Sensitivity encoding (SENSE) is a parallel magnetic resonance imaging (MRI) reconstruction model by utilizing the sensitivity information of receiver coils to achieve image reconstruction. The existing SENSE-based rec...
详细信息
Non-thermal plasma(NTP)surface modification technology is a new method to control the surface properties of materials,which has been widely used in the field of environmental protection because of its short action tim...
详细信息
Non-thermal plasma(NTP)surface modification technology is a new method to control the surface properties of materials,which has been widely used in the field of environmental protection because of its short action time,simple process and no *** this study,Cu/ACF(activated carbon fiber loaded with copper)adsorbent was modified with NTP to remove H_(2)S and PH_(3) simultaneously under low temperature and micro-oxygen ***,the effects of different modified atmosphere(air,N_(2) and NH_(3)),specific energy input(0–13 J/mL)and modification time(0–30 min)on the removal of H_(2)S and PH_(3) were *** test results indicated that under the same reaction conditions,the adsorbent modified by NH_(3) plasma with 5 J/mL for 10 min had the best removal effect on H_(2)S and PH_(3).CO_(2) temperature-programmed desorption and X-ray photoelectron spectroscopy(XPS)analyzes showed that NH_(3) plasma modification could introduce amino functional groups on the surface of the adsorbent,and increase the types and number of alkaline sites on the ***-Emmett-Teller and scanning electron microscopy showed that NH_(3) plasma modification did not significantly change the pore size structure of the adsorbent,but more active components were evenly exposed to the surface,thus improving the adsorption *** addition,X-ray diffraction and XPS analysis indicated that the consumption of active components(Cu and Cu_(2)O)and the accumulation of sulfate and phosphate on the surface and inner pores of the adsorbent are the main reasons for the deactivation of the adsorbent.
The EU has offered new roles and responsibilities to the active consumer in order to control the generation and use of electrical energy, seeing it as an opportunity towards sustainable development for future generati...
详细信息
With the widespread integration of deep learning in intelligent transportation and various industrial sectors, target detection technology is gradually becoming one of the key research areas. Accurately detecting road...
详细信息
This paper considers the problem of evaluating the effectiveness of the finished goods warehouse of a manufacturing company, in which a modified TPM method - Total Productive Management (TPM2) - was applied to improve...
详细信息
This paper considers the problem of evaluating the effectiveness of the finished goods warehouse of a manufacturing company, in which a modified TPM method - Total Productive Management (TPM2) - was applied to improve productivity. A multi-stage methodology was proposed, including a decision to modify the system, determination of the scope of changes, monitoring the results obtained and a multi-criteria evaluation of the changes made. The decision to make modifications to the existing system was motivated by the lower-than-expected quality of customer service (frequent delivery delays). With regard to the transport department, lean flow pillar activities were focused on analysing losses (muda) in warehouse processes (product loading and package unloading). The purpose of these activities was to minimise interruptions in warehouse processes (product loading and package unloading). "The steps for solving the problem" methodology based on Deming's PDCA cycle was used to solve the problem. The analysis covered, among other things, the information flow processes between production planning and the customer service department, the planning processes of the dispatcher, the efficiency of the loading processes, and the causes of interruptions in warehouse operations. The analyses employed the chronometry of selected works, the 5W + 1H method and the Pareto method. By using the 5S method and some characteristics of the SMED method, the organisation of loading work was decisively changed (shunting yard changes, appropriate buffers for transport equipment). The changes introduced in the system were monitored for several months. Appropriately defined OEE indicators were used to assess the behaviour of the system after the changes. The indicators consider the use of available warehouse time, the efficiency of the loading process and the quality of the tasks performed. The results that can be achieved are presented using the specific example of the finished goods warehouse of a ma
The purpose of this paper is to highlight the solar energy potential of the city of Constanța for the propulsion of electric cars. The solar energy available to the city of Constanța was obtained with the help of the ...
详细信息
The present paper analyses and tests the standard oxygen transfer efficiency (SOTE) of a diffused air aeration system with fine bubble disc diffusers. The proposed diffuser density was required to demonstrate an oxyge...
详细信息
The necessity of replacing hazardous chemicals with natural compounds with similar activity is urgent, in different fields, from environmental protection to cultural heritage protection. In this respect, the aim of th...
详细信息
The BallBot,a versatile robot system,finds applications in various domains of *** comprises a frame moved by three wheels mounted on a *** robot performance is significantly influenced by its parametric configuration,...
详细信息
The BallBot,a versatile robot system,finds applications in various domains of *** comprises a frame moved by three wheels mounted on a *** robot performance is significantly influenced by its parametric configuration,including body mass,chassis size,and ball *** study examines the impact of these configuration parameters on the control of the *** mathematical model of the BallBot is discussed,considering the assumptions and coordinate *** control the robot,a Linear Quadratic Regulator controller is ***,the simulation model is used to assess the effects of changing the initial parametric *** is observed that altering the robot mass has a notable impact on the BallBot response,while changes in the ball diameter have a relatively insignificant effect.
Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions i...
详细信息
Regular exercise is a crucial aspect of daily life, as it enables individuals to stay physically active, lowers thelikelihood of developing illnesses, and enhances life expectancy. The recognition of workout actions in videostreams holds significant importance in computer vision research, as it aims to enhance exercise adherence, enableinstant recognition, advance fitness tracking technologies, and optimize fitness routines. However, existing actiondatasets often lack diversity and specificity for workout actions, hindering the development of accurate recognitionmodels. To address this gap, the Workout Action Video dataset (WAVd) has been introduced as a significantcontribution. WAVd comprises a diverse collection of labeled workout action videos, meticulously curated toencompass various exercises performed by numerous individuals in different settings. This research proposes aninnovative framework based on the Attention driven Residual Deep Convolutional-Gated Recurrent Unit (ResDCGRU)network for workout action recognition in video streams. Unlike image-based action recognition, videoscontain spatio-temporal information, making the task more complex and challenging. While substantial progresshas been made in this area, challenges persist in detecting subtle and complex actions, handling occlusions,and managing the computational demands of deep learning approaches. The proposed ResDC-GRU Attentionmodel demonstrated exceptional classification performance with 95.81% accuracy in classifying workout actionvideos and also outperformed various state-of-the-art models. The method also yielded 81.6%, 97.2%, 95.6%, and93.2% accuracy on established benchmark datasets, namely HMDB51, Youtube Actions, UCF50, and UCF101,respectively, showcasing its superiority and robustness in action recognition. The findings suggest practicalimplications in real-world scenarios where precise video action recognition is paramount, addressing the persistingchallenges in the field. TheWAVd datas
暂无评论