Collection Equipment Research Articles

Scale adaptive subdomain matching network for bearing fault diagnosis

The wide application of transfer learning technology can effectively solve the problem of the difference between data collection and actual application equipment of traditional intelligent fault diagnosis methods in the practical application process. However, the difference in subdomain space and the serious imbalance of data samples in the process of simultaneous transfer restricts the deep transfer learning technology to the engineering application of high-precision diagnosis. In order to solve the problem of subdomain matching with different subspaces and unbalanced data samples, in this paper we study the subdomain adaptive method and propose a scale adaptive subdomain matching (SASM) method. The SASM method divides the global feature space according to the sample labels, and features with the same label will be divided into the same sub-feature space. Using the edge distribution of the sample and the category weight of the label, the SASM method can effectively optimize the feature distribution of the same subdomain and the weight distribution of different subdomains. Based on the establishment of a clearer internal structure of features, the field adaptation effect is improved, and the matching ability is enhanced when the sample is unevenly distributed. At the same time, the SASM network (SASMN) method for unsupervised bearing fault diagnosis is constructed and validated by experiments. The results indicate that SASMN can effectively optimize the subdomain adaptive effect, and the diagnostic accuracy of the target domain data set is significantly higher than the other three currently popular domain adaptive fault diagnosis methods.

PENGARUH GUIDANCE COACHING TERHADAP KINERJA TUGAS YANG DIMEDIASI OLEH KINERJA ADAPTIF PADA KARYAWAN PT. PLN UNIT PELAKSANA PELAYANAN PELANGGAN (UP3) BANDA ACEH

This study aims to examine the effect of Guidance Cocahing to task performance with Task Adaptive as a mediator for employees of PLN UP3 Banda Aceh. The sample used in this study were 141 employees using purposive sampling technique. Then, this study used data collection equipment, namely a questionnaire (questionnaire). This study uses H path analysis as an analytical method to determine the effect of the variables involved in mediation testing in this study. Based on the results of the path analysis, it shows that guidance coaching partially has a positive and significant influence to task performance and adaptive performance of PT PLN UP3 Banda Aceh employees. Adaptive performance also partially has a positive and significant influence to task performance of PT PLN UP3 Banda Aceh employees, and guidance coaching to task performance are not mediated by adaptive performance of PT PLN UP3 Banda Aceh employees.

PENGARUH REPUTASI DAN KUALITAS INFORMASI YANG DIMEDIASI OLEH KEPERCAYAAN TERHADAP MINAT BELI PADA PENGGUNA SHOPEE DI KOTA BANDA ACEH

This study aims to measure the effect of Reputation and Quality Information on Purchase Intention mediated by Trust at Shopee‟s buyers in Banda Aceh City. The sample used in this study were customers of Shopee in Banda Aceh City, amounting to 150 respondents. Data collection equipment used in this study is a questionnaire. The sampling technique used is nonprobability sampling and purposive sampling. Hierarchical Linear Modelling (HLM) is used as an analytical method to determine the effect of the variables involved. Based on the results of HLM that reputation has a significant effect on trust, Quality information has a significant effect on trust, Reputation has a significant effect on purchase intention, Quality information has a significant effect on purchase intention, Trust has a significant effect on purchase intention, Trust mediates the effect of reputation on purchase intention and trust mediates the effect of quality information on purchase intemtion

PENGARUH ONLINE CUSTOMER REVIEW DAN SHOPPING EXPERIENCE TERHADAP REPURCHASE INTENTION YANG DIMEDIASI OLEH TRUST (STUDI KASUS PADA ONLINE MARKETPLACE)

This study aims to determine the Effect of Online Customer Review and Shopping Experiences on Repurchase Intention Mediated by Trust (Case Study on Online Marketplace). The population of this study was the society in Banda Aceh City that had purchased fashion products more than once on the online marketplace. The sampling technique was non-probability sampling with the purposive sampling method. The sample consisted of 230 respondents, but only 191 respondents met the sampling criteria. Data collection equipment was a questionnaire and google form. The analysis technique used was Structural Equation Modeling (SEM) using AMOS software. The results showed that Online Customer Review has a significant effect on Repurchase Intention, but Shopping Experience has no significant effect on Repurchase Intention. Further, Online Customer Review has a significant effect on Trust and Shopping Experience has a significant effect on Trust. This study also found that Trust has no significant effect on Repurchase Intention. Online Customer Review mediated by Trust has no significant effect on Repurchase Intention, and Shopping Experience mediated by Trust has no significant effect on Repurchase Intention.

Next‐generation ultrasonic recorders facilitate effective bat activity and distribution monitoring by citizen scientists

AbstractTime and budgetary resources are often a limiting factor in the collection of large‐scale ecological data. If data collected by citizen scientists were comparable to data collected by researchers, it would allow for more efficient data collection over a broad geographic area. Here, we compare the quality of data on bat activity collected by citizens (high school students and teachers) and researchers. Both researchers and citizen scientists used the same comprehensive instructions when choosing study sites. We found no statistically significant difference in total bat activity minutes recorded by citizens and researchers. Instead, citizen scientists collected data from a wider variety of habitats than researchers. Involvement of citizens also increased the geographical coverage of data collection, resulting in the northernmost documentation of the Nathusius’s pipistrelle so far in Finland. Therefore, bat research can benefit from the use of citizen science when participants are given precise instructions and calibrated data collection equipment. Citizen science projects also have other far‐reaching benefits, increasing, for example, the scientific literacy and interest in natural sciences of citizens. Involving citizens in science projects also has the potential to enhance their willingness to conserve nature.

Оценка экологических последствий от объектов энергетики при реализации перспективных проектов освоения месторождений арктических территорий восточных регионов России

The ecological aspects of the functioning of energy facilities in the Arctic zones of the eastern regions of Russia are of increasing importance for the strategic interests of the country, on the one hand, and due to the specific features of territories with a weak ability to restore the natural environment, on the other hand. The studies carried out at the Energy Systems Institute of Siberian Branch of the Russian Academy of Sciences revealed the fact that the current environmental situation in the eastern regions of the Arctic is unfavorable. Promising projects for the development of mineral deposits are associated with an increase in the consumption of all types of energy resources. In addition, this will require intensive development of the energy sector: from the expansion of existing power facilities to the construction of new ones using associated petroleum gas, and possibly LNG. In general, the implementation of projects will lead to the following distribution of the total emission of pollutants from the energy sector: 47% — the Taimyr-Turukhan zone, 30% — the North Yakutsk zone with a predominant contribution from coal-fired boilers, and, accordingly, 23% of all emissions will enter the atmosphere of the Chukotka zone, where coal-fired boiler houses also prevail. With the implementation of advanced development projects, CO2 emissions will also increase from 7 to 16.6 million tons with their predominance in the Taimyr-Turukhan zone (11,9 million tons). Thus, the assessment of the environmental impact from the development of promising deposits in the Arctic territories of the eastern regions of Russia has shown that the emissions of pollutants will increase by 1.6-1.8 times, and those of carbon dioxide by 2.2-2.3 times. Given that the particulate matter will remain the main impurity in the composition of pollutants (up to 35-37%) due to the existing power facilities, coal-fired thermal power plants and boiler houses need a large-scale modernization of the collection equipment. Sulfur dioxides are becoming another predominant impurity, mainly due to newly commissioned facilities running on associated petroleum gas. Therefore, it is necessary to envisage measures to reduce them.

Development of IOT Device for Sensing Weather and Environmental Pollutants

Pollutants emitted into the atmosphere, such as ozone, which raises temperature, contributes to climate change. This may have inverse effect on the local air quality. However, other Particulate Matter (PM) components can heat or cool the temperature. Weather and environmental pollution can cause headaches, heart disease, respiratory problems, acid rain, fever, and other symptoms that are harmful to both people and the environment. This research center on development of smart sensors to monitor our environment's exposure to weather and environmental contaminants. This was made possible by developing an interface between data collection and monitoring equipment that interfaced with a website and analysis software. The online portal records and analyzes the measured data from the monitoring device in accordance with the WHO (World Health Organization) standard. It also compares the measured data from various locations. The main microcontroller in this work is an Arduino UNO which helps in data collection; and the CoolTerm application which helps exchange data with hardware connected to serial ports with the microcontroller. The system monitors environmental changes such as temperature and precipitation. The data is displayed as graphical statistics on the web site's design in the form of web portal information.
 Offices on the Federal Polytechnic Ile Oluji campus, in addition to the production powerhouse, are used to test the equipment. Each dataset was generated in three minutes and compared to the WHO standard. People who live near generators, according to the findings, face a greater risk to their health.

Features of NATO’s soldiers limbs combat trauma treatment during armed conflicts on the territory of Iraq and Afghanistan (literature review)

The article describes armed conflicts on the territory of Iraq and Afghanistan. Improvement of individual and collective protection equipment has reduced the number of cases of soft tissue wounds in the extremities. The main cause of mortality and wound complications is antibiotic-resistant microflora. Purulent complications lead to chronic treatment of the wound healing process and a long period of specialized treatment and rehabilitation, which entails difficulties in the socialization of wounded servicemen, as well as significant financial costs from the state. When providing medical care to wounded military personnel, it is negative pressure wound therapy. Phage therapy is a promising method for treating infectious complications.

Exposure Determinants in the French Database COLCHIC (1987-2019): Statistical Modeling across 77 Chemicals.

The COLCHIC database contains workplace exposure results of chemical samples collected by the French prevention network since 1987. We aimed to investigate potential associations between exposure levels and ancillary variables in COLCHIC across a broad range of chemical agents in order to provide insight into how to best interpret and exploit the information in this national database. We selected personal and area measurements in COLCHIC and collected outside respiratory personal protective equipment (PPE), restricted to chemical agents that had at least 1000 samples available. We used Tobit models to estimate associations between exposure concentrations and sample year, sampling duration, PPE, workforce size, collective protective equipment, origin of request, and reason for request for each chemical agent for the period 1987-2019. Models for period 2002-2019 also included type of process (open/closed) and exposure frequency. We used separate models for each combination of agent, period, and personal or area samples. We then applied Bayesian meta-analytical methods to assess average effects and effect heterogeneity of exposure factors across agents. COLCHIC contained 720 282 exposure results (62% personal and 38% area samples) to 77 agents, including 346 766 results for the more recent period 2002-2019 (67% personal and 33% area samples). Sample year and duration, PPE, and process type had the strongest and most consistent associations with exposure levels across agents. Personal and area exposure levels decreased yearly (6% for the entire period and 9% since 2002), and 30-min samples were approximately twice as high as 240-min samples. Workers wearing PPE were exposed to levels 1.7 times higher on average than those without PPE for both area and personal samples. Personal exposure levels associated with enclosed or semi-enclosed processes were approximately 20-30% lower compared with open processes. The associations for the other exposure variables were weaker and more inconsistent between agents. Between-agent heterogeneity of estimated effects, based on 80% prediction intervals, was lowest for sampling duration, time trends, and the presence of PPE. Sampling duration, time trends, and the presence of PPE are important factors to take into account when analyzing COLCHIC and had similar associations with exposure levels across agents. Other variables generally showed weaker associations or variable effects. These results will be used to adjust exposure estimates for the French working population from measurements stored in COLCHIC.

Development of optimum СО2 transportation for its storage in geological formations

The sources of a large amount of carbon dioxide emissions into the atmosphere in Azerbaijan have been identified, the volume of burned hydrocarbons and the amount of waste calculated as well. The methods of centralized collection, transportation and disposal of waste from sources on the territory were studied as the main object of research work. The relevant geological formations existing in Azerbaijan were studied and their gas capacity specified by identifying geological formations for storage of accumulated CO2 gases in underground formations (underground gas storage). The study is based on global experience, real production facilities, new projects, modern technologies and equipment for CO2 collection.

Indigenous knowledge on camel milk and camel milk products hygienic handling, processing and utilization in Borana Area, Southern Ethiopia

The study was conducted to assess traditional camel milk and camel milk products handling, preservation and processing, as well as utilization in Borana area. A total of 132 and 24 respondents were selected from milk producers and supplies, respectively through purposive sampling technique and interviewed on various aspects of camel milk and camel milk products using a single-visit multiple-subject diagnostic survey. Survey results revealed that the majority of camel dairying was done by women. Result showed hygienic handling of camel milk and milk products of pastoralists and agro-pastoralists was poor. Respondents reported that they preserved camel milk by washing and smoking milk vessels, keeping milk in a cold place and processing into other milk products. All most all respondents use camel milk mainly in its raw state for home consumption. Most of the respondents in the study area traditionally process camel milk into other camel milk products mainly during surplus milk production. The major product produced by respondents was fermented sour camel milk, locally named chuuchee. According to respondents lack of cooling facilities, improper collection center, lack of milk collection equipment, market milk selling shed, quick spoilage of milk due to the hot environment, seasonality of milk supply and marketing are the main constraints. Establishment of milk collection centers and introduction of small-scale milk processing plants with market linkage might help to solve camel milk hygienic handling and marketing problems in the study area.

Solar Irradiation Evaluation through GIS Analysis Based on Grid Resolution and a Mathematical Model: A Case Study in Northeast Mexico

The estimation of the solar resource on certain surfaces of the planet is a key factor in deciding where to establish solar energy collection systems. This research uses a mathematical model based on easy-access geographic and meteorological information to calculate total solar radiation at ground surface. This information is used to create a GIS analysis of the State of Nuevo León in Mexico and identify solar energy opportunities in the territory. The analyzed area was divided into a grid and the coordinates of each corner are used to feed the mathematical model. The obtained results were validated with statistical analyses and satellite-based estimations from the National Aeronautics and Space Administration (NASA). The applied approach and the results may be replicated to estimate solar radiation in other regions of the planet without requiring readings from on-site meteorological stations and therefore reducing the cost of decision-making regarding where to place the solar energy collection equipment.

Deep learning-based road damage detection and classification for multiple countries

Many municipalities and road authorities seek to implement automated evaluation of road damage. However, they often lack technology, know-how, and funds to afford state-of-the-art equipment for data collection and analysis of road damages. Although some countries, like Japan, have developed less expensive and readily available Smartphone-based methods for automatic road condition monitoring, other countries still struggle to find efficient solutions. This work makes the following contributions in this context. Firstly, it assesses usability of Japanese model for other countries. Secondly, it proposes a large-scale heterogeneous road damage dataset comprising 26,620 images collected from multiple countries (India, Japan, and the Czech Republic) using smartphones. Thirdly, it proposes models capable of detecting and classifying road damages in more than one country. Lastly, the study provides recommendations for readers, local agencies, and municipalities of other countries when one other country publishes its data and model for automatic road damage detection and classification. A part of the proposed dataset was utilized for Global Road Damage Detection Challenge’2020 and can be accessed at (https://github.com/sekilab/RoadDamageDetector/).

Study on Optimization of Passenger Flow at a Metro Station Based on AnyLogic—Case Study of Youfangqiao Station of Nanjing Metro Line 2

In this study, simulation software AnyLogic was used to establish a station simulation model for a metro line. First, a basic model of the environment of the metro station was drawn, and accordingly, reasonable assumptions and simplifications were proposed. Then, a diagram of the passenger walking path was created and the simulation variables and functions for passenger flow management were designed. Considering Youfangqiao Station of Nanjing Metro Line 2 in China as an example, the real passenger flow data of this station were statistically analyzed. To simulate the station passenger flow management, input parameters such as the passenger space diameter, passenger flow generation rate, delay rate of automatic fare collection equipment and security check machine, and the number of gates were considered. Passenger flow management was optimized for the morning and evening peak periods, and reasonable suggestions were proposed based on the optimization results, providing a theoretical basis for the construction planning and pre-evaluation of station operation capacities of urban rail transit systems.

Modeling and simulation of solar flat plate collector for energy recovery at varying regional coordinates.

Pakistan has remained an energy-deficient country, and most of the industrial sectors are closed due to the loading shedding of electricity. Even though Pakistan is located on the "solar belt" and receives over 2 MWh/m2 solar irradiation per year with 1500-3000 h of sunshine, unfortunately solar energy is not harnessed to fulfill the energy needs of the country. Solar flat plate collectors (SFPC) are widely employed for collecting solar radiations from the sun. Currently, worldwide solar thermal energy is widely used in household and commercial equipment for energy collection and utilization. The working fluid selected for this research work is water; numerical simulations were performed using Ansys FLUENT. On selected geographical coordinates, solar ray tracing model was employed to incorporate solar heat flux. Nawabshah (NWB), Hyderabad (HYB), Jacobabad (JCB), and Mirpurkhas (MPK) cities were selected for the measuring of performance of SPFC. Firstly, parallel to ground (at a 0° tilt angle) orientation of SFPC was performed. Furthermore, the performance of SFPC was measured using tilt angles of 15°, 30°, and 45°, respectively. The maximum exit water temperature in JCB at a tilt angle of 30° was 97.8 °C in March and a minimum of 88.09 °C in June. In HYD, at a tilt angle of 45°, the maximum temperature rise was recorded at 98.01 °C in November and the minimum was noticed at 76.37 °C in June. While in JCA, at an angle of 30°, the highest temperature was recorded at 97.83 °C in February and a minimum of 78.54 °C in June. The specific aim of this research study was to measure the performance of the SFPC at different tilt angles and at varying geographical coordinates through numerical simulations.

Health Impact and Psychosocial Perceptions among French Medical Residents during the SARS-CoV-2 Outbreak: A Cross-Sectional Survey.

This study compared the impact on mental health and the psychosocial perceptions of medical residents and healthcare workers (HCWs) in a hospital after the first peak of the SARS-CoV2 outbreak in France. A validated version of the SATIN questionnaire with a modified scoring system was used to collect data on health and psychosocial factors. This questionnaire was sent to all workers at the hospital in July 2020 and was self-administered online. Using a multivariate multinomial regression model, the study included demographic variables such as age, gender, years at workplace and the relevant of covariate as HCW status. One thousand, four hundred and six questionnaires were available for analysis including 393 non-HCWs, 891 HCWs and 122 medical residents. Medical resident status is a risk factor for stress (OR 4.77 [2.48–9.18] p < 0.001), worse global health (OR 4 [1.7–9.6] p < 0.001) and mental health (OR 2.58 [1.3–5.1] p = 0.02), negative perception of work demand (OR 8.25 [3.5–19.6] p <0.001), work activity environment (OR 3.18 [1.5–6.7] p = 0.02) and organizational context (OR 4.9 [2.38–10.4] p <0.001). Action on collective support, protection equipment, organizational context and framework are important.

PENGARUH MEDIA SOSIAL DAN REKOMENDASI SELEBGRAM TERHADAP KEPUTUSAN PEMBELIAN DENGAN EWOM SEBAGAI PEMEDIASI PADA PENGGUNA SHOPEE DI BANDA ACEH

This study aims to examine the effect of Social Media and Celebrity Recommendations on Purchase Decisions with Electronic Word of Mouth (e-WOM) as a mediator for Shopee users in Banda Aceh. The sample used in this study were 168 Shoppe users using non-probability sampling technique. Then, this study used data collection equipment, namely a questionnaire (questionnaire). This study uses Hirarchical Lineal Modeling (HLM ) as an analytical method to determine the effect of the variables involved in mediation testing in this study. Based on the results of the HLM analysis, it shows that social media has an effect on E-wom, Selebgram Recommendations have an effect on E-wom, Social Media has an effect on Purchase Decisions, Selebgram Recommendations have an effect on Purchasing Decisions, E-wom has an effect on Purchase Decisions, Social Media has an effect on Purchase Decision with E-wom as a mediating variable, and Selebgram Recommendations affect the Purchase Decision with E-wom as a mediating variable. Social Media, Celebrity Recommendation, E-wom, Purchase Decision, Hirarchical Lineal Modeling (HLM)

Occupational exposure of workers to noise in a carpentry

Abstract Background Currently, we can find a more industrialized and developed society that has contributed to the large-scale expansion of sound levels. Noise is already identified as one of the main risk factors for the health of workers, due to the high frequency of workers daily exposed and risky professional activities. In this sense, it is necessary to carry out assessments of occupational noise in order to understand whether or not workers' exposure is within the limit values and what preventive measures to adopt. Methods The present study had as main objective to evaluate the occupational exposure to noise of the workers of a carpentry, located in a municipality in the Center of Portugal, and to understand its influence on their health. Measurements were performed using two devices, a Cesva dosimeter, model DC 112 and a Cesva model SC420 sound level meter. Results The results obtained demonstrated the existence of noise in some of the evaluated workstations and also the existence of some workers exposed to high levels of noise. It was also possible to observe that although all workers have hearing protection, it is not always effective. Conclusions We conclude that carpentry is a noise-producing work environment, and with the help of appropriate collective and/or individual protective equipment, it is possible to mitigate this exposure to noise, either by workers or by machines/equipment, ensuring thus the safety and health of workers.

DIGITAL TWIN OF GAS RECIPROCATING COMPRESSOR UNIT: CONCEPT, ARCHITECTURE &amp; PILOT IMPLEMENTATION

Combination of information and operational technologies has led to a new way of production, to a new technological revolution, known as Industry 4.0. The Digital Twin plays a central role in this technology. The Digital Twin is a predictive maintenance tool, and allows you to simulate various options for device failures taking into account their operation modes, environmental influences and various degrees of wear. The concept of creating a digital twin of a real physical object of research is proposed - an AJAX DPS-180 internal combustion engine with a gas piston compressor, which is designed to pump gas from gas wells. A feature of its work is autonomous long-term operation in the field with the remoteness of the service personnel, direct environmental impact and ensuring the reliability and stability of work. Therefore, monitoring the parameters of the engine with the subsequent prediction of its failures is especially important. The work on creating a digital twin for AJAX DPS-180 is being carried out in cooperation and with the support of Armco-Engineering, the operator of this equipment.&#x0D; Six stages of the process of creating a digital twin of a given object are shown: collection and preliminary processing of data on the technical state of a real object; early detection of malfunctions, predicting the time of failure; service planning; optimization of financial and time resources for service. Equipping a real object with various sensors made it possible to continuously collect data on its technical condition, and technologies of the industrial Internet of things, such as Big Data and the predictive statistical model, predict failure times with high accuracy.&#x0D; The developed and implemented schemes for equipping an object with data collection equipment and a diagram of the flow of this data in the Internet of Things are presented. The basis of the data collection system is a microcontroller, a set of a crankshaft speed sensor and thermocouples, a multiplexer and 16-bit analog-to-digital converters that convert thermo-EMF of thermocouples. At the moment, channels for measuring the speed, coolant and exhaust gas temperatures have been implemented. It is proposed to use the ThingSpeak server as a remote resource as a cloud aggregator and carrier of this data. The MATLAB mathematical package integrated into the resource is used as a data analyzer.

Surface Activity-Tuned Metal Oxide Chemiresistor: Toward Direct and Quantitative Halitosis Diagnosis.

Continuous monitoring of hydrogen sulfide (H2S) in human breath for early stage diagnosis of halitosis is of great significance for prevention of dental diseases. However, fabrication of a highly selective and sensitive H2S gas sensor material still remains a challenge, and direct analysis of real breath samples has not been properly attempted, to the best of our knowledge. To address the issue, herein, we introduce facile cofunctionalization of WO3 nanofibers with alkaline metal (Na) and noble metal (Pt) catalysts via the simple addition of sodium chloride (NaCl) and Pt nanoparticles (NPs), followed by electrospinning process. The Na-doping and Pt NPs decoration in WO3 grains induces the partial evolution of the Na2W4O13 phase, causing the buildup of Pt/Na2W4O13/WO3 multi-interface heterojunctions that selectively interacts with sulfur-containing species. As a result, we achieved the highest-ranked sensing performances, that is, response (Rair/Rgas) = 780 @ 1 ppm and selectivity (RH2S/REtOH) = 277 against 1 ppm ethanol, among the chemiresistor-based H2S sensors, owing to the synergistic chemical and electronic sensitization effects of the Pt NP/Na compound cocatalysts. The as-prepared sensing layer was proven to be practically effective for direct, and quantitative halitosis analysis based on the correlation (accuracy = 86.3%) between the H2S concentration measured using the direct breath signals obtained by our test device (80 cases) and gas chromatography. This study offers possibilities for direct, highly reliable and rapid detection of H2S in real human breath without the need of any collection or filtering equipment.