Why are Michigan nonprofits getting millions from taxpayers?

Party platform calls corporate welfare ‘unsustainable,’ but its policies are a different story

Jon Sanders discusses the feasibility of renewable energy in North Carolina

Imagine you have a large translation memory in Translator’s Workbench (Trados 2007) format with thousands of units and one day, when you try to open the TM, you get this error: “50050: Source segment is empty!” You cannot use the TM … Continue reading →

I’ve written quite a few articles in the last year or so on the use of AI in a localization setting, and in general as a tool to help you complete technical tasks you may not have been able to do without help until now.  Certainly I’ve been making extensive use of this technology to … Continue reading AI and Community

Many dilemmas of style arise when translating legislation into English. This post looks at the most common ones and solutions to them. By legislation I mean any laws or rules set down by a governing body, be that of a country, company or university. So everything from a criminal code to a health and safety […]

In this paper we introduce eXVisXML, a visual tool to explore documents annotated with the mark-up language XML, in order to easily perform over them tasks as knowledge extraction or document engineering.

eXVisXML was designed mainly for two kind of users. Those who want to analyze an annotated document to explore the information contained-for them a visual inspection tool can be of great help, and a slicing functionality can be an effective complement.

The other target group is composed by document engineers who might be interested in assessing the quality of the annotation created. This can be achieved through the measurements of some parameters that will allow to compare the elements and attributes of the DTD/Schema against those effectively used in the document instances.

Both functionalities and the way they were delineated and implemented will be discussed along the paper.

We describe the design of a mobile collaborative tool that helps teams managing critical computing infrastructures in organizations, a task that is usually designated Business Continuity Management. The design process started with a requirements definition phase based on interviews with professional teams. The elicited requirements highlight four main concerns: collaboration support, knowledge management, team performance, and situation awareness. Based on these concerns, we developed a data model and tool supporting the collaborative update of Situation Matrixes. The matrixes aim to provide an integrated view of the operational and contextual conditions that frame critical events and inform the operators' responses to events. The paper provides results from our preliminary experiments with Situation Matrixes.

This paper systematically discusses the security and privacy concerns for e-learning systems. A five-layer architecture of e-learning system is proposed. The security and privacy concerns are addressed respectively for five layers. This paper further examines the relationship among the security and privacy policy, the available security and privacy technology, and the degree of e-learning privacy and security. The digital identity attributes are introduced to e-learning portable devices to enhance the security and privacy of e-learning systems. This will provide significant contributions to the knowledge of e-learning security and privacy research communities and will generate more research interests.

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.

Visualization of search results is an essential step in the textual Information Retrieval (IR) process. Indeed, Information Retrieval Interfaces (IRIs) are used as a link between users and IR systems, a simple example being the ranked list proposed by common search engines. Due to the importance that takes visualization of search results, many interfaces have been proposed in the last decade (which can be textual, 2D or 3D IRIs). Two kinds of evaluation methods have been developed: (1) various evaluation methods of these interfaces were proposed aiming at validating ergonomic and cognitive aspects; (2) various evaluation methods were applied on information retrieval systems (IRS) aiming at measuring their effectiveness. However, as far as we know, these two kinds of evaluation methods are disjoint. Indeed, considering a given IRI associated to a given IRS, what happens if we associate this IRI to another IRS not having the same effectiveness. In this context, we propose an IRI evaluation framework aimed at evaluating the suitability of any IRI to different IR scenarios. First of all, we define the notion of IR scenario as a combination of features related to users, IR tasks and IR systems. We have implemented the framework through a specific evaluation platform that enables performing IRI evaluations and that helps end-users (e.g. IRS developers or IRI designers) in choosing the most suitable IRI for a specific IR scenario.

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.

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.

No Comment : Tyrannosaure Rex, un mannequin pas comme les autres

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

Faster flowing glaciers could help predict nearby volcanic activity  Phys.org

1. Song Jae-lim, South Korean Actor, Dies at 39  Variety
2. South Korean actor Song Jae-lim dead at 39  CNN
3. South Korean Actor Song Jae-rim Dies in His Seoul Apartment at 39  PEOPLE
4. South Korean actor Song Jae-lim found dead at 39  CTV News
5. Song Jae Rim death: South Korean actor's last Instagram post sparks concern among fans  The Economic Times

Running and longevity: Sub-four-minute milers increase their lifespan by up to 9 years  Genetic Literacy Project

1. UN chief warns COP29 summit to pay up or face climate-led disaster for humanity  The Globe and Mail
2. Climate Summit, in Early Days, Is Already on a ‘Knife Edge’  The New York Times
3. At COP29 summit, nations big and small get chance to bear witness to climate change  The Globe and Mail
4. Terence Corcoran: COP29 hit by political ‘dunkelflaute’  Financial Post
5. COP29: Albania PM goes off script to ask 'What on Earth are we doing?'  Euronews

To reduce the location cost of cross-border e-commerce logistics sites, this article proposes a multi-logistics site location method based on return uncertainty. Firstly, a site selection model is established with the objective function of minimising site construction costs, transportation costs, return costs, and operating costs, and the constraint conditions of return recovery costs and delayed pick-up time; Then, using the Monte Carlo method to simulate the number of returned items, and using an improved chicken swarm algorithm based on simulated annealing, the cross-border e-commerce multi-logistics site location model is solved to complete the location selection. Experimental results show that this method can effectively reduce the related costs of cross-border e-commerce multi-logistics site selection. After applying this method, the total cost of multi-logistics site selection is 19.4 million yuan, while the total cost of the five comparative methods exceeds 20 million yuan.

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.

The current study has outlined slow fashion (SF) research trends and created a future research agenda for this field. It is a thorough analysis of the literature on slow fashion. Numerous bibliometric features of slow fashion have been discussed in the paper. This study comprises 182 research articles from the Scopus database. The database was utilised for bibliometric analysis. To identify certain trends in the area of slow fashion, a bibliometric study is done. For bibliometric analysis, the study employed R-software (the Biblioshiny package). Here, VOSviewer software is used to determine the co-occurrence of authors, countries, sources, etc. The study has outlined the gap that still exists in the field of slow fashion. Here, the research outcome strengthens the domain of slow fashion for sustainable consumption. The study findings will be useful for policymakers, industry professionals, and researchers.

The emergence of digital technology and the increasing prevalence of smartphones have promoted innovations in payment options available in finance and consumption markets. Banks providing mobile payment must ensure the information security. Inadequate security control leads to information leakage, which severely affects user rights and service providers' reputations. This study uses control objectives for Information and Related Technologies 4.1 as the mobile payment security control framework to examine the emergent field of mobile payment. A literature review is performed to compile studies on the safety risk, regulations, and operations of mobile payments. In addition, the Delphi questionnaire is distributed among experts to determine the practical perspectives, supplement research gaps in the literature, and revise the prototype framework. According to the experts' opinions, 59 control objectives from the four domains of COBIT 4.1 are selected. The plan and organise, acquire and implement, deliver and support, and monitor and evaluate four domains comprised 2, 5, 10, and 2 control objectives that had mean importance scores of > 4.50. Thus, these are considered the most important objectives by the experts, respectively. The results of this study can serve as a reference for banks to construct secure frameworks in mobile payment services.

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.

Food quality is defined as a collection of properties that differentiate each unit and influences acceptability degree of food by users or consumers. Owing to the nature of food, food quality prediction is highly significant after specific periods of storage or before use by consumers. However, the accuracy is the major problem in the existing methods. Hence, this paper presents a BEFA_DRNN approach for accurate food quality prediction using dairy products. Firstly, input data is fed to data normalisation phase, which is performed by min-max normalisation. Thereafter, normalised data is given to feature fusion phase that is conducted employing DNN with Canberra distance. Then, fused data is subjected to data augmentation stage, which is carried out utilising oversampling technique. Finally, food quality prediction is done wherein milk is graded employing DRNN. The training of DRNN is executed by proposed BEFA that is a combination of BES and FA. Additionally, BEFA_DRNN obtained maximum accuracy, TPR and TNR values of 93.6%, 92.5% and 90.7%.

In order to further improve the public health assurance system and the infectious diseases early warning system to give play to their positive roles and enhance their collaborative capacity, this paper, based on the big and thick data analytics technology, designs a 'rolling-type' data synergy model. This model covers districts and counties, municipalities, provinces, and the country. It forms a data blockchain for the public health assurance system and enables high sharing of data from existing system platforms such as the infectious diseases early warning system, the hospital medical record management system, the public health data management system, and the health big and thick data management system. Additionally, it realises prevention, control and early warning by utilising data mining and synergy technologies, and ideally solves problems of traditional public health assurance system platforms such as excessive pressure on the 'central node', poor data tamper-proofing capacity, low transmission efficiency of big and thick data, bad timeliness of emergency response, and so on. The realisation of this technology can greatly improve the application and analytics of big and thick data and further enhance the public health assurance capacity.

In order to reduce the challenges encountered by learners and educators in engaging in educational activities, this paper classifies learners' roles in virtual learning communities, and explores the role of behaviour characteristics and their positions in collaborative knowledge construction networks in promoting the process of knowledge construction. This study begins with an analysis of the relationship structure among learners in the virtual learning community and then applies the FCM algorithm to arrange learners into various dimensional combinations and create distinct learning communities. The test results demonstrate that the FCM method performs consistently during the clustering process, with less performance oscillations, and good node aggregation, the ARI value of the model is up to 0.90. It is found that they play an important role in the social interaction of learners' virtual learning community, which plays a certain role in promoting the development of artificial intelligence.

E-government serves as a vital channel for citizen interactions with the public sector, where user enjoyment is of paramount importance. To date, few studies have comprehensively examined the determinants of citizen enjoyment in e-government. To address this research gap, we administered a survey and gathered data from 363 Australian residents using myGov for tax filing. Our analysis revealed a pronounced discrepancy between reported enjoyment and the intention to continue using the services. Although users demonstrated a strong intent to use e-government services, this intent did not uniformly align with enjoyment. Additionally, informed by self-determination theory, we developed and tested an e-government service enjoyment model to study the impacts of effort expectancy, technophilia, technology humanness, and engagement in fostering user enjoyment. Unexpectedly, the results showed that information privacy concerns, commonly seen as a deterrent in e-government adoption, did not significantly affect enjoyment. Our findings advance the discourse on e-government service improvement.

Over recent decades, advanced economies have been characterised by reduced rates of productivity. In this article, we advance the hypothesis that one of the potential causes of this trend might be the new knowledge capitalisation practices. Capitalisation of intangible assets is justified by the limited exhaustibility of knowledge, which implies its slow obsolescence, and hence, having the potential of being capitalised to reflect its prolonged period of contribution to productivity. However, the capitalisation of an increasing proportion of the assets that initially were accounted for as labour or intermediate inputs is having a direct effect on increasing capital and theoretical output and reducing total factor productivity (TFP). Our empirical analysis based on US-listed firms shows that the capitalisation of knowledge strongly reduces both the levels of TFP, and because of its fast increase in the last two decades, its rates of growth.

Science-based university spin-offs face considerable technology and market uncertainty over extended periods of time, increasing the challenges of commercialisation. Scientist-entrepreneurs can play formative roles in commercialising lab-based scientific inventions through the formation of well-endowed university spin-offs. Through case study analysis of three science-based university spin-offs within a biotechnology innovation ecosystem, we unpack the impact of <i>pre-formation</i> intangible assets of academic scientists (research excellence, patenting, and international networks) and their entrepreneurial capabilities on spin-off performance. We find evidence that the pre-formation entrepreneurial capabilities of academic scientists can endow science-based university spin-offs by leveraging the scientists' pre-formation intangible assets. A theory-driven model depicting the role of pre-formation intangible assets and entrepreneurial capabilities in endowing science-based university spin-offs is developed. Recommendations are provided for scholars, practitioners, and policymakers to more effectively commercialise high potential inventions in the university lab through the development and deployment of pre-formation intangible assets and entrepreneurial capabilities.

This study aimed to assess the level of GW in Jordanian university students and compare the level of awareness of students according to their academic level (high and low), faculty (science and humanities), gender (male and female), and year of study (first and final years). This study is quantitative research that provides a comprehensive view of GW in Jordanian universities. A total of 383 university students of currently registered undergraduate programs from six independent universities in Jordan were recruited. An online questionnaire covering three aspects of GW was sent to participants in December 2020. Inferential and descriptive statistics were used to analyse data. Participants had 'good' (67%) overall knowledge about GW, a 'very good' level of GW causes (81%), and a 'poor' level of knowledge about the GW impacts on humans and the environment (47%) and knowledge about GW possible solutions (59%). Significant differences were founded between males and females, students from scientific faculties and students from other faculties, students with higher academic achievement than lower achievement in the total GW knowledge. But no significant differences were between students in the first year and the final years.

The face of the hospitality sector in India is continuously changing and in times of career transitiveness, it is important to know the factors that support a successful career. The current research aims to explore the relationship between career planning, employee optimism, career adaptability and career satisfaction in the Indian hospitality sector. The study included 283 employees from Indian hospitality sector. Additionally, the study used SEM and bootstrap method to measure the dual mediating relationship between career planning, employee optimism dimensions, career adaptability dimensions, and career satisfaction in Indian setting. The results indicated that optimism dimensions and career adaptability dimensions partially mediate the relationship between career planning and career satisfaction in Indian hospitality sector. The study suggests useful implications for academia and industrial purpose. The limitations and future research avenues have been discussed. The study would contribute to the sparse literature on employee optimism, career planning, career adaptability and subjective career success. It would contribute to the social cognitive career theory (SCCT).

Teaching advanced programming can be a challenge, especially when the students are pursuing different majors with diverse analytical and problem-solving capabilities. The purpose of this paper is to explore the efficacy of using a particular problem as a vehicle for imparting a broad set of programming concepts and problem-solving techniques. We present a classic brain teaser that is used to communicate and demonstrate advanced software development concepts and techniques. Our results show that students with varied academic experiences and goals, assuming at least one procedural/structured programming pre-requisite, can benefit from and also be challenged by such an exercise. Although this problem has been used by others in the classroom, we believe that our use of this problem in imparting such a broad range of topics to a diverse student population is unique.

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: This study aimed to examine whether there is a difference between manual feedback and online feedback with regard to feedback quality, respondents’ percentage, reliability and the amount of verbal comments written by students. Background: The quality of teaching is an important component of academic work. There are various methods for testing the quality of teaching; one of these methods is through students’ feedback. Methodology: This study used a quantitative approach, including the quantification of qualitative verbal data collected through an open question in the questionnaire. A sample of 180 courses was randomly chosen, 90 courses were evaluated manually and 90 were evaluated online. The number of students ranges from 7 to 60 students per course. In total 4678 students participated in the study. Contribution: The findings show that there is almost an identical pattern of feedback of manual and online course teaching evaluation. These findings encourage a continued use of this evaluation method. Findings: No significant differences were found between manual feedback and online feedback in the students’ evaluation of the lecturer/course. The percentage of respondents was significantly higher in the manual feedback than in the online feedback. The number of qualitative comments was significantly greater in the online feedback than in the manual feedback. Impact on Society: The findings of this study refute the claims with regard to the unreliability of an online teaching evaluation. These findings reflect the advantages of using online feedback, such as cost savings, granting more time to students in order to provide feedback, and reducing disturbance during lectures. Future Research: The gender aspect was not taken into account in the study. Therefore, we recommend conducting a follow-up study that will examine gender differences in directions of- difference between male and female lecturers, and differences between male and female students in teaching evaluation.

Aim/Purpose: The traditional method of teaching e-safety by lecturing is not very effective. Despite learners often being equipped with the right knowledge, they reject the need to act accordingly. There is a need to improve the way digital e-safety is taught. Background: The study compares four different teaching styles, examining how each affected the way students perceive a range of e-safety keywords and consequently the way they approach this issue. Methodology: The semantic differential technique was used to carry out the research. Students completed a semantic differential questionnaire before and after lessons. A total of 405 first year undergraduates took part in the study. Contribution: The paper contributes to the debate on appropriate methods for teaching e-safety, with an aim to influence learners’ attitudes. Findings: Experience-based learning seems to be very effective, confronting students with an e-safety situation and providing them with a negative experience. This teaching method had the biggest influence on students who were deceived by the prepared e-safety risk situation. Recommendations for Practitioners: E-safety instruction can be enhanced by ensuring that lessons provide students with a personal experience. Recommendation for Researchers: The semantic differential technique can be used to measure changes in learners’ attitudes during the teaching process. Impact on Society: Our findings may bring improvements to the way e-safety topics are taught, which could, in turn, evoke in learners a more positive e-safety attitude and a desire to improve their e-safety behavior. Future Research: More research needs to be carried out to examine how the experiential learning method affects the attitudes of younger learners (primary, middle, and high school students).

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.