As some of you already know, the TR?ICTIO Invoicing System is a simple invoicing platform focusing on freelance translators. I have been developing the system for about 12 months and after extensive personal testing and actual use in my business, as … Continue reading →

This paper proposes a new approach to water flow algorithm for the text line segmentation. Original method assumes hypothetical water flows under a few specified angles to the document image frame from left to right and vice versa. As a result, unwetted image frames are extracted. These areas are of major importance for text line segmentation. Method modifications mean extension values of water flow angle and unwetted image frames function enlargement. Results are encouraging due to text line segmentation improvement which is the most challenging process stage in document image processing.

This work describes a methodology that supports the design and implementation of software modules, which represent the individual and collaborative three-dimensional interaction process phases. The presented methodology integrates three modeling approaches: Petri Nets, a collaborative manipulation model based on the combination of single user interaction techniques taxonomy, and object-oriented programming concepts. The combination of these elements allows for the description of interaction tasks, the sequence of interaction processes being controlled by Petri Nets with the codes generated automatically. By the integration of these approaches, the present work addresses not only the entire development cycle of both individual and collaborative three-dimensional interaction, but also the reuse of developed interaction blocks in new virtual environment projects.

Collaborative Filtering(CF) is a well-known technique in recommender systems. CF exploits relationships between users and recommends items to the active user according to the ratings of his/her neighbors. CF suffers from the data sparsity problem, where users only rate a small set of items. That makes the computation of similarity between users imprecise and consequently reduces the accuracy of CF algorithms. In this article, we propose a clustering approach based on the social information of users to derive the recommendations. We study the application of this approach in two application scenarios: academic venue recommendation based on collaboration information and trust-based recommendation. Using the data from DBLP digital library and Epinion, the evaluation shows that our clustering technique based CF performs better than traditional CF algorithms.

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.

Feature modeling is an approach to represent commonalities and variabilities among products of a product line. Context-aware applications use context information to provide relevant services and information for their users. One of the challenges to build a context-aware product line is to develop mechanisms to incorporate context information and adaptation knowledge in a feature model. This paper presents UbiFEX, an approach to support feature analysis for context-aware software product lines, which incorporates a modeling notation and a mechanism to verify the consistency of product configuration regarding context variations. Moreover, an experimental study was performed as a preliminary evaluation, and a prototype was developed to enable the application of the proposed approach.

Ontology evaluation is an integral and important part of the ontology development process. Errors in ontologies could be catastrophic for the information system based on those ontologies. As per our experiments, the existing ontology evaluation systems were unable to detect many errors (like, circulatory error in class and property hierarchy, common class and property in disjoint decomposition, redundancy of sub class and sub property, redundancy of disjoint relation and disjoint knowledge omission) as defined in the error taxonomy. We have formulated efficient algorithms for the evaluation of these and other errors as per the extended error taxonomy. These algorithms are implemented (named as OntEval) and the implementations are used to evaluate well-known ontologies including Gene Ontology (GO), WordNet Ontology and OntoSem. The ontologies are indexed using a variant of already proposed scheme Ontrel. A number of errors and warnings in these ontologies have been discovered using the OntEval. We have also reported the performance of our implementation, OntEval.

Des frappes de Tsahal ont fait plus de 50 morts au Liban et à Gaza, tirs de roquettes sur Israël

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

Au moins 22 personnes tuées dans des frappes au Liban et à Gaza, et le cessez-le-feu au point mort

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

The increased volume of accessible internet data creates an opportunity for researchers and practitioners to improve time series forecasting for many indicators. In our study, we assess the value of web traffic data in forecasting the number of short-term visitors travelling to Australia. We propose a feature-based model selection framework which combines random forest with feature ranking process to select the best performing model using limited and informative number of features extracted from web traffic data. The data was obtained for several tourist attraction and tourism information websites that could be visited by potential tourists to find out more about their destinations. The results of random forest models were evaluated over 3- and 12-month forecasting horizon. Features from web traffic data appears in the final model for short term forecasting. Further, the model with additional data performs better on unseen data post the COVID19 pandemic. Our study shows that web traffic data adds value to tourism forecasting and can assist tourist destination site managers and decision makers in forming timely decisions to prepare for changes in tourism demand.

This research explores vehicular ad hoc networks (VANETs) and their extensive applications, such as enhancing traffic efficiency, infotainment, and passenger safety. Despite significant study, widespread deployment of VANETs has been hindered by security and privacy concerns. Challenges in implementation, including scalability, flexibility, poor connection, and insufficient intelligence, have further complicated VANETs. This study proposes leveraging cloud computing to address these challenges, marking a paradigm shift. Cloud computing, recognised for its cost-efficiency and virtualisation, is integrated with VANETs. The paper details the nomenclature, architecture, models, services, applications, and challenges of VANET-based cloud computing. Three architectures for VANET clouds - vehicular clouds (VCs), vehicles utilising clouds (VuCs), and hybrid vehicular clouds (HVCs) - are discussed in detail. The research provides an overview, delves into related work, and explores VANET cloud computing's architectural frameworks, models, and cloud services. It concludes with insights into future work and a comprehensive conclusion.

1. Apparition en plein concert ! Cameron Hallyday se montre pour son père David Hallyday, sa tante Laura Smet conquise  Purepeople
2. Duo virtuel avec Johnny, Sylvie Vartan, Laura et Santa invitées… David Hallyday a frappé fort à Paris  Le Parisien
3. David Hallyday et Laura Smet, le frère et la sœur réunis sur scène après 7 ans  Paris Match
4. Rendez-vous culture : show, sang pour sang Hallyday !  TF1+
5. « C’est si émouvant» : David Hallyday rejoint sur scène par sa mère Sylvie Vartan et sa sœur Laura Smet  La Voix du Nord

1. Fnac et Darty frappent fort et dégainent 7 offres dignes du Black Friday  Clubic
2. Amazon: le 'Black Friday' débutera le jeudi 21 novembre  Boursorama
3. C’est officiel : on connaît enfin les dates du Black Friday et la Black Friday Week Amazon  Capital.fr
4. Déjà disponible, ce top 7 des offres du Black Friday Fnac est absolument inratable  Ouest-France
5. Tout savoir sur la Black Friday Week Amazon 2024  La Provence

1. Sauvetage de Casino: les syndicats retirent leur plainte en appel après avoir conclu un accord avec la direction  Le Figaro
2. Plan de sauvetage de Casino : accord avec la direction, les représentants du personnel retirent leur plainte en appel  France 3 Régions
3. Sauvetage de Casino : un accord social enfin trouvé pour clore le dossier  Capital.fr
4. Casino: les représentants du personnel retirent leur appel formulé à l'encontre du plan de sauvegarde  Investir
5. Plan de sauvegarde de Casino : la direction trouve un accord avec le personnel  La Tribune.fr

1. First Oppo Reno13 image appears online - GSMArena.com news  GSMArena.com
2. First look at Oppo Reno 13 shows an iPhone-like design  Notebookcheck.net
3. Oppo Reno13 series to arrive on November 25 - GSMArena.com news  GSMArena.com

1. Stop Using Chrome On Your iPhone, Warns Apple—Millions Of Users Must Now Decide  Forbes
2. 4 new Chrome improvements for iOS  The Keyword
3. Chrome on your iPhone can search using pictures and words at the same time  The Verge
4. Google Rolls Out Four New Chrome Features for iOS  iPhone in Canada
5. Chrome 131 for iOS adding new Google Drive, Maps integrations  9to5Google

By Hasan Basri Cifci[1] In the world of 2014, the Commission of Facebook/WhatsApp merger case[2] concluded that integration and interoperation of Facebook and WhatsApp were unfeasible. However, Facebook integrated its three subsidiaries (WhatsApp, Instagram, and Facebook) under its brand in

Inquiet par le coronavirus ? Vous pouvez appeler le numï¿œro vert 0 800 130 000. C'est Emmanuel Macron lui-mï¿œme qui en a fait la promotion dans un tweet en avril 2020, en plein confinement. Ce 0 800 fait partie de la longue liste...

Image forgery detection techniques refer to the process of detecting manipulated or altered images, which can be used for various purposes, including malicious intent or misinformation. Image forgery detection is a crucial task in digital image forensics, where researchers have developed various techniques to detect image forgery. These techniques can be broadly categorised into active, passive, machine learning-based and hybrid. Active approaches involve embedding digital watermarks or signatures into the image during the creation process, which can later be used to detect any tampering. On the other hand, passive approaches rely on analysing the statistical properties of the image to detect any inconsistencies or irregularities that may indicate forgery. In this paper for the detection of scaling and cropping attack a deep learning method has been proposed using ResNet. The proposed method (Res-Net-Adam-Adam) is able to achieve highest amount of accuracy of 99.14% (0.9914) while detecting fake and real images.

Constrained programming is the concept used to select possible alternatives from an incredibly diverse range of candidates. This paper proposes an AI-assisted Backtracking Scheme (AI-BS) by integrating the generic backtracking algorithm with Artificial Intelligence (AI). The detailed study observes that the extreme dual ray associated with the infeasible linear program can be automatically extracted from minimum unfeasible sets. Constraints are used in artificial intelligence to list all possible values for a group of variables in a given universe. To put it another way, a solution is a way of assigning a value to each variable that these values satisfy all constraints. Furthermore, this helps the study reach a decreased search area for smart backtracking without paying high costs. The evaluation results exhibit that the IB-BC algorithm-based smart electricity schedule controller performs better electricity bill during the scheduled periods than comparison approaches such as binary backtracking and binary particle swarm optimiser.

To improve the effectiveness of online training for music education, it was investigated how to improve the pulse-coupled neural network in image processing for spectral image segmentation. The study proposes a two-scale descent method to achieve oblique spectral correction. Subsequently, a convolutional neural network was optimised using a two-channel feature fusion recognition network for music theory notation recognition. The results showed that this image segmentation method had the highest accuracy, close to 98%, and the accuracy of spectral tilt correction was also as high as 98.4%, which provided good image pre-processing results. When combined with the improved convolutional neural network, the average accuracy of music theory symbol recognition was about 97% and the highest score of music majors was improved by 16 points. This shows that the method can effectively improve the teaching effect of online training in music education and has certain practical value.

5G mobile communication systems are an in-depth fusion of multi-radio access technologies characterised with frequent handover between cells. Handover management is a particularly challenging issue for 5G networks development. In this article, a novel optimised handover framework is proposed to find the optimal network to connect with a good quality of service in accordance with the user's preferences. This framework is based on an extension of IEEE 802.21 standard with new components and new service primitives for seamless handover. Moreover, the proposed vertical handover process is based on an adaptive heuristic model aimed at achieving an optimised network during the decision-making stage. Simulation results demonstrate that, compared to other existing works, the proposed framework is capable of selecting the best network candidate accurately based on the quality-of-service requirements of the application, network conditions, mobile terminal conditions and user preferences. It significantly reduces the handover delay, handover blocking probability and packet loss rate.

This article studies the application of artificial intelligence technology in natural resource planning and management. This article first introduces the background of NR and AI intelligent technology, then conducts academic research and summary on NR planning management and AI intelligent technology. Then, an algorithm model based on multi-objective intelligent planning algorithm is established. Finally, simulation experiments are conducted, and experiments summary and discussion are provided. The experimental results show that the average efficiency value of the four stages of NR planning and management before use is 5.25, and the average efficiency value of the four stages of NR planning and management after use is 7. The difference in the average efficiency value before and after use is 1.75. It can be seen that the use of AI intelligent technology can effectively improve the efficiency of natural resource planning and management.

Intelligent digital virtual technology has become an indispensable part of modern construction, but there are also some problems in its practical application. Therefore, it is necessary to strengthen the design of intelligent building image processing systems from many aspects. Starting from image digital processing methods, this paper studies the digital twin virtual design scene construction method and related algorithms, converts the original image into a colour digital image through a greyscale algorithm, and then combines morphological knowledge and feature point extraction methods to complete the construction of a three-dimensional virtual environment. Finally, through the comparison of traditional image processing effects with smart building images based on digital twins and BIM technology, the results show that the optimised image processing results have higher clarity, sharper contrast, and a sensitivity increased by 5.84%, presenting better visual effects and solving the risk of misjudgement caused by inaccurate image recognition.

The study investigated the influence of ebullient supervision on employee commitment in a Ghanaian public university through the mediating role of employee engagement. The simple random sampling technique was used to draw 302 administrative staff of the university to respond to the self-administered questionnaire on the constructs. Furthermore, the partial least square structural equation technique was deployed to test the research hypotheses in the study. The results showed that ebullient supervision had a significant positive relationship with employee commitment and employee engagement. The findings further revealed that employee engagement positively correlated with employee commitment. Finally, the study's findings established that employee engagement partially mediated the link between ebullient supervision and employee commitment. The study emphasised that various supervisors in a university's administration should create an environment that favours fun where subordinates can form ties with one another.

A number of studies have applied social network analysis (SNA) to show that the patterns of social interaction between software developers explain important organisational outcomes. However, these insights are based on a single network relation (i.e., uniplex social ties) between software developers and do not consider the multiple network relations (i.e., multiplex social ties) that truly exist among project members. This study reassesses the understanding of software developer networks and what it means for performance in software development settings. A systematic review of SNA studies between 1990 and 2020 across six digital libraries within the IS and management science domain was conducted. The central contributions of this paper are an in-depth overview of SNA studies to date and the establishment of a research agenda to advance our knowledge of the concept of multiplexity on how a multiplex perspective can contribute to a software developer's coordination of tasks and performance advantages.

As mobile devices become prevalent, there is always a need for apps.  How hard is it to develop an app especially a cross-platform app? The paper shares an experience in a project involved the development of a student services web app that can be run on cross-platform mobile devices.  The paper first describes the background of the project, the clients, and the proposed solution.  Then, it focuses on the step-by-step development processes and provides the illustration of written codes and techniques used.  The goal is for readers to gain an understanding on how to develop a mobile-friendly web app.  The paper concludes with teaching implications and offers thoughts for further development.  

Since the advent of the iPhone and rise of mobile technologies, educational apps represent one of the fastest growing markets, and both the mobile technology and educational app markets are predicted to continue experiencing growth into the foreseeable future. The irony, however, is that even with a booming market for educational apps, very little research regarding the quality of them has been conducted. Though some instruments have been developed to evaluate apps geared towards student learning, no such instrument has been created for teacher resource apps, which are designed to assist teachers in completing common tasks (e.g., taking attendance, communicating with parents, monitoring student learning and behavior, etc.). Moreover, when teachers visit the App Store or Google Play to learn about apps, the only ratings provided to them are generic, five-point evaluations, which do not provide qualifiers that explain why an app earned three, two, or five points. To address that gap, previously conducted research related to designing instructional technologies coupled with best practices for supporting teachers were first identified. That information was then used to construct a comprehensive rubric for assessing teacher re-source apps. In this article, a discussion that explains the need for such a rubric is offered before describing the process used to create it. The article then presents the rubric and discusses its different components and potential limitations and concludes with suggestions for future research based on the rubric.

Aim/Purpose: Compared student academic performance on specific course requirements in a C# programming course across three instructional approaches: traditional, online, and flipped. Background: Addressed the following research question: When compared to the online and traditional instructional approaches, does the flipped instructional approach have a greater impact on student academic performance with specific course requirements in a C# programming course? Methodology: Quantitative research design conducted over eight 16-week semesters among a total of 271 participants who were undergraduate students en-rolled in a C# programming course. Data collected were grades earned from specific course requirements and were analyzed with the nonparametric Kruskal Wallis H-Test using IBM SPSS Statistics, Version 23. Contribution: Provides empirical findings related to the impact that different instructional approaches have on student academic performance in a C# programming course. Also describes implications and recommendations for instructors of programming courses regarding instructional approaches that facilitate active learning, student engagement, and self-regulation. Findings: Resulted in four statistically significant findings, indicating that the online and flipped instructional approaches had a greater impact on student academic performance than the traditional approach. Recommendations for Practitioners: Implement instructional approaches such as online, flipped, or blended which foster active learning, student engagement, and self-regulation to increase student academic performance. Recommendation for Researchers: Build upon this study and others similar to it to include factors such as gender, age, ethnicity, and previous academic history. Impact on Society: Acknowledge the growing influence of technology on society as a whole. Higher education coursework and programs are evolving to encompass more digitally-based learning contexts, thus compelling faculty to utilize instructional approaches beyond the traditional, lecture-based approach. Future Research: Increase the number of participants in the flipped instructional approach to see if it has a greater impact on student academic performance. Include factors beyond student academic performance to include gender, age, ethnicity, and previous academic history.

Aim/Purpose: To examine the early perceptions (acceptability) and usability of EASEL (Education through Application-Supported Experiential Learning), a mobile platform that delivers reflection prompts and content before, during, and after an experiential learning activity. Background: Experiential learning is an active learning approach in which students learn by doing and by reflecting on the experience. This approach to teaching is often used in disciplines such as humanities, business, and medicine. Reflection before, during, and after an experience allows the student to analyze what they learn and why it is important, which is vital in helping them to understand the relevance of the experience. A just-in-time tool (EASEL) was needed to facilitate this. Methodology: To inform the development of a mobile application that facilitates real-time guided reflection and to determine the relevant feature set, we conducted a needs analysis with both students and faculty members. Data collected during this stage of the evaluation helped guide the creation of a prototype. The user experience of the prototype and interface interactions were evaluated during the usability phase of the evaluation study. Contribution: Both the needs analysis and usability assessment provided justification for continued development of EASEL as well as insight that guides current development. Findings: The interaction design of EASEL is understandable and usable. Both students and teachers value an application that facilitates real-time guided reflection. Recommendations for Practitioners: The use of a system such as EASEL can leverage time and location-based services to support students in field experiences. This technology aligns with evidence that guided reflection provides opportunities for metacognition. Recommendation for Researchers: Iterative prototyping, testing, and refinement can lead to a deliberate and effective app development process. Impact on Society: The EASEL platform leverages inherent functionality of mobile devices, such as GPS and persistent network connectivity, to adapt reflection tasks based on lo-cation or time. Students using EASEL will engage in guided reflection, which leads to metacognition and can help instructors scaffold learning Future Research: We will continue to advance the application through iterative testing and development. When ready, the application will be vetted in larger studies across varied disciplines and contexts.

Aim/Purpose: As smartphones proliferate, many different platforms begin to emerge. The challenge to developers as well as IS educators and students is how to learn the skills to design and develop apps to run on cross-platforms. Background: For developers, the purpose of this paper is to describe an alternative to the complex native app development. For IS educators and students, the paper provides a feasible way to learn and develop fully functional mobile apps without technical burdens. Methodology: The methods used in the development of browser-based apps is prototyping. Our proposed approach is browser-based, supports cross-platforms, uses open-source standards, and takes advantage of “write-once-and-run-anywhere” (WORA) concept. Contribution: The paper illustrates the application of the browser-based approach to create a series of browser apps without high learning curve. Findings: The results show the potentials for using browser app approach to teach as well as to create new apps. Recommendations for Practitioners : Our proposed browser app development approach and example would be useful to mobile app developers/IS educators and non-technical students because the source code as well as documentations in this project are available for downloading. Future Research: For further work, we discuss the use of hybrid development framework to enhance browser apps.

Aim/Purpose: This study was aimed at enhancing students’ learning of software engineering methods. A collaboration between the Computer Science, Business Management, and Product Design programs was formed to work on actual projects with real clients. This interdisciplinary form of collaboration simulates the realities of a diverse Software Engineering team. Background: A collaborative approach implemented through projects has been the established pedagogy for introducing the Software Engineering course to undergraduate Computer Science students. The collaboration, however, is limited to collaboration among Computer Science students and their clients. This case study explored an enhancement to the collaborative approach to project development by integrating other related disciplines into the project development framework; hence, the Interdisciplinary Approach. Methodology: This study adopted the case method approach. An interdisciplinary service innovation activity was proposed to invite other disciplines in the learning process of the computer science students. The agile methodology Scrum was used as the software development approach during project development. Survey data were collected from the students to establish (a) their perception of the interdisciplinary approach to project development; (b) the factors that influenced success or failure of their team to deliver the project; and (c) the perceived skills or knowledge that they acquired from the interdisciplinary approach. Analysis of data followed a mixed method approach. Contribution: The study improved the current pedagogy for Software Engineering education by integrating other related disciplines into the software project development framework. Findings: Data collected showed that the students generally accepted the interdisciplinary approach to project development. Factors such as project relevance, teamwork, time and schedule, and administration support, among others, affect team performance towards project completion. In the case of the Computer Science students, results show that students have learned skills during the experience that, as literature reveal, can only be acquired or mastered in their future profession as software engineers. Recommendations for Practitioners: The active collaboration of the industry with the University and the involvement of the other related courses in teaching software engineering methods are critical to the development of the students, not only in learning the methodology but also as a working professional. Recommendation for Researchers: It is interesting to know and eventually understand the interactions between interdisciplinary team members in the conduct of Software Engineering practices while working on their projects. More specifically, what creative tensions arise and how do the interdisciplinary teams handle the discourse? Impact on Society: This study bridges the gap between how Software Engineering is taught in the university and how Software Engineering teams work in real life. Future Research: Future research is targeted at refining and elaborating the elements of the interdisciplinary framework presented in this paper towards an integrated course module for Software Engineering education.

Aim/Purpose: In this study, the researchers investigated whether the out-of-class learning approach could help the students to attain any valuable learning outcomes for cybersecurity learning and could enhance the perceived value of cybersecurity education among the students. Background: Cybersecurity learning poses challenges for its students to learn a complicated subject matter and the students may be intimidated by the challenging courses in cybersecurity programs. Therefore, it is essential for the faculty members to devise some mechanisms to promote cybersecurity learning to increase its student retention. The mechanism suggested by this study was the out-of-class learning approach. Methodology: The researchers in this study employed a content analysis and adopted a semiotic method to analyze qualitative data. The researchers also conducted crosstabulation analyses using chi-square tests to detect the significant differences in the emerging learning outcomes from the two different out-of-class learning activities investigated in this study. Contribution: This study addressed the difficulty of cybersecurity education and proposed a viable mechanism to promote the student learning in such a complicated subject matter. Findings: For cybersecurity education, the out-of-class learning approach is a viable pedagogical mechanism that could lead the students to several learning outcomes, including connecting them to the real-life scenarios related to the cybersecurity profession, guiding them to their career choices and development, stimulating their intellectual growth, creating their justification of learning, and raising their cybersecurity awareness. Recommendations for Practitioners: The instructors of any cybersecurity programs should incorporate some out-of-class learning activities into the courses in their programs, especially the introductory-level courses. Additionally, it is important to coordinate the out-of-class learning activities with the in-class lessons to enable the students to justify what they have learned in their classrooms and motivate them to learn more. Recommendation for Researchers: Researchers could look beyond in-class learning and laboratory learning to investigate the impacts of out-of-class learning activities on cybersecurity education to help the students to attain better learning outcomes. Impact on Society: By promoting cybersecurity education, universities and colleges could attain a higher retention rate of the students in their cybersecurity programs. The higher retention rate of the students in cybersecurity programs would help to ease the critical shortage of cybersecurity talent. Future Research: Future research could explore the impacts of other out-of-class learning activities on cybersecurity learning; for example: job shadowing, attending cybersecurity conferences, internship, developing cybersecurity systems or tools for actual customers, working on cybersecurity research with faculty members. Additionally, future studies could investigate the effects of the out-of-class learning approach on promoting other academic programs that are characterized by intensely complex and technical nature, similar to cybersecurity programs.