Processing Methods Research Articles

Novel Wearable System to Recognize Sign Language in Real Time.

The aim of this study is to develop a practical software solution for real-time recognition of sign language words using two arms. This will facilitate communication between hearing-impaired individuals and those who can hear. We are aware of several sign language recognition systems developed using different technologies, including cameras, armbands, and gloves. However, the system we propose in this study stands out for its practicality, utilizing surface electromyography (muscle activity) and inertial measurement unit (motion dynamics) data from both arms. We address the drawbacks of other methods, such as high costs, low accuracy due to ambient light and obstacles, and complex hardware requirements, which have limited their practical application. Our software can run on different operating systems using digital signal processing and machine learning methods specific to this study. For the test, we created a dataset of 80 words based on their frequency of use in daily life and performed a thorough feature extraction process. We tested the recognition performance using various classifiers and parameters and compared the results. The random forest algorithm emerged as the most successful, achieving a remarkable 99.875% accuracy, while the naïve Bayes algorithm had the lowest success rate with 87.625% accuracy. The new system promises to significantly improve communication for people with hearing disabilities and ensures seamless integration into daily life without compromising user comfort or lifestyle quality.

Triple-0: Zero-shot denoising and dereverberation on an end-to-end frozen anechoic speech separation network.

Speech enhancement is crucial both for human and machine listening applications. Over the last decade, the use of deep learning for speech enhancement has resulted in tremendous improvement over the classical signal processing and machine learning methods. However, training a deep neural network is not only time-consuming; it also requires extensive computational resources and a large training dataset. Transfer learning, i.e. using a pretrained network for a new task, comes to the rescue by reducing the amount of training time, computational resources, and the required dataset, but the network still needs to be fine-tuned for the new task. This paper presents a novel method of speech denoising and dereverberation (SD&D) on an end-to-end frozen binaural anechoic speech separation network. The frozen network requires neither any architectural change nor any fine-tuning for the new task, as is usually required for transfer learning. The interaural cues of a source placed inside noisy and echoic surroundings are given as input to this pretrained network to extract the target speech from noise and reverberation. Although the pretrained model used in this paper has never seen noisy reverberant conditions during its training, it performs satisfactorily for zero-shot testing (ZST) under these conditions. It is because the pretrained model used here has been trained on the direct-path interaural cues of an active source and so it can recognize them even in the presence of echoes and noise. ZST on the same dataset on which the pretrained network was trained (homo-corpus) for the unseen class of interference, has shown considerable improvement over the weighted prediction error (WPE) algorithm in terms of four objective speech quality and intelligibility metrics. Also, the proposed model offers similar performance provided by a deep learning SD&D algorithm for this dataset under varying conditions of noise and reverberations. Similarly, ZST on a different dataset has provided an improvement in intelligibility and almost equivalent quality as provided by the WPE algorithm.

Recent Advances in Non-Contact Food Decontamination Technologies for Removing Mycotoxins and Fungal Contaminants.

Agricultural food commodities are highly susceptible to contamination by fungi and mycotoxins, which cause great economic losses and threaten public health. New technologies such as gamma ray irradiation, ultraviolet radiation, electron beam irradiation, microwave irradiation, pulsed light, pulsed electric fields, plasma, ozone, etc. can solve the problem of fungal and mycotoxin contamination which cannot be effectively solved by traditional food processing methods. This paper summarizes recent advancements in emerging food decontamination technologies used to control various fungi and their associated toxin contamination in food. It discusses the problems and challenges faced by the various methods currently used to control mycotoxins, looks forward to the new trends in the development of mycotoxin degradation methods in the future food industry, and proposes new research directions.

Obtention of Suitable Pregnant Leach Solution (PLS) for Copper Solvent Extraction Plants from Copper Concentrate Using Hydrogen Peroxide and Iodine in a Sulfuric Acid–Chloride Medium

Copper leaching presents an environmentally friendly alternative to traditional sulfide ore processing methods. This study investigates an efficient leaching process for copper concentrate, utilizing a solution of sulfuric acid (H2SO4) and potassium iodide (KI) in a chloride medium (NaCl), enhanced by hydrogen peroxide (H2O2) at room temperature. A significant aspect of this research was optimizing the KI concentration to minimize iodide sublimation into iodine gas (I2). Through the experimental design, the optimal dosages of reagents were determined, leading to maximized copper extraction of approximately 27% in 45 min of testing at room temperature. The results showed that it is possible to obtain a suitable pregnant leach solution (PLS) (i.e., in the range of 3 to 8 g/L of Cu) for treatment in available copper solvent extraction (SX) plants with a cost of less than 4.5 USD/t Cu, according to the economic analysis carried out. The results of this study determine the most effective operational conditions for leaching and ensure a suitable PLS for SX plants in a cost-effective and environmentally friendly manner. This approach could significantly contribute to more sustainable practices in the mining and processing of copper ores.

Deconvolution-based correction of pre-strike arc voltage measurement in medium voltage switches

Abstract Switching arc characterization, e.g. measuring the arc voltage and current, is crucial for assessing the performance of power switchgears under different working conditions. This is especially challenging for short circuit current making as one of the most severe operations for medium voltage load break switches. By closing the switch, a short circuit current flows through the arc which is ignited by the electrical breakdown in the gap between contacts before the contacts touch. This results in an abrupt change from the rated voltage of the power network, i.e. tens of thousands of volts, to the switching arc voltage, i.e. a few tens of volts and ultimately zero when the contacts touch. The inherent response of the measurement system to this very large step preceding the arc formation overlaps with the switching arc voltage and results in unrealistic arc voltages which makes correction of the distorted voltage waveform necessary. In this paper, a post processing method based on deconvolution correction technique, i.e. deconvolution of the measured voltage in time and frequency domains, is examined using experimentally determined impulse responses of the measurement system. To demonstrate its effectiveness, this method is applied to three different measurement system configurations with various step responses. The results show practically identical deconvoluted (corrected) voltage waveforms in all three measurement systems, although the directly measured waveforms have significant differences. The corrected arc voltage waveforms are in agreement with the indirect measurements proposed in previous studies.

Deep learning-based cell segmentation for rapid optical cytopathology of thyroid cancer

Fluorescence polarization (Fpol) imaging of methylene blue (MB) is a promising quantitative approach to thyroid cancer detection. Clinical translation of MB Fpol technology requires reduction of the data analysis time that can be achieved via deep learning-based automated cell segmentation with a 2D U-Net convolutional neural network. The model was trained and tested using images of pathologically diverse human thyroid cells and evaluated by comparing the number of cells selected, segmented areas, and Fpol values obtained using automated (AU) and manual (MA) data processing methods. Overall, the model segmented 15.8% more cells than the human operator. Differences in AU and MA segmented cell areas varied between − 55.2 and + 31.0%, whereas differences in Fpol values varied from − 20.7 and + 10.7%. No statistically significant differences between AU and MA derived Fpol data were observed. The largest differences in Fpol values correlated with greatest discrepancies in AU versus MA segmented cell areas. Time required for auto-processing was reduced to 10 s versus one hour required for MA data processing. Implementation of the automated cell analysis makes quantitative fluorescence polarization-based diagnosis clinically feasible.

FİZİKİ MƏHDUDLUĞU OLAN ATICILARIN MƏŞQ PROSESİ ÜÇÜN SƏMƏRƏLİ VASİTƏ VƏ METODLARIN TƏYİNİ

Determination of Effective Tools and Methods for the Training Process of Physically Disabled Shooters Summary The topic we are addressing has been relevant for almost all time. We are talking about people with physical disabilities. It is a fact that this issue will always be on the agenda of the society as long as humanity exists. Disability is not only the result of certain unpleasant events, but also a consequence of birth. That is, this urgent issue is approached from a medical point of view. A more important issue is the rehabilitation of disabled people, their integration into society. As one of the main means of effectively organizing the leisure time of the disabled, sports has attracted great interest among the disabled. Key words: shooting, air pistol, training process, physical limitation, instability, efficient tool, method

Possibilities of decontaminating organic waste from swine-farming complexes using anaerobic digestion

AbstractAnaerobic digestion with simultaneous production of biogas is one of the most common methods of recycling, processing and decontamination of organic waste to produce alternative fuels. A commonly used indicator of the sanitary safety of the substrate is eggs of Ascaris suum nematodes of pigs, which are characterised by extremely high resistance to environmental factors. The aim is to investigate the effect of the mesophilic mode of anaerobic digestion on the activity of pathogens, particularly Ascaris suum eggs. The eggs of the studied nematode species were placed in a biogas installation at a temperature of 37 °C. The digestate samples with eggs were then taken every 4 days for 28 days, followed by larvae culture to determine the viability of the eggs. The results of our research have shown that the mesophilic regime of anaerobic digestion is an effective method of controlling parasites, but at the same time, it needs to be improved, since only 7.6% of A. suum eggs remained alive after a 1-day stay, about 50% after the week stay and about 9% in the third week stay in the biogas reactor. Thus, further optimisation of anaerobic fermentation in the mesophilic mode can be aimed at improving the suppression of pathogenic activity.

The impact of using educational videos for the subject of management and economics on first-year female students Leadership and Business, in the North Hebron District

Technology has now become an urgent necessity in various fields, and it performs many functions that save people time and effort, and among these fields are: the educational process, where the demand for it has increased; Because of its ability to increase students’ effectiveness and academic achievement, especially educational videos. This study aimed to demonstrate the impact of using educational videos on raising the achievement of first year secondary school students - the Entrepreneurship and Business Branch in the subject of Management and Economics - at Bani Naim Secondary School for Girls. The experimental method was used to achieve the aim of the study. Due to its accuracy in observing the study population and its suitability to the research tool. The study demonstrated the positive impact of educational videos on the study population (students of entrepreneurship and business at Bani Naim Secondary School for Girls), as the students’ academic achievement increased and their grades in that subject rose. The researcher recommends that the teacher introduce educational videos into the teaching process, and consider them one of the modern educational methods in the teaching process

Production of plant protein from seeds and cake of industrial hemp: Overview of processing methods for food industry

Industrial hemp (Cannabis sativa L.) is a multifunctional raw material with a wide spectrum of applications. A huge interest in hemp has arisen in the food industry comparatively recently. Seeds and cake of hemp have the high protein content (20.00-38.70% and 27.90-40.70%, respectively), which makes them a promising raw material for production of concentrates, isolates, and hydrolysates for the food industry. Hemp cake is distinguished by the high content of fiber (17.41-60.38%) and can be used as a prebiotic component of food. In terms of the amino acid content, the amino acid composition of hemp exceeds the corresponding indicators of the reference protein recommended by WHO. The content of lysine is the only indicator, in which hemp protein is inferior to the “ideal” protein. Digestibility of protein of hulled hemp seeds is in a range from 90.8% to 97.5%, which is comparable to digestibility of casein. Digestibility of hemp isolate is 88-91%, which is 21.9% higher than that of soy protein isolate. Peptides and amino acids contained in hydrolysates of hemp protein can show the high biological activity. Hydrolysates attract interest among researchers not only because of their bioactivity but also because of their high digestibility and nutritional value. Targeted proteolysis is a tool that facilitates an improvement in the functional-technological properties of protein. Seeds and cake are a promising raw material for using in food technologies to produce vegetable oil, dietary fiber, protein preparations and functional products. The aim of this paper is to analyze the main methods for industrial hemp processing and promising directions of using protein products from waste of hemp oil production in the food industry.

Study of the toxicity of a corrosion inhibitor for macrophytes

This article presents the results of studies of the toxicity of a corrosion inhibitor used to treat oilfield equipment in relation to a representative of submerged aquatic plants – Elodea canadensis. The characteristics of the toxicant and research methods are given in detail. The method of mathematical processing is indicated. The work presents the results of studying the toxicity of the substance in a wide range of concentrations: from 100 to 5000 mg/dm³ (4 days – acute experience) and 0,05–500,0 mg/dm³ (30 days – chronic experience). During the experiment, changes in the condition and survival of plants, morphological indicators (growth of the main shoot, number of lateral shoots and their length, number of roots and their length, total growth of elodea) were observed. It has been established that the maximum amounts of the substance (5000 and 500 mg/dm³ – acute and chronic experiments, respectively) cause 100% plant death. Lower concentration ranges stimulate morphological parameters. According to the research results, 0,5 mg/l can be taken as a threshold concentration for an inhibitor, and 0,05 mg/l is acceptable.

Hazardous High-Energy Seismic Event Discrimination Method Based on Region Division and Identification of Main Impact Factors: A Case Study

An investigation of risk factors has been identified as a crucial aspect of the routine management of rockburst. However, the identification methods for principal impact factors and the examination of the relationship between seismic energy and other source parameters have not been extensively explored to conduct dynamic risk management. This study aims to quantify impact risk factors and discriminate hazardous high-energy seismic events. The analytic hierarchy process (AHP) and entropy weight method (EWM) are utilized to ascertain the primary control factors based on geotechnical data and nearly two months of seismic data from a longwall panel. Furthermore, the distribution law and correlation relationship among seismic source parameters are systematically analyzed. Results show that the effect of coal depth, coal seam thickness, coal dip, and mining speed covers the entire mining process, while the fault is only prominent in localized areas. There are varying degrees of log-positive correlations between seismic energy and other source parameters, and this positive correlation is more pronounced for hazardous high-energy seismic events. Utilizing the linear logarithmic relationship between seismic energy and other source parameters, along with the impact weights of dynamic risks, the comprehensive energy index for evaluating high-energy seismic events is proposed. The comprehensive energy index identification method proves to be more accurate by comparing with the high-energy seismic events based on energy criteria. The limitations and improvements of this method are also synthesized to obtaining a wide range of applications.

Digital Transformation Techniques for Manuscripts

The world is witnessing continuous technological developments that have an impact on societies and institutions. Therefore, all countries seek to keep pace with these developments and introduce them into various fields. Digital transformation has become one of the most important necessities that all institutions must adopt today, as digital transformation is capable of creating a competitive technological environment to achieve the highest levels of quality at the lowest costs. Manuscripts are of interest to many scholars and researchers due to their scientific and artistic value. Preserving them means preserving national identity, especially with the emergence of technology. It has become imperative to preserve manuscripts from damage and loss and make them available to the largest number of beneficiaries. In the past, Arabs were among the most important peoples who contributed to the preservation of manuscripts. One of the most important challenges facing modern society is managing, preserving, and retrieving information from the vast amount of paper documents and files that are increasing daily. By using technology, the time taken to search for the required document or distribute documents to the relevant parties leads to a significant increase in the productivity of the institution. Information technology and electronic communication systems have revolutionized traditional methods of processing, preserving, and exchanging information. The presence of advanced technologies provides us with ease and accuracy in accessing information. Archiving as a general concept relies on storing and classifying papers in a way that makes it easy to refer back to them when needed. With the advent of computers, the process has become easier, providing more flexibility and ease in retrieval, as well as reducing the costs of preservation and storage. This technology has a direct impact on the archival profession, as archivists have turned to electronic means and imaging storage systems, as well as audiovisual methods, in an attempt to solve the storage and preservation problem. Modern digital technology affects all areas of life due to the integrated scientific environment it provides. All societies have begun to transition towards the digital age because of its remarkable development in information and communication technology. Keywords: Information, Manuscript, Technology, Scanning, Digitization

It's time for artificial intelligence governance

Advances in Internet of Things and Artificial Intelligence have transformed society with the potential to foster the prosperity of human beings and improving societal welfare. However, at the same time, there are concerns about their potential negative impact. In this regard, it is of utmost importance to establish a regulatory framework for the Artificial Intelligence and the Internet of Things that will ensure that human rights and fundamental freedoms are respected, promoted, and protected.In this sense, the goal of this article is to propose the Artificial Intelligence and the Internet of Things Governance model. To achieve a better regulation concept, for the Regulatory Impact Assessment we used the Analytical Hierarchy Process method.

Swelling of Sealing Assembles Parts Manufactured from Composite Materials

One of the advantages of plastics over metals and other materials is that there are very simple and inexpensive ways to make products from them. It is known that there are more than 100 methods for manufacturing plastic products. The use of these methods depends on the configuration of the product being manufactured, the technical conditions required of it, its purpose and economic efficiency. Although there are more than 100 processing methods, the most common of them are mainly extrusion in the production of large-sized products, including pipes, sheet materials, webs, various profiles, rods, as well as in the production of medium-sized products. and small parts in terms of quantity, casting pressure and pressing methods. Based on economic indicators, the optimal method for preparing any composite materials should be taken into account and grouped in advance. The development of new technological methods for manufacturing parts and products from polymers and their compositions is of great importance.

A Positioning Alarm System for Explosive Impact Debris Protective Suit Based on an Accelerometer Array.

Protection suits are vital for firefighters' safety. Traditional protection suits physically protect firemen from burns, but cannot locate the position of bodily injuries caused by impact debris. Herein, we present a wearable impact debris positioning system for firefighter protection suits based on an accelerometer array. Wearable piezoelectric accelerometers are distributed regularly on the suit to detect the vibration on different body parts, which is conducive to determining the position of injured body parts. In addition, the injured parts can be displayed on a dummy body model on the upper computer with a higher localization accuracy of 4 cm. The positioning alarm system has a rapid response time of 0.11 ms, attributed to the smart signal processing method. This work provides a reliable and smart method for locating and assessing the position of bodily injuries caused by impact debris, which is significant because it enables fire commanders to rescue injured firefighters in time.

Review of Natural Language Processing Methods for Automatically Generating Test Tasks

Review of Natural Language Processing Methods for Automatically Generating Test Tasks

Determinants of Unemployment: Empirical Evidence from Indonesia

Indonesia faces the challenge of a rapidly increasing labor force that is not proportional to the number of jobs available, resulting in unemployment. This study examines the effect of economic growth, inflation, and minimum wage on unemployment in 34 provinces in Indonesia from 2018 to 2022. This research uses secondary data from the Central Bureau of Statistics and Bank Indonesia. The data processing method uses panel data regression with the Fixed Effect model. The results of the analysis show that economic growth and inflation have a negative and significant relationship with unemployment in Indonesia. In contrast, the provincial minimum wage has a positive and significant relationship with unemployment in Indonesia.

The Synthesis of Integrative Sustainable Capability to Indonesian Sustainable Eco-print Fashion

With a focus on small businesses that are oriented towards sustainable fashion in the Eco-print business, this research focuses on forming a synthesis of Integrative Sustainable Capability variables which are derived from a systematic process through the derivation process of Resources Based Theory and Strategic Orientation. The synthesis of Strategic Resources in the theory of Resources Based and Strategic Orientation leads to the construction of a new concept, namely Integrative Sustainable Capability as a competency to integrate environmental and social considerations to strategically acquire, combine and deploy the resources in business operations and cooperation included in knowledge management to generate performance values. The structured idea process method is used to synthesize novelty constructed in the Integrative Sustainable Capability. The Integrative Sustainable Capability is used as a mediator in the relationship between Knowledge Management Capabilities and Entrepreneurial Performance in the context of Eco-print small businesses. The conceptual model was formed by linking these three variables of Knowledge Management and Entrepreneurial Performance with Integrative Sustainable Capability as a mediation derived from the synthesis of novelty process in the context of Eco-print small business.

EFFECT OF TOMATO POMACE ON SENSORY AND TEXTURAL PROPERTIES OF RAW-COOKED MEAT PRODUCT

In the meat industry, there is a growing interest in the use of innovative processing methods, reformulated products, and the replacement of synthetic ingredients with natural bioactive compounds. Replacing synthetic antioxidants with natural antioxidants is a challenging process, but it can bring positive results. Our current research focuses on sensory and textural properties of raw-cooked meat product (frankfurters), which we observed on the 1st, 7th, 14th and 21st days of storage. We incorporated extract from tomato pomace into frankfurters as natural antioxidants. We used two concentrations of extract (3 mL.kg-1 and 5 mL.kg-1), the control with the addition of ascorbic acid and negative control. Sensory quality of meat product is one of the most important indicators that can influence the consumer. In the taste parameter, the best rated groups were Con-C and TCP-2. Furthermore, the addition of tomato pomace extract does not cause a significant change in the consistency of the meat products. After textural analysis, no statistically significant differences were observed between individual samples in any of the evaluated parameters.