Miracle-dz/UniFAR-FTUs huggingface dataset:
Explainable Demand Forecasting: A Data Mining Goldmine

Demand forecasting is a crucial component of demand management. Value is provided to the organization through accurate forecasts and insights into the reasons driving the forecasts to increase confidence and assist decision-making. In this Ph.D., we aim to develop state-of-the-art demand forecasting models for irregular demand, develop explainability mechanisms to avoid exposing models fine-grained information regarding the model features, create a recommender system to assist users on decision-making and develop mechanisms to enrich knowledge graphs with feedback provided by the users through artificial intelligence-powered feedback modules. We have already developed models for accurate forecasts regarding steady and irregular demand and architecture to provide forecast explanations that preserve sensitive information regarding model features. These explanations highlighting real-world events that provide insights on the general context captured through the dataset features while highlighting actionable items and suggesting datasets for future data enrichment.
MODEL PREDICTIVE BASED LOAD FREQUENCY CONTROL DESIGN

In this paper, A new load frequency control (LFC) using the model predictive control MPC technique is presented. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. A simplified frequency response model is introduced, and physical constraints of the governor and turbine are considered in this model. The model was employed in the MPC structure. Digital simulations for a single control area are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the system performance has a good robustness in the face of uncertainties due to governor and turbine parameters variation and load disturbance. A performance comparison between the proposed controller and a conventional integral control scheme is carried out confirming the superiority of the proposed MPC technique.
Spherical fuzzy extension of AHP‐ARAS methods integrated with modified k‐means clustering for logistics hub location problem

Like most other industries, logistics services are currently encountering enormous transformation. Many companies worldwide are applying big data analytics to implement operational strategies and facilitate location selection. Logistics companies need to focus on now and explore some futures of logistics hub location problems. Creating a profitable logistic network is a crucial task for airline and postal services. To establish a cost‐effective network, transportation expenses should be decreased, and networks should be simplified. Hub location problem is born out of these needs. The concept of hub cumulates the flows and makes networks more reliable. In this article, a novel hub location selection approach is introduced in a group decision making (GDM) environment with uncertainty by integrating a modified weighted k‐means clustering algorithm with multi‐criteria decision‐making (MCDM) tools. The combined MCDM method integrates analytic hierarchy process (AHP) to measure criteria weights and Additive Ratio Assessment technique to measure the performance of hub location alternatives in a spherical fuzzy set (SFS) environment. The SFS has shown definite advantages in handling vagueness and uncertainty over crisp, fuzzy, or intuitionistic fuzzy sets to depict experts' evaluations with a richer structure, allowing for more representative decision making. Using Turkish logistics data, big data algorithm facilitates 15 possible locations, and these sites are ranked in order by the integrated GDM methodology. The validation of the proposed evaluation model is illustrated in an application of the network structure in Turkey. Finally, sensitivity and comparison evaluations are introduced to demonstrate the feasibility and effectiveness of the proposed approach.
A framework for system dependability validation under the influence of intrinsic parameters fluctuation

This paper presents a framework to analyze and evaluate effects of cell failures induced by impact of intrinsic parameters fluctuation (IPF) on system dependability. The method of evaluation is based on generating the actual cell failures model and the realistic conditions of hardware-software interactions, where the actual error pattern can be captured. The case study of this paper is the impact of cell failures in L1 data cache of a general-purpose microprocessor. The failure modules are generated corresponding to the individual and combined impact of IPF sources in nanometer scale Ultra Thin Body – Silicon on Isolator (UTB-SOI) transistor on 6T-SRAM cell stability. A novel fault injection mechanism has been introduced to propagate errors, through modifying data of cache transactions according to error(s) incurred, dynamically at system-level. By applying a representative system workload using a well-selected suit of real benchmark programs, this study demonstrates that the framework: 1) provides an accurate user visible description for the implications of cell failures at the higher levels of abstraction induced by IPF sources at the lower levels of abstraction, 2) links individual and combined impact of IPF sources with the corresponding implications at system-level which offers a tool to systems designer to involve IPF impacts within the design plan, 3) allows for a detailed simulation process of a system-level environment in the presence of cell failures induced by IPF within an accepted period of time using the look-up file technique and thus offers a foundation to system dependability studies that require vast statistical models, 4) offers high credible evaluation results because the framework is based on the actual error pattern incurred in the system, and 5) improves system reliability where it offers valuable perceptions for an optimal fault tolerance technique in L1 cache with a high failures rate.
Statistical analysis of kinetic energy entrainment in a model wind turbine array boundary layer

For large wind farms, kinetic energy must be entrained from the flow above the wind turbines to replenish wakes and enable power extraction in the array. Various statistical features of turbulence causing vertical entrainment of mean-flow kinetic energy are studied using hot-wire velocimetry data taken in a model wind farm in a scaled wind tunnel experiment. Conditional statistics and spectral decompositions are employed to characterize the most relevant turbulent flow structures and determine their length-scales. Sweep and ejection events are shown to be the largest contributors to the vertical kinetic energy flux, although their relative contribution depends upon the location in the wake. Sweeps are shown to be dominant in the region above the wind turbine array. A spectral analysis of the data shows that large scales of the flow, about the size of the rotor diameter in length or larger, dominate the vertical entrainment. The flow is less incoherent below the array, causing decreased vertical fluxes the.
Detection of shorted-turns in the field winding of turbine-generator rotors using novelty detectors-development and field test

A method for detecting shorted windings in operational turbine-generators is described. The method is based on the traveling wave method described by El-Sharkawi, et. al. (1971). The method is extended in this paper to operational rotors by the application of a neural network feature extraction and novelty detection. The results of successful laboratory experiments are also reported.
Virtual display aids for teleoperation

This paper describes a concept called virtual image and discusses its applications to telerobotics. The virtual image is a graphical tool which allows the operator to see the environment from any perspective that he wants. This concept proves critical in two situations: (1) when a sensor (i.e., wrist camera) from which the operator needs information is obscured and the information is not directly provided by any sensor, and (2) when the task requires moving a selected object relative to another object which is itself moving. These two problems are discussed in detail along with the method by which the virtual image concept offers the solution. A simulation was created in which the virtual image concept was tested under a varying set of parameters for a teleoperational task. The parameter categories are camera/graphical views, graphical display content, written display content, and operator interface. The simulation is described in detail along with the results and conclusions. In addition, the possibility of introducing automation as an aid for teleoperation is discussed and a relevant simulation scenario is analyzed. Throughout the paper, the real-world applicability of these ideas is emphasized.
Nursing care for bed bath in patients with COVID-19: an integrative review.

OBJECTIVE to identify the main nursing care procedures for performing bed bath in patients with COVID-19. METHOD an integrative literature review. Five stages were followed for this research: research question elaboration (identification of the problem), search of studies in literature, study assessment, data analysis, and presentation of review. To search for primary studies, the VHL and SciELO databases were selected. RESULTS initially, 55 publications were found. After reading and analyzing the abstracts, the sample consisted of 15 studies. CONCLUSION patients with the new coronavirus have specific care to perform a bed bath, oral, intimate and skin hygiene. It is important that professionals use adequate personal protective equipment, perform humanized care, continuously observing patients' vital signs to avoid occurrence of adverse events, promoting patient safety.
Vibration control of ultra-sensitive facilities

Feature sizes continue to decrease in computer processors, display units and media, while experimental facilities demand ever increasing measurement resolution. As a result, the requirements for controlling vibration levels in the structures of factories and laboratories become more severe and govern structural design more frequently. Design guidance in the UK and elsewhere is so far limited and vibration control exercises are presently case specific. Vibration control is a process by which simulated or measured vibration response of a vibration-sensitive facility can be managed and mitigated, before it is too late and the experiment or industrial process has failed (at great cost). Vibration control, as defined here, involves establishment of acceptance standards (vibration norms), measurement or estimation of inputs, simulation of structures and foundations with design iterations, study of vibration propagation mechanisms and finally comparison with vibration norms. The present paper distils experiences.
Influence of Asphalt Emulsion Inclusion on Fly Ash/Hydrated Lime Alkali-Activated Material

Supplementary cementitious materials have been widely used to reduce the greenhouse gas emissions caused by ordinary Portland cement (OPC), including in the construction of road bases. In addition, the use of OPC in road base stabilization is inefficient due to its moisture sensitivity and lack of flexibility. Therefore, this study investigates the effect of hybrid alkali-activated materials (H-AAM) on flexibility and water prevention when used as binders while proposing a new and sustainable material. A cationic asphalt emulsion (CAE) was applied to increase this cementless material’s resistance to moisture damage and flexibility. The physical properties and structural formation of this H-AAM, consisting of fly ash, hydrated lime, and sodium hydroxide, were examined. The results revealed that the addition of CAE decreased the material’s mechanical strength due to its hindrance of pozzolanic reactions and alkali activations. This study revealed decreases in the cementitious product’s peak in the x-ray diffraction analysis (XRD) tests and the number of tetrahedrons detected in the Fourier transform infrared spectroscopy analysis (FTIR) tests. The scanning electron microscope (SEM) images showed some signs of asphalt films surrounding hybrid alkali-activated particles and even some unreacted FA particles, indicating incomplete chemical reactions in the study material’s matrix. However, the H-AAM was still able to meet the minimum road base strength requirement of 1.72 MPa. Furthermore, the toughness and flexibility of the H-AAM were enhanced by CAE. Notably, adding 10% and 20% CAE by weight to the hybrid alkali-activated binder produced a significant advantage in terms of water absorption, which can be explained by its influence on the material’s consolidation of its matrices, resulting in significant void reductions. Hence, the outcomes of this study might reveal an opportunity for developing a new stabilizing agent for road bases with water-prevention properties and flexibility that remains faithful to the green construction material concept.
A path planning method for real time correction of image distortion in atomic force microscope

The image quality and accuracy of the atomic force microscope are seriously affected due to drift and hysteresis of Piezoelectric positioning platform. Currently, the distortion correction methods had been confined in tracking a certain area or image correction after images are acquired, which makes it difficult for the atomic force microscope (AFM) to obtain low distortion images. In this study, the scanning path of the AFM is redesigned. The scanning route is spiral in a whole with many blocks which are scanned once at a time, and the drift of blocks is corrected in real-time during the scanning process. This method is suitable for real-time correction of drift during long-time scanning, compared with the traditional scanning method.
ANFIS Model for Time Series Prediction

This paper describes an architecture of ANFIS (adaptive network based fuzzy inference system), to the prediction of chaotic time series, where the goal is to minimize the prediction error. We consider the stock data as the time series. This paper focuses on how the stock data affect the prediction performance. In the experiments we changed the number of data as input of the ANFIS model, the type of membership functions and the desired goal error, thereby increasing the complexity of the training.
Development of High Intensity Interval Training (HIIT) for Reactive Agility Tennis: Literature Review and Validity of Aiken

Background The purpose of this study was to examine High Intensity Interval Training (HIIT) for Reactive Agility Tennis with a literature review approach and develop HIIT for Reactive Agility Tennis with Aiken validation. Methods This research method consists of two stages: the first stage using the Literature review method and the second stage is Aiken validation. In the first stage, the participants of this research used documents. Data collection through the Pubmed database, and Google Scholar, used the PRISMA. Data analysis uses thematic analysis through three stages. The second stage is validating the HIIT model for Reactive Agility Tennis. The participants of this study used eight experts. Data analysis using the Aiken formula. Results the results of previous research on HIIT for reactive agility tennis found similarities, namely in general, using high intensity, a minimum number of eight types, training frequency at least 3 times per week, whereas in general the difference in training intervals, the type of HIIT exercise in previous studies for Increases reactive tennis agility. In addition, there are very few HIIT studies for reactive agility in tennis. Therefore, it is necessary to develop HIIT for reactive agility tennis. The second stage of this research has found a high validity of Aiken value in the development of HITT for reactive agility tennis. Conclusions HIIT highly increasing reactive tennis agility, therefore, HIIT can be used by coaches to increase tennis athletes' reactive agility, and further research needs to be done. Systematic Review registrations: SYSR-D-21-00999
Research on Dynamic Clonal Selection Algorithm Combined with Artificial Fish School

As in the dynamic clone selection algorithm, the detector use factor is low, the overall importance is bad, this article proposed that the behavior of follows, gathers which has the overall importance and the rapid convergence in the artificial school of fish algorithm applicant in the dynamic clone selection algorithm detector generation phase. Meanwhile, the efficiency of algorithm is improved, and many questions which stochastically the detector takes are solved. The simulation experiment indicated that the improved algorithm has the advantage of the artificial school fish algorithm and made up the question that earlier period to restrain slowly, the detector production efficiency low in its own system.
THE KIMOLOS GEOTHERMAL DESALINATION PROJECT

The Kimolos Geothermal Desalination Project is concerned with the exploitation of the low enthalpy geothermal potential of Kimolos island for the production of fresh water through geothermal water desalination, with the intent of achieving water sufficiency for the island. Funding for the project was provided by the THERMIE EU-DGXVII program through contract No. GE-438-94-HE. The island of Kimolos, faces pronounced water scarcity problems, as other Aegean Sea islands also do. Nevertheless, Kimolos Isl. is fortunate enough to possess a very significant source of environmentally friendly energy which is renewable and of low cost, that is the low enthalpy geothermal energy potential. The desalination method applied is that of Multiple-Effe ct Distillation (MED) with distillation under vacuum in vertical tubes. The unit will use low enthalpy geothermal energy (with a wellhead temperature of approximately 61 o C) as the heating and feed-water medium. The unit, built during the period of 1998-1999 produced, in average, 3.24 m 3 /h of fresh water, when a geothermal water flow-rate of 50 m 3 /h at a wellhead temperature of 61 o C was utilized. The fresh water produced had a Total Dissolved Solid (TDS) content of less than 10 ppm, according to the plant’s built-in salinity meter. Several tests to measure and quantify the differential production of the unit tookplace during the monitoring period. Different geothermal water yields were tested against the fresh-water production rate of the unit. According to the results of this project the exploitation of low enthalpy geothermal energy in the unit results in the substitution of at least 500 TOE/year [1 TOE (Tonnes Oil Equivalent) = 8,000,000 kcal/h]. Our intention in this demonstrative project is to demonstrate the technology of producing clear fresh desalinated water from low enthalpy geothermal resources on Kimolos Isl. Further-on, we investigate the technical and financial feasibility for applying and disseminating such innovative desalination schemes in other regions of Greece and the EU with similar renewable energy sources potential.
Coupled Vibration Analysis of a Fluid-Filled Pipe by Wavenumber Prediction

The stability and vibration of fluid-filled pipes are important in many engineering situations and have been extensively studied. In this paper, coupled fluid–structure analysis is carried on by wavenumber prediction. Pipe equations for axisymmetric wave motion are derived, and two kind of axial waves are studied analytically at low frequencies, i.e., , which is a predominantly fluid-borne wave, and , is predominantly a shell wave. Numerical results are subsequently given to show the definitely influence of the pipe and the fluid.
Increasing numbers of harbour seals and grey seals in the Solent

Abstract Harbour seals (Phoca vitulina) and grey seals (Halichoerus grypus) both occur within the UK, but display regional contrasting population trends. While grey seals are typically increasing in number, harbour seals have shown varying trends in recent decades following repeated pandemics. There is a need for monitoring of regional and local populations to understand overall trends. This study utilized a 20‐year dataset of seal counts from two neighboring harbours in the Solent region of south England. Generalized additive models showed a significant increase in the numbers of harbour (mean 5.3–30.5) and grey (mean 0–12.0) seals utilizing Chichester Harbour. Conversely, in Langstone Harbour there has been a slight decrease in the number of harbour seals (mean 5.3–4.0). Accompanying photographic data from 2016 to 18 supports the increase in seal numbers within Chichester Harbour, with a total of 68 harbour and 8 grey seals identified. These data also show evidence of site fidelity of harbour seals in this area, with almost a quarter of animals resighted within the past three years. Overall, this long‐term study indicates an increasing number of both harbour and grey seals within the Solent. However, more research is required to identify the drivers of this trend.
Development of Prototype Fractional Order Controller for a Grid-Tied Photovoltaic System

This brief presents design of a robust fractional order proportional-integral (FO-PI) prototype controller for a grid connected photovoltaic (PV) system. The robustness in face of parameter variation is handled by designing a suitable controller considering sensitivity function, gain margin and phase margin for both inner and outer control loops. As FO-PI controller is not yet available in physical form and due to complexity involved in grid-tied PV system, we propose an alternative way of hardware implementation of inner loop FO-PI controller by using fractor through $RC$ ladder network. Firstly, an emulator circuit of the inner current loop comprising the FO-PI controller (including fractor and the proportional gain) along with the transfer function of inverter and filter is developed and the response is verified through a real-time simulator (OPAL-RT). Finally, the FO-PI part of the emulator circuit is interfaced with the PC target to form a hardware-in-loop (HIL) by employing OPAL-RT. The performance of the complete system is verified through OPAL-RT simulator. The result shows the improved robustness by the proposed control design method.
Lost in Virtual Reality? Cognitive Load in High Immersive VR Environments

With the rapid development of high Immersive Virtual Reality (IVR), cognitive load computing has been much studied in its relationship to the design and implementation of high IVR. This study presents a systematic review of the literature on cognitive load in high IVR. A total of 46 empirical studies are selected based on selection criteria. The study reviews the studies and extracts information to answer research questions. The study reports trends in publication, including dates and originating countries of publication, participant selection and sample size, research areas, high IVR devices used, measurement channels and methods, and main results. Findings identify research gaps and suggest reconsidering the relationship between cognitive load and outcomes in high IVR. Furthermore, this study points to several future directions researchers could take to help designers and practitioners to apply high IVR more effectively.