Tesseract: Real-Time Cryptocurrency Exchange using Trusted Hardware

We propose Tesseract, a secure real-time cryptocurrency exchange service. Existing centralized exchange designs are vulnerable to theft of funds, while decentralized exchanges cannot offer real-time cross-chain trades. All currently deployed exchanges are also vulnerable to frontrunning attacks. Tesseract overcomes these flaws and achieves a best-of-both-worlds design by using Intel SGX as a trusted execution environment. Furthermore, by running a consensus protocol among SGX-enabled servers, Tesseract mitigates denial-of-service attacks. Tesseract supports not only real-time cross-chain cryptocurrency trades, but also secure tokenization of assets pegged to cryptocurrencies. For instance, Tesseract-tokenized bitcoins can circulate on the Ethereum blockchain for use in smart contracts. We provide a reference implementation of Tesseract that supports Bitcoin, Ethereum, and similar cryptocurrencies

Wireless communication system for unmanned vehicle

With the maturing of applicable technologies, Unmanned Aerial Vehicle (UAV) has been given a higher priority in recent society because of its great scientific significance and widespread application value especially in the information field. A means of communication for UAV available at present is to use Ultra-wide band impulse radio (UWB-IR) technology. This project involves hardware and software development of a wireless communication system for communication between an UAV and a control site in an indoor environment. The real-time data collected from sensors on UAV was sent to a microcontroller and repackaged before transmitted through UWB front-end. Another microcontroller collected data from the UWB receiver and decoded them on the receiving end. Finally, the acquired data was uploaded to a PC and visualized using Code Composer Studio (CCS) graph tool to demonstrate the performance.Bachelor of Engineerin

A three-stage optimization method for logistics management

Logistics management is a complex engineering optimization problem involving multi-objective formulations. The management competences such as vehicle routes planning, delivery and pick-up jobs scheduling, and distribution centers location design are crucial skills for each logistics company. With the rapid development of economy, there is a significant demand from logistics industry to solve the above mentioned problems in a more intelligent way. In this project, a three-echelon model is proposed to address several traditional distinct logistics optimization problems in an integrated manner. In the first phase, a large number of delivery tasks are grouped into several segments for vehicles assignment using a set of clustering rules. After segmentation, each subgroup could be simplified as an independent travelling salesman problem (TSP). In the second phase, the customized genetic algorithm is employed to solve the TSP. Computational experiments conducted in Matlab show that this algorithm can obtain a generally satisfying solution for the TSP. Finally, a set of distribution centers are selected from the demand sites using immune-genetic algorithm to further enhance the distribution efficiency in the last phase. This multi-stage method improves the solution’s performance, and can be extended to deal with large-scale problems.Master of Science (Communications Engineering

Consequences of firm-specific stock price crashes on analyst forecasts: Evidence from China

Abstract The phenomenon of stock price crash events (SPCs) has always attracted market attention, but existing research mainly focuses on its causes or determinants and rarely examines the consequences of SPCs. This study aims to fill this gap by examining the consequences of firm-specific stock price crash events (SPCs) on analyst forecast accuracy. Using the sample of analysts and listed companies from 2001 to 2020 and employing a difference-in-differences design, we find that after the company’s stock price crashed, the analyst forecast error decreased and the accuracy increased. For analysts who have not conducted site visits before SPC, and have no geographical advantages, this effect is more obvious, thus validating our hypothesis following analyst attention theory. Additional analysis shows that SPCs stimulate forecast accuracy more significantly for lowly-reputed analysts than for highly-reputed analysts. Channel analysis documents that, for the aforementioned group of analysts, the enhancement effect of SPCs on analyst forecasts is mediated by analyst effort increasing. This study adds to the evidence that SPCs bring positive externalities from the analyst perspective, that is, SPCs attract the attention of some analysts and improve their forecast accuracy. This study also enhances our understanding of analyst behavior under uncertainty, finally enriching the literature on the determinants of analyst forecast accuracy

Research on Risk Evaluation of Transnational Power Networking Projects Based on the Matter-Element Extension Theory and Granular Computing

In project management, risk assessment is crucial for stakeholders to identify the risk factors during the whole life cycle of the project. A risk evaluation index system of a transnational networking project, which provides an effective way for the grid integration of clean electricity and the sustainable development of the power industry, is constructed in this paper. Meanwhile, a combination of granular computing and order relation analysis (G1 method) is applied to determine the weight of each indicator and the matter-element extension evaluation model is also employed to seek the global optimal decision during the risk assessment. Finally, a case study is given to validate the index system and evaluation model established in this paper by assessing two different investment schemes of a transnational high voltage direct current (HVDC) transmission project. The result shows that the comprehensive risk level of Scheme 1 is “Low” and the level of Scheme 2 is “General”, which means Scheme 1 is better for the stakeholders from the angle of risk control. The main practical significance of this paper lies in that it can provide a reference and decision support for the government’s power sectors, investment companies and other stakeholders when carrying out related activities

Estimation of Spatial-Temporal Distribution of Grazing Intensity Based on Sheep Trajectory Data

In the arid grasslands of northern China, unreasonable grazing methods can reduce the water content and species numbers of grassland vegetation. This project uses solar-powered GPS collars to obtain track data for sheep grazing. In order to eliminate the trajectory data of the rest area and the drinking area, the kernel density analysis method was used to cluster the trajectory point data. At the same time, the vegetation index of the experimental area, including elevation, slope and aspect data, was obtained through satellite remote sensing images. Therefore, using trajectory data and remote sensing image data to establish a neural network model of grazing intensity of sheep, the accuracy of the model could be high. The results showed that the best input parameters of the model were the combination of vegetation index, sheep weight, duration, moving distance and ambient temperature, where the coefficient of determination R2=0.97, and the mean square error MSE = 0.73. The error of grazing intensity obtained by the model is the smallest, and the spatial-temporal distribution of grazing intensity can reflect the actual situation of grazing intensity in different locations. Monitoring the grazing behavior of sheep in real time and obtaining the spatial-temporal distribution of their grazing intensity can provide a basis for scientific grazing

Review of history and research on airport collaborative decision making

The airport collaborative decision making can effectively improve the operational efficiency of airports， so as to improve the operational efficiency of the whole civil aviation transportation network. The relevant standards，policy files and research papers of collaborative decision making are compiled in this paper. The development history of in airports and the current situation of research and application on collaborative decision making in academia and industry，both in China and abroad are collated. The future development trend of collaborative decision making in airports and the challenges faced by collaborative decision making in the current period are discussed and analyzed. Some suggestions for the development of collaborative decision making in airports based on the actual situation in China are given. The theoretical support and basis for improving the operational efficiency and economic benefits of airports and the whole air transportation network are summarized. The study in this paper can provide theoretical support and basis for operational efficiency and economic efficiency of the whole air traffic network

Dissecting the novel abilities of aripiprazole: The generation of anti-colorectal cancer effects by targeting Gαq via HTR2B

Colorectal cancer (CRC) is a type of malignant tumor that seriously threatens human health and life, and its treatment has always been a difficulty and hotspot in research. Herein, this study for the first time reports that antipsychotic aripiprazole (Ari) against the proliferation of CRC cells both in vitro and in vivo, but with less damage in normal colon cells. Mechanistically, the results showed that 5-hydroxytryptamine 2B receptor (HTR2B) and its coupling protein G protein subunit alpha q (Gαq) were highly distributed in CRC cells. Ari had a strong affinity with HTR2B and inhibited HTR2B downstream signaling. Blockade of HTR2B signaling suppressed the growth of CRC cells, but HTR2B was not found to have independent anticancer activity. Interestingly, the binding of Gαq to HTR2B was decreased after Ari treatment. Knockdown of Gαq not only restricted CRC cell growth, but also directly affected the anti-CRC efficacy of Ari. Moreover, an interaction between Ari and Gαq was found in that the mutation at amino acid 190 of Gαq reduced the efficacy of Ari. Thus, these results confirm that Gαq coupled to HTR2B was a potential target of Ari in mediating CRC proliferation. Collectively, this study provides a novel effective strategy for CRC therapy and favorable evidence for promoting Ari as an anticancer agent