transfer unit
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Cross-domain sequential recommendation is the task of predict the next item that the user is most likely to interact with based on past sequential behavior from multiple domains. One of the key challenges in cross-domain sequential recommendation is to grasp and transfer the flow of information from multiple domains so as to promote recommendations in all domains. Previous studies have investigated the flow of behavioral information by exploring the connection between items from different domains. The flow of knowledge (i.e., the connection between knowledge from different domains) has so far been neglected. In this article, we propose a mixed information flow network for cross-domain sequential recommendation to consider both the flow of behavioral information and the flow of knowledge by incorporating a behavior transfer unit and a knowledge transfer unit . The proposed mixed information flow network is able to decide when cross-domain information should be used and, if so, which cross-domain information should be used to enrich the sequence representation according to users’ current preferences. Extensive experiments conducted on four e-commerce datasets demonstrate that the proposed mixed information flow network is able to improve recommendation performance in different domains by modeling mixed information flow. In this article, we focus on the application of mixed information flow network s to a scenario with two domains, but the method can easily be extended to multiple domains.

The validation and accuracy of internet protocol version 6 (IPv6) performance using jumbo frames is still not perfect, due to peer-to-peer connections testing within the same operating system and between operating systems. Therefore, inaccurate data test results. To mitigated, testing with a wider platform is recommended, a medium-scale network connection is proposed such as metropolitan area networks. In this works, a connection between computer devices connected by three proxy routers are made, with different IPv6 segments on each port. Then each computer device sends traffic data to each other using a traffic-generator application. The first test through three routers without tunnel connection is carried out as the first scenario to compare performance with tunnel-based testing. Three parameters have been used in this test, such as maximum transfer unit (MTU) 1500 bytes, MTU 400 bytes and MTU 9000 bytes. The results of the tests conducted show that the use of jumbo frames using a proxy is less effective, even though it produces a larger throughput when using the MTU 4000, but there is fragmentation in the packet passing through the proxy because the packet passing through the proxy is split into 1500 byte sizes.

Abstract The current paper enhances the methods presented in ASME PTC 4.1 and 4.4 and proposes an exergy-based loss method for assessing heat recovery steam generators (HRSGs) performance. First, energy and exergy analyses are applied to one HRSG unit in an existing combined cycle power plant. Then, the calculated exergy destructions are further split into avoidable and unavoidable parts. The sources of inefficiency consist of three energy and exergy loss terms and two exergy destruction terms. The loss terms are associated with the release of the exhaust gas to the atmosphere, Carbon Monoxide formation, and the heat loss from the casing, while the destruction terms represent exergy destruction within the duct burner and the heat transfer unit. The advanced exergy analysis was conducted based on a realistic perspective, considering the integrated operation of both subcomponents. Results reveal that the main source of inefficiency corresponds to the losses associated with the exhaust gas from the stack. Moreover, utilizing semi-ideal heat exchangers can avoid a considerable part (18.8%) of the exergy destruction in the heat transfer unit. The HRSG exergy efficiency is obtained by 71.7% and can be increased to 75.3% in unavoidable operating conditions.

The article discusses the calibration results of reference standards-copies according to the State Primary Standard of the Mass Unit using the new CCL 1007 vacuum comparator and buoyancy artifacts. The authors provided historical data on the calibrations of copies of the International Prototype of the Kilogram (IPK) starting from 1892, including the Russian prototype № 12. The instability of the prototype of the kilogram No. 12 corresponds to international values and is assessed at 5 · 10–11 kg per year. Changes in the mass of copies are assessed in relation to the mass of the IPK, but it is impossible to determine to what extent it has changed. This was the reason for the adoption of a new value of the kilogram. Following the adoption at the 26th meeting of the General Conference on Weights and Measures (CGPM) held in Paris in November 2018, Planck constant was numerically established with absolute accuracy, and total uncer tainty of 1 · 10–8 kg was assigned to the mass of the IPK. Thus, the authors set the aim to preserve the numerical value of the total uncertainty of the reference standards-copies by reducing the transfer error of the State Primary Standard by 10 times. The article presents the calibration results of six reference standards-copies in relation to prototype No. 12 with the primary data processing using the method of least squares, and the uncertainty budget is provided. The calibration results of the reference standards-copies confirmed the accuracy increase of the transfer unit by 10 times in the range from 6 · 10–9 kg to 6 · 10–10 kg by the use of a vacuum comparator graduated 0.1 μg and buoyancy and sorption artifacts in direct measurements of air density. This has made it possible to compensate for the additional uncertainty attributed to the IPK based on the determination of the Planck constant value and to ensure the mass calibration of all accuracy grades preserving the entire hierarchical system of transferring the mass unit in the country.

Rosella merupakan salah satu sumber zat antosianin. Antosianin diambil dari kelopak bunga rosella menggunakan metode leaching. Penelitian ini dilakukan untuk menentukan tahap kesetimbangan leaching antosianin dari kelopak bunga Rosella menggunakan continous screw extractor. Tahapan leaching dimulai dengan penyaringan dan pengecilan ukuran kelopak bunga rosella. Selanjutnya, dilakukan variasi rasio pelarut dan padatan (L/S) pada tahap maserasi. Konsentrasi hasil ekstrak (overflow) dan cairan hasil perasan (underflow) digunakan untuk membuat diagram kesetimbangan yang kemudian digunakan untuk perancangan dan penentuan jumlah tahap kesetimbangan. Rasio pelarut dan padatan yang digunakan pada screw extractor yaitu 1,5:1, waktu kontak efektif 411 detik, laju alir pelarut air 1,633 g/detik, dan laju alir padatan 1,089 g/detik. Dengan menggunakan diagram kesetimbangan, didapatkan NTU (Number of Transfer Unit) sebesar 4 tahap, panjang kolom (Z) sebesar 0,42 m, dan nilai HTU (Height of Transfer Unit) sebesar 0,12 m.

Meningkatnya pencemaran lingkungan merupakan akibat penggunaan bahan kimia yang tidak ramah lingkungan. Penggunaan bahan kimia dietilen glikol dan metanol sebagai pendingin (coolant) pada mesin merupakan salah satu aplikasi yaitu blending larutan dietilen glikol dan metanol. Penelitian ini bertujuan mendapatkan data pengaruh suhu, laju alir blending larutan dietilen glikol – metanol dalam heat exchanger type shell and tube 1-1 guna didapatkan nilai terbaik dari NTU dan efektivitas alat. Didalam penelitian ini, digunakan variabel laju alir fluida dingin masuk dengan kisaran 140 – 248 L/jam. Laju alir fluida panas masuk dengan rentang 50 – 75 L/jam. Sedangkan suhu fluida panas masuk berkisar antara 34 – 45oC. Rasio mol blending dietilen glikol – metanol 1 : 1, 1 : 3, dan 3 : 1. Dari hasil penelitian didapatkan pada rasio mol 1 : 1 blending fluida dietilen glikol - metanol dengan suhu fluida dingin 34oC didapat harga terbaik NTU = 3,39 dan efektivitas = 0,94.

An experimental study is conducted to show the influence of the tubes material type of the heat exchanger on the refrigeration system performance. The system is operated by using R134a as a working fluid, 2 mm internal diameter, and different lengths of capillary tubes which were 120, 135, and 150 cm. The experimental results showed that when increasing the refrigerant mass flowrates led to reducing each of the performance coefficient COP, number of transfer unit NTU and evaporator effectiveness ε. However, the highest improvement had appeared for each parameter COP, NTU, and ε which were 21%, 113.38%, and 59.42% respectively at a capillary tube length of 120 cm and [Formula: see text] = 3.19 g/s compared to the length of capillary tube 150 cm. Besides, it was found an increase in [Formula: see text] with the incrementing in the capillary tube length from 120 cm to 150 cm. The biggest percentage of compression power was 23% at the capillary tube length of 150 cm compared to others at [Formula: see text] = 3.71 g/s. Finally, the experimental results of COP and [Formula: see text] were validated by comparing them with other publications.

AbstractSensors can produce large amounts of data related to products, design, and materials; however, it is important to use the right data for the right purposes. Therefore, detailed analysis of data accumulated from different sensors in production and assembly manufacturing lines is necessary to minimize faulty products and understand the production process. Additionally, when selecting analytical methods, manufacturing companies must select the most suitable techniques. This paper presents a data analytics approach to extract useful information, such as important measurements for the dimensions of a shim, a small part for aligning shafts, from the manufacturing data of a power transfer unit (PTU). This paper also identifies the best techniques and analytical approaches within the following six individual areas: (1) identifying measurements associated with faults; (2) identifying measurements associated with shim dimensions; (3) identifying associations between station codes; (4) predicting shim dimensions; (5) identifying duplicate samples in faulty data; and (6) identifying error distributions associated with measurement. These areas are analysed in accordance with two analytical approaches: (a) statistical analysis and (b) machine learning (ML)-based analysis. The results show (a) the relative importance of measurements with regard to the faulty unit and shim dimensions, (b) the error distribution of measurements, and (c) the reproduction rate of faulty units. Additionally, both statistical analysis and ML-based analysis have shown that the measurement ‘PTU housing measurement’ is the most important measurement among available shim dimensions. Additionally, certain faulty stations correlated with one another. ML is shown to be the most suitable technique in three areas (e.g. identifying measurements associated with faults), while statistical analysis is sufficient for the other three areas (e.g. identifying measurements associated with shim dimensions) because they do not require a complex analytical model. This study provides a clearer understanding of assembly line production and identifies highly correlated and significant measurements of a faulty unit.

A performance calculation method based on heat transfer unit (HTU) simulation is proposed to calculate heat transfer capacity and air-side pressure drop of Annular radiator (AR), which can avoid the problem of a huge amount of grids, and at the same time, ensure the calculation accuracy. Calculation results are compared with experimental data, and the average errors of heat transfer capacity and air-side pressure drop are 11.5%, and 5.9%, respectively, which effectively validates the effectiveness and the reliability of this method. Besides, based on HTU simulation knowledge database, a configuration optimization method of AR using Non-dominated Sorted Genetic Algorithm-II (NSGA-II) is introduced. Number of fins in circumferential direction, number of fins in axial direction, and fin height are chosen as design parameters, and two conflicting optimization objectives include heat transfer capacity maximization and air-side pressure drop minimization. Three optimal structures of AR are obtained, and the optimal results indicate that the heat transfer capacity of the optimal configurations increases by 34.31% on average compared with the original one, while the air-side pressure drop decreases by 24.00% on average, which indicates that this method is feasible and valid and can provide significant guidance for structural design of AR.