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This paper introduces HLLSet (HyperLogLog Set), a probabilistic data structure that behaves like a set under all standard operations while containing no explicit elements. Unlike traditional HyperLogLog, which only estimates cardinality, HLLSets support full set operations (union, intersection, difference) through enhanced register structures and provide a principled framework for representing semantic relationships. We establish a…

Our world is characterised by uncertainty and complex, relational structures that carry temporal information, yielding large dynamic probabilistic relational models at the centre of many applications. We consider an example from logistics in which the transportation of cargoes using vessels (objects) driven by the amount of supply and the potential to generate revenue (relational) changes…

Contextual continuous word representation showed promising performances in different natural language processing tasks. It stems from the fact that these word representations consider the context in which a word appears. But until recently, very little attention was paid to the contextual representations in Arabic question classification task. In the present study, we employed a contextual…

The technical and vocational institutions are the key feeders for skilled human capital in the robotic revolution economy. It is essential to engage the students by creating new, affordable robotics at a fraction of the cost. This study presents the design and simulation of a six-axis robot manipulator specifically made for education and training. The…

Face sketch recognition aims at matching face sketch images to face photo images. The main challenge lies in modality discrepancy between face photo and sketch images. In this work, we propose a new facial sketch-to-photo recognition approach by adopting VGG-Face deep learning network, with which face images can be represented by compact and highly discriminative…

The increase of textual information published in Arabic language on the internet, public libraries and administrations requires implementing effective techniques for the extraction of relevant information contained in large corpus of texts. The purpose of indexing is to create a document representation that easily find and identify the relevant information in a set of documents.…

The determination of length of survival, or prognosis, is often viewed through statistical hazard models or with respect to a future reference time point in a classification approach (e.g., survival after 2 or 5 years). In this research, regression was used to determine a patient’s prognosis. Also, multiple behavioral representations of clinical data, including difference…

In this work, we present CIRB-Edge, a novel integer compression method designed specifically to overcome the limitations of traditional techniques such as Huffman coding, Delta encoding, and dictionary-based algorithms. These legacy methods often fall short in meeting the stringent requirements of secure, energy-efficient, and real-time edge computing due to their high computational overhead, memory demands,…

As society ages, the imbalance between family caregivers and elderly individuals increases, leading to inadequate support for seniors in many regions. This situation has ignited interest in automatic health monitoring systems, particularly in fall detection, due to the significant health risks that falls pose to older adults. This research presents a vision-based fall detection system…

Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…

The aim of this study is to develop an advanced framework that not only recognize the dominant facial emotion, but also contains modules for gesture recognition and text-to-speech recognition. Each module is meticulously designed and integrated into unified system. The implemented models have been revised, with the results presented through graphical representations, providing prevalent emotions…

We present an inverted pendulum design using readily available V-slot rail components and 3D printing to construct custom parts. To enable the examination of different pendulum characteristics, we constructed three pendulum poles of different lengths. We implemented a brake mechanism to modify sliding friction resistance and built a paddle that can be attached to the…

In the context of adopting cloud Infrastructure-as-a-Service (IaaS), prospective consumers need to consider a wide array of both business and technical factors associated with the service. The development of an intelligent tool to aid in the assessment of IaaS offerings is highly desirable. However, the creation of such a tool requires a robust foundation of…

In a challenging and increasingly technological world, it is important to promote critical thinking, multidisciplinary problem solving, and collaboration through STEAM education; however, there are important economic, administrative, and especially pedagogical manage- ment limitations for its implementation at the secondary level. Therefore, this paper presents systematic recommendations for an effective and sustainable implementation of STEAM…

Sleep stage performs a vital role in people’s daily lives in the detection of sleep-related diseases. Conventional automated sleep stage classifier models are not efficient due to the complexity linked to the design of mathematical models and extraction of hand-engineering features. Further, quick oscillations amongst sleep stages frequently lead to indistinct feature extraction, which might…

In the present contribution, a robust output H∞ control ensuring the stability, reliability and security for nonlinear systems when actuator attacks (data deception attacks) occur. A new design method based on the polytopic rewriting of the attacked system as an uncertain one subject to external disturbances will be detailed. Robust polytopic state feedback observer sta-…

Social networks have become a valuable platform for tracking and analyzing Internet users’ feelings. This analysis provides crucial information for decision-making in various areas, such as politics and marketing. In addition to this challenge and our interest in the field of big data and sentiment analysis in social networks, we have dedicated this work to…

Real-world applications modelled by time-dependent dynamical systems with specific properties such as long-range dependence or self-similarity are usually described by fractional Brownian motion. The investigation of the qualitative behaviour of its realisations is an important topic. For this purpose, efficient mappings from realisations of the dynamical system, i.e., time series, to a set of scalar-valued…

Classical clustering algorithms often require an a-priori number of expected clusters and the presence of all documents beforehand. From practical point of view, the use of these algorithms especially in more dynamic environments dealing with growing or shrinking corpora therefore is not applicable. Within the last years, graph-based representations of knowledge such as co-occurrence graphs…

Virtual reality (VR) is finding applications in a wide range of industries; however, a significant number of users find VR experience considerably different from the real-world experience. To match the real-world experience, the VR experience should look real, should be immersive, and be in line with the users’ anticipation. Achieving realism in the virtual representation…

This paper presents a new floating-point technology: Bounded Floating Point (BFP) that constrains inexact floating-point values by adding a new field to the standard floating point data structure. This BFP extension to standard floating point identifies the number of significant bits of the representation of an infinitely accurate real value, which standard floating point cannot.…

In this study, we developed and evaluated an automatic abstractive summarization algorithm in Japanese using a neural network. We used a sequence-to-sequence encoder-decoder model for practical purposes. The encoder obtained a feature-based input vector of sentences using the bidirectional encoder representations from transformers (BERT) technique. A transformer-based decoder returned the summary sentence from the output…

Advances in channel modeling allow wireless communication designers to accurately model and understand the channel’s phenomena within different propagation scenarios. A precise channel model results in the wireless system’s optimized performance while considering trade-offs due to the effects of the channel. The geometric-based stochastic channel model considers different interacting objects affecting the parameters using the…

This paper focuses on a string encoding algorithm, which produces sparse distributed representations of text data. A characteristic feature of the algorithm described here, is that it works without tokenizing the text and can avoid other data preparation steps, such as stemming and lemmatization. The text can be of arbitrary size, whether it is a…

The difficulty of learning the underlying structure between processes is a common task found throughout the sciences, however not much work is dedicated towards this problem. In this paper, we attempt to use the language of structure learning to address learning the dynamic influence network between partially observable processes represented as dynamic Bayesian networks. The…