Exploring the Optimal Sensitivity of Sum-Variance Nonseparability Criteria for Spin-1/2 Systems

We report on experimental and theoretical studies on recently introduced entanglement measures which use a sum of spin-variance criteria for two spin-1∕2 particles. Three inequalities are explored which exhibit useful concatenating properties. They are each shown to have greater sensitivities than a Bell’s measurement, while each requiring fewer measurements than a Bell’s measurement to obtain. The simplest inequality, requiring just four measurements, is shown to be efficient at testing for entanglement in down-conversion sources which naturally exhibit maximally polarized noise. The most complex inequality, requiring just 12 measurements, is shown to have a sensitivity equal to that of the Peres separability criterion for maximally polarized and Werner noise. This increased sensitivity implies optimality of the measure

Experimental Demonstration of High Two-Photon Time-Energy Entanglement

We report on the experimental demonstration of high energy-time entanglement in two-photon states created in the process of spontaneous parametric down-conversion. We show that the classical variance product, which we violate by three orders of magnitude, actually represents a lower bound estimate of the number of information eigenmodes K. Explicit measurements estimate K to be greater than 100, with theoretical estimates predicting a value of as high as 1×106. These results provide incentive for the practical feasibility of large bandwidth quantum information processing, particularly in cryptography over large distances

Hong-Ou-Mandel Cloning: Quantum Copying Without an Ancilla

In this paper we report an experimental realization of an ancilla-free 1→2 phase-covariant quantum cloner. The cloner is realized by interfering a linearly polarized photon, which we wish to clone with a circularly polarized photon at a beam splitter. The two-photon effect can be understood in light of Hong-Ou-Mandel interference. The fidelity of the cloner was measured as 0.829±0.008 for the 0∕90 basis and 0.835±0.006 for the 45∕135 basis, which is in good agreement with the theoretical prediction of 5∕6 fidelity. The experimental scheme is straightforward and has a high cloning success rate

ByteStack-ID: Integrated Stacked Model Leveraging Payload Byte Frequency for Grayscale Image-based Network Intrusion Detection

In the ever-evolving realm of network security, the swift and accurate identification of diverse attack classes within network traffic is of paramount importance. This paper introduces "ByteStack-ID," a pioneering approach tailored for packet-level intrusion detection. At its core, ByteStack-ID leverages grayscale images generated from the frequency distributions of payload data, a groundbreaking technique that greatly enhances the model's ability to discern intricate data patterns. Notably, our approach is exclusively grounded in packet-level information, a departure from conventional Network Intrusion Detection Systems (NIDS) that predominantly rely on flow-based data. While building upon the fundamental concept of stacking methodology, ByteStack-ID diverges from traditional stacking approaches. It seamlessly integrates additional meta learner layers into the concatenated base learners, creating a highly optimized, unified model. Empirical results unequivocally confirm the outstanding effectiveness of the ByteStack-ID framework, consistently outperforming baseline models and state-of-the-art approaches across pivotal performance metrics, including precision, recall, and F1-score. Impressively, our proposed approach achieves an exceptional 81\% macro F1-score in multiclass classification tasks. In a landscape marked by the continuous evolution of network threats, ByteStack-ID emerges as a robust and versatile security solution, relying solely on packet-level information extracted from network traffic data.Comment: 6 pages, 6 figure

Knowledge about asthma: A cross-sectional survey in 4 major hospitals of Karachi, Pakistan

Objective: To determine knowledge and misconceptions about asthma among the local population..Methods: This cross-sectional study was conducted at four tertiary care hospitals; Aga Khan University Hospital, Civil Hospital Karachi, Jinnah Postgraduate Medical Centre and Ojha Institute of Chest Diseases, Karachi, from October to November 2016, and comprised hospital attendants. The questionnaire used in the study comprised 26 questions answered with a true, false or not sure answer.SPSS 20 was used for data analysis.Results: There were 400 participants. The overall mean age was 41.2±14.2 years, and 214(53.5%) of the participants were males. Moreover, 75(19%) participants thought that asthma was a psychological disorder while 181(45%) considered it an infectious disease. Nearly 174(43.5%) believed that inhaled medications had significant side effects. Besides, 264(66%) participants considered steam inhalation to be an effective treatment for asthma, 269(67%) thought that patients with asthma should avoid rice in their diet and 167(42%) considered milk as a common trigger.CONCLUSIONS: Participants\u27 knowledge about asthma was poor and misconceptions were common about the condition