Sensor locations to detect Poisson-distributed targets, such as seabed sensors that detect shipping traffic, can be selected to maximize the so-called void probability, which is the probability of detecting all targets. Because evaluation of void probability is computationally expensive, we propose a new approximation of void probability that can greatly reduce the computational cost of selecting locations for a network of sensors. We build upon prior work that approximates void probability using Jensen's inequality. Our new approach better accommodates uncertainty in the (Poisson) target model and yields a sharper error bound. The proposed method is evaluated using historical ship traffic data from the Hampton Roads Channel, Virginia, demonstrating a reduction in the approximation error compared to the previous approach. The results validate the effectiveness of the improved approximation for maritime surveillance applications.

The Edge Assembly Crossover (EAX) algorithm is the state-of-the-art heuristic for solving the Traveling Salesperson Problem (TSP). It regularly outperforms other methods, such as the Lin-Kernighan-Helsgaun heuristic (LKH), across diverse sets of TSP instances. Essentially, EAX employs a two-stage mechanism that focuses on improving the current solutions, first, at the local and, subsequently, at the global level. Although the second phase of the algorithm has been thoroughly studied, configured, and refined in the past, in particular, its first stage has hardly been examined. In this paper, we thus focus on the first stage of EAX and introduce a novel method that quickly verifies whether the AB-cycles, generated during its internal optimization procedure, yield valid tours -- or whether they need to be repaired. Knowledge of the latter is also particularly relevant before applying other powerful crossover operators such as the Generalized Partition Crossover (GPX). Based on our insights, we propose and evaluate several improved versions of EAX. According to our benchmark study across 10 000 different TSP instances, the most promising of our proposed EAX variants demonstrates improved computational efficiency and solution quality on previously rather difficult instances compared to the current state-of-the-art EAX algorithm.

Motivated by the emerging demand in the financial industry for the automatic analysis of unstructured and structured data at scale, Question Answering (QA) systems can provide lucrative and competitive advantages to companies by facilitating the decision making of financial advisers. Consequently, we propose a novel financial QA system using the transformer-based pre-trained BERT language model to address the limitations of data scarcity and language specificity in the financial domain. Our system focuses on financial non-factoid answer selection, which retrieves a set of passage-level texts and selects the most relevant as the answer. To increase efficiency, we formulate the answer selection task as a re-ranking problem, in which our system consists of an Answer Retriever using BM25, a simple information retrieval approach, to first return a list of candidate answers, and an Answer Re-ranker built with variants of pre-trained BERT language models to re-rank and select the most relevant answers. We investigate various learning, further pre-training, and fine-tuning approaches for BERT. Our experiments suggest that FinBERT-QA, a model built from applying the Transfer and Adapt further fine-tuning and pointwise learning approach, is the most effective, improving the state-of-the-art results of task 2 of the FiQA dataset by 16% on MRR, 17% on NDCG, and 21% on Precision@1.

Zero-Day Botnet Attack Detection in IoV: A Modular Approach Using Isolation Forests and Particle Swarm Optimization Abdelaziz Amara korba 2, Nour Elislem Karabadji 1, and Y acine Ghamri-Doudane 2 1 National Higher School of T echnology and Engineering, LTSE, E3360100, Annaba, Algeria. 2 L3I, University of La Rochelle, France Abstract --The Internet of V ehicles (IoV) is transforming transportation by enhancing connectivity and enabling autonomous driving. However, this increased interconnectivity introduces new security vulnerabilities. Bot malware and cyberattacks pose significant risks to Connected and Autonomous V ehicles (CA Vs), as demonstrated by real-world incidents involving remote vehicle system compromise. T o address these challenges, we propose an edge-based Intrusion Detection System (IDS) that monitors network traffic to and from CA Vs. Our detection model is based on a meta-ensemble classifier capable of recognizing known (N-day) attacks and detecting previously unseen (zero-day) attacks. The approach involves training multiple Isolation Forest (IF) models on Multi-access Edge Computing (MEC) servers, with each IF specialized in identifying a specific type of botnet attack. These IFs, either trained locally or shared by other MEC nodes, are then aggregated using a Particle Swarm Optimization (PSO) based stacking strategy to construct a robust meta-classifier . The proposed IDS has been evaluated on a vehicular botnet dataset, achieving an average detection rate of 92.80% for N-day attacks and 77.32% for zero-day attacks.

Continuous Integration/Continuous Deployment (CI/CD) is fundamental for advanced software development, supporting faster and more efficient delivery of code changes into cloud environments. However, security issues in the CI/CD pipeline remain challenging, and incidents (e.g., DDoS, Bot, Log4j, etc.) are happening over the cloud environments. While plenty of literature discusses static security testing and CI/CD practices, only a few deal with network traffic pattern analysis to detect different cyberattacks. This research aims to enhance CI/CD pipeline security by implementing anomaly detection through AI (Artificial Intelligence) support. The goal is to identify unusual behaviour or variations from network traffic patterns in pipeline and cloud platforms. The system shall integrate into the workflow to continuously monitor pipeline activities and cloud infrastructure. Additionally, it aims to explore adaptive response mechanisms to mitigate the detected anomalies or security threats. This research employed two popular network traffic datasets, CSE-CIC-IDS2018 and CSE-CIC-IDS2017. We implemented a combination of Convolution Neural Network(CNN) and Long Short-Term Memory (LSTM) to detect unusual traffic patterns. We achieved an accuracy of 98.69% and 98.30% and generated log files in different CI/CD pipeline stages that resemble the network anomalies affected to address security challenges in modern DevOps practices, contributing to advancing software security and reliability.

Charles McBee stops by Fox News Saturday Night With Jimmy Failla to give his take on actor John Boyega calling out the "Star Wars" franchise for its overwhelming whiteness. The White House slammed the "radical left" in a social media post Sunday, showing an AI-generated image of President Donald Trump wielding a lightsaber in celebration of May the Fourth, or "Star Wars Day." May 4 has long been regarded as a day to celebrate the iconic movie franchise as fans post on social media "May the Fourth be with you," an offshoot of the memorable Star Wars quote "May the force be with you." On Sunday, the White House took an opportunity to celebrate the popular day with a post on X, while also taking digs at the Trump administration's biggest critics. "Happy May the 4th to all, including the Radical Left Lunatics who are fighting so hard to bring Sith Lords, Murderers, Drug Lords, Dangerous Prisoners, & well known MS-13 Gang Members, back into our Galaxy. You're not the Rebellion--you're the Empire," the White House wrote.

Russian President Vladimir Putin has said that there has so far been no need to use nuclear weapons in Ukraine, expressing "hope" that they will not be required. Putin said his country had enough "strength and means" to bring the three-year war, sparked by Russia's 2022 invasion of Ukraine, to a "logical conclusion with the outcome Russia requires". His comments were part of a documentary marking his quarter century in power by state television channel Rossiya 1 that was released on Sunday. Responding to a question from journalist Pavel Zarubin about the Russian response to Ukrainian strikes on Russian territory, Putin said: "There has been no need to use those [nuclear] weapons … and I hope they will not be required." His comments came ahead of his unilaterally declared three-day ceasefire over May 8-10 to mark the 80th anniversary of the victory of the Soviet Union and its allies over Nazi Germany in World War II, an initiative that he claimed would test Kyiv's readiness for long-term peace.

Former Biden administration aide Michael LaRosa claimed the White House pressured CNN to not book him after he left the White House, which CNN denied to Fox News Digital. A new book revealed that former President Joe Biden's team chose not to have the president take a cognitive test in February 2024, over concerns that taking the test itself would raise more questions about his age, The New York Times reported Sunday. Authors Tyler Pager, a reporter for The New York Times, Josh Dawsey, a reporter for the Wall Street Journal and Isaac Arnsdorf, a reporter for the Washington Post, wrote the book, titled, "2024: How Trump Retook the White House and the Democrats Lost America," which is set to be released in July. The book, one of several about the tumultuous 2024 presidential election, details that Biden's top aides debated having him complete a cognitive test to quell concerns about his age. The aides were reportedly confident Biden would pass the test.

Right now, most big AI labs have a team figuring out ways that rogue AIs might escape supervision, or secretly collude with each other against humans. But there's a more mundane way we could lose control of civilisation: we might simply become obsolete. This wouldn't require any hidden plots – if AI and robotics keep improving, it's what happens by default. Well, AI developers are firmly on track to build better replacements for humans in almost every role we play: not just economically as workers and decision-makers, but culturally as artists and creators, and even socially as friends and romantic companions. What place will humans have when AI can do everything we do, only better?

Sudan's army says the paramilitary Rapid Support Forces (RSF) attacked a military airbase and other facilities in the vicinity of Port Sudan airport. The army said on Sunday that the airbase was targeted using a drone, as well as a cargo warehouse and some civilian facilities, in the first attack in the eastern city by the RSF. There are reports of some damage after drones hit an ammunition depot. "Both the civilian and military airports are in the same place. What we know from residents in the port city is that five drones were launched by the RSF and targeted the airbase," Al Jazeera's Hiba Morgan said, reporting from the capital, Khartoum.