Hasil untuk "Electrical engineering. Electronics. Nuclear engineering"

Shu-Yu Liang, Run-Qiu Zhu, Hong Xia et al.

Laser micro-nano processing technologies have been developed to address challenges that are otherwise difficult to solve in industrial applications and diverse scientific fields. These technologies offer designable patterning, arraying capabilities, three-dimensional (3D) processing, and high precision. Recent advancements in laser technologies have demonstrated their effectiveness as powerful tools for micro-nano processing of optoelectronic materials. By utilizing various laser techniques—such as laser-induced polymerization, laser ablation, laser-induced transfer, laser-directed assembly, and laser-assisted crystallization—broad applications in image sensors, displays, solar cells, lasers, anti-counterfeiting, and information encryption have been enabled. This review comprehensively summarizes recent progress in the laser micro-nano processing of optoelectronic materials, including the technologies used for preparation, patterning, arraying, and modification. These laser fabrication methods uniquely provide capabilities such as annealing, phase transitions, and ion exchange in optoelectronic materials. We also discuss the perspectives and challenges for future developments, including the advantages, disadvantages, and potential applications of different laser micro-nano processing technologies. With the rapid advancements in laser micro-nanofabrication, we foresee significant growth in advanced, high-performance optoelectronic applications. This review aims to provide researchers with insights into the current state and future prospects of laser-based micro-nano processing, encouraging further exploration and innovation in this promising field.

Opeyemi Bamigbade, Mark Scanlon, John Sheppard

Embeddings remain the best way to represent image features, but do not always capture all latent information. This is still a problem in representation learning, and computer vision descriptors struggle with precision and accuracy. Improving image embedding with other features is necessary for tasks like image geolocation, especially for indoor scenes where descriptive cues can have less distinctive characteristics. This work proposes a model architecture that integrates image N-dominant colours and colour histogram vectors in different colour spaces with image embedding from deep metric learning and classification perspectives. The results indicate that the integration of colour features improves image embedding, surpassing the performance of using embedding alone. In addition, the classification approach yields higher accuracy compared to deep metric learning methods. Interestingly, different saturation points were observed for image colour-improved embedding features in models and colour spaces. These findings have implications for the design of more robust image geolocation systems, particularly in indoor environments.

SHEN Xueli, HAN Qianwen

Click-Through Rate(CTR) prediction is one of the most important tools for ad placement.Predicting the CTR of an ad and making recommendations to users can increase ad revenue.Field-aware click-through rate prediction models are superior to other click-through rate prediction models because they consider the field information; however, they generate a large amount of redundant information during feature interaction, which results in a low prediction accuracy.A Field-aware Attention Embedding Neural Network(FAENN) model is herein proposed.This model uses a Self-Attentive Mechanism(SAM) to distribute weights to the input vectors of the embedding layer.This helps to clearly identify the importance of the field-aware embedded features, speeding up the training process.The lower-order feature interaction layer focuses on the explicit first-order information of the features and the second-order interaction feature information and outputs the effective features to the higher-order interaction layer.The higher-order feature interaction layer combines the learned interaction vectors with the deep neural network to capture higher-order feature interactions to improve prediction accuracy.The experimental results show that the FAENN model has a higher prediction accuracy than the FM, FFM, and AFM models.

DIVYA, T., RAMAPRABHA, R.

The modeling and the implementation of the embedded switched z-source type cascaded multilevel inverter for photovoltaic (PV) interfaced applications have been presented. With the ability to draw continuous current with an inherent filtering capability, the embedded switched z-source type inverter provides a single-stage conversion with a high output gain which makes it suitable for PV arrays with a low voltage rating. By applying a modular cascading method with a reduced number of H-bridge the multilevel inverter (MLI) is designed for a series-parallel connected PV array. It is controlled using the basic multicarrier PWM technique and synchronized with the grid. With the derived design equations for each mode, its stability has been analyzed and compared for different duty cycles. The developed MLI connected with a PV array has been simulated with the idea of reducing the impact of partial shading by using shorter series of strings, providing a high gain conversion with lower stress across the components. A prototype of the MLI has been tested to give a power rating of 2 kW and the results from both the simulation and the hardware have been discussed.

Nathalia Raquel Salazar Tigrero

El objetivo principal de este artículo se enfoca en el análisis del principio de estabilidad laboral de las personas con enfermedades catastróficas, como un derecho fundamental que permite el goce de una protección diferenciada en el ámbito laboral, en vista de su condición de doble vulnerabilidad reconocida en la Constitución y en la ley Orgánica de la Salud. La metodología científica ha permitido revelar la gran importancia de este principio en la protección de los derechos de los trabajadores. La revisión bibliográfica de la literatura se hizo utilizando las Tecnologías de la Información y las Comunicaciones (TIC) para contextualizar esta área de particular interés a través de la identificación, evaluación e interpretación del conjunto de trabajos de investigación que describen dicha área. Los resultados obtenidos reflejaron que lamentablemente, la inefectiva aplicación de este principio en el Ecuador ha generado frecuentemente condiciones no favorables para estos y que se traducen en la vulneración de sus derechos. Se hace importante que las instituciones gubernamentales produzcan nuevas políticas públicas que garanticen la honra y dignidad de estas personas que llevan una doble condición de vulnerabilidad en el Ecuador.

Jeniffer Gracia, Paola Acevedo, Emiro Trujillo

This research contains a study performed in different companies from the lithographic sector of Bogotá city, Puente Aranda neighborhood. Currently, these companies require high consumption of raw materials and chemical substances to manufacture books, magazines, manuals, posters, brochures, and others. As a result, they lead to wasted paper, inks, glues, and solvents derived from different processes, generating various environmental impacts and occupational diseases. To contribute to these companies' Industrial Safety and Occupational Health and environmental management and identify their environmental impacts, quality management tools and search for solutions were applied to the analysis of processes and products. It allowed the collection of relevant information on resource consumption, waste production (quantity and type of waste) and final disposal, and emissions at the source, heading to identifying the critical points to determine improvement opportunities. According to the results obtained, approximately 21.33 Kg of toxic waste is generated monthly as hazardous waste or wastes during the manufacturing process. It causes different environmental impacts such as atmospheric toxic emissions and contamination of water sources, of which 56% corresponds to the waste and discharges through the production area; these discharges correspond to toxic wastes such as inks, glues, and reagents, which have special handling for this type of companies.

Ahmad Faisal, Frisma Handayanna, Indah Purnamasari

The application of online learning in various educational institutions in the Covid-19 Pandemic has had an impact on behavioral attitudes where many educators and students have also complained about the limited technology facilities, operations, and internet networks in some areas or quotas to access online learning. Followed by the popularity of the Zoom application in supporting education, the authors researched the application of the Technology Acceptance Model (TAM) to the acceptance of the Zoom application in online learning to determine the effect of using applications in online learning with 4 variables accompanied by multiple linear regression hypothesis testing, F-test and T-test. using SPSS. The test results in Perceived Usefulness, Perceived Ease of Use, and Behavioral Intention to Use affect Actual System Usage with significant and positive results of 20.21. Behavioral Intention to Use is more dominant than other variables with a value of 5.31, while the lowest is Perceived Ease of Use with a value of (-0.50).

Haifeng Wan, Lei Gao, Manman Su et al.

Achieving high detection accuracy of pavement cracks with complex textures under different lighting conditions is still challenging. In this context, an encoder-decoder network-based architecture named CrackResAttentionNet was proposed in this study, and the position attention module and channel attention module were connected after each encoder to summarize remote contextual information. The experiment results demonstrated that, compared with other popular models (ENet, ExFuse, FCN, LinkNet, SegNet, and UNet), for the public dataset, CrackResAttentionNet with BCE loss function and PRelu activation function achieved the best performance in terms of precision (89.40), mean IoU (71.51), recall (81.09), and F1 (85.04). Meanwhile, for a self-developed dataset (Yantai dataset), CrackResAttentionNet with BCE loss function and PRelu activation function also had better performance in terms of precision (96.17), mean IoU (83.69), recall (93.44), and F1 (94.79). In particular, for the public dataset, the precision of BCE loss and PRelu activation function was improved by 3.21. For the Yantai dataset, the results indicated that the precision was improved by 0.99, the mean IoU was increased by 0.74, the recall was increased by 1.1, and the F1 for BCE loss and PRelu activation function was increased by 1.24.

Petar Sabev Varbanov, Hon Huin Chin, Jirí Jaromír Klemeš et al.

This article evaluates the processing of Municipal Solid Waste (MSW) and its contribution to sustainability from the viewpoint of its net exergy balance. The evaluation follows the recent framework for estimation of Exergy Footprint and Exergy Profit for a given Process System. The method evaluates the Exergy Assets and Liabilities, estimating the Exergy Profit as the balance of these two. The concept of avoided exergy by substituting the useful chemical to its primary production, similar to the concept of avoided emission is also proposed in this work. The obtained estimate is the specific contribution of the considered MSW processing system. For estimating the overall impacts, the obtained Exergy Profit has to be added to the contributions of the potential upstream and downstream processes. The results show the potential value that can be obtained and sustainability contribution to be achieved by the extraction of useful chemicals from waste and waste-to-energy conversion. The chemical extraction option shows a marginally higher Exergy Profit compared with the typical MSW incineration practice, indicating that, as long as there is a sufficient market demand for the chemical products, this route can be more beneficial. An important outcome is that the product substitution can lead to three-fold increase in the Exergy Profit and the related emission savings.

FAN Xinyang, WANG Min, HONG Xu et al.

BackgroundDigital shaping algorithms are widely applied to improving the energy resolution of digital nuclear instruments.PurposeThis work aims to improve and analyze the performance of cusp-like shaping algorithm for digital nuclear signal with emphasis on the influence of shaping parameters on the shape of the shaped pulse.MethodsBased on the peak pulse forming algorithm, flat-top parameter was introduced into cusp-like pulse shaping algorithm. The fast silicon drift detector (FAST-SDD) detector produced by Amptek company was employed to measure the pulse signal obtained from manganese sample, the effect of shaping parameters on the shape of the output signal and the separation of pile-up pulses were investigated by the cusp-like pulse shaping method, and compared with the common trapezoidal pulse shaping methods. In addition, Cusp-like shaping and trapezoidal pulse shaping were used for the sampled nuclear pulse signals, and then amplitude discrimination was performed to obtain energy spectrum information. Finally, the influences of the two methods on the counting rate and energy resolution of the same time were studied.ResultsThe results show that the cusp-like pulse shaping has a fast falling edge and a narrow pulse width, makes it easier to separate the pile-up pulses than triangle pulse shaping.ConclusionsUnder the same peak time, trapezoidal pulse shaping has more advantages in energy resolution than cusp-like shaping, while cusp-like pulse shaping shows better performance in count rate.

Wendong Wang, Hanhao Li, Dezhi Kong et al.

The utilization of upper extremity exoskeleton robots has been proved to be a scientifically effective approach for rehabilitation training. In the process of rehabilitation training, it is necessary to detect the fatigue degree during rehabilitation training in order to formulate a reasonable training plan and achieve better training efficiency. Based on the integral value of surface electromyography (sEMG), heart rate variability, and instantaneous heart rate, this article proposes a fatigue judgment method for multi-information fusion. Based on the integral value data, the feature extraction of the bioelectrical signals were implemented separately, then the fatigue recognition was conducted using the decision-level data fusion method. The bioelectrical signal acquisition system of electromyogram signals and electrocardiograph signals was developed for upper limb exoskeleton rehabilitation robot, and the acquisition and processing of electromyogram signals and electrocardiograph signals were completed. Finally, the fuzzy logic controller with instantaneous heart rate, heart rate variability, and surface electromyography signal was designed to judge fatigue degree, including the fuzzy device, fuzzy rule selector, and defuzzifier. The moderate fatigue state data were selected for testing, and the experimental results showed that the error of fatigue judgment is 4.3%, which satisfies the requirements of fatigue judgment.

Yun Yu, Xiao Han, Rui Jiang et al.

Uncertainty, a critical factor of causing congestion and extra travel costs in the commute, can be mitigated by providing information. This paper studies the welfare effects of accurate pre-trip information on departure time and route choices in the morning commute under binary stochastic bottleneck capacity. We consider a classical two-route network. Each route has a single bottleneck where congestion occurs during the rush hours. The two routes' bottleneck capacities vary from day-to-day due to events such as bad weather, accidents, and temporary road closures. We derive all equilibrium solutions in consideration of the differences between routes in free-flow travel time, the shadow value of travel time, the severity of bottleneck capacity reductions, and the degree of correlation between two routes in travel conditions. Furthermore, we investigate the benefit changes from zero-information to full-information and prove that accurate pre-trip information about the bottleneck conditions is strictly welfare-improving. Finally, these theoretical results are supplemented by case studies that show examples of benefit gains from pre-trip information.

A.M. Sirunyan, A. Tumasyan, W. Adam et al.

The fiducial cross section for Y(1S) pair production in proton-proton collisions at a center-of-mass energy of 13 TeV in the region where both Y(1S) mesons have an absolute rapidity below 2.0 is measured to be 79±11(stat)±6(syst)±3(B)pb assuming the mesons are produced unpolarized. The last uncertainty corresponds to the uncertainty in the Y(1S) meson dimuon branching fraction. The measurement is performed in the final state with four muons using proton-proton collision data collected in 2016 by the CMS experiment at the LHC, corresponding to an integrated luminosity of 35.9fb−1. This process serves as a standard model reference in a search for narrow resonances decaying to Y(1S)μ+μ− in the same final state. Such a resonance could indicate the existence of a tetraquark that is a bound state of two b quarks and two b¯ antiquarks. The tetraquark search is performed for masses in the vicinity of four times the bottom quark mass, between 17.5 and 19.5 GeV, while a generic search for other resonances is performed for masses between 16.5 and 27 GeV. No significant excess of events compatible with a narrow resonance is observed in the data. Limits on the production cross section times branching fraction to four muons via an intermediate Y(1S) resonance are set as a function of the resonance mass.

Adla Vinod, A. Sinha

This article introduces an adequate method to estimate the unknown parameters of one diode PV cell. Considering this scheme, actual estimation of parameters which are unknown is identified by objective function minimization by employing eminent adequate grey wolf optimizer (GWO) algorithm. Mentioned (GWO) algorithm is implemented for estimation of parameter to one diode PV cell and tabulation results are correlated with others, by recent advance memetic algorithm, cuckoo search, pattern search, simulated annealing, particle swarm optimization, and genetic algorithm. Experimental data and simulation results depict that GWO algorithm is adequate to accomplish all the parameter by great accuracy. This GWO algorithm outperforms previous algorithms correlated in this consideration. Chan, Y., Phang, J.C., Chan, D.S. & Phang, J.C. 1986.  Analytical methods for the extraction of solar-cell single and double diode model parameters from IV characteristics.  Solar Energy.4:1–12. 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M. I. Vashkevich, E. S. Azarov, A. A. Petrovsky

The paper presents a combined noise and acoustic feedback reduction algorithm. The algorithm is based on spectral subtraction and is robust to rapid changes in acoustic feedback path which makes it suitable for using in a smartphone-based hearing aid.

Shuai Zheng, Xiong Du, Jun Zhang et al.

The cooling system, including the thermal grease, heatsinks, plays an important role in the power converters for its reliable operation. While in the long-term operation situation, the cooling system will degrade with different kinds of failure mechanism of the components and finally result in the damage to the power converters. In this paper, the method was proposed to monitor the thermal network parameters of the cooling system using the cooling curves of junction temperature. By establishing the relationship between the RC parameters of Cauer network and time constants of cooling curves, the thermal parameters about cooling system can be obtained. Experimental tests are performed to verify the accuracy of proposed method. Results indicate the degradation state of the cooling system can be evaluated by monitoring the variation of thermal network parameters of the cooling system.

Aftab Khan, Umair Khan, Muhammad Waleed et al.

Cultivation of olive trees for the past few years has been widely spread across Mediterranean countries, including Spain, Greece, Italy, France, and Turkey. Among these countries, Spain is listed as the largest olive producing country with almost 45&#x0025; of olive oil production per year. Dedicating land of over 2.4 million hectares for the olive cultivation, Spain is among the leading distributors of olives throughout the world. Due to its high significance in the country&#x2019;s economy, the crop yield must be recorded. Manual collection of data over such expanded fields is humanly infeasible. Remote collection of such information can be made possible through the utilization of satellite imagery. This paper presents an automated olive tree counting method based on image processing of satellite imagery. The images are pre-processed using the unsharp masking followed by improved multi-level thresholding-based segmentation. Resulting circular blobs are detected through the circular Hough transform for identification. Validation has been performed by evaluating the proposed scheme for the dataset formed by acquiring images through the &#x201C;El Sistema de Informaci&#x00F3;n Geogr&#x00E1;fica de Parcelas Agr&#x00ED;colas&#x201D; viewer over the region of Spain. The proposed algorithm achieves an accuracy of 96&#x0025; in detection. Computation time was recorded as 24 ms for an image size of <inline-formula> <tex-math notation="LaTeX">$300\times300$ </tex-math></inline-formula> pixels. The less spectral information is used in our proposed methodology resulting in a competitive accuracy with low computational cost in comparison to the state-of-the-art technique.

Anatoly Arkadyevich Korotkiy, Boris Fedorovich Ivanov, Alexey Victorovich Panfilov, et al.

The need to formulate accurate requirements for the training organizations engaged in training the service personnel for passenger ropeways (PRW), and pre-certification training on the industrial safety of the ropeways is identified. “A model PRW employee” is presented. It reflects the skills and professional level of an employee, his intellectual potential capacity required under current conditions taking into account the requirements of Rostekhnadzor. The prospects for applying the distance learning methods using the information and communication technologies to significantly reduce the cost of training are identified. Thus, the training time can be distributed more reasonably; the efficiency of the expertise formation increases. The program “Inforesurs-Certification” which has a number of competitive advantages is proposed and analyzed. In particular, it can help employees of the enterprises far removed from the training center passing the pre-certification training. At this, one can work with the program at any time using any device (laptop, tablet PC, smartphone, etc.). The training material retention level increases. The opportunity of regular communication with a tutor or a supervisor (mobile telephony, emailing), and an adequate control contribute to it. This cuts the on-job training time and significantly decreases its cost.

P. Altimari, F. Di Caprio, L. Toro et al.

Hydrogen photo-production by a wild type and two engineered strains of Chlamydomonas reinhardtii was investigated. Growth rate values and hydrogen yields attained as the concentration of acetate and nitrogen vary were compared. In the analysis of microalgal growth, the interaction between organic carbon (acetate) and nitrogen (nitrate) was investigated by recourse to an experimental factorial design. This analysis evidenced the existence of a statistically significant interaction between organic carbon and nitrate. Hydrogen production was attained by cultivating microalgae previously grown in mixotrophic regime with sulphur deprived medium. The influence of varying the photobioreactor headspace on hydrogen production was investigated. This analysis revealed an increase in the hydrogen produced per unit volume of culture of about one order of magnitude when the headspace volume is modified from 100 to 350 mL. This result provides valuable indications on how to design and operate photobioreactors for hydrogen production optimization and was thoroughly discussed in terms of the metabolic pathways activated by sulphur depletion.