Eco-driving: the role of feedback in reducing emissions from everyday driving behaviours

Eco-driving has been proposed as an approach to significantly reduce greenhouse gas emissions arising from personal automobile use. Eco-driving is the adoption of a measured driving style, minimising unnecessary breaking and aggressive acceleration. Eco-driving can be seen as a low cost and immediate approach to emission reduction as it involves the modification of drivers’ behaviours as opposed to the development and implementation of newer, more efficient technology. Despite the proposed benefits of eco-driving, numerous challenges are faced in order to encourage the adoption of these behaviours and maintain them long term. This narrative review presents the concept of eco-driving, with a focus on the long-term maintenance of these behaviours, including training programmes and feedback devices. It is clear within current literature that, despite the economic and environmental benefits of adopting eco-driving, drivers require feedback on their actions in order to promote long-term, behavioural, change.     

A Frame Breaking Based Hybrid Algorithm for UHF RFID Anti-Collision

Multi-tag collision imposes a vital detrimental effect on reading performance of an RFID system. In order to ameliorate such collision problem and to improve the reading performance, this paper proposes an efficient tag identification algorithm termed as the Enhanced Adaptive Tree Slotted Aloha (EATSA). The key novelty of EATSA is to identify the tags using grouping strategy. Specifically, the whole tag set is divided into groups by a frame of size F. In cases multiple tags fall into a group, the tags of the group are recognized by the improved binary splitting (IBS) method whereas the rest tags are waiting in the pipeline. In addition, an early observation mechanism is introduced to update the frame size to an optimum value fitting the number of tags. Theoretical analysis and simulation results show that the system throughput of our proposed algorithm can reach as much as 0.46, outperforming the prior Aloha-based protocols.     

Location Privacy in Device-Dependent Location-Based Services: Challenges and Solution

With the evolution of location-based services (LBS), a new type of LBS has already gain a lot of attention and implementation, we name this kind of LBS as the Device-Dependent LBS (DLBS). In DLBS, the service provider (SP) will not only send the information according to the user’s location, more significant, he also provides a service device which will be carried by the user. DLBS has been successfully practised in some of the large cities around the world, for example, the shared bicycle in Beijing and London. In this paper, we, for the first time, blow the whistle of the new location privacy challenges caused by DLBS, since the service device is enabled to perform the localization without the permission of the user. To conquer these threats, we design a service architecture along with a credit system between DLBS provider and the user. The credit system tie together the DLBS device usability with the curious behaviour upon user’s location privacy, DLBS provider has to sacrifice their revenue in order to gain extra location information of their device. We make the simulation of our proposed scheme and the result convince its effectiveness.     

Tibetan Multi-Dialect Speech and Dialect Identity Recognition

Tibetan language has very limited resource for conventional automatic speech recognition so far. It lacks of enough data, sub-word unit, lexicons and word inventories for some dialects. And speech content recognition and dialect classification have been treated as two independent tasks and modeled respectively in most prior works. But the two tasks are highly correlated. In this paper, we present a multi-task WaveNet model to perform simultaneous Tibetan multi-dialect speech recognition and dialect identification. It avoids processing the pronunciation dictionary and word segmentation for new dialects, while, in the meantime, allows training speech recognition and dialect identification in a single model. The experimental results show our method can simultaneously recognize speech content for different Tibetan dialects and identify the dialect with high accuracy using a unified model. The dialect information used in output for training can improve multi-dialect speech recognition accuracy, and the low-resource dialects got higher speech content recognition rate and dialect classification accuracy by multi-dialect and multi-task recognition model than task-specific models.     

Effect of preparation method on physicochemical properties and catalytic performances of LaCoO_3 perovskite for CO oxidation

Perovskite oxides LaCoO_3 prepared by templating, co-precipitation and sol-gel method with different complexants were systematically characterized and its catalytic performances for CO oxidation were investigated. The samples were characterized by X-ray diffraction, thermogravimetry analysis and differential scanning calorimetry, N_2 physisorption, transmission electron microscopy, temperature program reduction of hydrogen, temperature program desorption of oxygen and X-ray photoelectron spectroscopy measurement, results of which show that the properties of LaCoO_3, such as surface morphology, surface area, surface compositions, redox capability, oxygen vacancy, as well as the calcination temperature and formation mechanism, depend intimately on the preparation method. Catalytic tests indicate that the sample prepared by carbon templating method shows the best activity for CO oxidation, with full CO conversion obtained at 135 ℃. In particular, the catalyst can be activated and significant increase of activity can be obtained with the increase of reaction time. The cyclic and longterm stability of catalysts were discussed and compared.     

A double‐mode cell to measure pitting and crevice corrosion

Pitting corrosion and crevice corrosion of passivated steels were measured by using a double‐mode syringe electrolyte cell built on an environment chamber. The setup, when set in noncontact mode, could measure pitting potentials and critical temperatures, and crevice corrosion potentials if in contact mode. It could be employed to distinguish the pitting and crevice corrosion damage of reinforcing steel in concrete.