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Purpose: Hospital out-patient departments (OPDs) in India face severe queue inefficiencies with average waiting times of 90+ minutes and poor patient communication. Methodology: This study presents MediQueue — a full-stack intelligent queue management system built with React.js, Node.js, MySQL, Socket.io, and a self-learning ML engine. A dual-prediction architecture (Random Forest + equal-distribution fallback) predicts per-department wait times. A nightly recalibration scheduler updates slot capacities from verified treatment records. Findings: The system achieves a Mean Absolute Error (MAE) of […]

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The integration of large language models (LLMs) into peer review raises a concern beyond authorship and detection: the potential cascading automation of the entire editorial process. As reviews become partially or fully machine-generated, it becomes plausible that editorial decisions may also be delegated to algorithmic systems, leading to a fully automated evaluation pipeline. They risk reshaping the criteria by which scientific work is assessed. This paper argues that machine-driven assessment may systematically favor standardized, pattern-conforming research while penalizing […]

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For years, we’ve treated coding interviews as the gateway to software engineering. Solve a few algorithm problems under pressure, and you’re “in.” Struggle with them, and suddenly your ability as an engineer is questioned. But here’s the uncomfortable truth: LeetCode-style interviews have never been a reliable measure of engineering skill. At best, they’re a hit-or-miss signal. Sometimes you’re in the zone. Sometimes the pressure gets to you. Sometimes you’ve seen a similar problem before. Sometimes you blank out […]

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Efficient ground state search is fundamental to advancing combinatorial optimization problems and quantum chemistry. While the Variational Imaginary Time Evolution (VITE) method offers a useful alternative to Variational Quantum Eigensolver (VQE), and Quantum Approximate Optimization Algorithm (QAOA), its implementation on Noisy Intermediate-Scale Quantum (NISQ) devices is severely limited by the gate counts and depth of manually designed ansatz. Here, we present an automated framework for VITE circuit design using Double Deep-Q Networks (DDQN). Our approach treats circuit construction […]

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Software-Defined Network (SDN) renders flexible traffic engineering, but consumes a lot of energy. There is an overhead on the control-plane because of flow-rule updates are done always and the energy consumption by the forwarding hardware. Current energy-aware SDN methods mostly focus on static or greedy optimisations. This can cause too many Ternary Content-Addressable Memory (TCAM) updates and unstable rule churn when traffic changes over time. This article introduces a Dynamic Flow Rule Placement (DFRP) framework for real-time energy […]

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Stereo matching has witnessed rapid advances on curated benchmarks, yet deploying models in unconstrained real-world environments remains a fundamental challenge. This paper presents a sparse self-prompt guided network (SSPGNet) for stereo matching with strong generalization across diverse environments. Our core innovation lies in a sparse self-prompt guidance mechanism: 1) a sparse disparity map, used as a prompt, is self-estimated from visual foundation model features via cost aggregation; and 2) the sparse disparity is progressively refined into dense disparity […]

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Being over 20 years old in the sphere of enterprise technology is a reality that can no longer be ignored: the very thing that once made enterprises stable—legacy systems—has now become a significant challenge. These systems were designed and built with accuracy and reliability in mind, and over the years they have effectively supported business operations. However, their limitations have become more evident as business needs have evolved and digital transformation has accelerated. As a result, legacy systems […]

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As AI agents begin executing trades, managing risk, and interacting with markets through natural language, exchanges are quietly undergoing one of their most significant architectural shifts since the invention of the order book itself. The platforms that win the next cycle may not be the ones with the deepest order books, they may be the ones that are the most programmable, the most interoperable, and the most agent-ready. Victor Wu is building that shift from the inside at […]

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Post-training has become central to turning pretrained large language models (LLMs) into aligned and deployable systems. Recent progress spans supervised fine-tuning (SFT), preference optimization, reinforcement learning (RL), process supervision, verifier-guided methods, distillation, and multi-stage pipelines. Yet these methods are often discussed in fragmented ways, organized by labels or objective families rather than by the behavioral bottlenecks they address. This survey argues that LLM post-training is best understood as structured intervention on model behavior. We organize the field first […]

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London, UK Busha, a Nigerian SEC-licensed digital asset exchange, expands to the UK to serve families with connections across both regions   Busha selected Uphold as its platform partner thanks to experience in delivering on-chain infrastructure services in the UK   Busha, a crypto platform focused on building the future of money in Africa, has selected Uphold, the modern infrastructure provider for on-chain finance, to support the launch of its services in the UK. Busha serves more than a million […]

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