Stream Depletion and Pumping Test Interpretation in a Horizontally Anisotropic Aquifer Near a Stream

Conventional pumping test theories such as Theis solution often assume a horizontally isotropic media. Horizontal anisotropy exists in certain aquifer settings and its impact on pumping tests is not clearly demonstrated before, particularly when the aquifer is bounded by a stream. In this thesis, based on a newly developed mathematical model for pumping tests in a horizontally anisotropic aquifer bounded by a stream, the corresponding interpretation procedures will be illustrated. Stream depletion will be calculated as a result of stream bank pumping based on the new model as well. The results of this research reflect that (1) aquifer parameters derived from newly developed interpretation methods are acceptable in the range of allowable error; so these methods can be used in practical field experiment; (2) with the increase of Ta/Tb, stream depletion rate under the steady state also increases where Ta and Ta are the major and minor principal transmissivity values ( Ta>Tb); (3) when the angle between the X axis and the direction of Ta increases from 0 to pi/2, stream depletion increases, where the X-axis is one of the working coordinate; conversely, when such an angle increases from pi/2 to pi, stream depletion decreases. This research is expected to fill the gap of knowledge on present stream-aquifer interaction and pumping test theories for aquifers

Performance analysis of mix-kernel convolutional neural network

Deep convolutional neural networks (DCNN) have achieved the state-of-the-art performance in a number of computer vision tasks in recent years, including object detection, classification and recognition. The DCNN is very computation-intensive, whose computational complexity can be controlled by a set of network configuration parameters. The relationship between the DCNN computational complexity and its classification accuracy has not been well understood. In this thesis, we aim to conduct a series of training-testing experiments with DCNN on benchmark datasets, such as MNIST and CIFAR-10, to characterize the complexity-accuracy behavior of DCNN. We demonstrate that, with proper configuration of the DCNN, we are able to significantly reduce the computational complexity of DCNN without much degradation on the classification accuracy. This provides important guidelines for practical implementation and use of DCNN

An n/2 Byzantine node tolerate Blockchain Sharding approach

Traditional Blockchain Sharding approaches can only tolerate up to n/3 of nodes being adversary because they rely on the hypergeometric distribution to make a failure (an adversary does not have n/3 of nodes globally but can manipulate the consensus of a Shard) hard to happen. The system must maintain a large Shard size (the number of nodes inside a Shard) to sustain the low failure probability so that only a small number of Shards may exist. In this paper, we present a new approach of Blockchain Sharding that can withstand up to n/2 of nodes being bad. We categorise the nodes into different classes, and every Shard has a fixed number of nodes from different classes. We prove that this design is much more secure than the traditional models (only have one class) and the Shard size can be reduced significantly. In this way, many more Shards can exist, and the transaction throughput can be largely increased. The improved Blockchain Sharding approach is promising to serve as the foundation for decentralised autonomous organisations and decentralised database

MWPoW: Multiple Winners Proof of Work Protocol, a decentralisation strengthened fast-confirm blockchain protocol

Blockchain mining should not be a game among power oligarchs. In this paper, we present the Multiple Winners Proof of Work Protocol (MWPoW), a mining-pool-like decentralised blockchain consensus protocol. MWPoW enables disadvantaged nodes which post only a small amount of calculation resource in the mining game to create blocks together and compete with power oligarchs without centralised representatives. A precise Support Rate of blocks can be determined through the mining process; the mechanism of the mainchain determination is therefore changed and has become faster and more straightforward. A method that periodically adjusts the block size and the block interval is introduced into MWPoW, which increases the system flexibility in the changes of network conditions and data flow. Experiments suggest, without lifting calculation and bandwidth requirements, MWPoW is more attractive to disadvantaged nodes due to its mostly increased reward expectation for disadvantaged nodes. The transaction pending time is shortened chiefly, and either the block interval or the block size can be adapted amid the changes of overall network conditions

Segment blockchain: a size reduced storage mechanism for blockchain

The exponential growth of the blockchain size has become a major contributing factor that hinders the decentralisation of blockchain and its potential implementations in data-heavy applications. In this paper, we propose segment blockchain, an approach that segmentises blockchain and enables nodes to only store a copy of one blockchain segment. We use PoW as a membership threshold to limit the number of nodes taken by an Adversary—the Adversary can only gain at most n/2 of nodes in a network of n nodes when it has 50% of the calculation power in the system (the Nakamoto blockchain security threshold). A segment blockchain system fails when an Adversary stores all copies of a segment, because the Adversary can then leave the system, causing a permanent loss of the segment. We theoretically prove that segment blockchain can sustain a $(AD/n)^m$ failure probability when the Adversary has no more than AD number of nodes and every segment is stored by m number of nodes. The storage requirement is mostly shrunken compared to the traditional design and therefore making the blockchain more suitable for data-heavy applications

MMSE Reconstruction for 3D Freehand Ultrasound Imaging

The reconstruction of 3D ultrasound (US) images from mechanically registered, but otherwise irregularly positioned, B-scan slices is of great interest in image guided therapy procedures. Conventional 3D ultrasound algorithms have low computational complexity, but the reconstructed volume suffers from severe speckle contamination. Furthermore, the current method cannot reconstruct uniform high-resolution data from several low-resolution B-scans. In this paper, the minimum mean-squared error (MMSE) method is applied to 3D ultrasound reconstruction. Data redundancies due to overlapping samples as well as correlation of the target and speckle are naturally accounted for in the MMSE reconstruction algorithm. Thus, the reconstruction process unifies the interpolation and spatial compounding. Simulation results for synthetic US images are presented to demonstrate the excellent reconstruction

Contract-connection:An efficient communication protocol for Distributed Ledger Technology

Distributed Ledger Technology (DLT) is promising to become the foundation of many decentralised systems. However, the unbalanced and unregulated network layout contributes to the inefficiency of DLT especially in the Internet of Things (IoT) environments, where nodes connect to only a limited number of peers. The data communication speed globally is unbalanced and does not live up to the constraints of efficient real-time distributed systems. In this paper, we introduce a new communication protocol, which enables nodes to calculate the tradeoff between connecting/disconnecting a peer in a completely decentralised manner. The network layout globally is continuously re-balancing and optimising along with nodes adjusting their peers. This communication protocol weakened the inequality of the communication network. The experiment suggests this communication protocol is stable and efficient

Anchoring the value of cryptocurrency

A decade long thrive of cryptocurrency has shown its potential as a source of alternative-finance and the security and the robustness of the underpinning blockchain technology. However, most cryptocurrencies fail to show inimitability and their meanings in the real world. As a result, they usually start off as favourites but quickly become the outcasts of the digital asset market. The blockchain society attempts to anchor the value of cryptocurrency with real values by employing smart contracts and link it with computation resources and the digital-productivity that have value and demands in the real world. But their attempts have some undesirable effects due to a limited number of practical applications. This limitation is caused by the dilemma between high performance and decentralisation (universal joinability). The emerging of blockchain sharding models, however, has offered a possible solution to address this dilemma. In this paper, we explore a financial model for blockchain sharding that will build an active link between the value of cryptocurrency and computation resources as well as the market and labour behaviours. Our model can adjust the price of resources and the compensation for maintaining a system based on those behaviours. We anchor the value of cryptocurrency by the amount of computation resources participated in and give the cryptocurrency a meaning as the exchange between computation resources globally. Finally, we present a working example which, through financial regularities, regulates the behaviour of anonymous participants, also incents/discourages participation dynamically