Estimating Bridge Deterioration Age Using Artificial Neural Networks حسب AL HUSSEIN, ASEEL

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Data redundancy management for leaf-edges in connected environments حسب Mansour, Elio

"…To address these limitations, we propose here DRMF: Data Redundancy Management for leaF-edges allowing to identify and remove data redundancies in connected environments at the device level. DRMF considers both static and mobile edge devices, and provides two algorithms for temporal and spatio-temporal redundancy detection. …"
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A conjugate self-organizing migration (CSOM) and reconciliate multi-agent Markov learning (RMML) based cyborg intelligence mechanism for smart city security حسب S. Shitharth (12017480)

"…However, it limits the critical problems of high time complexity, computational cost, difficulty to understand, and reduced level of security. Therefore, the proposed work intends to implement a group of novel methodologies for developing an effective Cyborg intelligence security model to secure smart city systems. …"

C-3PA: Streaming Conformance, Confidence and Completeness in Prefix-Alignments حسب Raun, Kristo

"…This paper introduces a novel approximate streaming conformance checking algorithm that enriches prefix-alignments with confidence and completeness measures. …"
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A simple approach for testing web service based applications حسب Tarhini, Abbas

"…In our technique, a web application and its composed components are specified by a two-level abstract model. The web application is represented as Task Precedence Graph (TPG) and the behavior of the composed components is represented as a Timed Labeled Transition System (TLTS). …"
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SemIndex+: A semantic indexing scheme for structured, unstructured, and partly structured data حسب Tekli, Joe

"…Various weighting functions and a parallelized search algorithm have been developed for that purpose and are presented here. …"
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Oversampling techniques for imbalanced data in regression حسب Samir Brahim Belhaouari (9427347)

"…For image datasets, we employ Multi-Level Autoencoders, consisting of Convolutional and Fully Connected Autoencoders. …"

Blockchain-Based Decentralized Architecture for Software Version Control حسب Muhammad Hammad (17541570)

"…<p dir="ltr">Version control is an important component of configuration management, and most enterprise-level software uses different tools and technologies to manage the software version control such as CVS, Subversion, or Perforce. …"

CAD TOOL FOR THE AUTOMATIC-GENERATION OF MICROPROGRAMS حسب Sait, Sadiq M.

"…Abstract A methodology for automatic synthesis of microprograms for digital systems modeled in the UAHPL register-transfer-level language is described. …"
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A novel few shot learning derived architecture for long-term HbA1c prediction حسب Marwa Qaraqe (10135172)

"…A novel normalized FSL-distance (FSLD) metric is proposed for accurately separating the features of different HbA1c levels. Finally, a K-nearest neighbor (KNN) model with majority voting is implemented for the final classification task. …"

The architecture of a highly reconfigurable RISC dataflow array processor حسب Sait, Sadiq M.

"…The processor array is modelled at the behavioural level in VHDl. The gate level implementation and VLSi layout of both the PE and the array are obtained with the help of OASIS silicon compiler by translating the functionality. …"
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Impact Of Inspection Errors On The Performance Measures Of A General: Repeat Inspection Plan حسب Duffuaa, S. O.

"…The impact of the errors is studied by conducting sensitivity analysis on the errors utilizing computer software which implements an algorithm that determines the optimal parameters of the model of the plan. …"
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Mobile Energy Storage Systems for Benefit Maximization in Resilient Smart Grids حسب Alshaal, Dima

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Integration of nonparametric fuzzy classification with an evolutionary-developmental framework to perform music sentiment-based analysis and composition حسب Abboud, Ralph

"…Unlike existing solutions, MUSEC is: (i) a hybrid crossover between supervised learning (SL, to learn sentiments from music) and evolutionary computation (for music composition, MC), where SL serves at the fitness function of MC to compose music that expresses target sentiments, (ii) extensible in the panel of emotions it can convey, producing pieces that reflect a target crisp sentiment (e.g., love) or a collection of fuzzy sentiments (e.g., 65% happy, 20% sad, and 15% angry), compared with crisp-only or two-dimensional (valence/arousal) sentiment models used in existing solutions, (iii) adopts the evolutionary-developmental model, using an extensive set of specially designed music-theoretic mutation operators (trille, staccato, repeat, compress, etc.), stochastically orchestrated to add atomic (individual chord-level) and thematic (chord pattern-level) variability to the composed polyphonic pieces, compared with traditional evolutionary solutions producing monophonic and non-thematic music. …"
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A lightweight adaptive compression scheme for energy-efficient mobile-to-mobile file sharing applications حسب Sharafeddine, Sanaa

"…Moreover, we derive an empirical energy model that analytically quantifies the energy consumed during data transmission as a function of the signal strength level and during data compression as a function of the data size. …"
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Image-CNN Based Process Control of Profile حسب Zeinab, Zeinab Jihad

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Exploring the System Dynamics of Covid-19 in Emergency Medical Services حسب Ali, Muhammad

"…The predictive analysis yielded a model of response times for emergency missions through machine learning, specifically using a random forest algorithm. …"
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Application of Data Mining to Predict and Diagnose Diabetic Retinopathy حسب Haniyeh, Maryam

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Reinforcement Learning-Based School Energy Management System حسب Yassine Chemingui (18891757)

"…The performance is evaluated on a school model simulated environment considering thermal comfort, CO2 levels, and energy consumption. …"

Reliability of artificial intelligence in predicting total knee arthroplasty component sizes: a systematic review حسب Loay A. Salman (14150322)

"…All included studies were published between 2021 and 2022, with a total of nine different AI algorithms reported. Among these AI models, the accuracy of TKA femoral component sizing prediction ranged from 88.3 to 99.7% within a deviation of one size, while tibial component sizing exhibited an accuracy ranging from 90 to 99.9% ± 1 size.…"