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An imaging system based on the transmission and reflection modes in the terahertz (THz) region is developed by using a backward-wave oscillator (BWO) as source, a Golay-Cell as detector, and an oscilloscope as data acquisition unit.
The system software based on the oscilloscope is designed to control the object movement, and the capture and display of the continuous THz wave image data.
The data form the Local Area Network (LAN) of oscilloscope (Agilent DSO5052A) are acquired and stored by computer.
The automatic control process and data recorded by the oscilloscope are controlled by software designed for the imaging system.
The software is mainly composed of three modules, including the platform operation control module, the serial data processing module based on the Electronic Industry Association-Recommended standard-232 (RS-232), and the LAN interface data acquisition module.

The experiments were repeated at least three times in the same conditions in order to achieve a statistical distribution of the acquired data: such data are then used as a reference for the 2009 edition of the extrusion benchmark.
The third step is the comparison of the results: during the conference the hidden results of the experiment are disclosed and the different FEM codes predictions are compared to the experimental data, thus providing an interesting evaluation of codes capabilities.
In this direction, for example, the software houses can promote their codes capabilities on the basis of scientific and well monitored experimental data, the industrial users can verify their ability to properly perform a simulation with their own code or even select a code among those participating the contest.
Fig. 2: Thermocouple position The billets were heated up to 450 °C in a furnace, with the billet surface decreasing to 432 °C just before extrusion: the billet temperature reduction was caused by the billet loading procedure that took about 1 minute.
It is worth noting that the curve of the velocitymeter of the bottom profile showed a lower scatter distribution of the data compared to the other curve, this being in relation with the velocitymeter models: the velocitymeter used on the top profile is older than that used on the bottom, thus producing a worse filtering of acquired data.

The average data of each test is used to produce the load-displacement graphs of the specimens, from which stress-strain curves are extracted to show the behaviour of epoxy polymer.
The average data was used to draw the load-displacement diagrams and subsequently the stress-strain curves were extracted to show the total behaviour of epoxy polymer.
The mixing ratio of resin and hardener are selected according to the data sheet from the supplier.
The stress reduction at fracture (Fig. 4) can be explained from observation of the cracks.

R2 denotes the fitting degree of the fitting formula with the FEM data.
There are 110 data sets with K>1, and the maximum result is K=1.027.
There are 140 sets of data with K<1, and the minimum result is K=0.966.
The fluctuation amplitude of the first 150 groups of data is larger, while the fluctuation amplitude of the last 100 groups of data is tiny.
Therefore, the fitting formula calculates ideal data, and both are less than 0, indicating that the corresponding pressure ratio data is more aggressive.

More complete data on modal characteristics were obtained in [5–6] by methods of experimental modal analysis.
The experimental data on the decrease in natural frequencies of the samples are consistent with those presented in [5, 6].
Figure 4 shows a reduction of the Young module E11 during its fatigue test.
The data obtained for the set of samples, various fatigue test loads and various total lifetime are included.
Fatigue damage evaluation of notched specimens through resonance and anti-resonance data.

During combustion, competitive reaction of chlorination/sulphatation and oxidation/reduction will lead to a partitioning of elements between flue-gas and ash phases.
This approach is closely linked with the evolution of non destructive methods to provide accurate data on corrosion distribution along the tubes.
Some studies refer to electrochemical monitoring using corrosion probes [27, 28] but lifetime of the probe, localisation of the probes and interpretation of electrochemical data seem to remain limiting factors in MSWI environnement, - identification of the performances of materials in MSWI conditions is required to be able to make the choice of materials in regards with operation conditions.
Such upgrading should be an important way to reduce CO emission (reduction condition), high velocity laminar flow, metal and gas temperatures spikes and finally decrease corrosion and erosion of superheaters, - geometry and the assembly of the different heat exchangers (screen tubes/superheaters) are also important ways of progress that may give interesting answers.
Acknowledgement Authors wish to acknowledge operators of Veolia Envionmental Services E-f-W facilities for their collaboration to collect suitable data and the useful discussion on maintenance operation.

However, limited data are available on its behavior in hot forming processes.
Given the lack of data on AA2198’s high-temperature formability, this research explores its potential for hot stamping into complex shapes.
To ensure data reliability, three tests in each condition have been done.
As shown, a 10-minute holding time in the SHT treatment and AA at 160 °C appears insufficient to fully dissolve the precipitates, leading to a significant reduction in mechanical properties.
The material supplier had previously estimated a mechanical property reduction of approximately 40 MPa, which aligns with the results obtained.

The “consistency and comparability” of “county-level data” over-time significantly “increased the difficulty” of “data acquisition”, resulting in a “limited” number of “indicators”.
In the future, the types of data can be “further expanded”, and the “interplay” between the improvement of “rural production”, “living, and ecological” environments prerequisites to be “considered to address” potential biases in the “assessment process” and expand the “evaluation system” of “rural human” reimbursement “environment sustainability indicators” [18].
As per the literature, the studies that have been done so far have been on Sustainable poverty reduction models for social economy and environment, “Urban sustainability” valuation for “traditional built environments”, Valuations of “microbial and heavy metal” contaminations in the “water supply systems” for Environment and Sustainable Development, sustainable urban tourism environment optimization and heating systems in the built environment.
Implementing waste reduction strategies, such as promoting reusable products and packaging, can also help to “reduce” the quantity of “waste generated” in the “first place”.
Sustainable poverty reduction models for the coordinated development of the social economy and environment in China.

Communication connecting layer mainly executes the interface data interaction with external systems.The interface systems include customer service system, interactive platform, monitoring system on smart house, electric data collection system, electric vehicle charging system, distribution automatic system.
Upgoing data is firstly uploaded from device layer to communication connecting layer.Various communication machine in communication connecting layer gather and transfer the receiving data.Then communication connecting layer transmits the data that have been transformed into standard model to host information layer.Host information layer builds a unified information model to achieve data’s consistency interpretation and storage.Downward data with unified data format is sent from host information layer to communication connecting layer.Communication connecting layer interprets by data format and then send commands to device layer.When the machines receive the commands,they executes the commands immediately.
Fig.2 Physical structure diagram The database server is mainly used to store related electric key data of intelligent community.The app database needs to calculate all kinds of data,do statistics and command control.Interface server has the duty to exchange interface data with external systems and send commands.Web server displays the electric data of intelligent community in server pages.Workstatison A is set for managing and maintaining,and workstation B is set for monitoring.
(3) data service layer.Data service layer mainly handles various data that function rendering layer needs to display.By collecting data from external systems,it executes calculation.statistics and alarm processing.It builds accurate authority and system management based on the analysis on the functions of power management platform.
(4) function rendering layer.Function rendering layer uses the data provided by data service layer to achieve all kinds of functions of ICPMP.This layer is a window that faces the managers and the users.It provides the functions including electric data monitoring, electric data management, release of electric data, DSM management, electric vehicle monitoring, smart house monitoring,interactive service, distribution monitoring.In this layer,the manager monitors the power running status of intelligent community and the users get their power comsuption messages,manage the electric vehicle charging and control start/stop of the electrical machines.

While [10] uses a scenario-based SDG interaction framework to demonstrate how clean energy transitions support non-energy development goals like health, poverty reduction, and education, [11] provides a data-driven classification of 49 SSA countries, showing wide disparities in energy access, particularly in clean cooking fuels, urban-rural electrification, and renewable uptake.
Future iterations should include real-world grid data, socio-demographic EV diffusion rates, and storage economics to validate feasibility in deployment zones. 6.
These developments, although not V2G-specific, demonstrate the city’s growing capacity for data-driven energy systems and real-time control architectures that V2G platforms require.
Investments in grid digitization, smart meters, data platforms, interoperable protocols, are foundational.
Furthermore, integrating V2G data into national planning enables more accurate load forecasting and infrastructure investment strategies.