Quick Search Research Articles

Screw rotor manufacturing via 5-axis flank CNC machining using conical tools

We propose a new method for 5-axis flank computer numerically controlled (CNC) machining of screw rotors using conical tools. The flanks of screw rotors consist of helical surfaces, which predetermines the motion of the milling tool and reduces the search space for tool positioning to only 4-parametric family, which allows a quick search for good initial positions of a given conical tool. We initialize the search by looking at second order line contact between the tool and the helical flank of the rotor. Several positions of the tool are found, covering major part of the flank of the rotor, followed by global optimization that further reduces the tool-surface error and makes sure that there are no gaps between neighboring sweeps of the tool. We demonstrate our approach on several benchmark screw rotors, showing that our approach meets fine industrial tolerances with only few sweeps of the tool.

MarineMetagenomeDB: a public repository for curated and standardized metadata for marine metagenomes

BackgroundMetagenomics is an expanding field within microbial ecology, microbiology, and related disciplines. The number of metagenomes deposited in major public repositories such as Sequence Read Archive (SRA) and Metagenomic Rapid Annotations using Subsystems Technology (MG-RAST) is rising exponentially. However, data mining and interpretation can be challenging due to mis-annotated and misleading metadata entries. In this study, we describe the Marine Metagenome Metadata Database (MarineMetagenomeDB) to help researchers identify marine metagenomes of interest for re-analysis and meta-analysis. To this end, we have manually curated the associated metadata of several thousands of microbial metagenomes currently deposited at SRA and MG-RAST.ResultsIn total, 125 terms were curated according to 17 different classes (e.g., biome, material, oceanic zone, geographic feature and oceanographic phenomena). Other standardized features include sample attributes (e.g., salinity, depth), sample location (e.g., latitude, longitude), and sequencing features (e.g., sequencing platform, sequence count). MarineMetagenomeDB version 1.0 contains 11,449 marine metagenomes from SRA and MG-RAST distributed across all oceans and several seas. Most samples were sequenced using Illumina sequencing technology (84.33%). More than 55% of the samples were collected from the Pacific and the Atlantic Oceans. About 40% of the samples had their biomes assigned as ‘ocean’. The ‘Quick Search’ and ‘Advanced Search’ tabs allow users to use different filters to select samples of interest dynamically in the web app. The interactive map allows the visualization of samples based on their location on the world map. The web app is also equipped with a novel download tool (on both Windows and Linux operating systems), that allows easy download of raw sequence data of selected samples from their respective repositories. As a use case, we demonstrated how to use the MarineMetagenomeDB web app to select estuarine metagenomes for potential large-scale microbial biogeography studies.ConclusionThe MarineMetagenomeDB is a powerful resource for non-bioinformaticians to find marine metagenome samples with curated metadata and stimulate meta-studies involving marine microbiomes. Our user-friendly web app is publicly available at https://webapp.ufz.de/marmdb/.

Data-driven multi-objective optimization with neural network-based sensitivity analysis for semiconductor devices

Statistical modeling and optimization are critical for product quality management and technology development in the manufacturing industry. As the emerging device appears and technology advances, it consists of highly-correlated multivariate parameters and has a non-linear relationship. Moreover, technology development requires extensive cost and effort, and often it takes several years to establish a physical model after the advent of new technology. Thus, this paper presents an effective data-driven multi-objective optimization with neural network-based sensitivity analysis for semiconductor devices before explicitly developing a physical or compact model. Sensitivity analysis allows a quick search for influential parameters and selects design parameter candidates for a customized solution. Then, the selected parameters are adjusted to maintain within the set range by the scaled sensitivities and to have robustness against noise. It optimizes design variables to meet performance and variation requirements simultaneously, considering correlation between parameters. Therefore, multi-objective solutions hold physical consistency and are found with ¡ 1.7% error. The proposed method is efficient in computational time, which is significantly reduced by more than 80% compared to Bayesian optimization for process optimization. This approach is a general methodology applicable to various industries besides the semiconductor field. Finally, we expect this study to help shorten development time and improve yield through customized multi-objective solutions.

MULTISOURCE INTELLIGENT PARKING ASSISTANT

Problem searching for a parking space is time-consuming and highly relevant both in Ukraine and abroad. Time spent searching for a parking space leads to excessive traffic, more traffic jams, air pollution and increased fuel consumption. These factors also affect the daily stress levels of drivers. Due to this, the process of finding a parking space should be fast and convenient. At the same time, there has been significant development of real estate in Lviv over the past few years. Accordingly, the need for organizing the process of parking cars of residents of residential areas is growing. This paper presents the results of the development of an application for a quick and convenient search for a parking space. A review of similar software applications was conducted. Proposed solutions use various technologies to solve the problem of searching for a free parking space including IoT, sensors, machine learning for image recognition. Even though they solve the problem of searching for a free parking space, most of them can be expensive to implement, maintain, they don’t provide the ability to work with different data sources. An activity diagram of system is presented and it shows two main flows of the system: displaying the current state of parking spaces and displaying parking space by the number of the car entering the territory of the complex. System consists of three modules. The first module is responsible for working with different data sources, storing the status of parking spaces, processing requests. Image processing module is responsible for determining the occupied and free parking spaces from the image. The third module is responsible for the correct display of parking spaces and their statuses. It is also demonstrated how the application works with different data sources and how exceptions are handled. The system works correctly and has a сlear interface. The parking assistant is a great helper and significantly reduces the time required to find a free parking space.

Natural Language Processing Techniques for Text Classification of Biomedical Documents: A Systematic Review

The classification of biomedical literature is engaged in a number of critical issues that physicians are expected to answer. In many cases, these issues are extremely difficult. This can be conducted for jobs such as diagnosis and treatment, as well as efficient representations of ideas such as medications, procedure codes, and patient visits, as well as in the quick search of a document or disease classification. Pathologies are being sought from clinical notes, among other sources. The goal of this systematic review is to analyze the literature on various problems of classification of medical texts of patients based on criteria such as: the quality of the evaluation metrics used, the different methods of machine learning applied, the different data sets, to highlight the best methods in this type of problem, and to identify the different challenges associated. The study covers the period from 1 January 2016 to 10 July 2022. We used multiple databases and archives of research articles, including Web Of Science, Scopus, MDPI, arXiv, IEEE, and ACM, to find 894 articles dealing with the subject of text classification, which we were able to filter using inclusion and exclusion criteria. Following a thorough review, we selected 33 articles dealing with biological text categorization issues. Following our investigation, we discovered two major issues linked to the methodology and data used for biomedical text classification. First, there is the data-centric challenge, followed by the data quality challenge.

Application of the boyer moore method in the application dictionary of web-based information technology terms (case study: pt. erefka tiga pilar utama)

The emergence of many new terms in information technology because of the rapid development of technology makes people, especially those who pursue the IT field, must know and learn terms related to information technology. Therefore we need the availability of an information technology dictionary. Dictionary of the term information technology that circulates a lot in the form of printed media / books. However, dictionaries in the form of print media have a weakness in the form of a search process that takes a long time and cannot be updated at any time, therefore a digital / electronic dictionary exists to overcome this weakness. The dictionary application of the term information technology by applying the Boyer Moore algorithm in the search for the term word can help it. The Boyer Moore algorithm applies the good suffix principle where the character being searched for is parallel to the like character, as well as the principle of a bad character where if the character does not have similarities, it is immediately eliminated. The field used in this search is the word term, by entering the term search term as input in the search column, then we can find out the meaning of the term word. The results of this application display the entire pattern that matches the text, with a total search time below 300 milliseconds.

The current state of legal regulation of labor relations in Ukraine

The experts’ point of view regarding the concept of “labor legal relations” has been studied and the author’s definition has been given, which means the volitional, legal relationship between an employee and an employer, arising on the basis of an employment contract, regarding the employee’s performance of work with its payment and ensuring the working conditions necessary for it performance provided for by labor legislation, collective agreement and agreement of the parties.
 The current state of legal regulation of labor relations has been considered. It is well-founded that the Labor Code of Ukraine has not been adopted to date, therefore the Labor Code of Ukraine should really be the main regulatory legal act that comprehensively regulates all aspects of labor relations. Ensuring this, first of all, will contribute to a clear understanding of the normative material and its quick search. It is noted that today, due to certain circumstances, the Labor Code does not fulfill the role of the main act of labor legislation: firstly, along with the Labor Code, there are traditionally other laws that regulate certain aspects of labor relations, namely the laws of Ukraine “On Labor Payment”, “On vacations”, “On labor protection”; secondly, the norms of the Law of Ukraine “On the Organization of Labor Relations in the Conditions of Martial Law”, adopted on March 15, 2022, suspended a large number of norms of the Labor Code and established other parameters of working conditions for all employees during the period of martial law.
 The analysis of the norms of modern national legislation shows that the changes established by the Law of Ukraine “On the Organization of Labor Relations in the Conditions of Martial Law” worsen the working conditions of employees established by the Labor Code. It has been proven that the introduction of most of these changes is correct in the conditions of martial law, when the country’s economy needs radical transformations and additional resources. The inexpediency of reducing the guarantees established by the Labor Code for women who have a child under the age of three has also been proven, since raising a child is an extremely important social function of women in society and the state.
 The expediency of introducing wording changes in Articles 8 and 9 of the Law of Ukraine “On the Organization of Labor Relations in the Conditions of Martial Law” from the words “women who have a child under the age of one year” and “of women who have a child under the age of one year” to, respectively, the words “women who have a child under the age of three” and “of women who have a child under three years of age” has been grounded in the article.

Конструкторско-технологическое проектирование деталей из слоистого тканевого композита

The article considers the features of solving the problem of designing complex shape constructions made from layered fabric composites considering the triad "material-technology-construction". Based on the developed models, the design problem is formulated in terms of non-linear mathematical programming. The novelty is the approach to choosing the main design variables by dividing the digital model of the product into structural and technological groups, which pro-vide a quick and visual search for a rational distribution of material in the structure using a genetic optimization algo-rithm. The proposed approach is a development of the “precision design” methodology. It ensures the technological feasibility of composite items with a layered structure and their high weight return with minimal modifications at the early stages of design. The application of the technique is shown on the example of solving the problem of designing a composite bracket for the spoiler hinge of a modern passenger aircraft. Comparison of the designed bracket made of a layered fabric composite with a metal counterpart showed a significant reduction in the weight of the bracket.

A combined GA and DLS parallel algorithm for multimode Rayleigh wave inversion

Multichannel analysis of surface waves (MASW) is a vital method in near-surface exploration. Linear algorithms, such as damped least square method (DLS), are highly dependent on the initial model and are prone to trapping in local minima. While nonlinear algorithms such as genetic algorithm (GA) are globally optimal but inefficient, they are not very practical for complex calculations.In this paper, we propose a combined GA and DLS parallel algorithm (GA-DLS), which has a global search capability due to the GA framework, and has a quick local search capability due to the DLS parallel computing. To simulate the earth model in complex near-surface conditions, we set a low-velocity layer among a layered earth model (LVL) and a high-velocity layer among a layered earth model (HVL), we perform the inversion with DLS, GA, and GA-DLS, respectively. The comparison shows that the GA-DLS inversion gets an efficient and accurate result. Finally, we use the GA-DLS algorithm to invert the field data and achieve good results, verifying the effectiveness of the algorithm.

Comparative RNA-Seq analysis reveals insights in Salmonella disease resistance of chicken; and database development as resource for gene expression in poultry

Salmonella, one of the major infectious diseases in poultry, causes considerable economic losses in terms of mortality and morbidity, especially in countries that lack effective vaccination programs. Besides being resistant to diseases, indigenous chicken breeds are also a potential source of animal protein in developing countries. For understanding the disease resistance, an indigenous chicken line Kashmir faverolla, and commercial broiler were selected. RNA-seq was performed after challenging the chicken with Salmonella Typhimurium. Comparative differential expression results showed that following infection, a total of 3153 genes and 1787 genes were differentially expressed in the liver and spleen, respectively. The genes that were differentially expressed included interleukins, cytokines, NOS2, Avβ-defensins, toll-like receptors, and other immune-related gene families. Most of the genes and signaling pathways involved in the innate and adaptive immune responses against bacterial infection were significantly enriched in the Kashmir faverolla. Pathway analysis revealed that most of the enriched pathways were MAPK signaling pathway, NOD-like receptor signaling pathway, TLR signaling pathway, PPAR signaling pathway, endocytosis, etc. Surprisingly some immune-related genes like TLRs were upregulated in the susceptible chicken breed. On postmortem examination, the resistant birds showed small lesions in the liver compared to large necrotic lesions in susceptible birds. The pathological manifestations and RNA sequencing results suggest a balancing link between resistance and infection tolerance in Kashmir faverolla. Here we also developed an online Poultry Infection Database (https://skuastk.org/pif/index.html), the first publicly available gene expression resource for disease resistance in chickens. The available database not only shows the data for gene expression in chicken tissues but also provides quick search, visualization and download capacity.

Direct Evaluation of the Sensitivity of the Nonlinear Critical Point to Geometrical Imperfections

AbstractA generalized path‐following method is proposed for the direct evaluation of the critical point sensitivity to geometrical imperfections expressed as combination of given shapes. After a finite element discretization, the critical point is defined by a system of nonlinear algebraic equations imposing equilibrium and critical condition according to the null vector method. An arc‐length equation is added to follow a path of critical points in the imperfection space. The solution of the extended system by a Newton scheme requires a Jacobian involving also the derivatives of the critical condition with respect to the FE DOFs and the derivatives of all the problem equations with respect to the imperfection parameters. An analytical and efficient computation of the Jacobian is achieved by a solid‐shell model and a strain‐based model of the imperfection. In addition, a mixed stress‐displacement iterative scheme is devised for a highly efficient and robust solution. Finally, the derivatives of the critical point with respect to the imperfection parameters are also obtained analytically and can be used to generate a gradient‐based critical path for a quick search of the worst‐case imperfection. A compressed cold‐formed lipped channel beam is analyzed as a case study.

Penerapan String Matching Menggunakan Algoritma Boyer-Moore Pada Pengembangan Sistem Pencarian Buku Online

The Bayer Moore algorithm can be applied in online book searches with the aim of making it easier for elementary school students to high school students to find books they want to study or find out which subjects are being sought. In developing an online book search using the Bayer Moore algorithm, several stages of research are needed in a planned, regular, and systematic way. This research stage is the development of a research framework that will determine the success of a system. The stages of the Research and Development (R&D) method. The data collection used in this study is a collection of data obtained from crawling results using the PHP programming language. The Crawling data will later become a searchbox about a book that will be able to use Shopee, Tokopedia, and Gramedia links. The systematic procedure used to collect data is quantitative research methods. The implementation of quantitative research methods focuses on the use of numbers, tables, data, codes, rules and to display the results of the data obtained and will be used for data analysis materials on book search websites using the Boyer-Moore algorithm. Based on the results of research and testing results from the book search website using the Boyer-Moore method in php, the results obtained indicate that the program is declared feasible to use, because the associative rules formed and the resulting search value are the same as the output of the developed program.

How How to Use Graph Theory Benefiting the Neighborhoods Environment

Graph Theory is a popular field with wide applications. It also has the reputation of being the type of math that is more up-to-date with modern times. However, a quick search of the math curriculum at the secondary level will show a striking absence. This paper hopes to reverse the trend and bring to light both a way to introduce graph theory and also to show the application to the real world all in one unified story. Within this article, the reader will move from little to no knowledge toward a fundamental understanding of one component of graph theory. The reader will also be able to walk away with the ability to analyze efficient routes in real-world networks. This work is a crafted message, a student-to-student message, on building intuition for theories and then using them directly. This article is primarily an argument for the importance of engaging with graph theory early in mathematics study. It argues that graph theory is more than a fashionable buzzword. It is the methodical study of interconnection, and it applies to most of the biggest critical global problems we face today: Environmental Protection, Nuclear Safety, Global Food Supply, and Artificial Intelligence Control. In the end, this article may focus on building one application, resource conservation, and logistic optimization, though the reach will be much further. The tools of graph theory are easily adapted to any problem involving systems and their related parts.

An Applied Knowledge Framework to enable knowledge reuse in consulting firms

Knowledge is a core product of management consultancies. Consulting firms consider knowledge management to be a core capability for achieving competitive advantage. ​Knowledge management, especially in project management, faces a lot of challenges that are crucial for the efficiency of work and as a result the success of the projects. According to ISO 30401, there are some knowledge management enablers like human capital, knowledge processes, technology and infrastructure, governance and knowledge sharing culture. Among them are corporate sharing culture, technology and the structure of knowledge which is the most important for companies. The challenges of knowledge management in a consulting business, for example, time saving and efficiency can be solved within the creation of a structured and target-oriented knowledge framework which enables the reuse of knowledge in the whole consulting company. Qualitative methods were used to conceive, design, and to implement the knowledge framework. The approach has involved workshops that included associates, managers, senior consultants, and project directors. This approach enabled the author to record internal requirements and pain points in the current knowledge management base approach, conduct analysis, set priorities, and conceive a new knowledge framework that was able to solve the pain points of consultants and project managers and support them in their daily business. The new framework includes the following components: a flexible structure that adopts itself to defined tagging structure, the storage of knowledge according to the allocation of the content format, and automatically generated statistics to newly upload and download as well as most used files and documents. The results of conducted feedback workshops and interviews showed that the alignment of the new knowledge framework information architecture to the company’s service portfolio and user-friendly design enabled a quick and target-oriented search for the documents and awareness of relevant and important information and knowledge and as a result lead to the increased efficiency of project work in the consulting company.

Similarity Identification Based on Word Trigrams Using Exact String Matching Algorithms

Several studies regarding excellent exact string matching algorithms can be used to identify similarity, including the Rabin-Karp, Winnowing, and Horspool Boyer-Moore algorithms. In determining similarities, the Rabin-Karp and Winnowing algorithms use fingerprints, while the Horspool Boyer-Moore algorithm uses a bad-character table. However, previous research focused on identifying similarities using these algorithms based on character n-gram. In contrast, identification based on the word n-gram to determine the similarity based on its linguistic meaning, especially for longer strings, had not been covered yet. Therefore, a word-level trigram was proposed to identify similarities based on the word trigrams using the three algorithms and compare each performance. Based on precision, recall, and running time comparison, the Rabin-Karp algorithm results were 100%, 100%, and 0.19 ms, respectively; the Winnowing algorithm results with the smallest window were 100%, 56%, and 0.18 ms, respectively; and the Horspool algorithm results were 100%, 100%, and 0.06 ms. From these results, it can be concluded that the performance of the Horspool Boyer-Moore algorithm is better in terms of precision, recall, and running time.

Application of Digital Information Technology in Book Classification and Quick Search in University Libraries.

A digital library is a digital information resource system supported by modern high technology, a next-generation information resource management model on the Internet, and the result of the digitization of library collections, and with the development of society and the accelerated pace of people's lives, people cannot spend too much time classifying and finding books, so the study of book classification and quick finding in university libraries is very important. This paper mainly researches and analyzes the classification and quick search of books in the university library through the algorithms and methods of digital information technology and finds a better algorithm. This paper mainly conducts experiments on automatic text and support vector machine (one-to-many and global optimization) methods and compares the obtained experimental data, such as classification accuracy, classification time, search time, and other data. The experimental results show that the classification accuracy of these three classification methods is in the range of 86%–94%. However, compared with the two methods of automatic text classification and one-to-many classification, the global optimization classification has the highest accuracy in the sample size of each interval. Among them, the classification time is the lowest for automatic text classification, which is less than 30s, and the one-to-many classification sample takes the most time, and their average fitness is in the range of 24%–27%.

An Applied Knowledge Framework to Enable Knowledge Reuse in Consulting Firms

Knowledge is a core product of management consultancies. Consulting firms consider knowledge management to be a core capability for achieving competitive advantage. Knowledge management, especially in project management, faces a lot of challenges that are crucial for the efficiency of work and as a result the success of the projects. According to ISO 30401, there are some knowledge management enablers like human capital, knowledge processes, technology and infrastructure, governance and knowledge sharing culture. Among them are corporate sharing culture, technology and the structure of knowledge which is the most important for companies. The challenges of knowledge management in a consulting business, for example, time saving and efficiency can be solved within the creation of a structured and target-oriented knowledge framework which enables the reuse of knowledge in the whole consulting company. Qualitative methods were used to conceive, design, and to implement the knowledge framework. The approach has involved workshops that included associates, managers, senior consultants, and project directors. This approach enabled the author to record internal requirements and pain points in the current knowledge management base approach, conduct analysis, set priorities, and conceive a new knowledge framework that was able to solve the pain points of consultants and project managers and support them in their daily business. The new framework includes the following components: a flexible structure that adopts itself to defined tagging structure, the storage of knowledge according to the allocation of the content format, and automatically generated statistics to newly upload and download as well as most used files and documents. The results of conducted feedback workshops and interviews showed that the alignment of the new knowledge framework information architecture to the company’s service portfolio and user-friendly design enabled a quick and target-oriented search for the documents and awareness of relevant and important information and knowledge and as a result lead to the increased efficiency of project work in the consulting company.

Indexing complex networks for fast attributed kNN queries

The k nearest neighbor (kNN) query is an essential graph data-management tool used for finding relevant data entities suited to a user-specified query node. Graph indexing methods have the potential to achieve a quick kNN search response and thus are promising approaches. However, they struggle to handle large-scale attributed complex networks. This is because constructing indices and querying kNN nodes in large-scale networks are computationally expensive, and they are not designed to handle node attributes included in the networks. In this paper, we propose a novel graph indexing algorithm, namely CT index, for fast kNN queries on large complex networks. To overcome the aforementioned limitations, our algorithm generates two types of indices based on the topological properties of complex networks. In addition, we further propose BAG index along with CT index so that our algorithm enables to explore kNN nodes based on the attribute similarity. Our extensive experiments on real-world graphs show that our algorithm achieves up to 18,074 times faster indexing and 146 times faster kNN query than other state-of-the-art methods.

A Review of the Presence of SARS-CoV-2 in Wastewater: Transmission Risks in Mexico.

The appearance of SARS-CoV-2 represented a new health threat to humanity and affected millions of people; the transmission of this virus occurs through different routes, and one of them recently under debate in the international community is its possible incorporation and spread by sewage. Therefore, the present work’s research objectives are to review the presence of SARS-CoV-2 in wastewater throughout the world and to analyze the coverage of wastewater treatment in Mexico to determine if there is a correlation between the positive cases of COVID-19 and the percentages of treated wastewater in Mexico as well as to investigate the evidence of possible transmission by aerosol sand untreated wastewater. Methodologically, a quick search of scientific literature was performed to identify evidence the presence of SARS-CoV-2 RNA (ribonucleic acid) in wastewater in four international databases. The statistical information of the positive cases of COVID-19 was obtained from data from the Health Secretary of the Mexican Government and the Johns Hopkins Coronavirus Resource Center. The information from the wastewater treatment plants in Mexico was obtained from official information of the National Water Commission of Mexico. The results showed sufficient evidence that SARS-CoV-2 remains alive in municipal wastewater in Mexico. Our analysis indicates that there is a low but significant correlation between the percentage of treated water and positive cases of coronavirus r = −0.385, with IC (95%) = (−0.647, −0.042) and p = 0.030; this result should be taken with caution because wastewater is not a transmission mechanism, but this finding is useful to highlight the need to increase the percentage of treated wastewater and to do it efficiently. In conclusions, the virus is present in untreated wastewater, and the early detection of SAR-CoV-2 could serve as a bioindicator method of the presence of the virus. This could be of great help to establish surveillance measures by zones to take preventive actions, which to date have not been considered by the Mexican health authorities. Unfortunately, wastewater treatment systems in Mexico are very fragile, and coverage is limited to urban areas and non-existent in rural areas. Furthermore, although the probability of contagion is relatively low, it can be a risk for wastewater treatment plant workers and people who are close to them.

In plain sight: hidden Stanislavski: part 2

ABSTRACT A quick search of acting texts on Amazon UK returns 8000 results. This is a staggering number of books about acting. Certainly, there are duplications, and a quick scroll shows that not all of them are how-to books. But even if these amounted to 90% of the total, that’s still 800 acting texts. Many of them will be by teachers espousing their own special technique that they have developed over years of performance experience and teaching. This presents some questions: just how “original” are these techniques? How many of them merely re-name the ideas of Konstantin Stanislavski without crediting him? How many even know that their ideas originated from him? As we consider the legacy of Stanislavski in the public mind and his contributions, it is worth exploring where he hides. In this second part, the author will continue the examination of these issues and ideas asking the question: is it possible that Stanislavski’s ubiquity is such that he has become hidden and that people are no longer aware of what is his?