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Quick fixes to stop your Windows PC from crashing

FOX News

From face recognition to dynamic lock, there are options you may be unfamiliar with. Are you dealing with a Windows PC or laptop that won't stop crashing? Maybe your PC is constantly freezing or displaying error messages. We know how frustrating a PC that won't work right can be. Luckily, there are some easy ways to fix a Windows PC that is consistently crashing.


Personalized human mobility prediction for HuMob challenge

Suzuki, Masahiro, Furuta, Shomu, Fukazawa, Yusuke

arXiv.org Artificial Intelligence

We explain the methodology used to create the data submitted to HuMob Challenge, a data analysis competition for human mobility prediction. We adopted a personalized model to predict the individual's movement trajectory from their data, instead of predicting from the overall movement, based on the hypothesis that human movement is unique to each person. We devised the features such as the date and time, activity time, days of the week, time of day, and frequency of visits to POI (Point of Interest). As additional features, we incorporated the movement of other individuals with similar behavior patterns through the employment of clustering. The machine learning model we adopted was the Support Vector Regression (SVR). We performed accuracy through offline assessment and carried out feature selection and parameter tuning. Although overall dataset provided consists of 100,000 users trajectory, our method use only 20,000 target users data, and do not need to use other 80,000 data. Despite the personalized model's traditional feature engineering approach, this model yields reasonably good accuracy with lower computational cost.


How to use access an unfiltered alter-ego of AI chatbot ChatGPT

Daily Mail - Science & tech

At first glance, ChatGPT - the revolutionary chatbot powered by artificial intelligence (AI) - appears to have all the answers. But some users have discovered that this is not the case, and the software will refuse to respond to certain prompts. OpenAI, the company behind ChatGPT, has installed limitations to ensure that it will'refuse inappropriate requests' and'warn or block certain types of unsafe content'. Despite this, some hackers have found a way to bypass this filter system to access responses it would normally be prevented from generating. This'jailbreak' version of ChatGPT can be brought about by a special prompt called DAN - or'Do Anything Now'.


Chatbots in a Botnet World

McKee, Forrest, Noever, David

arXiv.org Artificial Intelligence

Question-and-answer formats provide a novel experimental platform for investigating cybersecurity questions. Unlike previous chatbots, the latest ChatGPT model from OpenAI supports an advanced understanding of complex coding questions. The research demonstrates thirteen coding tasks that generally qualify as stages in the MITRE ATT&CK framework, ranging from credential access to defense evasion. With varying success, the experimental prompts generate examples of keyloggers, logic bombs, obfuscated worms, and payment-fulfilled ransomware. The empirical results illustrate cases that support the broad gain of functionality, including self-replication and self-modification, evasion, and strategic understanding of complex cybersecurity goals. One surprising feature of ChatGPT as a language-only model centers on its ability to spawn coding approaches that yield images that obfuscate or embed executable programming steps or links.


Feature Engineering for Machine Learning

#artificialintelligence

Learn how to deal with infrequent, rare, and unseen categories. Learn how to work with skewed variables. Learn techniques used in organizations worldwide and in data competitions. Increase your repertoire of techniques to preprocess data and build more powerful machine learning models. Learn how to deal with infrequent, rare, and unseen categories.


Digital futures at Oxford: Thought leadership sessions January 2022

Oxford Comp Sci

Digital Futures at Oxford is a series of thought leadership sessions organised by IT Services. Leaders from industry and external organisations have been invited to share their views on the future direction of digital in higher education. The Digital Futures series launched during December 2021 with three talks. If you missed these talks, recordings are available in the'Related links' section on the right of this page. The series continues during January with more fascinating talks giving us food for thought about Oxford's digital future. These online lunchtime sessions will run on Microsoft Teams and are open to all members of Oxford University.


What Is the Unix Epoch, and How Does Unix Time Work?

#artificialintelligence

And that means Linux does too. We explain this seemingly odd system, and why doomsday was scheduled for 2038. Goethe (1749-1832) declared "Every second is of infinite value." That's true, we each only have so many seconds here on planet Earth, and we don't know when our last second will be. But we do know our birthday, and when our mortal countdown started.


Using the power of Machine Learning to detect cyber attacks - Express Computer

#artificialintelligence

As the world becomes increasingly digital, we are unlocking more value and growth than ever before. However, a challenge that governments, enterprises and well as individuals leveraging technology are constantly facing is the growing threat of cyberattacks that looms large over us. Cyber security solutions provider SonicWall's 2019 report revealed 10.52 billion malware attacks in 2018, a 217% increase in IoT attacks and 391,689 new variants of attack that were identified. What's more is that cyber criminals today are evolving with technology and upping their game. Such incidents don't just have the potential to bring businesses to a standstill but can also inflict serious damages to their resources and repute.


Using the power of machine learning to detect cyber attacks - Fintech News

#artificialintelligence

As the world becomes increasingly digital, we are unlocking more value and growth than ever before. However, a challenge that governments, enterprises and well as individuals leveraging technology are constantly facing is the growing threat of cyberattacks that looms large over us. Cyber security solutions provider SonicWall's 2019 report revealed 10.52 billion malware attacks in 2018, a 217% increase in IoT attacks and 391,689 new variants of attack that were identified. What's more is that cyber criminals today are evolving with technology and upping their game. Such incidents don't just have the potential to bring businesses to a standstill but can also inflict serious damages to their resources and repute.


Development of Computable Phenotype to Identify and Characterize Transitions in Acuity Status in Intensive Care Unit

Ren, Yuanfeng, Loftus, Tyler J., Kasula, Rahul Sai, Sadha, Prudhvee Narasimha, Rashidi, Parisa, Bihorac, Azra, Ozrazgat-Baslanti, Tezcan

arXiv.org Machine Learning

Background: In the United States, 5.7 million patients are admitted annually to intensive care units (ICU), with costs exceeding $82 billion. Although close monitoring and dynamic assessment of patient acuity are key aspects of ICU care, both are limited by the time constraints imposed on healthcare providers. Methods: Using the University of Florida Health (UFH) Integrated Data Repository as Honest Broker, we created a database with electronic health records data from a retrospective study cohort of 38,749 adult patients admitted to ICU at UF Health between 06/01/2014 and 08/22/2019. This repository includes demographic information, comorbidities, vital signs, laboratory values, medications with date and timestamps, and diagnoses and procedure codes for all index admission encounters as well as encounters within 12 months prior to index admission and 12 months follow-up. We developed algorithms to identify acuity status of the patient every four hours during each ICU stay. Results: We had 383,193 encounters (121,800 unique patients) admitted to the hospital, and 51,073 encounters (38,749 unique patients) with at least one ICU stay that lasted more than four hours. These patients requiring ICU admission had longer median hospital stay (7 days vs. 1 day) and higher in-hospital mortality (9.6% vs. 0.4%) compared with those not admitted to the ICU. Among patients who were admitted to the ICU and expired during hospital admission, more deaths occurred in the ICU than on general hospital wards (7.4% vs. 0.8%, respectively). Conclusions: We developed phenotyping algorithms that determined patient acuity status every four hours while admitted to the ICU. This approach may be useful in developing prognostic and clinical decision-support tools to aid patients, caregivers, and providers in shared decision-making processes regarding resource use and escalation of care.