Le commerce de la Chine avec les autres �conomies de l'APEC a atteint un niveau record de 21.270 milliards de yuans (environ 2.950 milliards de dollars) au cours des dix premiers mois de 2024, selon les donn�es publi�es mercredi par l'Administration...

Published at LXer: Reor is a private AI personal knowledge management tool. Think of it as a notes program on steroids. Each note is saved as a Markdown file to a �vault� directory on your machine....

Michael Jackson with Britney Spears legs! Oh my! It's the DNA slot machine, bet on mixing and matching celebrities DNA.

The manga tech start up Orange Inc recently raised over 19 million USD in funding for machine translated manga. We were quite intrigued beca...

Made for the Chinese new year of 2005, this animation of a flying dragon is accompanied by traditional chinese music. The dragon is believed to ward off evil spirits for the new year.

Mauslot Slot Machines: Cara Mendapatkan Kemenangan Sering Seperti Seorang Pro   Mauslot adalah salah satu permainan kasino online yang paling populer di Indonesia. Game slot ini menawarkan kesempatan untuk memenangkan alternatif mauslot  jackpot besar dengan cara yang sederhana. Namun, untuk meningkatkan peluang kemenangan Anda, Anda perlu memahami beberapa strategi dasar. Berikut adalah beberapa tips untuk […]

The post Mauslot Slot Machines: Cara Mendapatkan Kemenangan Sering Seperti Seorang Pro appeared first on DOMINOQQ - DOMINO QQ ONLINE - DOMINO QIU QIU ONLINE.

About the total body workout benefits that Elliptical exercise machines and trainers provide.

The elliptical machine you buy should be based on the features of the elliptical trianer and a number of factors including your fitness goals, body and budget.

How to do the LifeFitness machine glute exercise which also works the secondary muscles of the legs - quadriceps, hamstrings. Good glute and full leg workout.

How and why to use a rowing machine at home or at the gym.

What types of weight training exercise equipment should you be using when strength training or bodybuilding.

How to do the incline chest press on Iso HammerStrength machine with video.

Comparison of elliptical to treadmill machines to determine which is best for your fitness workout.

Strengthens and tones the glutes but also works the leg muscles.

How to do the iso row back exercise using the Hammer Strength machine.

Incline chest press exercise using a wide-grip on the Hammer Strength machine.

Shoulder shrugs exercise options using 2 dumbbells or the Smith machine.

Johanna Zorn is leaving the Third Coast Festival. The executive director and co-founder of the Chicago-based audio documentary conference will be departing in the fall, and the search for her replacement will kick off later this week. The move was announced Wednesday through a letter published on the Third Coast website.

Obviously, this is a major development for the beloved conference, which has become one of the most, if not the most important gatherings for radio and podcast producers since its founding almost two decades ago. Third Coast grew particularly quickly over the past few years — tracking the growth spurt in the audio world around it — the biggest expression of which was the decision to shift the festival towards an annualized schedule in 2016. (It was previously held every two years.)

complete article

Lengthy jail terms have been handed to 22 Chinese citizens - and a Cameroonian man - for cyber-related crimes in Zambia. The gang's only female...

With one of the world's most diverse food scenes, China makes it nearly impossible to put together one single list that truly encompasses the "best" Chinese dishes.

This Wednesday I’ll be speaking at AltConf on Machine Learning on iOS: Integrating IBM Watson with Core ML. Here’s the abstract I submitted: Apple recently announced a partnership with IBM to integrate Core ML with Watson, allowing visual recognition to run locally on iOS devices. The ability to use machine learning while offline opens up […]

The post Altconf 2018 – Machine Learning on iOS: Integrating IBM Watson with Core ML first appeared on Tom Markiewicz.

Earlier this year I attended AltConf in San Jose, a community-driven and supported event held alongside Apple’s WWDC. IBM sponsored the event and offered numerous workshops to attendees. In addition to assisting with the workshops and manning the booth, I had a talk accepted on Machine Learning on iOS: Integrating IBM Watson with Core ML. […]

The post Video: Machine Learning on iOS, Integrating IBM Watson with Core ML at AltConf first appeared on Tom Markiewicz.

The year is 2010 and Machine Head are wrapping up a tour supporting the now legendary studio record The Blackening...

The first major release in heavy music this year veers quite wide of the mark providing very few highlights.

SAVE 15% off on regular priced shoes

Bislang stützen sich die europäischen Suchmaschinen Ecosia und Qwant vor allem auf die Bing-Plattform von Microsoft. Künftig wollen sie nicht mehr auf US-Technologieriesen angewiesen sein.

Students at Kumaraguru Institutions in Coimbatore designed a hydrogen fuel cell car for the Shell Eco-Marathon, pushing boundaries in sustainable automotive technology

Fully updated to reflect modern developments in the field, the Fifth Edition of An Introduction to Optimization fills the need for an accessible, yet rigorous, introduction to optimization theory and methods, featuring innovative coverage and a straightforward approach. The book begins with a review of basic definitions and notations while also providing the related fundamental background of linear algebra, geometry, and calculus. With this foundation, the authors explore the essential topics of unconstrained optimization problems, linear programming problems, and nonlinear constrained optimization. In addition, the book includes an introduction to artificial neural networks, convex optimization, multi-objective optimization, and applications of optimization in… [Continue Reading]

Fr. John Whiteford tells about St. Mitrophan, the first Chinese priest and martyr of the Boxer Rebellion, and encourages us to stand firm in the Faith.

"The Holy Martyrs of China were native Chinese Orthodox Christians brought up in piety at the Russian Orthodox Mission in Peking, which had been founded in 1685. During the Boxer Rebellion of 1900 against the foreign powers occupying China, native Chinese Christians were commanded by the Boxers to renounce Christianity or be tortured to death. Two hundred and twenty-two members of the Peking Mission, led by their priest Metrophanes Tsi-Chung and his family, refused to deny Christ, and were deemed worthy of a martyric death." ( Great Horologion)

"The Holy Martyrs of China were native Chinese Orthodox Christians brought up in piety at the Russian Orthodox Mission in Peking, which had been founded in 1685. During the Boxer Rebellion of 1900 against the foreign powers occupying China, native Chinese Christians were commanded by the Boxers to renounce Christianity or be tortured to death. Two hundred and twenty-two members of the Peking Mission, led by their priest Metrophanes Tsi-Chung and his family, refused to deny Christ, and were deemed worthy of a martyric death." ( Great Horologion)

"Families can be hard, but they're so worth fighting for. They might be one of the only things that are." Steve and Christian watched the new Netflix film, "The Mitchells vs. The Machines." The guys discuss family, belonging, and being corrects vs being connected. Philanthropy Spotlight: Christ's last words to the Apostles were "Go into all the world and preach the Gospel to all people". Since 1987, OCMC has sent Missionaries and Mission Teams to work, worship and witness around the world. Continue this tradition by joining a Virtual Mission Team. If not you, then who? Find out more at www.ocmc.org

What is the secret behind South Africa’s eight-man machine – arguably the most formidable and feared scrum in rugby?

Alliance pays tribute to its "ground-breaking" and "trailblazing" former assembly member, Anna Lo.

Rail ticket machines across the UK fell out of service during the morning commute.

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.

To achieve psychological and emotional analysis of massive internet chats, researchers have used statistical methods, machine learning, and neural networks to analyse the dynamic tendencies of texts dynamically. For long readers, the author first compares and explores the differences between the two psychoanalysis algorithms based on the emotion dictionary and machine learning for simple sentences, then studies the expansion algorithm of the emotion dictionary, and finally proposes an extended text psychoanalysis algorithm based on conditional random field. According to the experimental results, the mental dictionary's accuracy, recall, and F-score based on the cognitive understanding of each additional ten words were calculated. The optimisation decreased, and the memory and F-score improved. An <i>F</i>-value greater than 1, which is the most effective indicator for evaluating the effectiveness of a mental analysis problem, can better demonstrate that the algorithm is adaptive in the literature dictionary. It has been proven that this scheme can achieve good results in analysing emotional tendencies and has higher efficiency than ordinary weight-based psychological sentiment analysis algorithms.

Aim/Purpose: This paper presents a machine learning approach for analyzing Course Learning Outcomes (CLOs). The aim of this study is to find a model that can check whether a CLO is well written or not. Background: The use of machine learning algorithms has been, since many years, a prominent solution to predict learner performance in Outcome Based Education. However, the CLOs definition is still presenting a big handicap for faculties. There is a lack of supported tools and models that permit to predict whether a CLO is well written or not. Consequently, educators need an expert in quality and education to validate the outcomes of their courses. Methodology: A novel method named CLOCML (Course Learning Outcome Classification using Machine Learning) is proposed in this paper to develop predictive models for CLOs paraphrasing. A new dataset entitled CLOC (Course Learning Outcomes Classes) for that purpose has been collected and then undergone a pre-processing phase. We compared the performance of 4 models for predicting a CLO classification. Those models are Support Vector Machine (SVM), Random Forest, Naive Bayes and XGBoost. Contribution: The application of CLOCML may help faculties to make well-defined CLOs and then correct CLOs' measures in order to improve the quality of education addressed to their students. Findings: The best classification model was SVM. It was able to detect the CLO class with an accuracy of 83%. Recommendations for Practitioners: We would recommend both faculties’ members and quality reviewers to make an informed decision about the nature of a given course outcome. Recommendation for Researchers: We would highly endorse that the researchers apply more machine learning models for CLOs of various disciplines and compare between them. We would also recommend that future studies investigate on the importance of the definition of CLOs and its impact on the credibility of Key Performance Indicators (KPIs) values during accreditation process. Impact on Society: The findings of this study confirm the results of several other researchers who use machine learning in outcome-based education. The definition of right CLOs will help the student to get an idea about the performances that will be measured at the end of a course. Moreover, each faculty can take appropriate actions and suggest suitable recommendations after right performance measures in order to improve the quality of his course. Future Research: Future research can be improved by using a larger dataset. It could also be improved with deep learning models to reach more accurate results. Indeed, a strategy for checking CLOs overlaps could be integrated.

Aim/Purpose: The study focused on learner sentiments and experiences after using the Moodle assessment module and trained a machine learning classifier for future sentiment predictions. Background: Learner assessment is one of the standard methods instructors use to measure students’ performance and ascertain successful teaching objectives. In pedagogical design, assessment planning is vital in lesson content planning to the extent that curriculum designers and instructors primarily think like assessors. Assessment aids students in redefining their understanding of a subject and serves as the basis for more profound research in that particular subject. Positive results from an evaluation also motivate learners and provide employment directions to the students. Assessment results guide not just the students but also the instructor. Methodology: A modified methodology was used for carrying out the study. The revised methodology is divided into two major parts: the text-processing phase and the classification model phase. The text-processing phase consists of stages including cleaning, tokenization, and stop words removal, while the classification model phase consists of dataset training using a sentiment analyser, a polarity classification model and a prediction validation model. The text-processing phase of the referenced methodology did not utilise tokenization and stop words. In addition, the classification model did not include a sentiment analyser. Contribution: The reviewed literature reveals two major omissions: sentiment responses on using the Moodle for online assessment, particularly in developing countries with unstable internet connectivity, have not been investigated, and variations of the k-fold cross-validation technique in detecting overfitting and developing a reliable classifier have been largely neglected. In this study we built a Sentiment Analyser for Learner Emotion Management using the Moodle for assessment with data collected from a Ghanaian tertiary institution and developed a classification model for future sentiment predictions by evaluating the 10-fold and the 5-fold techniques on prediction accuracy. Findings: After training and testing, the RF algorithm emerged as the best classifier using the 5-fold cross-validation technique with an accuracy of 64.9%. Recommendations for Practitioners: Instead of a closed-ended questionnaire for learner feedback assessment, the open-ended mechanism should be utilised since learners can freely express their emotions devoid of restrictions. Recommendation for Researchers: Feature selection for sentiment analysis does not always improve the overall accuracy for the classification model. The traditional machine learning algorithms should always be compared to either the ensemble or the deep learning algorithms Impact on Society: Understanding learners’ emotions without restriction is important in the educational process. The pedagogical implementation of lessons and assessment should focus on machine learning integration Future Research: To compare ensemble and deep learning algorithms

Currently, Android is a booming technology that has occupied the major parts of the market share. However, as Android is an open-source operating system there are possibilities of attacks on the users, there are various types of attacks but one of the most common attacks found was malware. Malware with machine learning (ML) techniques has proven as an impressive result and a useful method for malware detection. Here in this paper, we have focused on the analysis of malware attacks by collecting the dataset for the various types of malware and we trained the model with multiple ML and deep learning (DL) algorithms. We have gathered all the previous knowledge related to malware with its limitations. The machine learning algorithms were having various accuracy levels and the maximum accuracy observed is 99.68%. It also shows which type of algorithm is preferred depending on the dataset. The knowledge from this paper may also guide and act as a reference for future research related to malware detection. We intend to make use of Static Android Activity to analyse malware to mitigate security risks.

More than a half billion people use the internet in China, and the environment in which these users work, study, and play using the internet is a rapidly changing one. User perceptions of the quality of information accessed through the internet and through more traditional sources of information may shift over time as the underlying social, cultural, and political environment changes. This study reports the results of a longitudinal survey study of perceptions of information quality of young adults using the internet in China. Results suggest that perceptions of the information quality of internet-based information have shifted more from 2007 to 2012 than perceptions of traditional text sources of information. Implications of the findings for researchers, educators, and information providers are discussed.