Bacterial contamination of chicken food egg with automated and manual sorting and packaging

Chicken eggs are a staple food for humans and are consumed all over the world. Chicken eggs have a leading position among food products in terms of nutritional value and taste. During storage, under the influence of air oxygen and microorganisms, eggs deteriorate, contamination of opportunistic and pathogenic microflora increases. Purpose: analysis of the results of bacteriological studies of eggs of various producers during automatic and manual sorting and packaging from the trading network in Sumy and the Sumy region in accordance with DSTU 5028:2008 “Edible hen eggs. Specifications” and Microbiological Criteria for Establishing Food Safety Indicators. Materials and methods. Bacteriological studies of shell washings and egg contents were carried out according to standard methods. Samples of edible chicken eggs with automatic and manual sorting and packaging corresponded to DSTU 5028:2008, Microbiological criteria for establishing food safety indicators and BIE No. 5061-89. Pathogenic and opportunistic pathogens of bacterial diseases were not isolated from the surface of eggs of the control group during automated sorting and packing, spore bacteria of the genus Bacillus (Bacillus subtilis) were isolated. In washes from the egg shell surface with manual sorting and packaging, Streptococcus spp was found – 12 % of the number of samples examined, E. faecalis – 34 %, P. aeruginosa – 11 %, and spore bacteria of the genus Bacillus (B. subtilis) – 43 %. The number of QMA&OAMO and CGB (coli-forms) in both groups corresponded to the established norms, but the QMA&OAMO indicator in the products of enterprises with manual collection and packaging was 34 % higher compared to eggs from enterprises with automated sorting and packaging. Automation of the process of sorting and packing eggs provides the best microbiological indicators of the safety of edible hen eggs in comparison with those when using manual labor during sorting and packing. A complete transition to the automation of production processes for the production of edible eggs in Ukraine is required.

Potential for tourism to promote indigenous resources for community development in Musina Municipality, Vhembe District, Limpopo Province, South Africa

Purpose This study evaluates “potentials for using tourism in promoting indigenous resources for community development at Musina Municipality, Limpopo Province, South Africa.”Design/methodology/approach The study used a questionnaire survey, focus group discussions, and field observations to gather data. Microsoft Excel, Spreadsheet, cross-tabulation analysis, and manual sorting contributed to quantitative and qualitative data analyses.Findings The study uncovered vast significant indigenous species, resources, and tourism potentials with low impacts of indigenous species and resource benefits to the local communities. The details pointing to the actual and potential indigenous resources situations around tourism activities in Musina municipality emerged prominently. Thus, the study concluded such significant indigenous species, resources, and better tourism potentials need a well-combined strategy to channel the benefits to the local community's livelihoods.Originality/value The issue of indigenous resources, forests, trees, and tourism concerning rural community livelihoods has become of curiosity in the past few years. Nonetheless, few such studies have investigated the synergies between tourism and significant indigenous species and resources to improve their livelihoods.

An Analysis of Interpersonal Meaning of Modal Verbs in Abstracts from Scientific Papers: Case Study of Progress in Aerospace Sciences

The aims of this study are to explore the distribution features of modal verbs in abstracts from scientific papers, analyze the reasons for those features and figure out the role modal verbs play in achieving interpersonal meaning. The study has selected 60 abstracts randomly from Progress in Aerospace Sciences from 2015 to 2019 as research samples. It combines Halliday’s value of modality with Biber et al.’s two classifications to process modal verbs. The instruments adopted in this research are AntConc 3.2.4, manual sorting and SPSS Statistics 21. Based on the results, the study finds that: firstly, the overall occurrence of modal verbs in 60 abstracts is 59 times, among which low-value modal verbs are the most frequently distributed (74.6%), median-value modal verbs the second (22.0%) and high-value modal verbs the least (3.4%); secondly, the achievement of interpersonal meaning relies on value of modality, and when the value of modality is lower, a better degree of interpersonal meaning can be achieved; thirdly, high-value modal verbs achieve tough interpersonal meaning, median-value modal verbs achieve comfortable interpersonal meaning, and low-value modal verbs achieve harmonious interpersonal meaning.

Topic Detection Using Multiple Semantic Spider Hunting Algorithm

In every moment, there is a huge capacity of data and information communicated through social network. Analyzing huge amounts of text data is very tedious, time consuming, expensive and manual sorting leads to mistakes and inconsistency. Document dispensation phase is still not accomplished of extracting data as a human reader. Furthermore the significance of content in the text may also differ from one reader to another. The proposed Multiple Spider Hunting Algorithm has been used to diminish the time complexity in compare with single spider move with multiple spiders. The construction of spider is dynamic depends on the volume of a corpus. In some case tokens may related to more than one topic and there is a need to detect Topic on semantic way. Multiple Semantic Spider Hunting Algorithm is proposed based on the semantics among terms and association can be drawn between words using semantic lexicons. Topic or lists of opinions are generated from the knowledge graph. News articles are gathered from five dissimilar topics such as sports, business, education, tourism and media. Usefulness of the proposed algorithms have been calculated based on the factors precision, recall, f-measure, accuracy, true positive, false positive and topic detection percentage. Multiple Semantic Spider Hunting Algorithm produced good result. Topic detection percentage of Spider Hunting Algorithm has been compared to other algorithms Naïve bayes, Neural Network, Decision tree and Particle Swarm Optimization. Spider Hunting Algorithm produced more than 90% precise detection of topic and subtopic.

Review Paper on Microcontroller Based Object Sorting

Sorting of products is a very difficult industrial process. Continuous manual sorting creates consistency issues. This paper describes a working prototype designed for automatic sorting of objects based on the metal detector KY-036 sensor was used to detect the colour of the product and the PIC16F628A microcontroller was used to control the overall process. The identification of the colour is based on the frequency analysis of the output of TCS230 sensor. One conveyor belts were used, it controlled by separate DC motors. The belt is for placing the product to be analysed by the colour sensor, having separated compartments, in order to separate the products. The experimental results promise that the prototype will fulfil the needs for higher production and precise quality in the field of automation.

An Analysis of Interpersonal Meaning of Modal Verbs in Abstracts from Scientific Papers: Case Study of Progress in Aerospace Sciences

The aims of this study are to explore the distribution features of modal verbs in abstracts from scientific papers, analyze the reasons for those features and figure out the role modal verbs play in achieving interpersonal meaning. The study has selected 60 abstracts randomly from Progress in Aerospace Sciences from 2015 to 2019 as research samples. It combines Halliday’s value of modality with Biber et al.’s two classifications to process modal verbs. The instruments adopted in this research are AntConc 3.2.4, manual sorting and SPSS Statistics 21. Based on the results, the study finds that: firstly, the overall occurrence of modal verbs in 60 abstracts is 59 times, among which low-value modal verbs are the most frequently distributed (74.6%), median-value modal verbs the second (22.0%) and high-value modal verbs the least (3.4%); secondly, the achievement of interpersonal meaning relies on value of modality, and when the value of modality is lower, a better degree of interpersonal meaning can be achieved; thirdly, high-value modal verbs achieve tough interpersonal meaning, median-value modal verbs achieve comfortable interpersonal meaning, and low-value modal verbs achieve harmonious interpersonal meaning.

Results of Laboratory Studies of the Automated Sorting System for Root and Onion Crops

The roller and sieve machines most commonly used in Russia for the post-harvest processing of root and tuber crops and onions have a number of disadvantages, the main one being a decrease in the quality of sorting due to the contamination of working bodies, which increases the quantity of losses during sorting and storage. To obtain high-quality competitive production, it is necessary to combine a number of technological operations during the sorting process, such as dividing the material into classes and fractions by quality and size, as well as identifying and removing damaged products. In order to improve the quality of sorting of root tubers and onions by size, it is necessary to ensure the development of an automatic control system for operating and technological parameters, the use of which will eliminate manual sorting on bulkhead tables in post-harvest processing. To fulfill these conditions, the developed automatic control system must have the ability to identify the material on the sorting surface, taking into account external damage and ensuring the automatic removal of impurities. In this study, the highest sorting accuracy of tubers (of more than 91%) was achieved with a forward speed of 1.2 m/s for the conveyor of the sorting table, with damage to 2.2% of the tubers, which meets the agrotechnical requirements for post-harvest processing. This feature distinguishes the developed device from similar ones.

Music Recommendation Based on Face Emotion Recognition

We propose a new approach for playing music automatically using facial emotion. Most of the existing approaches involve playing music manually, using wearable computing devices, or classifying based on audio features. Instead, we propose to change the manual sorting and playing. We have used a Convolutional Neural Network for emotion detection. For music recommendations, Pygame & Tkinter are used. Our proposed system tends to reduce the computational time involved in obtaining the results and the overall cost of the designed system, thereby increasing the system’s overall accuracy. Testing of the system is done on the FER2013 dataset. Facial expressions are captured using an inbuilt camera. Feature extraction is performed on input face images to detect emotions such as happy, angry, sad, surprise, and neutral. Automatically music playlist is generated by identifying the current emotion of the user. It yields better performance in terms of computational time, as compared to the algorithm in the existing literature.

Intelligent machine for sorting semi-precious minerals

This paper proposes is devoted to solving the problem of sorting workpieces from minerals and semi-precious stones that are used in jewelry production. Intensive development of production leads to a reduction of natural resources, including semi-precious minerals. Therefore, the task of saving the use of minerals is relevant. The solution is based on the idea a new method for sorting semi-precious minerals is proposed, as well as the design of an intelligent installation for implementing this method. An increase in the accuracy of sorting semiprecious minerals has been achieved through the use of charge-coupled device (CCD) matrices, which automatically determine the volume of each mineral in 3D space. From the simulation work, it was found in comparison with manual sorting, the proposed method has reduced the amount of waste in the manufacture of jewelry by 15% ... 20%. Experimental studies were carried out using the example of such a semiprecious mineral as amber. The cost of raw amber in the amount of one kilogram on the modern market is in the range of 1200…2200 US dollars. The result confirms that the method is superior to the alternative method, with the achieved average waste saving of 20%, the proposed sorting technology makes it possible to obtain a profit of 240...440 US dollars per kilogram of amber. Ultimately, these solutions can improve the efficiency of jewelry production.

Artificial Intelligence in the Sorting of Municipal Waste as an Enabler of the Circular Economy

The recently finalized research project “ZRR for municipal waste” aimed at testing and evaluating the automation of municipal waste sorting plants by supplementing or replacing manual sorting, with sorting by a robot with artificial intelligence (ZRR). The objectives were to increase the current recycling rates and the purity of the recovered materials; to collect additional materials from the current rejected flows; and to improve the working conditions of the workers, who could then concentrate on, among other things, the maintenance of the robots. Based on the empirical results of the project, this paper presents the main results of the training and operation of the robotic sorting system based on artificial intelligence, which, to our knowledge, is the first attempt at an application for the separation of bulky municipal solid waste (MSW) and an installation in a full-scale waste treatment plant. The key questions for the research project included (a) the design of test protocols to assess the quality of the sorting process and (b) the evaluation of the performance quality in the first six months of the training of the underlying artificial intelligence and its database.