Integrated utilization of low-grade thermal energy in hot coal mine

This paper explores the integrated utilization of low-grade thermal energy in hot coal mines, based on analysis of original heating, refrigerating, mine draining, bath draining and air exhaust systems, and in combination with the actual conditions of Tangkou Coal Mine in Shandong Province. It presents a set of comprehensive and integrated utilization schemes for the various different kinds of low quality heat energy. With heat pumps, the recycling of the low quality heat energy from the drainage, bathing water and the exhaust air can occur in winter, and in summer, there exists condensed heat of the refrigerating system. When in conjunction with solar collectors, the thermal utilization of solar power can be realized for the whole year. The system achieves mine drainage and bathing water purification and recycling, as well as purifying exhaust air by water spraying. It also satisfies the demands of a whole year＇s bathing heat for the coal mine, with refrigeration in summer, and heating for the ground house and shaft house in winter. It is able to integrate different kinds of low quality heat energy and low emission drainage and dust, and can replace the traditional boiler heating system. Finally, the system reduces conventional energy consumption and the amount of mine water drainage.

A Research on College English Network Teaching Resources Integration and Utilization in Big Data Era

Based on the background of ＂big-data-blowout＂, this thesis is about research on college English network teaching resources integration and utilization confronted with the chance of ＂data value, the data assets and data say＂, analyzing the inevitable challenge of ＂competition, digital divide and data privacy＂, discussing that the researchers should hold big data thinking of ＂peaks of road ＆ dances with wolves ＆ be interdependent＂, emphasizing the improvement from college English teacher＇s modem education technical information literacy[1] and putting forward to resource integration and utilization strategy in the era of big data.

The status quo and prospect of geothermal resources exploration and development in Beijing-Tianjin-Hebei region in China

The Beijing-Tianjin-Hebei region boasts rich geothermal resources and new achievements have been made in the exploration and development of geothermal resources in this region based on previous regional investigation.In detail,geothermal reservoirs of Gaoyuzhuang Formation of Jixian System and Changcheng System in Xiongan New Area have been recently discovered,opening up the second space of geothermal resources;the calculation method of the recoverable resources of geothermal fluid with reinjection being considered has been improved in Beijing-Tianjin-Hebei region,and uniform comprehensive assessment of shallow geothermal energy,hydrothermal geothermal resources,and hot dry rocks(HDR)geothermal resources in the whole Beijing-Tianjin-Shijiazhuang region has been completed.The scientific research base for cascade development and utilization of geothermal resources in Beijing-Tianjin-Hebei region has applied hydraulic fracturing technology to the geothermal reservoirs in Gaoyuzhuang Formation.As a result,the production capacity doubled and two-stage cascade utilization composed of geothermal power generation and geothermal heating were realized,with the first-phase installed capacity of 280 kW and the geothermal heating is 30000 m2.In this way,a model of the exploration,development,and utilization of geothermal resources formed.Large-scale utilization has become the future trend of geothermal resource development in Beijing-Tianjin-Hebei region,and great efforts shall be made to achieve breakthroughs in reinjection technology,geothermal reservoir reconstruction technology,thermoelectric technology and underground heat exchange technology.

Point-of-Interest Recommendation in LocationBased Social Networks with Personalized Geo-Social Influence

Point-of-interest(POI) recommendation is a popular topic on location-based social networks(LBSNs).Geographical proximity,known as a unique feature of LBSNs,significantly affects user check-in behavior.However,most of prior studies characterize the geographical influence based on a universal or personalized distribution of geographic distance,leading to unsatisfactory recommendation results.In this paper,the personalized geographical influence in a two-dimensional geographical space is modeled using the data field method,and we propose a semi-supervised probabilistic model based on a factor graph model to integrate different factors such as the geographical influence.Moreover,a distributed learning algorithm is used to scale up our method to large-scale data sets.Experimental results based on the data sets from Foursquare and Gowalla show that our method outperforms other competing POI recommendation techniques.

Call for Papers Journal of Electronic Science and Technology Special Section on Data Sciences and Data Engineering

Guest Editors Prof.Tao Zhou Univ.of Electronic Science and Technology of China zhutouster@gmail.comProf.Zenglin Xu Univ.of Electronic Science and Technology of China zenglin@gmail.comIn this digital era,enormous amounts of data are ubiquitous and pervasive,which are known as Big Data.

Call for Papers Journal of Electronic Science and Technology Special Section on Data Sciences and Data Engineering

Guest Editors Prof.Tao Zhou Univ.of Electronic Science and Technology of China zhutouster@gmail.comProf.Zenglin Xu Univ.of Electronic Science and Technology of China zenglin@gmail.comIn this digital era,enormous amounts of data are ubiquitous and pervasive,which are known as Big Data.These data are about different domains,from different sources,and in different formats.In order to manipulate,integrate,and utilize the knowledge and value hidden in these data, it has been critical in the areas of Data Sciences and Data Engineering （DSDE） to discuss how to develop theories and techniques for data management, data distribution, data storage, data integration, data analytics, and novel applications of big data.

Thermodynamic and experimental study of high-temperature roasting of blast furnace gas ash for recovery of metallic zinc and iron

A high-temperature reduction roasting method was used to achieve metallic iron and zinc recovery from blast furnace gas ash(BFA).The reduction processes for Zn-containing and Fe-containing oxides were analyzed in detail by using ther-modynamic equilibrium calculation and the principle of minimum free energy.The results showed that the main reaction in the system is the reduction of ZnFe_(2)_(4)and iron oxides.Over the full temperature range,iron oxides were more easily reduced than zinc oxides.Regardless of the amount of CO contained in the system,the reduction of ZnO to Zn was difficult to proceed below the boiling point(906℃)of Zn.When the reduction temperature is below 906℃,the reduction process of zinc ferrate was ZnFe_(2)_(4)→ZnO;when the reduction temperature is above 906℃,its reduction process becomed ZnFe_(2)_(4)→ZnO→Zn(g).The metallization and dezincification rates of the BFA gradually increased with increasing reaction temperature.As the C/O ratio increased,the metallization and dezincification rates first increased and then decreased.The effect of reduction time on BFA reduction was similar to that of reaction temperature.

An Interactive Operating Demand Response Approach for Hybrid Power Systems Integrating Renewable Energy Sources

The increased deployment of renewable energy in existing power networks has jeopardized rotational inertia,resulting in system degradation and insta-bility.To address the issue,this paper proposes a demand response strategy for ensuring the future reliability of the electrical power system.In addition,a modified fuzzy logic control topology-based two-degree-of-freedom(fractional order proportional integral)-tilt derivative controller is designed to regulate the frequency within a demand response framework of a hybrid two-area deregulated power system.The test system includes thermal power plants,renewable energy sources(such as wind,parabolic trough solar thermal plant,biogas),and electric vehicle assets.To adaptively tune the controller’s coefficients,a quasi-opposition-based harris hawks optimization(QOHHO)algorithm is developed.The effectiveness of this algorithm is compared to other optimization algorithms,and the stability of the system is evaluated.The results demonstrate that the designed control algorithm significantly enhances system frequency stability in various scenarios,including uncertainties,physical constraints,and high penetration of renewables,compared to existing work.Additionally,an experimental assessment through OPAL-RT is conducted to verify the practicality of the proposed strategy,considering source and load intermittencies.

Enhancement of the CO_(2)adsorption and hydrogenation to CH_(4)capacity of Ru–Na–Ca/γ–Al_(2)O_(3)dual function material by controlling the Ru calcination atmosphere

Integrated CO_(2)capture and utilization(ICCU)technology requires dual functional materials(DFMs)to carry out the process in a single reaction system.The influence of the calcination atmosphere on efficiency of 4%Ru-8%Na_(2)CO_(3)-8%CaO/γ-Al_(2)O_(3)DFM is studied.The adsorbent precursors are first co-impregnated onto alumina and calcined in air.Then,Ru precursor is impregnated and four aliquotes are subjected to different calcination protocols:static air in muffle or under different mixtures(10%H_(2)/N_(2),50%H_(2)/N_(2)and N_(2))streams.Samples are characterized by XRD,N_(2)adsorption-desorption,H_(2)chemisorption,TEM,XPS,H_(2)-TPD,H_(2)-TPR,CO_(2)-TPD and TPSR.The catalytic behavior is evaluated,in cycles of CO_(2)adsorption and hydrogenation to CH_(4),and temporal evolution of reactants and products concentrations is analyzed.The calcination atmosphere influences the physicochemical properties and,ultimately,activity of DFMs.Characterization data and catalytic performance discover the acccomodation of Ru nanoparticles disposition and basic sites is mostly influencing the catalytic activity.DFM calcined under N_(2)flow(RuNaCa-N_(2))shows the highest CH_(4)production(449μmol/g at 370℃),because a well-controlled decomposition of precursors which favors the better accomodation of adsorbent and Ru phases,maximizing the specific surface area,the Ru-basic sites interface and the participation of different basic sites in the CO_(2)methanation reaction.Thus,the calcination in a N_(2)flow is revealed as the optimal calcination protocol to achieve highly efficient DFM for integrated CO_(2)adsorption and hydrogenation applications.

BioLeT: A new design strategy for functional bioluminogenic probes

By integrating photoinduced electron transfer（PET） into the design of functional bioluminogenic probes,Urano and his coworkers recently developed a new rational design strategy, BioLeT. It is expected that this BioLeT strategy will enable us to design and develop new bioluminescence probes for detecting various biomolecules with no catalytic or reactive activity.