Number Of Plates Research Articles

Application of Taro Beneng Inulin and Red Dragon Fruit Peel Extract in Making Ice Cream

The characteristics of ice cream with the addition of beneng taro inulin and red dragon fruit extract were evaluated in this study. Various concentrations of beneng taro inulin (3%, 4%, and 5%) and dragon fruit extract (25%, 30%, and 35%) were added as fat substitutes and natural dyes, respectively. The results showed that the addition of 4% taro beneng inulin had a significant effect on the overrun value, melting time, and fat content of ice cream. The addition of 30% red dragon fruit peel extract significantly affected the color of ice cream, fat content, antioxidant activity, and total plate number. There is an interaction between the treatment of the addition of taro beneng inulin and red dragon fruit peel extract on color analysis, namely the L* notation (brightness) and a* notation (redness). A3B3 ice cream was selected as the best ice cream formula based on existing criteria

Virtual plates: Getting the best out of high content screens

High content screening (HCS) is becoming widely adopted as a high throughput screening modality, using hundred-of-thousands compounds library. The use of machine learning and artificial intelligence in image analysis is amplifying this trend. Another factor is the recognition that diverse cell phenotypes can be associated with changes in biological pathways relevant to disease processes. There are numerous challenges in HCS campaigns. These include limited ability to support replicates, low availability of precious and unique cells or reagents, high number of experimental batches, lengthy preparation of cells for imaging, image acquisition time (45–60 min per plate) and image processing time, deterioration of image quality with time post cell fixation and variability within wells and batches. To take advantage of the data in HCS, cell population based rather than well-based analyses are required. Historically, statistical analysis and hypothesis testing played only a limited role in non-high content high throughput campaigns. Thus, only a limited number of standard statistical criteria for hit selection in HCS have been developed so far. In addition to complex biological content in HCS campaigns, additional variability is impacted by cell and reagent handling and by instruments which may malfunction or perform unevenly. Together these can cause a significant number of wells or plates to fail. Here we describe an automated approach for hit analysis and detection in HCS. Our approach automates HCS hit detection using a methodology that is based on a documented statistical framework. We introduce the Virtual Plate concept in which selected wells from different plates are collated into a new, virtual plate. This allows the rescue and analysis of compound wells which have failed due to technical issues as well as to collect hit wells into one plate, allowing the user easier access to the hit data.

QbD-driven RP-HPLC method for novel chemo-herbal combination, in-silico, force degradation studies, and characterization of dual drug-loaded polymeric and lipidic nanocarriers

BackgroundIn cancer therapies, chemo-herbal combinations are receiving increased attention. A multiple tyrosine kinase inhibitor, lenvatinib (LTB) is beneficial in treating thyroid, lung, endometrial, and liver cancers. An isoflavone called biochanin A (BCA) is well known for its diverse biological properties that have been studied to potentiate the anti-cancer potential and lower the normal cell toxicities of other therapeutics. LTB and BCA can be combined for cancer treatment and may increase their therapeutic potential at lower doses. In brief, the quality by design (QbD)-driven RP-HPLC method was developed, validated, and utilized for applications employing the study of forced degradants and the successful development of LTB and BCA co-loaded nanocarriers.ResultsThe RP-HPLC method employed Box–Behnken design with peak resolution 6.70 ± 0.006, tailing factor 1.06 ± 0.05 for BCA and 1.17 ± 0.021 for LTB, and theoretical plates number > 2000. RP-HPLC applications utilized the investigation of a total of 41.17% and 70.58% degradants for LTB and BCA in contrast to in-silico predicted studies using Zeneth software. The poly (lactic-co-glycolic acid) nanoparticles (PLGA NPs) were formed with particle size 185.3 ± 12.3 nm, zeta potential − 13.3 ± 0.35 mV, and percentage entrapment efficiency (%EE) for the LTB and BCA 53.64 ± 4.81% and 61.29 ± 4.67%, respectively. However, the developed Cubosomes (CBs) exhibited 182.4 ± 16.3 nm aerodynamic particle size, − 10.8 ± 0.39 mV zeta potential, and % EE for LTB and BCA 55.62 ± 7.73% and 72.88 ± 5.52%, respectively. The percentage drug loading (%DL) of LTB and BCA from PLGA NPs was found to be 3.7 ± 0.46% and 4.63 ± 0.48%, whereas CBs exhibited higher % DL for BCA (5.42 ± 1.10%) and LTB (4.43 ± 0.77%).ConclusionThe RP-HPLC method was developed and validated according to ICH and USP guidelines. In-vitro and in-silico forced degradation studies are evident to quantify the type of degradant and its exact mechanism of degradation. In-silico toxicity assessment for LTB, BCA, and their degradants explains the necessity of conducting degradation studies during drug development. Finally, the applications of the developed RP-HPLC method explain the usefulness of analytical methods in the development of chemo-herbal drug nanocarriers (polymeric and lipidic).Graphical abstract

Study on energy dissipation performance of low-yield-point steel shear panel dampers

To investigate the energy dissipation performance of low-yield-point steel shear panel dampers (LSSPD), the eleven full-scale LSSPD specimens were designed and tested. By conducting quasi-static cyclic tests and numerical simulations, the influence of shear plate aspect ratios, flange plate thickness, numbers and layout of stiffeners on the failure modes for energy dissipation performance of LSSPD have been investigated. The results indicate that: The energy-dissipating capacity of the damper is positively correlated with the shear plate's cross-sectional area. Increasing the flange plate thickness can improve the bearing capacity and energy dissipation of LSSPD, but with a limit. The stiffeners can enhance the ultimate bearing capacity of the damper. A single stiffener in both horizontal and vertical directions effectively controls the out-of-plane buckling deformation of the shear plate. It achieves a damper with a full hysteretic curve and a high energy dissipation capacity. However, the arrangement of stiffeners on different sides will decrease the ultimate bearing capacity of the damper. Through finite element supplementary analysis, it is recommended to select the shear plate aspect ratio between 20 and 41, and the flange restraint coefficient βf should not be <10 for damper design. Meanwhile, limiting the stiffener restraint coefficient βs within 45 is recommended to achieve better energy dissipation performance for low-yield-point dampers.

Optimization of the structure and cathode operating parameters of a serpentine PEMFC with longitudinal vortex generators by response surface method

An improved method based on a concept for enhancing heat and mass transfer based on longitudinal vortex system is proposed for optimizing the performance and water-thermal management of proton exchange membrane fuel cells (PEMFCs). A certain number of rectangular plates are added to the cathode channel of the serpentine plate to create the longitudinal vortex to enhance the diffusion of fuel gas, the discharge of water, and temperature distribution uniformity of the fuel cell. A series of numerical studies are conducted employing the response surface method to evaluate the effect of cathode operating parameters on the efficiency and power density of the fuel cell system. The results obviously suggest that the installation of twenty groups of Longitudinal vortex generators(LVGs) in the first four straight flow channels can enhance the mean current density by 5.02 % compared with the condition without LVGs. Meanwhile, LVGs in the cathode flow channel close to the inlet can also enhance the distribution uniformity of membrane temperature by 11.38 %, which can contribute to the diffusion enhancement of oxygen by 36.94 % at the cathode and the improvement of water distribution uniformity by 10.87 %. The main reason for this phenomenon is that the rectangular-plate longitudinal vortex generator can increase the local turbulence intensity of the fuel gas in the cathode channel; therefore, more fuel gas can be transported from the channel to the diffusion layer, leading to a greater current density, in addition to the fact that the generated longitudinal vortex system can assist the exiting of the generated water from the channel. In addition to these, increasing pressure or reducing temperature or relative humidity can enhance power density, while reducing relative humidity is beneficial for improving system efficiency.

Preliminary Results of Rib Osteosynthesis at the Teaching Hospital Sylvanus Olympio in Lomé

Introduction: Flaps and rib fractures can be life-threatening due to disruption of hematosis. In certain “many” situations, it is important to quickly restore parietal rigidity by costal osteosynthesis. The objective of our work is to report the surgical results of a first Togolese series of rib osteosynthesis performed in the context of chest trauma.Patients and methods: We proceed by a retrospective study on a series of patients treated for severe blunt chest trauma and who underwent osteosynthesis from 2020 to 2022. Epidemiological and clinical data, in particular the radiological lesion assessment clinic, the therapeutic measures as well as the immediate operative follow-up were collected.Results: six patients with blunt chest trauma. They were four men and two women whose mean age was 44.4 years. Five patients were admitted for polytrauma and one patient for a serious thoracic trauma. All were admitted to intensive care unit on day 0 of the trauma. The radioclinical assessment had noted staged fractures of ribs and/or thoracic flap with an average of six affected ribs. All the patients presented pleural effusions and benefited from pleural drainage on their admission to intensive care, often after a chest X-ray or after carrying out a chest CT scan or a whole-body CT scan. The indication for rib osteosynthesis was retained on the clinical criteria, in particular the existence of a pleural effusion, the instability of the wall and the impact on hematosis, by the drop in peripheral oxygen saturation (Sp02). Despite oxygen therapy above 6 l/min for more than 4 days, and according to the results of the chest CT scan and the evolution of the patient after the implementation of the means of resuscitation. The osteosynthesis material used was “third tube” orthopedic plates molded intraoperatively in three patients, pelvic plates in one patient. The average number of plates used was 4.5 and that of Vis was 18. Two patients underwent osteosynthesis by Judet staple.Conclusion: rib osteosynthesis contributes to a regression of symptoms, in particular chest pain, to reduce the duration of hospitalization, morbidity and mortality, and then improves the functional respiratory prognosis in the short and long term. Despite our reduced technical platform, the results are generally good, reducing the hospital stay in intensive care. This encourages the practice of surgical management of multiple rib fractures associated or not with a rib flap.

Laporan Akhir Kerja Praktik (KP) Aplikasi Surat Perintah Perjalanan Dinas Di UPTD PPD Medan Utara Bapenda Provsu

The Regional Revenue Agency (BAPEDA) is a government operational support component that carries out financial support tasks in the field of regional income. The author conducted a study of the official travel system while working practically, and at the UPTD PPD North Medan Bapenda PROVSU Medan produced an official travel order application. The author's aim in carrying out this practical work is to support the personnel department in the process of updating employee data including data entry and output. Assist in verifying car number plates and payment of vehicle tax that has just been registered on the e-Samsat application via the website with the branch office. Assist in preparing official travel orders and vehicle transfer reports. After a month of direct practice, the author found many incidents where after discussing with agency superiors, the author discussed the issue of Official Travel Orders (SPPD). The agency will use an inefficient and time-consuming system to handle future cases. because getting permission for official travel requires you to personally navigate a protracted bureaucracy. Therefore, the author used the skills he acquired in college to create an official travel booking system for an agency based on a website, making it easier for the department employees who handle it to obtain permits via the internet only. It can be concluded that students gain new information and experience through practical work that they would not get from face-to-face lectures. A clear picture of the overall scope of activities of an agency is provided through practical work. Additionally, practitioners receive training on how to perform their work with care, diligence, and analysis.

Test of Escherichia Coli and Total Microbes on Burger Meat Sold in Kedinding and Pogot Villages, Surabaya, East Java

A burger is a type of fast food that consists of a bun in the middle that contains a patty (ground beef), vegetables, and some sauce. There are several parameters in determining food quality and safety, one of which is analyzing the content of microbiology such as bacteria, viruses, and protozoa in food. Biological hazards, especially in food, need special attention because they are often the causative agents of food poisoning cases. This study aims to determine Eschericia coli contamination and Total Plate Number (TPC) in burger meat samples sold in Kedinding and Pogot villages, Surabaya, East Java. This research is observational with a cross sectional approach. The inspection method used to determine Escherichia coli contamination and the Total Plate Count (TPC) is the Most Likely Number method to determine E. coli and the Total Plate Count (TPC). The results of this study showed that there was no E. coli in all burger meat samples and there were 6 burger meat samples contaminated with bacteria, namely in Samples A, B, C, G, H and I, which exceeded the contamination limit according to to SNI 8503 (2018).

Sol-Gel Functionalized Polyurethane Foam-Packed Mini-Column as an Efficient Solid Extractor for the Rapid and Ultra-Trace Detection of Textile Dyes in Water.

Textile dyes widely used in industrial products are known as a major threat to human health and water ecological security. On the other hand, sol gel represents a principal driver of the adoption of dispersive solid-phase microextractors (d-µ SPME) for pollutants residues in water. Thus, the current study reports a new and highly rapid and highly efficient hybrid sol-gel-based sponge polyurethane foam as a dispersive solid-phase microextractor (d-µ-SPME) platform packed mini-column for complete preconcentration and subsequent spectrophotometric detection of eosin Y textile dye in wastewater. The unique porous structure of the prepared sol-gel immobilized polyurethane foams (sol-gel/PUF) has suggested its use for the complete removal of eosin Y dye (EY) from water. In the mini-column, the number (N) of plates, the height equivalent to the theoretical plates (HETP), the critical capacity (CC), and the breakthrough capacities (BC) of the hybrid sol-gel-treated polyurethane foams towards EY dye were determined via the breakthrough capacity curve at various flow rates. Under the optimum condition using the matrix match strategy, the linear range of 0.01-5 µg L-1, LODs and LOQs in the range of 0.006 µg L-1, and 0.01 µg L-1 for wastewater were achieved. The intra-day and inter-day precisions were evaluated at two different concentration levels (0.05 and 5 μg L-1 of dye) on the same day and five distinct days, respectively. The analytical utility of the absorbents packed in pulses and mini-columns to extract and recover EY dye was attained by 98.94%. The column could efficiently remove different dyes from real industrial effluents, and hence the sol-gel/PUF is a good competitor for commercial applications. The findings of this research work have strong potential in the future to be used in selecting the most suitable lightweight growing medium for a green roof based on stakeholder requirements. Therefore, this study has provided a convenient pathway for the preparation of compressible and reusable sponge materials from renewable biomass for efficient removal of EY from the water environment.

Automatic Video Traffic Surveillance System with Number Plate Character Recognition Using Hybrid Optimization-Based YOLOv3 and Improved CNN

Recently, the increased count of surveillance cameras has manipulated the demand criteria for a higher effective video coding process. Moreover, the ultra-modern video coding standards have appreciably enhanced the efficiency of video coding, which has been developed for gathering common videos over surveillance videos. Various vehicle recognition techniques have provided a challenging and promising role in computer vision applications and intelligent transport systems. In this case, most of the conventional techniques have recognized the vehicles along with bounding box depiction and thus failed to provide the proper locations of the vehicles. Moreover, the position details have been vigorous in terms of various real-time applications trajectory of vehicle’s motion on the road as well as movement estimation. Numerous advancements have been offered throughout the years in the traffic surveillance area through the random propagation of intelligent traffic video surveillance techniques. The ultimate goal of this model is to design and enhance intelligent traffic video surveillance techniques by utilizing the developed deep learning techniques. This model has the ability to handle video traffic surveillance by measuring the speed of vehicles and recognizing their number plates. The initial process is considered the data collection, in which the traffic video data is gathered. Furthermore, the vehicle detection is performed by the Optimized YOLOv3 deep learning classifier, in which the parameter optimization is performed by using the newly recommended Modified Coyote Spider Monkey Optimization (MCSMO), which is the combination of Coyote Optimization Algorithm (COA) and Spider Monkey Optimization (SMO). Furthermore, the speed of the vehicles has been measured from each frame. For high-speed vehicles, the same Optimized YOLOv3 is used for detecting the number plates. Once the number plates are detected, plate character recognition is performed by the Improved Convolutional Neural Network (ICNN). Thus, the information about the vehicles, which are violating the traffic rules, can be conveyed to the vehicle owners and Regional Transport Office (RTO) to take further action to avoid accidents. From the experimental validation, the accuracy and precision rate of the designed method achieves 97.53% and 96.83%. Experimental results show that the proposed method achieves enhanced performance when compared to conventional models, thus ensuring the security of the transport system.

ON SMALL CONTINENTAL MAMMOTHS AND DWARFISM

In the evolution of proboscideans, the appearance of dwarf and semi-dwarf forms occurred repeatedly, in different territories and at different times, due to a lack of resources caused by geographic isolation on islands and by landscape isolation on the mainland. Despite a significant amount of information on the insular forms of mammoths and elephants, the question of the relationship between a decrease in body size and morphological changes in the dental system remains a matter of debate. Some data show that dwarfism was accompanied by a decreasing number of plates (lophs) and by tooth enamel thickening. Other data show that changes in the dental system on the islands indicate that the number of plates could either decrease or remain unchanged, or even increase. Taking into account the importance of the number of plates as a diagnostic feature in the species identification of proboscidean taxa and the lack of a consensus on the stability of the trend towards a decrease in the number of plates from large continental ancestors to insular dwarf descendants, we (1) summarize the data on the records of small tooth-mammoths of the genus Mammuthus with a reduced number of plates in sites across northern Eurasia, (2) provide new radiocarbon dates, and (3) consider the number of plates as a possible sign of dwarfization in continental mammoths. The small teeth of the last generation of M. primigenius from the coastal part of northeastern Siberia and a comparison with data from other regions show that the posterior sections of mammoth cheek teeth are the most variable and represent a reduction complex. For the woolly mammoth, reduction primarily affects that part of the crown which became more complex by the gradually increasing number of plates during the phyletic evolution in the Middle to Late Pleistocene. The rapid loss of the evolutionary achievements through reduction is not a unique feature of woolly mammoth teeth. This has been observed in other mammals as well. Similar reduction complexes are observed for the cheek teeth of proboscideans and rodents of the subfamily Arvicolinae, as is shown by a decrease in the number of serially homologous crown elements: plates in proboscideans and pairs of prisms in voles. A comparison of the number of plates with the size of the teeth of M. primigenius suggests that a decrease in the number of dental plates, while retaining other specific features of the tooth, can be used as a criterion for separating semi-dwarf and small specimens of the woolly mammoth. The largest decrease in size of mainland mammoths is observed during warming periods, which also showed significant transformations of landscapes in a reduction of available resources.

Detection of Vehicle Number Plate and Speed Using Machine Learning

In an era marked by a significant upsurge in vehicular traffic and the resultant increase in road accidents, the need for advanced traffic management systems is paramount. This paper presents an innovative solution, "Detection of vehicle number plate and speed using machine learning" which aims to enhance road safety by addressing the persistent problem of over-speeding. The project leverages state-of-the-art technologies, including machine learning, deep learning, and computer vision, to develop a smart system that can detect speeding vehicles, recognize license plates, and record crucial data related to speed limit violations. The primary motivation for this endeavor is the escalating rate of road accidents, particularly in India, driven by speeding in areas susceptible to accidents. The system employs image segmentation, corner detection algorithms, filtering algorithms, and automatic vehicle plate recognition techniques to achieve its objectives. By using machine learning and deep learning models, the system accurately identifies license plates, segments characters on these plates, and recognizes them. In summary, this project represents a significant advancement in road safety and traffic management. By deploying an intelligent system that can proactively detect over-speeding vehicles and maintain comprehensive records, it strives to create a safer and more responsible driving environment, ultimately working towards the prevention of accidents and saving lives. Key Words: Automatic Number Plate Recognition, Vehicle Speed Detection, Machine Learning, Computer Vision, Traffic Management.

Analytical Studies on Techniques and Algorithms of Automatic Number Plate Recognition

The city's efforts to improve traffic make a big step forward when license plates can be read. It explains how an intelligent transportation system should work and what steps should be taken for it to be successful. Because the number of cars is growing so quickly, ANPR is a must-have for managing traffic control. Automatic number plate recognition (ANPR) is mostly used to keep an eye on traffic and keep people safe. Number plate recognition uses image processing and the most recent advances in technology to automatically read the characters on a vehicle's license plate. In the last few years, there have been a number of technological advances in the field of studying how to read license plates. Image processing techniques like OCR make it possible for traffic surveillance to solve a wide range of problems that come up during criminal investigations, the collection of tolls, the monitoring of traffic, the regulation of speed, and the management of parking, among other things. If you want to control traffic and keep an eye on a large number of people in a transportation system, you need an ANPR system. Image processing techniques and the collection of photos of vehicles for use in the dataset have made it possible to keep an eye on traffic on a large scale. Automatic License Plate Reader (ANPR) is a way to take the steps needed to run a good intelligent transportation network. Traffic control has become an absolute must because the number of cars has grown so quickly. The main goal of ANPR is to keep an eye on and record traffic for defense purposes. To read the text on license plates, number plate recognition uses image processing, optical character recognition (OCR), and edge detection technology. The model is made up of three different parts called, respectively, the module for car detection, the module for license plate segmentation, and the module for recognition. Image processing made us more determined to stop a wide range of illegal activities, such as armed robberies of cars, breaking traffic rules, and the way law enforcement is handled. This review study looked at all of the different designs for reading license plates that have been put into use so far.

Effective Plate Object Segmentation and Recognition by Implementing Artificial Intelligent Model for Smart Transportation Systems.

The increase in the number of vehicles in the last few years has made it challenging to manually note the number plate text of the vehicle. Hence, in order to reduce the manual work, there is a need to propose a methodology that can detect the number plate region from the input image and recognize the characters of the number plate. Systems have been built for the same using Image Processing techniques, but this technique fails to provide accurate results occasionally in the case of real data. Modern technology such as Deep Learning overcomes this problem. Hence, a deep learning-based methodology is proposed to detect the number plate region from the input image and recognize its characters. Using the pre-trained based deep learning Networks. the number plate region is detected and using Convolutional Neural Networks (CNN), the characters are recognized from the detected plate region. The system also stores the number plate text with its state name into the database to maintain a record of number plates detected. The proposed system provides promising results. The model is judged against other models that are already out there, such as ResNet50, DenseNet, and DenseCapsNet. According to these studies, MobileNet has reached a level of accuracy of 98.69%, which is higher than other algorithms that are thought to be cutting-edge.

Design and Optimization of a Toothed-Plate Single-Roller Crushing Device for Waste Plastic Film

Waste plastic film often contains an abundance of impurities, such as crop stems and soil. To address this issue, a toothed-plate single-roller crushing device for waste plastic film was developed. By analyzing the movement and force pattern of the film, the feeding speed, the number of toothed plates, and the crushing roller rotation speed were used as test factors, and the size qualification rate and the impurity content of the crushed film were used as test indexes. Through a Box–Behnken test design, regression analysis, and ANOVA, a model between factors and indexes was established. The results showed that the size qualification rate and the impurity content of the crushed film were 82.55% and 9.57%, and the errors in the prediction and test values were 6.14% and 8.38%, which proved them to have good reliability. The findings of this study provide essential technical and equipment support for the resource recovery of waste plastic films.

On-column modification for the creation of temperature-responsive stationary phases

Temperature-responsive liquid chromatography (TRLC) offers an alternative for retention and selectivity optimisation in HPLC. This approach thereby exploits temperature gradients on stimuli-responsive stationary phases and forfeits the necessity for solvent gradients, allowing analyses to be performed using aqueous mobile phases. Consequently, it can be employed as a green alternative to reversed-phase separations. However, current production to obtain temperature-responsive columns inherently require dedicated column packing processes with polymer-modified particles. To facilitate the development of temperature-responsive phases, a flow-through modification procedure was developed allowing on-column modification of aminopropyl silica columns. Three columns were manufactured using this novel flow-through approach, which achieved identical column efficiencies compared to existing TRLC column. Demonstrating the possibility of bypassing the dedicated packing processes without losing efficiency. Additionally, it was observed that flow-through produced columns yielded higher retention at elevated temperatures despite their reduced carbon load. Further investigation of the carbon load revealed the presence of stationary phase gradients, whose influence was studied via novel developed retention experiments, which revealed a negligible change reduction in retention upon a change of polymer modification from 19.8% to 14.5%. However, further decrease from 14.5% to 12.3% resulted in a larger change. Interestingly, a further enhancement in apparent plate numbers was observed when operating the column under a reversed flow, yielding an increasing stationary phase gradient. This on-column modification procedure demonstrates the potential for modification of existing (commercial) packed columns to achieve temperature-responsive phases without loss of efficiency or retention. Thus, not only facilitating accessibility to temperature-responsive phases, but also aiding with development of further generations of temperature-responsive phases by removing the need for packing optimisation. Additionally, a novel experiment was set up to easily investigate the effect of inhomogeneous stationary phases retention.

Implementation of source extended multiple field plates and asymmetric doping on β-Ga2O3 MOSFET for high power applications

In the present work, source extended multiple field plate design is implemented on β – Ga2O3 MOSFET and asymmetric doping design has been adopted in the channel such that higher doping is present at the source side and lower doping is considered at the drain side to achieve superior performance for power applications. Extensive numerical simulations using TCAD Silvaco have been conducted and the optimization of various critical parameters of the proposed device, including the number and lengths of field plates and channel doping, has been undertaken to achieve superior power performance. Further, a comparison is drawn between the proposed device with (i) the device with multiple field plates at the source side and uniform channel doping, and (ii) the conventional device (without field plates and asymmetric channel doping) in terms of various critical attributes such as ON-state resistance, drain current, transconductance, breakdown voltage and power figure of merit etc. The present study demonstrates that the proposed device yields not only a remarkable improvement of 261 % in breakdown voltage and a substantial improvement in PFoM of 1120 % but also delivers higher drain current and peak transconductance when compared to the other devices under consideration. Additionally, the performance of all devices has been investigated at elevated temperatures and it has been found that the proposed device is well-suited for high-temperature applications as well since least degradation in drain current at higher temperatures is observed for the proposed device.

Numerical simulation study of wave dissipation performance of step‐type breakwaters

AbstractTo improve the force endurance capacity of plate breakwaters, a step‐type plate breakwater was proposed. The performance of the step‐type breakwater was investigated by numerical simulation method. First, a two‐dimensional numerical regular wave tank was constructed using FLUENT software, and the effectiveness of the tank application was verified by comparing with theoretical value and test data. Then, the numerical tank was used to simulate various working conditions, and the variation rules of the breakwater transmission coefficient with wave height, period, perforation rate, relative plate width, wave steepness, and number of layers were obtained. Finally, the difference in the wave dissipation mechanism between the step‐type breakwater and the “”‐type breakwater was discussed. The results indicated that the transmission coefficient of the step‐type breakwater was small, which also proved to be good at dissipating long‐period waves. In general, the wave dissipation performance of the step‐type breakwater was better than that of the “”‐type breakwater. The research can provide some clues for the research and design of corresponding breakwaters.

Electrocoagulation technique and statistical analysis for treatment of real effluent from the pulp and paper industry

The electrochemical treatment of Organic Pollutants is a promising technique for substances with biodegradability resistance. In this research, the black liquor effluent originating from the Rakta Paper and Paper Company's mill, which employs rice straw as a raw material for paper fiber production, was subjected to treatment using the electrocoagulation method utilizing monopolar aluminum electrodes. The experiments were carried out using a 2.5 L electrochemical cell equipped with monopolar aluminum electrodes connected in parallel. The study examined the impact of operating parameters such as initial pH, current density, number of plates and electrolyte concentration on percentage removal and power consumption. The results revealed a positive correlation between the percentage of color removal and the duration of electrolysis, current density, sodium chloride concentration, and the number of electrodes used. The maximum color removal was observed at initial solution pH 6.5, experimental time 120 min, current density 61.8 A m−2, initial NaCl solution concentration 2 g L−1 and six aluminum plates. The statistical and mathematical data based on experimental results were analyzed using the central composite design from response surface methodology (RSM). The quadratic model is deemed appropriate owing to its substantial coefficient of determination (R2 = 0.99) and statistically significant p-value (≤ 0.0002), suggesting the model's significance. The experimental results indicate that the utilization of electrocoagulation as a treatment method for paper mill effluents has demonstrated superior efficacy compared to the adsorption technique.

An Efficient and Robust Multi Directional Deep Learning Based Licence Plate Recognition

Smart cities must have all the important characteristics to achieve their intended goals. Proper traffic management and controlling, increased surveillance and safety, and enhanced management and avoidance of incidents must be the priorities of smart cities. Meanwhile, license plate recognition (LPR) has become the most debatable topic in the research community due to various real-time applications, such as “law enforcement, toll-free processing, access control, and traffic surveillance.” Automated LPR is a technique based on computer vision to recognize vehicles with their number plates. This study discusses various “Deep Learning based LPR” techniques to detect and identify “alphanumeric characters” in number plate. The projected model works on “license based detection” and “character recognition.” This technique uses “Optical Character Recognition (OCR)” technology to detect and extract the alphanumerical numbers from the license plate. This study is based on secondary data collected from various studies conducted on Licence Plate Recognition using various Deep Learning models published in databases like Google Scholar, Science Direct, NCBI, etc. Deep learning has been used widely in applications related to computer vision in recent years with great perfection. It is a great solution for modern and traditional image processing, object detection, and feature extraction issues. It has been widely used in different stages of LPR like character segmentation, license plate recognition, and OCR.