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Selecting the right features for further data analysis is important in the process of equipment anomaly detection, especially when the origin data source involves high dimensional data with a low value density. However, existing researches failed to capture the fact that the sensor data are usually correlated (e.g., duplicated deployed sensors), and the correlations would be broken when anomalies occur with happen to the monitored equipment. In this paper, we propose to capture such sensor data correlation changes to improve the performance of IoT (Internet of Things) equipment anomaly detection. In our feature selection method, we first cluster correlated sensors together to recognize the duplicated deployed sensors according to sensor data correlations, and we monitor the data correlation changes in real time to select the sensors with correlation changes as the representative features for anomaly detection. To that end, (1) we conducted curve alignment for the sensor clustering; (2) we discuss the appropriate window size for data correlation calculation; (3) and adopted MCFS (Multi-Cluster Feature Selection) into our method to adapt to the online feature selection scenario. According to the experiment evaluation derived from real IoT equipment, we prove that our method manages to reduce the false negative of IoT equipment anomaly detection of 30% with almost the same level of false positive. [ABSTRACT FROM AUTHOR]

Blends of poly(butylene adipate-co-terephthalate) (PBAT) and polylactide (PLA) have attracted the attention of academia and industry as a sustainable material. Unfortunately, this combination results in problems related to poor miscibility on the molecular level. This study mainly aims to determine the influence of molecular weights on the miscibility of PBAT/PLA blends. First, polymers with various molecular weights were obtained by the hydrolysis of PBAT and methanolysis of PLA. Second, the two components were solution-blended with different molecular weights and weight ratios. Third, each blend was heated to the molten state and subsequently stored at room temperature. Finally, the samples were tested using DSC and SEM. The thermal analysis indicated that the difference in glass transition temperature between both components decreased from about 91 °C to 57 °C and 0 °C, as the number-average molecular weights (Mn) decreased from 52/127 to 9.4/9 and 6.3/6.6 kg/mol. Moreover, the morphology changed from phase-separated with dispersed large particles gradually to uniform and homogeneous. This experimental work validated the trends predicted in the previous study, namely that PBAT/PLA blends changed the state from immiscible to partially miscible to fully miscible with decreasing Mn values. Moreover, we discussed the influencing factors such as weight ratio, temperature, and molecular structure on the miscibility. Based on the results, this work contributes to developing partially miscible and compatible blends without additives. [ABSTRACT FROM AUTHOR]

Designing polymer structures and polymer blends opens opportunities to improve the performance of plastics. Blending poly(butylene adipate-co-terephthalate) (PBAT) and polylactide (PLA) is a cost-effective approach to achieve a new sustainable material with complementary properties. This study aimed to predict the theoretical miscibility of PBAT/PLA blends at the molecular level. First, the basic properties and the structure of PBAT and PLA are introduced, respectively. Second, using the group contribution methods of van Krevelen and Hoy, the Hansen and Hildebrand solubility parameters of PBAT and PLA were calculated, and the effect of the molar ratio of the monomers in PBAT on the miscibility with PLA was predicted. Third, the dependence of the molecular weight on the blend miscibility was simulated using the solubility parameters and Flory–Huggins theory. Next, the glass transition temperature of miscible PBAT/PLA blends, estimated using the Fox equation, is shown graphically. According to the prediction and simulation, the blends with a number-average molecular weight of 30 kg/mol for each component were thermodynamically miscible at 296 K and 463 K with the possibility of spinodal decomposition at 296 K and 30% volume fraction of PBAT. This study contributes to the strategic synthesis of PBAT and the development of miscible PBAT/PLA blends. [ABSTRACT FROM AUTHOR]

Polymer blends of poly(butylene adipate-co-terephthalate) (PBAT) and polylactide (PLA) have been drawn attention due to the application potential as packaging or agricultural films. This study aims to determine the manufacturability, miscibility and mechanical properties of uncompatibilized PBAT/PLA blends prepared using different techniques. First, PBAT and PLA are melt-blended in a wide range of ratios from 90/10 to 10/90. The compounds are then processed into pressed panels, flat films and blown films. Finally, the thermal, morphological, rheological and mechanical properties of these blends are investigated. PBAT/PLA blends have a small difference of solubility parameters, predicting theoretically good miscibility. However, they show two almost unchanged glass transition temperatures in the DSC, phase separation in SEM and two relaxation mechanisms in the Cole–Cole plot. The phase morphology varies depending on both the blend ratios and the preparation techniques. Tensile tests indicate that with increasing PLA content the elongation at break decreases. A good correlation between the elongation at break and the tear propagation resistance is found. Furthermore, the trouser tear method is proven to be more applicable to differentiate highly extensible blown films compared with the Elmendorf tear method. [ABSTRACT FROM AUTHOR]

The domain name system (DNS) is an important infrastructure of the Internet, providing domain name resolution services for almost all Internet communication systems. However, the current DNS is centrally managed, leading to unfair sovereignty of the Internet among countries. A domestic DNS is unable to work normally, noted as isolated management risk (IMR), especially when the national network is isolated from the rest of the Internet. To improve understanding of the DNS isolated management risk for better DNS resource deployment, it is critical to determine how serious the IMR is among various countries. In order to quantify DNS isolated management risk, this paper proposed an effective approach to collect DNS resolution demand data from the network used by various intelligent devices and to conduct data analysis to estimate isolated management risk of certain country's domestic DNSs. Our idea is to quantify the domain name resolution demand and its relationship with the overseas resolution processes. We further used our quantitative method to compare the IMR of the USA and China and analyzed the difference between them. [ABSTRACT FROM AUTHOR]

The incredible development of Internet of things technology promotes the integration of application systems, which enable people to enjoy the convenience of multiple application services through a single intelligent device or terminal. In order to implement value exchange and information sharing between different applications, cross-domain access is inevitable. In order to prevent illegal access, identity authentication is necessary before the terminal accesses the service. Because of the need to introduce a trusted third party, the traditional centralized authentication model not only destroys the autonomy and flexibility of the application system, but also causes issues such as single point of failure and hidden dangers of unilateral control. This paper proposes an identity-based cross-domain authentication scheme for the Internet of Things. This scheme uses the Blockchain as a decentralized trust anchor instead of the traditional certificate of authority, and uses the identity-based self-authentication algorithm to replace the traditional PKI authentication algorithm. The scheme proposed in this paper implements a decentralized authentication model, which can guarantee the autonomy and initiative of the security domain. [ABSTRACT FROM AUTHOR]

Polylactide (PLA), poly(butylene succinate) (PBS) and blends thereof have been researched in the last two decades due to their commercial availability and the upcoming requirements for using bio-based chemical building blocks. Blends consisting of PLA and PBS offer specific material properties. However, their thermodynamically favored biphasic composition often restricts their applications. Many approaches have been taken to achieve better compatibility for tailored and improved material properties. This review focuses on the modification of PLA/PBS blends in the timeframe from 2007 to early 2019. Firstly, neat polymers of PLA and PBS are introduced in respect of their origin, their chemical structure, thermal and mechanical properties. Secondly, recent studies for improving blend properties are reviewed mainly under the focus of the toughness modification using methods including simple blending, plasticization, reactive compatibilization, and copolymerization. Thirdly, we follow up by reviewing the effect of PBS addition, stereocomplexation, nucleation, and processing parameters on the crystallization of PLA. Next, the biodegradation and disintegration of PLA/PBS blends are summarized regarding the European and International Standards, influencing factors, and degradation mechanisms. Furthermore, the recycling and application potential of the blends are outlined. [ABSTRACT FROM AUTHOR]

In recent years, location privacy concerns that arise when using the nearest neighbor query services have gained increasing attention, as such services have become pervasive in mobile social networks devices and the IoT environments. State-of-the-art privacy preservation schemes focus on the obfuscation of the location information, which has suffered from various privacy attacks and the tradeoff of the quality of service. By noticing the fact that the user’s location could be replaced by their surrounding wireless sensor infrastructures in proximity, in this paper, we propose a wireless sensor access point-based scheme for the nearest neighbor query, without using the location of the user. Then, a noise-addition-based method that preserves user’s location privacy was proposed. To further strengthen the adaptability of the approach to real-world environments, several performance-enhancing methods are introduced, including an R-tree-based Noise-Data Retrieval Algorithm (RNR), and a nearest neighbor query method based on our research. Both performance and security evaluations are conducted to validate our approach. The results show the effectiveness and the practicality of our work. [ABSTRACT FROM AUTHOR]