Removal of chloride ions from acidic solution with antimony oxides

Xuewen Wang,Yanping Du,Haoxiang Yang,Shenghui Tian,Qi Ge,Sheng Huang,Mingyu Wang 한국공업화학회 2021 Journal of Industrial and Engineering Chemistry Vol.93 No.-

This studyaims to investigate the removal of Cl- from acidic solutionwith antimony oxides. The effects of theadsorbenttype,reaction time,reaction temperature,Sb/Clmole ratio andacidityonadsorptionperformanceand the regeneration of loaded adsorbent were systematically studied. The results shows that Sb2O3 xH2Ohas the highest adsorption rate (97.64%) among Sb2O3 xH2O, Sb2O5 xH2O, Sb2O4 xH2O and Sb2O3 in thesolution containing 1.25 mol/L H2SO4under the condition of Sb/Cl mole ratio 3:1 and stirring for 2 h at roomtemperature, and the concentration of Cl- in the acid solution can be reduced to 280 mg/L. Then the residualSb in the adsorbed solution can be decreased from 48.21 mg/L to 16.09 mg/L by C-SbA which is made bySb2O5 xH2O. The C-SbA which has been used can be reused after calcining at 400 ℃ for 2 h. The loadedadsorbent was completely regenerated by adding it into NaOH or Na2CO3 solution whose pH is equal ormore than 9.5 according to S/L ratio 1:6 g/mL and was stirred for 0.5 h at room temperature. The Cl- in theregenerated solution was crystallized and precipitated in the form of NaCl without evaporation andconcentration according to the common ion effect of Na+, and the purity of NaCl was more than 99%.

Experimental Research on Hole Wall Integrity of TiBw/TC4 Based on Ultrasonic Vibration Assisted Drilling

Yong Feng,Haoxiang Wang,Min Zhang,Zihao Zhu,Xiaoyu Wang,Binhui Jia,Xiaolin Jia 한국정밀공학회 2020 International Journal of Precision Engineering and Vol.21 No.5

Titanium Matrix Composites (TMCs) are widely used in aerospace because of their excellent mechanical properties, but itis accompanied by the diffi culty of machining. Ultrasonic Vibration Assisted Drilling (UVAD) can eff ectively reduce theaxial force in the drilling process and improve the integrity of machined surface. In this paper, the discontinuous titaniummatrix composite TiBw/TC4 was developed by preparation method of in situ. In order to obtain the machining parameters ofTiBw/TC4 and guide the application of UVAD in TiBw/TC4, the contrast experiments between conventional drilling (CD)and UVAD were carried out to analyze the variation law of axial force. In this experiment, the frequency and amplitude ofultrasonic vibration were set as 35 kHz and 2.5 μm respectively, and the drilling conditions were that the spindle speed was(1500/1600/1700/1800/1900) r/min and the feed speed was (6/7/8/9/10) mm/min. The surface integrity of hole wall suchas roughness, residual stress and white layer was discussed. The experimental results show that the yield strength of TiBw/TC4 developed by in situ is 51% higher than that of pure TC4. Compared with CD, the axial force of TiBw/TC4 in UVADis signifi cantly reduced, and the formation of continuous chips and winding cutters is eff ectively reduced. Besides, the wearrate of the cutters is reduced. The number and size of hole wall defects, such as scratches, delamination and tearing, areobviously reduced. As well as the residual stress, white layer thickness and hole wall roughness are reduced by 4.67–16.31%,42.48% and 5.98–29.27% respectively. Within the limits of the experiment, when the spindle speed is 1700 r/min and thefeed speed is 8 mm/min, UVAD can obtain better hole wall surface integrity parameters.

Intelligent Power Equipment Management Based on Distributed Context-Aware Inference in Smart Cities

Choi, Chang,Esposito, Christian,Wang, Haoxiang,Liu, Zhe,Choi, Junho IEEE 2018 IEEE communications magazine Vol.56 No.7

<P>Smart cities are systematically promoting the transition to sustainable and effective energy systems by promoting policies for energy efficiency, regionalized/distributed renewable energy generation, and intelligent energy management. In particular, this transition toward a more integrated and intelligent energy supply has created a plethora of energy meta-information made available through the IoT smart grid, thereby allowing big data analytical services to forecast energy consumption and to manage usage patterns. In this article, we propose a context-aware framework for intelligent power equipment management. Our contribution is to present a design of the proposed framework based on context awareness, the definition of a context ontology for power equipment management, a specification of the inference rules for the context ontology, and a context-aware inference service for power equipment management. The proposed system has broad applications to handle system monitoring and express system controls, so as to be easily and effectively applied to various application domains.</P>

An Efficient of Coal and Gangue Recognition Algorithm

Kuidong Gao,Changlong Du,Haoxiang Wang,Shibo Zhang 보안공학연구지원센터(IJSIP) 2013 International Journal of Signal Processing, Image Vol.6 No.4

A novel CNN based security guaranteed image watermarking generation scenario for smart city applications

Li, Daming,Deng, Lianbing,Bhooshan Gupta, Brij,Wang, Haoxiang,Choi, Chang Elsevier science 2019 Information sciences Vol.479 No.-

<P><B>Abstract</B></P> <P>The rise of machine learning increases the current computing capabilities and paves the way to novel disruptive applications. In the current era of big data, the application of image retrieval technology for large-scale data is a popular research area. To ensure the robustness and security of digital image watermarking, we propose a novel algorithm using synergetic neural networks. The algorithm first processes a meaningful gray watermark image, then embeds it as a watermark signal into the block Discrete Cosine Transform (DCT) component. The companion algorithm for detection and extraction of the watermark uses a cooperative neural network, where the suspected watermark signal is used as the input while the output consists in the result of the recognition process. The simulation experiments show that the algorithm can complete certain image processing operations with improved performance, not only simultaneously completing watermark detection and extraction, but also efficiently determining the watermark attribution. Compared with other state-of-the-art models, the proposed model obtains an optimal Peak Signal-to-noise ratio (PSNR).</P>

Secure Surveillance Framework for IoT Systems Using Probabilistic Image Encryption

Muhammad, Khan,Hamza, Rafik,Ahmad, Jamil,Lloret, Jaime,Wang, Haoxiang,Baik, Sung Wook IEEE 2018 IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS - Vol.14 No.8

<P>This paper proposes a secure surveillance framework for Internet of things (IoT) systems by intelligent integration of video summarization and image encryption. First, an efficient video summarization method is used to extract the informative frames using the processing capabilities of visual sensors. When an event is detected from keyframes, an alert is sent to the concerned authority autonomously. As the final decision about an event mainly depends on the extracted keyframes, their modification during transmission by attackers can result in severe losses. To tackle this issue, we propose a fast probabilistic and lightweight algorithm for the encryption of keyframes prior to transmission, considering the memory and processing requirements of constrained devices that increase its suitability for IoT systems. Our experimental results verify the effectiveness of the proposed method in terms of robustness, execution time, and security compared to other image encryption algorithms. Furthermore, our framework can reduce the bandwidth, storage, transmission cost, and the time required for analysts to browse large volumes of surveillance data and make decisions about abnormal events, such as suspicious activity detection and fire detection in surveillance applications.</P>

Grey wolf optimization based clustering algorithm for vehicular ad-hoc networks

Fahad, Muhammad,Aadil, Farhan,Rehman, Zahoor-ur-,Khan, Salabat,Shah, Peer Azmat,Muhammad, Khan,Lloret, Jaime,Wang, Haoxiang,Lee, Jong Weon,Mehmood, Irfan Elsevier 2018 Computers & electrical engineering Vol.70 No.-

<P>In vehicular ad-hoc network (VANETs), frequent topology changes occur due to fast moving nature of mobile nodes. This random topology creates instability that leads to scalability issues. To overcome this problem, clustering can be performed. Existing approaches for clustering in VANETs generate large number of cluster-heads which utilize the scarce wireless resources resulting in degraded performance. In this article, grey wolf optimization based clustering algorithm for VANETs is proposed, that replicates the social behaviour and hunting mechanism of grey wolfs for creating efficient clusters. The linearly decreasing factor of grey wolf nature enforces to converge earlier, which provides the optimized number of clusters. The proposed method is compared with well-known meta-heuristics from literature and results show that it provides optimal outcomes that lead to a robust routing protocol for clustering of VANETs, which is appropriate for highways and can accomplish quality communication, confirming reliable delivery of information to each vehicle. (C) 2018 Elsevier Ltd. All rights reserved.</P>