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In this paper design of the robot Vacum Cleaner, based on the Arduino Mega 2560 is the can walk and vacuum the floor. In this study, a microcontroller is used to regulate the work of the robot based on data obtained by six sensors, and the robot’s movement is driven by motor driver to the left and right, forward and backward, where the input is given through the keypad in the form of dust and garbage thisness, provided that if the dust thickness is (30mg)/(mm)3 then the LCD will display binary logic “1”, and if the Dust thickness is ≥0,30 mg/mm3then the data will be displayed on the LCD is binary logic “0”. In designing this robot, four ultrasonic sensors are needed as proximity sensors, also needed a sensor to detect the thickness of the dust, as well as an infrared sensor as a sensor to detect thick garbage. In testing the vacuum cleaner robot, the four ultrasonic sensors, S1, S2, S3, S4 are designed as the cardinal directions, north south, east west, as input data on the microcontroller, and two motor drivers as microcontroller outputs that can move forward and backward, forward turn left, forward turn right, backward turn left, backward turn right as an output to move the robot vacuum cleaner. When the vacuum cleaner robot moves, the dust sensor will detect dust, if the dust thickness is 0,30 mgmm3, the LCD is logic “1”, the sensor will. Work and the vacuum cleaner will sweep the flour while sucking, if the dust thickness ≥30mgmm3, infra red sensor will work with a logic LCD display logic “0”, then the motor driver will stop. The vacuum cleaner does not suck up dust or thick garbage.

Despite an expanding array of molecular approaches for detecting microorganisms in a given sample, rapid and robust means of assessing the differential viability of the microbial cells, as a function of phylogenetic lineage, remain elusive. A propidium monoazide (PMA) treatment coupled with downstream quantitative polymerase chain reaction (qPCR) and pyrosequencing analyses was carried out to better understand the frequency, diversity, and distribution of viable microorganisms associated with debris collected from the crew quarters of the International Space Station (ISS). The cultured bacterial counts were more in the ISS samples than cultured fungal population. The rapid molecular analyses targeted to estimate viable population exhibited 5-fold increase in bacterial (qPCR-PMA assay) and 25-fold increase in microbial (adenosine triphosphate assay) burden than the cultured bacterial population. The ribosomal nucleic acid-based identification of cultivated strains revealed the presence of only four to eight bacterial species in the ISS samples, however, the viable bacterial diversity detected by the PMA-pyrosequencing method was far more diverse (12 to 23 bacterial taxa) with the majority consisting of members of actinobacterial genera (Propionibacterium, Corynebacterium) and Staphylococcus. Sample fractions not treated with PMA (inclusive of both live and dead cells) yielded a great abundance of highly diverse bacterial (94 to 118 taxa) and fungal lineages (41 taxa). Even though deep sequencing capability of the molecular analysis widened the understanding about the microbial diversity, the cultivation assay also proved to be essential since some of the spore-forming microorganisms were detected only by the culture-based method. Presented here are the findings of the first comprehensive effort to assess the viability of microbial cells associated with ISS surfaces, and correlate differential viability with phylogenetic affiliation.

Hannah takes a look at the vacuum cleaners, going behind the scenes with Dyson.

This study investigated the muscle activities, motor variability, and functional connectivity of the upper limb as a function of weight distributions in a handle of a cordless stick-type vacuum cleaner. Eighteen female college students with experience of vacuum cleaner-use participated in testing. Five handles with different centers of mass (CM) were prepared (centroid, top-rear, top-front, bottom-front, and bottom-rear), and electromyography for the muscles of the upper limb were measured during vacuuming. The results showed that the %MVC values of the Extensor Carpi Ulnaris (p = 0.0038) and Deltoid Middle (p = 0.0094) increased but that of the Biceps Brachii (p = 0.0001) decreased, as the CM moved from the top to bottom area of the handle. The motor variability of the Extensor Carpi Ulnaris (p = 0.0335) and Brachioradialis (p = 0.0394) significantly varied depending on the CM locations but failed to show significance in the post-hoc analyses. Lastly, the functional connectivity values of the muscle pairs such as the Extensor Carpi Ulnaris–Deltoid Middle (p = 0.0016), Extensor Carpi Ulnaris–Upper Trapezius (p = 0.0174), Brachioradialis–Biceps Brachii (p = 0.0356), and Biceps Brachii–Upper Trapezius (p = 0.0102) were significantly altered as a function of the CM locations. The lowest functional connectivity was found with the handle of which CM was at centroid.

Effectively fusing information between the visual and language modalities remains a significant challenge. To achieve deep integration of natural language and visual information, this research introduces a multimodal fusion neural network model, which combines visual information (RGB images and depth maps) with language information (natural language navigation instructions). Firstly, the authors used faster R-CNN and ResNet50 to extract image features and attention mechanism to further extract effective information. Secondly, GRU model is used to extract language features. Finally, another GRU model is used to fuse the visual- language features, and then the history information is retained to give the next action instruction to the robot. Experimental results demonstrate that the proposed method effectively addresses the localization and decision-making challenges for robotic vacuum cleaners.

The authors propose an approach to setting and solving the problem of optimal selection of product quality indicators, taking into account the interests of both the producer and consumer. The problem is formulated in terms of mathematical programming. The optimization criterion is the maximum proximity between the product attractiveness and the desire to purchase it; the controlled variables are the levels of producer- and consumer-specific indicators; the constraints are agreements regarding the necessary levels of indicators common to the producer and the consumer. Fuzzy cognitive maps are used to construct the dependencies that appear in the objective function, and optimal solutions are found using a genetic algorithm. The approach is illustrated by the example of a robot vacuum cleaner, which is one of the best-selling household applications of artificial intelligence.

Vacuum cleaners are one of the most widely used household appliances associated with unpleasant noises. Previous studies have indicated the severity of loud vacuum cleaner noise and its impact on the users nearby. The standalone quantified measurements of the generated noise are not sufficient for properly characterizing vacuum cleaners. Human perception should also be included for a better assessment of the quality of sound. A hybrid approach such as psychoacoustics analysis, which comprises subjective and objective evaluations of sounds, has recently been widely used. This paper focuses on the experimental assessment of vacuum cleaner noise and evaluates their psychoacoustical matrices. Three vacuum cleaners with different specifications have been selected as test candidates, and their sound qualities have been analyzed. Statistical analysis, ANOVA, has been performed in order to investigate the effectiveness of individual psychoacoustic metrics.

This project is inspired by the Swachh Bharat Abhiyaan. Swachh Bharat Abhiyaan an initiative by the prime minister of India Mr. Narendra Modi. The aim of this project is to clean the streets and road efficiently in very less time and at a low cost. In developing country the streets are really filled with dusts and debris so there is a need make a machine to clean the streets. Scooter is used to move the machine from one place to another. Vacuum cleaner is used as the main thing in cleaning the road. The street cleaner is able to suck at least 25 grams of small dusts and debris from the ground. The portable street vacuum cleaner is really effective in cleaning the roads.

This study focuses on multi-criteria decision-making theory to pick vacuum cleaner available in the Indian market. The choice of a vacuum cleaner for the customer is an intricate decision-making, the problem involving multiple conflicting criteria such as the cost of the vacuum cleaner, dust bag capacity, power consumption, and so on. The simple methodology based on the Technique for Order Preference by Similarity to Ideal Solution method is presented to choose a vacuum cleaner. Based on data collection, eight different companies/brands are considered with 26 diverse models. The ranks of the different alternatives obtained with Technique for Order Preference by Similarity to Ideal Solution method are presented. The result reveals that the alternative Karcher WD 3.200 comes out to be the first choice, followed by Karcher WD 4.200 and Eureka Forbes Sensi. This approach based upon multi-criteria decision-making is very beneficial for retailer and wholesalers to help consumers/customers for purchasing their product/item or the consumer itself can make use of this simple methodology. The established proof-of-concept could be further used in the different domains of engineering, science, and management, wherein the decision-making could be biased and vague.

Current issues in sustainable development concern research on comprehensiveness, coherence and practicality. Therefore, the objective was to develop and test a novelty approach to product sustainability assessment based on life cycle, quality, and costs. This approach extends the iterative design thinking process (DT), including overcoming the limitations of existing LCSA methods. We present a systematic process for obtaining and processing customer requirements with a survey and Pareto–Lorenz analysis. Then, using an algorithm developed in Matlab R2021a program, we generated product prototypes considering the key criteria presented in various dimensions of current and modified states. Next, we propose the modeling of prospective LCA for all prototypes in the OpenLCA program with Ecoinvent database. Finally, we aggregated the results considering the cost of prototypes in environmental–cost analysis to determine the direction of product sustainability. We tested this approach in detail with the example of vacuum cleaners for domestic and commercial use. After a literature review and survey research in customers, we developed 54 prototypes, where the modified key quality criteria were as follows: vacuum in the suction pipe, engine power, operating range, and length of the power cable. Using this approach, it was possible to select six prototypes that best meet customer requirements, are environmentally friendly, and cost-effective. Finally, we discuss contributions to DT and LCSA methodologies, and propose future directions for development within the application of artificial intelligence (AI). This approach can be a practical application in SMEs already in the early stages of product development (conceptualization), where access to detailed data is limited.