Explainable Artificial Intelligence (XAI) has emerged as a critical facet in the realm of machine learning and artificial intelligence, responding to increasing complexity models, particularly deep neural networks, subsequent need for transparent decision making processes. This research paper delves into essence XAI, unraveling its significance across diverse domains such healthcare, finance, criminal justice. As countermeasure opacity intricate explores various XAI methods techniques,...

Due to their light weight, low power, and practically unlimited identification capacity, radio frequency (RFID) tags associated devices offer distinctive advantages are widely recognized for promising potential in context-aware computing; by tagging objects with RFID tags, the environment can be sensed a cost- energy-efficient means. However, prerequisite fully realizing is accurate localization of which will enable enhance wide range applications. In this paper we show how exploit phase...

We present a parallel algorithm for k-nearest neighbor graph construction that uses Morton ordering. Experiments show our approach has the following advantages over existing methods: 1) faster of graphs in practice on multicore machines, 2) less space usage, 3) better cache efficiency, 4) ability to handle large data sets, and 5) ease parallelization implementation. If point set bounded expansion constant, requires one-comparison-based sort points, according order plus near-linear additional...

We study the minimum enclosing ball (MEB) problem for sets of points or balls in high dimensions. Using techniques second-order cone programming and "core-sets", we have developed (1 + ε)-approximation algorithms that perform well practice, especially very dimensions, addition to having provable guarantees. prove existence core-sets size O (1/ε), improving previous bound (1/ε 2 ), empirically how core-set grows with dimension. show our algorithm, which is simple implement, results fast...

Nearest neighbor searching of large databases in high-dimensional spaces is inherently difficult due to the curse dimensionality. A flavor approximation is, therefore, necessary practically solve problem nearest search. In this paper, we propose a novel yet simple indexing scheme, HD-Index , approximate k-nearest queries massive databases. consists set hierarchical structures called RDB-trees built on Hilbert keys database objects. The leaves store distances objects reference objects,...

Finding the k nearest neighbors (kNN) of a query point, or set points (kNN-Join) are fundamental problems in many application domains. Many previous efforts to solve these focused on spatial databases stand-alone systems, where changes database engine may be required, which limit their large data sets that stored relational management system. Furthermore, methods not automatically optimize kNN queries kNN-Joins when additional conditions specified. In this work, we study both and kNN-Join...

Federated Adversarial Learning (FAL) maintains the decentralization of adversarial training for data-driven innovations while allowing collaborative a common model to protect privacy facilities. Before sharing with bigger global aggregation, it allows users change settings locally over many iterations. However, strong network against attackers in Industry 5.0 towards consumer digital ecosystems is challenge methodologies. To solve this issue, novel FAL-based Customized Inequality-Aware...

Potholes are dangerous both to the users of road facilities and even authorities that in charge maintaining roads. Use computer vision real-time detection potholes, as described earlier, is a solution reduce such risks. For pothole new paradigm involving implementation YOLOv8, highly developed object model, employed. In our implementation, we conduct pre-processing images boost features train model on annotated sets. The trained incorporated surveillance system used for processing live...

The presence of GPU from different vendors demands the Lattice QCD codes to support multiple architectures. To this end, Open Computing Language (OpenCL) is one viable frameworks for writing a portable code. It interest find out how OpenCL implementation performs as compared code based on dedicated programming interface such CUDA Nvidia GPUs. We have developed an backend our already existing Wuppertal-Budapest collaboration. In contribution, we show benchmarks most time consuming part...

A formal method for checking equivalence between a given behavioral specification prior to scheduling and the one produced by scheduler is described. Finite state machine with data path (FSMD) models have been used represent both behaviors. The consists of introducing cutpoints in FSMD, visualizing its computations as concatenation paths from cutpoints, identifying equivalent finite segments other FSMD; process then repeated FSMDs interchanged. Unlike many reported techniques, this strong...

This Human-Computer Interaction (HCI) is a field in which the developer makes user friendly system. In this paper, real-time based on hand data glove and k-NN classifier for gesture recognition proposed. HCI becoming more natural intuitive to be used. The important part of body that most frequently used as interaction digital environment thus complexity flexibility motion research topic. To recognize accurately successfully Here, capture current position angle fingers, further classify it...

Given a set of points P and query point q, the reverse furthest neighbor (Rfn) fetches p isin such that q is their among all in PU{q}. This monochromatic Rfn (Mrfn) query. Another interesting version bichromatic (Brfn) P, Q Q, Brfn Q. The Rrfn has many applications spatial databases beyond. For instance, given large residential database (as P) potential sites Q) for building chemical plant complex, construction site should be selected as one maximum number neighbors. an instance paper...

We present an algorithm to reconstruct a collection of disjoint smooth closed curves from n noisy samples. Our noise model assumes that the samples are obtained by first drawing points on according locally uniform distribution followed perturbation each point in normal direction with magnitude smaller than minimum local feature size. The reconstruction is faithful probability approaches 1 as increases.We expect our approach can lead provable algorithms under less restrictive models and for...