined by the decisions taken early in the development process. Best practices in software engineering recommend the identification of important quality attributes during the requirements elicitation process, and the specification of software architectures to satisfy these requirements. Over the years the software engineering community has studied the relationship between quality attributes and the use of particular architectural styles and patterns. In this paper we study the relationship between quality attributes and Aspect-Oriented Software Architectures - which apply the principles of Aspect-Oriented Software Development (AOSD) at the architectural level. AOSD focuses on identifying, modeling and composing crosscutting concerns - i.e. concerns that are tangled and/or scattered with other concerns of the application. In this paper we propose to use AO-ADL, an aspect-oriented architectural description language, to specify quality attributes by means of parameterizable, and thus reusable, architectural patterns. We particularly focus on quality attributes that: (1) have major implications on software functionality, requiring the incorporation of explicit functionality at the architectural level; (2) are complex enough as to be modeled by a set of related concerns and the compositions among them, and (3) crosscut domain specific functionality and are related to more than one component in the architecture. We illustrate our approach for usability, a critical quality attribute that satisfies the previous constraints and that requires special attention at the requirements and the architecture design stages.




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QoS-based Approach for Dynamic Web Service Composition

Web Services have become a standard for integration of systems in distributed environments. By using a set of open interoperability standards, they allow computer-computer interaction, regardless the programming languages and operating systems used. The Semantic Web Services, by its turn, make use of ontologies to describe their functionality in a more structural manner, allowing computers to reason about the information required and provided by them. Such a description also allows dynamic composition of several Web Services, when only one is not able to provide the desired functionality. There are scenarios, however, in which only the functional correctness is not enough to fulfill the user requirements, and a minimum level of quality should be guaranteed by their providers. In this context, this work presents an approach for dynamic Web Service composition that takes into account the composition overall quality. The proposed approach relies on a heuristics to efficiently perform the composition. In order to show the feasibility of the proposed approach, a Web Service composition application prototype was developed and experimented with public test sets, along with another approach that does not consider quality in the composition process. The results have shown that the proposed approach in general finds compositions with more quality, within a reasonable processing time.




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An Aspect-Oriented Framework for Weaving Domain-Specific Concerns into Component-Based Systems

Software components are used in various application domains, and many component models and frameworks have been proposed to fulfill domain-specific requirements. The general trend followed by these approaches is to provide ad-hoc models and tools for capturing these requirements and for implementing their support within dedicated runtime platforms, limited to features of the targeted domain. The challenge is then to propose more flexible solutions, where components reuse is domain agnostic. In this article, we present a framework supporting compositional construction and development of applications that must meet various extra-functional/domain-specific requirements. The key points of our contribution are: i) We target development of component-oriented applications where extra-functional requirements are expressed as annotations on the units of composition in the application architecture. ii) These annotations are implemented as open and extensible component-based containers, achieving full separation of functional and extra-functional concerns. iii) Finally, the full machinery is implemented using the Aspect-Oriented Programming paradigm. We validate our approach with two case studies: the first is related to real-time and embedded applications, while the




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Context-Aware Composition and Adaptation based on Model Transformation

Using pre-existing software components (COTS) to develop software systems requires the composition and adaptation of the component interfaces to solve mismatch problems. These mismatches may appear at different interoperability levels (signature, behavioural, quality of service and semantic). In this article, we define an approach which supports composition and adaptation of software components based on model transformation by taking into account the four levels. Signature and behavioural levels are addressed by means of transition systems. Context-awareness and semanticbased techniques are used to tackle quality of service and semantic, respectively, but also both consider the signature level. We have implemented and validated our proposal for the design and application of realistic and complex systems. Here, we illustrate the need to support the variability of the adaptation process in a context-aware pervasive system through a real-world case study, where software components are implemented using Windows Workflow Foundation (WF). We apply our model transformation process to extract transition systems (CA-STS specifications) from WF components. These CA-STSs are used to tackle the composition and adaptation. Then, we generate a CASTS adaptor specification, which is transformed into its corresponding WF adaptor component with the purpose of interacting with all the WF components of the system, thereby avoiding mismatch problems.




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Software Components, Architectures and Reuse




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Descriptional Complexity of Ambiguity in Symmetric Difference NFAs

We investigate ambiguity for symmetric difference nondeterministic finite automata. We show the existence of unambiguous, finitely ambiguous, polynomially ambiguous and exponentially ambiguous symmetric difference nondeterministic finite automata. We show that, for each of these classes, there is a family of n-state nondeterministic finite automata such that the smallest equivalent deterministic finite automata have O(2n) states.




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Improving Security Levels of IEEE802.16e Authentication by Involving Diffie-Hellman PKDS

Recently, IEEE 802.16 Worldwide Interoperability for Microwave Access (WiMAX for short) has provided us with low-cost, high efficiency and high bandwidth network services. However, as with the WiFi, the radio wave transmission also makes the WiMAX face the wireless transmission security problem. To solve this problem, the IEEE802.16Std during its development stage defines the Privacy Key Management (PKM for short) authentication process which offers a one-way authentication. However, using a one-way authentication, an SS may connect to a fake BS. Mutual authentication, like that developed for PKMv2, can avoid this problem. Therefore, in this paper, we propose an authentication key management approach, called Diffie-Hellman-PKDS-based authentication method (DiHam for short), which employs a secret door asymmetric one-way function, Public Key Distribution System (PKDS for short), to improve current security level of facility authentication between WiMAX's BS and SS. We further integrate the PKMv1 and the DiHam into a system, called PKM-DiHam (P-DiHam for short), in which the PKMv1 acts as the authentication process, and the DiHam is responsible for key management and delivery. By transmitting securely protected and well-defined parameters for SS and BS, the two stations can mutually authenticate each other. Messages including those conveying user data and authentication parameters can be then more securely delivered.




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Least Slack Time Rate first: an Efficient Scheduling Algorithm for Pervasive Computing Environment

Real-time systems like pervasive computing have to complete executing a task within the predetermined time while ensuring that the execution results are logically correct. Such systems require intelligent scheduling methods that can adequately promptly distribute the given tasks to a processor(s). In this paper, we propose LSTR (Least Slack Time Rate first), a new and simple scheduling algorithm, for a multi-processor environment, and demonstrate its efficient performance through various tests.




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A Ranking Tool Exploiting Semantic Descriptions for the Comparison of EQF-based Qualifications

Nowadays, one of the main issues discussed at the Community level is represented by the mobility of students and workers across Europe. During the last years, in order to deal with the above picture, several initiatives have been carried out: one of them is the definition of the European Qualification Framework (EQF), a common architecture for the description of qualifications. At the same time, several research activities were established with the aim of finding how semantic technologies could be exploited for qualifications comparison in the field of human resources acquisition. In this paper, the EQF specifications are taken into account and they are applied in a practical scenario to develop a ranking algorithm for the comparison of qualifications expressed in terms of knowledge, skill and competence concepts, potentially aimed at supporting European employers during the recruiting phase.




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Ontology-based Competency Management: the Case Study of the Mihajlo Pupin Institute

Semantic-based technologies have been steadily increasing their relevance in recent years in both the research world and business world. Considering this, the present article discusses the process of design and implementation of a competency management system in information and communication technologies domain utilizing the latest Semantic Web tools and technologies including D2RQ server, TopBraid Composer, OWL 2, SPARQL, SPARQL Rules and common human resources related public vocabularies. In particular, the paper discusses the process of building individual and enterprise competence models in a form of ontology database, as well as different ways of meaningful search and retrieval of expertise data on the Semantic Web. The ontological knowledge base aims at storing the extracted and integrated competences from structured, as well as unstructured sources. By using the illustrative case study of deployment of such a system in the Human Resources sector at the Mihajlo Pupin Institute, this paper shows an example of new approaches to data integration and information management. The proposed approach extends the functionalities of existing enterprise information systems and offers possibilities for development of future Internet services. This allows organizations to express their core competences and talents in a standardized, machine processable and understandable format, and hence, facilitates their integration in the European Research Area and beyond.




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A Comparison of Different Retrieval Strategies Working on Medical Free Texts

Patient information in health care systems mostly consists of textual data, and free text in particular makes up a significant amount of it. Information retrieval systems that concentrate on these text types have to deal with the different challenges these medical free texts pose to achieve an acceptable performance. This paper describes the evaluation of four different types of information retrieval strategies: keyword search, search performed by a medical domain expert, a semantic based information retrieval tool, and a purely statistical information retrieval method. The different methods are evaluated and compared with respect to its appliance in medical health care systems.




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Cloud Computing




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Strasbourg et la récurrence complotiste des Réseaux Sociaux.

Comme on devait s’y attendre, l’attentat de Strasbourg n’a pas manqué, s’il en était encore besoin, de charrier son lot de rumeurs complotistes. Un regard rapide sur les réseaux sociaux de toute nature suffit à se rendre compte de ce triste phénomène....




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Avec l'Arizona, Donald Trump a désormais remporté la totalité des sept États clés

Avec l'Arizona, Donald Trump a désormais remporté la totalité des sept États clés




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Netanyahu s’est entretenu 3 fois avec Trump depuis sa réélection à propos de la "menace iranienne"

Netanyahu s’est entretenu 3 fois avec Trump depuis sa réélection à propos de la "menace iranienne"




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Trump et Poutine auraient discuté de la guerre en Ukraine, "une pure fiction", selon le Kremlin

Trump et Poutine auraient discuté de la guerre en Ukraine, "une pure fiction", selon le Kremlin




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Trump confie l'immigration à Tom Homan, le "tsar des frontières"

Trump confie l'immigration à Tom Homan, le "tsar des frontières"




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Gaza : au moins trois morts après une frappe israélienne sur le camp de réfugiés de Nouseirat

Gaza : au moins trois morts après une frappe israélienne sur le camp de réfugiés de Nouseirat




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Trump va nommer les "faucons" Rubio et Waltz à la tête de la politique étrangère (rapports)

Trump va nommer les "faucons" Rubio et Waltz à la tête de la politique étrangère (rapports)




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Donald Trump confie à Elon Musk et Vivek Ramaswamy "l'efficacité gouvernementale"

Donald Trump confie à Elon Musk et Vivek Ramaswamy "l'efficacité gouvernementale"









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What is walking pneumonia? As cases rise in Canada, the symptoms to look out for - The Globe and Mail

  1. What is walking pneumonia? As cases rise in Canada, the symptoms to look out for  The Globe and Mail
  2. Walking pneumonia on the rise in Kingston, but treatable  The Kingston Whig-Standard
  3. What parents need to know about walking pneumonia in kids  FingerLakes1.com
  4. Pediatric pneumonia is surging in Central Ohio  MSN
  5. Walking Pneumonia is spiking right now. How do you know you have it?  CBS 6 News Richmond WTVR










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Trump says Elon Musk, Vivek Ramaswamy will lead the Department of Government Efficiency - The Globe and Mail

  1. Trump says Elon Musk, Vivek Ramaswamy will lead the Department of Government Efficiency  The Globe and Mail
  2. Why is Elon Musk becoming Donald Trump's efficiency adviser?  BBC.com
  3. Elon Musk and Vivek Ramaswamy will lead new 'Department of Government Efficiency' in Trump administration  CTV News
  4. George Conway: Musk, Ramaswamy to lead ‘nonexistent department’  The Hill





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Retour d’expérience sur une campagne de boycott d’entreprises au Maroc

 

Le 20 avril 2018, un appel au boycott a été lancé sur les réseaux sociaux marocains contre trois entreprises leaders dans leurs secteurs d’activités. L’eau minérale de Sidi Ali, le lait de Centrale Danone et les stations de services Afriquia (pétrole) ont été victimes d’une guerre d’information, justifiée selon les internautes par des prix de vente élevés. Les appels au boycott ont été relayés par les internautes Marocains via des groupes et des pages ...




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Même dans le chrono, Thomas résiste au temps

Tom Dumoulin.
Dans la vingtième étape, un contre-la-montre sélectif entre Saint-Pée-sur-Nivelle et Espelette (31 km), victoire du Néerlandais Tom Dumoulin, une toute petite seconde devant Chris Froome, qui récupère sa marche sur le podium. Troisième de l’étape, le Gallois Geraint Thomas remporte son premier Tour de France.

Sur la route du Tour, envoyé spécial.
D’abord il plut sur les routes du pays basque, ensuite l’asphalte se réchauffa avant de sécher sommairement comme pour favoriser les ...




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Journᅵes parlementaires, campus rᅵgionaux : La Rᅵpublique en marche va dᅵpenser prᅵs d'un million d'euros pour sa rentrᅵe

C'est la rentrᅵe politique. Et qui dit rentrᅵe, dit universitᅵ d'ᅵtᅵ. Cette annᅵe, la Rᅵpublique en marche a vu les choses en grand en organisant ᅵ la fois des journᅵes...




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Pᅵle emploi a organisᅵ un sᅵminaire au Stade de France pour 300 000 euros

Le retour de Politique.net mᅵritait bien de commencer par une fᅵte. Selon Le Canard enchaᅵnᅵ, "le 17 juin, Pᅵle emploi Il-de-France s'est offert un sᅵminaire managers au Stade de France pour communier...




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Exploring the impact of TPACK on Education 5.0 during the times of COVID-19: a case of Zimbabwean universities




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The Impact of Physics Open Educational Resources (OER) on the Professional Development of Bhutanese Secondary School Physics Teachers




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Feature-aware task offloading and scheduling mechanism in vehicle edge computing environment

With the rapid development and application of driverless technology, the number and location of vehicles, the channel and bandwidth of wireless network are time-varying, which leads to the increase of offloading delay and energy consumption of existing algorithms. To solve this problem, the vehicle terminal task offloading decision problem is modelled as a Markov decision process, and a task offloading algorithm based on DDQN is proposed. In order to guide agents to quickly select optimal strategies, this paper proposes an offloading mechanism based on task feature. In order to solve the problem that the processing delay of some edge server tasks exceeds the upper limit of their delay, a task scheduling mechanism based on buffer delay is proposed. Simulation results show that the proposed method has greater performance advantages in reducing delay and energy consumption compared with existing algorithms.




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Enabling smart city technologies: impact of smart city-ICTs on e-Govt. services and society welfare using UTAUT model

Smart cities research is growing all over the world seeking to understand the effect of smart cities from different angles, domains and countries. The aim of this study is to analyse how the smart city ICTs (e.g., big data analytics, AI, IoT, cloud computing, smart grids, wireless communication, intelligent transportation system, smart building, e-governance, smart health, smart education and cyber security) are related to government. services and society welfare from the perspective of China. This research confirmed a positive correlation of smart city ICTs to e-Govt. Services (e-GS). On the other hand, the research showed a positive influence of smart city ICTs on society's welfare. These findings about smart cities and ICTs inform us how the thought paradigm to smart technologies can cause the improvement of e-GS through economic development, job creation and social welfare. The study offers different applications of the theoretical perspectives and the management perspective which are significant to building a society during recent technologised era.




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Machine learning and deep learning techniques for detecting and mitigating cyber threats in IoT-enabled smart grids: a comprehensive review

The confluence of the internet of things (IoT) with smart grids has ushered in a paradigm shift in energy management, promising unparalleled efficiency, economic robustness and unwavering reliability. However, this integrative evolution has concurrently amplified the grid's susceptibility to cyber intrusions, casting shadows on its foundational security and structural integrity. Machine learning (ML) and deep learning (DL) emerge as beacons in this landscape, offering robust methodologies to navigate the intricate cybersecurity labyrinth of IoT-infused smart grids. While ML excels at sifting through voluminous data to identify and classify looming threats, DL delves deeper, crafting sophisticated models equipped to counteract avant-garde cyber offensives. Both of these techniques are united in their objective of leveraging intricate data patterns to provide real-time, actionable security intelligence. Yet, despite the revolutionary potential of ML and DL, the battle against the ceaselessly morphing cyber threat landscape is relentless. The pursuit of an impervious smart grid continues to be a collective odyssey. In this review, we embark on a scholarly exploration of ML and DL's indispensable contributions to enhancing cybersecurity in IoT-centric smart grids. We meticulously dissect predominant cyber threats, critically assess extant security paradigms, and spotlight research frontiers yearning for deeper inquiry and innovation.




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International Journal of Information and Computer Security




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Impacts of social media usage on consumers' engagement in social commerce: the roles of trust and cultural distance

The prevalence of social media transforms e-business into social commerce and facilitates consumers' engagement in cross-cultural social commerce. However, social commerce operations encounter unpredictable challenges in cross-cultural business environment. It is vital to further investigate how contextual elements affect consumers' trust and their engagement when they are exposed to the complexity of cross-cultural business environment. The stimuli-organism-response paradigm is employed to examine how the two dimensions of social media usage influence consumers' engagement in cross-cultural social commerce. The current study surveyed 2,058 samples from 135 countries, and the regression analysis results illustrate the mechanism whereby informational and socialising usage of social media positively influences consumers' engagement in social commerce through consumers' trust toward social commerce websites. Additionally, the associations between two aspects of social media usage and consumers' trust towards social commerce are negatively moderated by cultural distance. Both theoretical and practical implications are also discussed.




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Learning the usage intention of robo-advisors in fin-tech services: implications for customer education

Drawing on the MOA framework, this study establishes a research model that explains the usage intention of robo-advisors. In the model, three predictors that consist of technology relative advantage, technology herding, and technology familiarity influence usage intention of robo-advisors directly and indirectly via the partial mediation of trust. At the same time, the effects of the three predictors on trust are hypothetically moderated by learning goal orientation and perceived performance risk respectively. Statistical analyses are provided using the data of working professionals from the insurance industry in Taiwan. Based on its empirical findings, this study discusses important theoretical and practical implications.




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A constant temperature control system for indoor environments in buildings using internet of things

The performance of a building's internal environment, which includes the air temperature, lighting and acoustics, is what determines the quality of the environment inside the building. We present a thermal model for achieving thermal comfort in buildings that makes use of a multimodal analytic framework as a solution to this challenge. In this study, a multimodal combination is used to evaluate several temperature and humidity sensors as well as an area image. Additionally, a CNN and LSTM combination is used to process the image and sensor data. The results show that heating setback and interior set point temperatures, as well as mechanical ventilation based on real people's presence and CO<SUB align=right>2 levels, are all consistently reduced when ICT-driven intelligent solutions are used. The CNN-LSTM model has a goodness of fit that is 0.7258 on average, which is much higher than both the CNN (0.5291) and LSTM (0.5949) models.




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Multi-agent Q-learning algorithm-based relay and jammer selection for physical layer security improvement

Physical Layer Security (PLS) and relay technology have emerged as viable methods for enhancing the security of wireless networks. Relay technology adoption enhances the extent of coverage and enhances dependability. Moreover, it can improve the PLS. Choosing relay and jammer nodes from the group of intermediate nodes effectively mitigates the presence of powerful eavesdroppers. Current methods for Joint Relay and Jammer Selection (JRJS) address the optimisation problem of achieving near-optimal secrecy. However, most of these techniques are not scalable for large networks due to their computational cost. Secrecy will decrease if eavesdroppers are aware of the relay and jammer intermediary nodes because beamforming can be used to counter the jammer. Consequently, this study introduces a multi-agent Q-learning-based PLS-enhanced secured joint relay and jammer in dual-hop wireless cooperative networks, considering the existence of several eavesdroppers. The performance of the suggested algorithm is evaluated in comparison to the current algorithms for secure node selection. The simulation results verified the superiority of the proposed algorithm.




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International Journal of Wireless and Mobile Computing