Miracle-dz/UniFAR-FTUs huggingface dataset:
A deep learning-based multi-model ensemble method for crack detection in concrete structures

– In civil infrastructures such as buildings, bridges, and tunnels, cracks are initial signs of degradation, which affect the structure's current and future performance adversely. Optimum maintenance plans in terms of cost and safety are important to evaluate the degree of deterioration of a structure. Manual inspection is usually performed, and cracks detected during inspections could help the inspectors to understand the damaged state of the concrete structures. However, these inspections are costly, laborious, and easily prone to human error. An automatic and fast crack detection at the earliest stage is crucial to avoid further degradation of the structure. In the past decades, various deep learning techniques have been introduced by researchers to automate the crack detection task. This paper introduces a deep learning-based multi-model ensemble approach for crack detection in concrete structures. The proposed architecture consists of five different customized convolutional neural networks (CNN) trained on data set created from two public datasets. The dataset consists of 8400 crack and non-crack images having a resolution of 224 * 224. Detailed experiments show that the majority voting ensemble technique shows better performance for crack detection in concrete structures. The accuracy of the individual CNN models 1, 2, 3, and 4 is recorded to be 95%,96%, 95%, and 97%, respectively, while the accuracy of the ensemble techniques is recorded to be 98%.
Combustion and emission characteristics of an off-road diesel engine fuelled with biodiesel–diesel blends

In this work, the combustion and emission characteristics were studied in a 186FA diesel engine fuelled with biodiesel–diesel to examine the effect of the percentage of biodiesel in the blends, and the experimental investigation was conducted with various blending ratios of biodiesel under different operating conditions. In addition, the combustion noise of the diesel engine fuelled with biodiesel–diesel was analysed, and then the emission characteristics of NOx and soot were studied through simulation analysis where the formation rate and distribution of NOx and soot for pure diesel and B20 fuel were described. Based on the simulation data of the original diesel engine fuelled with B20 fuel, the swirl ratio and fuel injection timing were optimised and the technical measures were suggested to reduce the two different emissions simultaneously. The simulation results showed the emission characteristics were optimal when the swirl ratio was 2.7 and fuel injection timing was 7.5° degree of crank angle before top dead centre respectively.
Diversity Discourse Analysis on Top Romanian Organizations

Although the Anglo-American notion of diversity management is dominating most of the global corporate discussions, this concept still has ample room for improvement in the Eastern European context. Having this in mind, in the current study, the websites of the top 20 organizations located in Romania were content analysed in search of statements and definitions related to diversity, equality, or inclusion. The main findings suggest that there are notable differences between how the top Romanian organizations address different diversity dimensions together with how elaborate the diversity discourse is presented. Throughout the research in the Romanian context, 19 diversity dimensions were identified. The majority of the analysed organizations have at least one diversity statement on their official website, addressing a minimum of three diversity dimensions, however, in the case of seven organizations, there was no statement referring to diversity, equality, or inclusion.
MATHEMATICAL AND EXPERIMENTAL MODELS FOR STUDYING SOMATOSENSORY FEEDBACK VIA PRIMARY AFFERENT MICROSTIMULATION

A significant problem with current prostheses is the challenge of controlling the device without being able to ‘feel’ it. Without somatosensory feedback, cognitively demanding visual and attentional processes must be relied upon. However, restoring somatosensory feedback offers the possibility of changing a prosthetic from an extracorporeal tool into a part of the user’s body, while enabling a far more natural control scheme. Although artificial somatosensory feedback of prostheses has been attempted since the 1960s, clinical implementations are lacking. This thesis will focus on the use of electrical stimulation to artificially activate the nervous system to restore feedback. With recent advances in electrode design, the possibility of implanting hundreds of electrodes into the nervous system is becoming a reality. However, current stimulation protocols are oriented towards using only a few electrodes. It is likely that new stimulation paradigms will be needed in order to fully take advantage of multichannel microelectrode arrays. This dissertation examines new methods for studying somatosensory feedback. Dorsal root ganglia microstimulation with concurrent nerve-cuff recordings is used to evaluate stimulation thresholds and the types of neurons first recruited. Computational models are developed to explore recruitment beyond threshold as well as the impact of simultaneous stimulation on changing neural recruitment. Finally, an experimental model is developed that uses the cortical response to primary afferent stimulation to assess information transfer to the brain. Together, these models offer new approaches for improving somatosensory feedback stimulation paradigms.
Dynamics of distribution networks with distributed generation

This paper discusses the results of case studies which assess transient and small-signal stability of distributed generators connected to utility distribution networks. It also presents an investigation of the interaction between the controllers of individual generators. Case studies are based on different levels of generation penetration and a variety of operating conditions of both the networks and the generators. Transient stability and small-signal stability were assessed using commercially available power system simulation software. The interaction between the controllers is initially examined using eigenanalysis. A novel approach, i.e., individual channel analysis and design (ICAD), is then utilised to obtain an insight into the dynamics of the multivariable control problem.
A Meta-Analysis: Whether Repetitive Transcranial Magnetic Stimulation Improves Dysfunction Caused by Stroke with Lower Limb Spasticity

Objective To evaluate the efficacy of repetitive transcranial magnetic stimulation (rTMS) in improving lower limb spasticity after stroke. Methods The PubMed, Web of Science, Cochrane Library, EMBASE, China National Knowledge Infrastructure (CNKI), China Biology Medicine (CBM) disc, China Science and Technology Journal Database (VIP), and Wanfang databases were searched online from their inception to May 2021 for randomized controlled trials (RCTs) involving repetitive transcranial magnetic stimulation for lower extremity spasticity after stroke. Valid data were extracted from the included literature, and the quality evaluation was conducted with the Cochrane Handbook for Systematic Reviews of Interventions along with the Physiotherapy Evidence Database scale (PE-Dro scale). The data that met the quality requirements were systematically analysed using Review Manager 5.4 software. Results A total of 554 patients from seven articles (nine studies) were quantitatively analysed. Outcomes included the Modified Ashworth Scale (MAS), Fugl–Meyer Assessment of Lower Extremity (FMA-LE), Modified Barthel Index (MBI), and Timed Up and Go (TUG), measured as the effect of rTMS compared with controls conditions after treatment. The systematic review showed that rTMS reduced MAS and increased MBI scores, respectively (SMD = −0.24, 95% CI [−0.45, −0.03], P = 0.02; MD = 6.14, 95% CI [−3.93,8.35], P ＜ 0.00001), compared with control conditions. Low-frequency rTMS (LF-rTMS) significantly improved FMA-LE scores (SMD = 0.32, 95% CI [0.13, 0.51], P = 0.001). However, there was no significant difference in FMA-LE scores when using high-frequency rTMS (HF-rTMS) (P > 0.1) and in TUG times (P > 0.1) between the treatment and control groups. Conclusions rTMS was effective in improving spasticity and activities of daily living. LF-rTMS has positive clinical effects on enhancing motor function in patients who experience lower extremity spasticity after stroke. To better validate the above conclusions, more multicentre, high-quality, and double-blind randomized controlled trials are needed.
Band-notched ultra-wideband circular slot antenna with inverted c-shaped parasitic strip

A novel ultra-wideband (UWB) circular slot antenna with a parasitic strip for immunity at 5.2/5.8 GHz is proposed. The antenna has an indented circular stub and an inverted C-shaped parasitic strip embedded inside the circular slot. The desired band-notched UWB operation can be obtained by choosing the size of the inverted C-shaped parasitic strip. The proposed antenna has advantages of low cost, compact size and easy design. Details of the proposed design and experimental results of the constructed antennas are presented.
Innovative Analysis of the Processes within a Society

In our research-project we are developing a duo-mining method (common evaluation of the results from text and data mining), what could extend the traditional measurement systems about the countries in the world. With our methodology we want to sophisticate such world country indexes like the “Index of Economic Freedom”. We are developing such evaluation-system with by these indexes could be confirmed or disconfirmed. The main aim our research to investigate, if it is possible to find an alternative method to evaluate a country. As result of the research we’ll get such a method, what can be based indirect data collection (independent from the replies and originally aim of the data collection) so the result will be untinged from any disfigured influence. In this presentation we are going to show you the weak side of the traditionally indexes, we are going to give a theoretically introduction, and we present the first results. Hopefully based on our methodology it will be possible to measure the processes within the modern societies.
A review of hydrodynamic and energy-transport models for semiconductor device simulation

Since Stratton published his famous paper four decades ago, various transport models have been proposed which account for the average carrier energy or temperature in one way or another. The need for such transport models arose because the traditionally used drift-diffusion model cannot capture nonlocal effects which gained increasing importance in modern miniaturized semiconductor devices. In the derivation of these models from Boltzmann's transport equation, several assumptions have to be made in order to obtain a tractable equation set. Although these assumptions may differ significantly, the resulting final models show various similarities, which has frequently led to confusion. We give a detailed review on this subject, highlighting the differences and similarities between the models, and we shed some light on the critical issues associated with higher order transport models.
Quantum-dot cellular automata : computing with coupled quantum dots

We discuss novel nanoelectronic architecture paradigms based on cells composed of coupled quantum-dots. Boolean logic functions may be implemented in specific arrays of cells representing binary information, the so-called quantum-dot cellular automata (QCA). Cells may also be viewed as carrying analogue information and we outline a network-theoretic description of such quantum-dot nonlinear networks (Q-CNN). In addition, we discuss possible realizations of these structures in a variety of semiconductor systems (including GaAs/AlGaAs, Si/SiGe, and Si/SiO2), rings of metallic tunnel junctions, and candidates for molecular implementations. We report the experimental demonstration of all the necessary elements of a QCA cell, including direct measurement of the charge polarization of a double-dot system, and direct control of the polarization of those dots via single electron transitions in driver dots. Our experiments are the first demonstration of a single electron controlled by single electrons.
Triple band RFID reader antenna for handheld applications

A novel compact microstrip antenna is presented for tri‐band RFID applications.The antenna consisting of a monopole like bent arm with a capacitively coupled small patch, printed on the alternative side of the ground plane, which might be common for multi‐layer reader circuitry. By adjusting the dimension of the bent arm as well as the embedded bent and capacitive coupling, tri‐band antenna has obtained in a small profile. The prototyped antenna shows broad impedance bandwidths (10 dB ≤ return loss) of 17.5, 32.7, and 25.5% accordingly in UHF (902–928MHz), 2.45GHz and 5.8GHz RFID bands with stable radiation characteristics. © 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26044
Parametric Coordinator for Engineering Design

Coordination of design information is essential for the design team to provide accurate technical documents for the actual construction. Design changes are inevitable during any ordinary building project. If the design changes are not properly managed, design conflicts will be created, which will result in more expensive design or even failure in the design-construction process. However, little research has been done to address the issue and thereby provide tools for the management of design changes. This paper presents a novel approach that can facilitate the coordination of design information through managing design changes with the help of a parametric coordinator. Design changes of dimensions between different building components are specially discussed. The proposed parametric coordinator provides each building component with the linking knowledge that is described as a dimensional property and a reference property. A group design method is applied to check the design consistency. Illustrative examples are presented to demonstrate the feasibility of the proposed parametric approach for design change management.
Modeling the Roadside Walking Environment: Pedestrian Level of Service

A method is needed to objectively quantify pedestrians’ perception of safety and comfort in the roadside environment. This quantification, or mathematical relationship, would provide a measure of how well roadways accommodate pedestrian travel. Essentially, it would provide a measure of pedestrian level of service (LOS) within a roadway environment. Such a measure of walking conditions would greatly aid in roadway cross-sectional design and would help evaluate and prioritize the needs of existing roadways for sidewalk retrofit construction. Furthermore, the measure can be used to evaluate traffic-calming strategies and streetscape designs for their effectiveness in improving the pedestrian environment. Such a measure would make it possible to merge pedestrian facility programming into the mainstream of transportation planning, design, and construction. To meet the need for such a method, as well as to fulfill a state mandate to establish levels of service standards for all transportation modes, the Florida Department of Transportation sponsored the development of the Pedestrian LOS Model. The model was developed through a stepwise multivariable regression analysis of 1,250 observations from an event that placed 75 people on a roadway walking course in the Pensacola, Florida, metropolitan area. The Pedestrian LOS Model incorporates the statistically significant roadway and traffic variables that describe pedestrians’ perception of safety or comfort in the roadway environment between intersections. It is similar in approach to methods used to assess automobile operators’ level of service established in the Highway Capacity Manual.
Solitonlike pulses in an actively mode-locked fiber laser

10 GHz repetition rate soliton-like pulses with duration of 29.85 ps have been obtained in an actively mode-locked fiber ring laser. 20 GHz rational harmonic mode-locked soliton-like pulses were also observed. A piezoelectric transducer driven cavity length feedback system was employed to realize the long-term stability of the laser source.
A PROPOSED RECOGNITION SYSTEM FOR ALZHEIMER’S DISEASE BASED ON DEEP LEARNING AND OPTIMIZATION ALGORITHMS

Alzheimer's disease (AD) is an advanced and incurable neurodegenerative disease that causes progressive impairment of memory and cognitive functions due to the deterioration of brain cells. Early diagnosis is substantial to avoid permanent memory loss and develop treatments that will be subtracted in the future. Deep learning (DL) is a vital technique for medical imaging systems for AD diagnostics. The problem is multi-class classification seeking high accuracy. DL models have shown strong performance accuracy for multi-class prediction. In this paper, a proposed DL architecture is created to classify magnetic resonance imaging (MRI) to predict different stages of AD-based pre-trained Convolutional Neural Network (CNN) models and optimization algorithms. The proposed model architecture attempts to find the optimal subset of features to improve classification accuracy and reduce classification time. The pre-trained DL models, ResNet-101 and DenseNet-201, are utilized to extract features based on the last layer, and the Rival Genetic algorithm (RGA) and Pbest-Guide Binary Particle Swarm Optimization (PBPSO) are applied to select the optimal features. Then, the DL features and selected features are passed separately through created classifier for classification. The results are compared and analyzed by accuracy, performance metrics, and execution time. Experimental results showed that the most efficient accuracies were obtained by PBPSO selected features which reached 87.3% and 94.8% accuracy with less time of 46.7 sec, 32.7 sec for features based ResNet-101 and DenseNet-201, receptively.
Attitudes of Students from the Faculty of Education on the Potentially Gifted Preschool Children

This paper presents the results of a research aimed at examining attitudes of the students from the faculties involved in teaching (pedagogical faculties), future educators in preschool institutions, about the potential giftedness of preschool children and working with them. The research was conducted on a sample of 174 students, future preschool educators. It was implemented at the Faculty of Educational Sciences of Pula (Croatia) and at the Faculty of Education of Jagodina (Serbia). The results of the research confirm: that future educators are sufficiently and qualitatively educated to work with gifted children; that future educators would like to have gifted individuals in their preschool groups and would love to work with gifted children; that the relationship between gifted and other kindergarten children is harmonious and gifted children should not be separated into special kindergarten groups; gifted children are a valuable resource for the community, they do not have any difficulties in socialization and they do not waste time in a regular kindergarten, and they are not bored with such kindergarten.
Modeling and simulation of the 16 megabit EPROM cell for write/read operation with a compact SPICE model

A compact SPICE model to stimulate an EPROM cell is presented. Starting from the physics-based MOS model and taking into account impact ionization and the parasitic bipolar effect, 'avalanche' leading to snap-back is described. Gate current, based on the 'lucky-electron' model, is integrated in one dimension along the channel. The floating gate voltage is induced by external biases and trapped charges. Threshold voltage as seen from the control gate is considered. Results from simulations of transient behavior during writing and reading operations are shown; they were satisfactorily used for the submicron cell in the design of the 16 megabit EPROM. <<ETX>>
Multilevel lot-sizing heuristics and freezing the master production schedule in material requirements planning systems

This paper compares the performance of a new improved heuristic (STIL) proposed by Coleman and McKnew (1991, Decision Sciences , 22 , 136-156) Wagner-Whitin (WW), cost-modified (MWW) and some simple lot-sizing rules found to perform well by Zhao et al . (1995, International Journal of Production Research , 33 (8), 2241-2276). It also investigates the impact of the lot-sizing ruleson the selection ofthe parametersfor freezing the master production schedule (MPS). The experimental settings include forecasting, master production scheduling and material requirements planning under a rolling time horizon. The result of the study shows that the STIL heuristic, WW rule and MWW rule do not really outperform the simple costmodified Silver-Meal (MSM) and the Silver-Meal/Lot-forLot (SM/LFL), even though they require substantially higher comheuristics against those of the Wagner-Whitin putation time. The study also shows that the selection of the parameters for freezing the MPS is not significantly influenced by the .
Knowledge on Newborn Life Support among the Healthcare Providers in a Tertiary Care Maternity Hospital in the Southern Province, Sri Lanka

Introduction The newborn life support (NLS) is a set of educational guidelines established by the academies of Paediatrics that outline the proper procedures for resuscitation of a newborn. The objective of this study was to determine the knowledge on NLS among the healthcare providers (HCPs) in a tertiary care maternity hospital in the Southern Province, Sri Lanka. Methods A hospital-based cross-sectional study was carried out among doctors, nurses, and midwives, using a self-administered questionnaire. Comparison of knowledge among different categories was made using the chi-square test. Total sample of 191 consisted of 118 (61.8%) nurses, 33 (17.3%) midwives, and 36 (18.8%) doctors. The majority of HCPs (76.7%) had good knowledge of NLS; however, following guidelines on NLS among HCPs was poor (33%). According to the category, 91% of doctors and 78% of nurses had good knowledge, whereas only 48% of midwives had good knowledge. The difference of knowledge on NLS among different categories of HCPs was statistically significant (p < 0.001). Only 33% of HCPs had good knowledge of following NLS guidelines. Of them, 52% were doctors, 31% were nurses, and only 18% were midwives. The difference in adherence to NLS guidelines among different categories of HCPs was highly significant statistically (p=0.003). Conclusion The majority of the healthcare providers had good knowledge of NLS. There was a significant difference in the level of knowledge on NLS among different categories of HCPs. Gaps in the knowledge in following guidelines of NLS were noted in the majority. Newborn resuscitation has to be included in nursing and midwifery curricula, and training on NLS is essential in the orientation programs for newly recruited HCPs in maternity hospitals.
RECONFIGURABLE INTELLIGENT SURFACES FOR WIRELESS COMMUNICATIONS: BEYOND 5G

The advancement in the technology has led to the tremendous variance in the 5G domain. Development in some of the physical layer technologies would help think beyond 5G. One such technology is Intelligent Reflecting Surfaces (IRS). IRS caters to focusing the reception of the signal, only to the intended receiver, without loss of power. This otherwise termed as beamforming. In this a new and vast dimension, the wireless environment, in which signal propagates, to be tuned, for reliable transmission. The paper deals about what are Intelligent Reflecting Surfaces, features, false ideas, and critical analysis of how IRS can be a part of future beyond 5G.