Probability Distributions.- Linear Models for Regression.- Linear Models for Classification.- Neural Networks.- Kernel Methods.- Sparse Kernel Machines.- Graphical Models.- Mixture Models and EM.- Approximate Inference.- Sampling Methods.- Continuous Latent Variables.- Sequential Data.- Combining Models.

Pattern Recognition and Machine Learning

『Google Scholar』の利点

The Internet of Things (IoT) envisages a future in which digital and physical things or objects (e.g., smartphones, TVs, cars) can be connected by means of suitable information and communication technologies, to enable a range of applications and services. The IoT’s characteristics, including an ultra-large-scale network of things, device and network level heterogeneity, and large numbers of events generated spontaneously by these things, will make development of the diverse applications and services a very challenging task. In general, middleware can ease a development process by integrating heterogeneous computing and communications devices, and supporting interoperability within the diverse applications and services. Recently, there have been a number of proposals for IoT middleware. These proposals mostly addressed wireless sensor networks (WSNs), a key component of IoT, but do not consider RF identification (RFID), machine-to-machine (M2M) communications, and supervisory control and data acquisition (SCADA), other three core elements in the IoT vision. In this paper, we outline a set of requirements for IoT middleware, and present a comprehensive review of the existing middleware solutions against those requirements. In addition, open research issues, challenges, and future research directions are highlighted.

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Middleware for Internet of Things: A Survey

In the last decade blockchain technology become mainstream research topic because of its decentralized, peer to peer transaction, distributed consensus, and anonymity properties. The blockchain technology overshadows regulatory problem and technical challenges. A smart contract is a set of programs which are self-verifying, self-executing and tamper resistant. Smart contract with the integration of blockchain technology capable of doing a task in real time with low cost and provide a greater degree of security. This paper firstly, explains the various components and working principle of smart contract. Secondly, identify and analyse the various use cases of smart contract along with the advantage of using smart contract in blockchain application. Lastly, the paper concludes with challenges lie in implementing smart contract the future real-life scenario.

An Overview of Smart Contract and Use Cases in Blockchain Technology

Smart contract, a term which was originally coined to refer to the automation of legal contracts in general, has recently seen much interest due to the advent of blockchain technology. Recently, the term is popularly used to refer to low-level code scripts running on a blockchain platform. Our study focuses exclusively on this subset of smart contracts. Such smart contracts have increasingly been gaining ground, finding numerous important applications (e.g., crowdfunding) in the real world. Despite the increasing popularity, smart contract development still remains somewhat a mystery to many developers largely due to its special design and applications. Are there any differences between smart contract development and traditional software development? What kind of challenges are faced by developers during smart contract development? Questions like these are important but have not been explored by researchers yet. In this paper, we performed an exploratory study to understand the current state and potential challenges developers are facing in developing smart contracts on blockchains, with a focus on Ethereum (the most popular public blockchain platform for smart contracts). Toward this end, we conducted this study in two phases. In the first phase, we conducted semi-structured interviews with 20 developers from GitHub and industry professionals who are working on smart contracts. In the second phase, we performed a survey on 232 practitioners to validate the findings from the interviews. Our interview and survey results revealed several major challenges developers are facing during smart contract development: (1) there is no effective way to guarantee the security of smart contract code; (2) existing tools for development are still very basic; (3) the programming languages and the virtual machines still have a number of limitations; (4) performance problems are hard to handle under resource constrained running environment; and (5) online resources (including advanced/updated documents and community support) are still limited. Our study suggests several directions that researchers and practitioners can work on to help improve developers’ experience on developing high-quality smart contracts.

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Smart Contract Development: Challenges and Opportunities

Falling is among the most damaging event elderly people may experience. With the ever-growing aging population, there is an urgent need for the development of fall detection systems. Thanks to the rapid development of sensor networks and the Internet of Things (IoT), human-computer interaction using sensor fusion has been regarded as an effective method to address the problem of fall detection. In this paper, we provide a literature survey of work conducted on elderly fall detection using sensor networks and IoT. Although there are various existing studies which focus on the fall detection with individual sensors, such as wearable ones and depth cameras, the performance of these systems are still not satisfying as they suffer mostly from high false alarms. Literature shows that fusing the signals of different sensors could result in higher accuracy and lower false alarms, while improving the robustness of such systems. We approach this survey from different perspectives, including data collection, data transmission, sensor fusion, data analysis, security, and privacy. We also review the benchmark data sets available that have been used to quantify the performance of the proposed methods. The survey is meant to provide researchers in the field of elderly fall detection using sensor networks with a summary of progress achieved up to date and to identify areas where further effort would be beneficial.

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Elderly Fall Detection Systems: A Literature Survey

The recent technological advent of cryptocurrencies and their respective benefits have been shrouded with a number of illegal activities operating over the network such as money laundering, bribery, phishing, fraud, among others. In this work we focus on the Ethereum network, which has seen over 400 million transactions since its inception. Using 2179 accounts flagged by the Ethereum community for their illegal activity coupled with 2502 normal accounts, we seek to detect illicit accounts based on their transaction history using the XGBoost classifier. Using 10 fold cross-validation, XGBoost achieved an average accuracy of 0.963 ( ± 0.006) with an average AUC of 0.994 ( ± 0.0007). The top three features with the largest impact on the final model output were established to be ‘Time diff between first and last (Mins)’, ‘Total Ether balance’ and ‘Min value received’. Based on the results we conclude that the proposed approach is highly effective in detecting illicit accounts over the Ethereum network. Our contribution is multi-faceted; firstly, we propose an effective method to detect illicit accounts over the Ethereum network; secondly, we provide insights about the most important features; and thirdly, we publish the compiled data set as a benchmark for future related works.

Detection of illicit accounts over the Ethereum blockchain

The notion of smart contracts in distributed ledger systems have been hailed as a safe way of enforcing contracts between participating parties. However, unlike legal contracts, which talk about ideal behaviour and consequences of not adhering to such behaviour, smart contracts are by their very nature executable code, giving explicit instructions on how to achieve compliance. Executable specification languages, particularly Turing complete ones, are notoriously known for the difficulty of ensuring correctness, and recent incidents which led to huge financial losses due to bugs in smart contracts, have highlighted this issue. In this paper we show how standard techniques from runtime verification can be used in the domain of smart contracts, including a novel stake-based instrumentation technique which ensures that the violating party provides insurance for correct behaviour. The techniques we describe have been partially implemented in a proof-of-concept tool ContractLarva, which we discuss in this paper.

Runtime Verification of Ethereum Smart Contracts

Decentralized Finance (DeFi) takes the promise of blockchain a step further and aims to transform traditional financial products into trustless and transparent protocols that run without involving intermediaries. Similar to how 2017 was the year of ICOs, 2020 was the year of DeFi, with more than fifteen billion dollars of total investments. The decentralized platforms utilize oracles to retrieve asset data from the external world, but their choice and management criteria are often unknown to the end-users. If oracles are poorly selected or managed, the funds of a rising number of investors are inevitably in danger. The issue, known as “the oracle problem”, which makes real-world applications controversial and debated due to the loss of decentralization, had recently drawn attention to DeFi, given the crescent number of related hacks that caused the loss of millions of dollars held in DeFi projects. Through a multivocal approach that considers academic papers, whitepapers, preprints, and opinion posts, this study aims to shed light on the pattern that identifies the oracle problem in DeFi and outline the most promising ways to overcome the related weaknesses. This research supports the view that the oracle problem in decentralized finance bears specific characteristics which require standardization and appropriate economic incentives to be addressed.

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The Blockchain Oracle Problem in Decentralized Finance—A Multivocal Approach

Much of the excitement around blockchain is mainly due to promising applications in the financial sector. However, many also believe in the technology’s potential to disrupt non-financial sectors and applications, including supply chains, energy, e-voting, healthcare, and education. The application of blockchain within the education sector is expected to make improvements to academic transcripts, credentials, digital libraries, and student records. Research in this domain is rapidly increasing, and current reviews summarize the proposed improvements. On the other hand, the analysis undertaken has remained at a general level that lacks the depth required to cover diverging proposals that have emerged. This review focuses on the application of blockchain for academic transcripts. The aim is to find, among the proposed models, converging aspects that resolve common challenges and may lead to a universally accepted de-facto standard. Furthermore, since academic institutions will serve as oracles to the particular blockchain applications, a discussion on their trustworthiness will be outlined to explore if the proposed applications efficiently address the oracle problem. The outcome of this review highlights the need for a standardized approach built on a public blockchain to promote faster adoption and acceptance. Furthermore, oracles should be incentivized in order for the system to be sustainable, while their identities and activities should be known and identifiable.

Joshua Ellul

Papers

Elderly Fall Detection Systems: A Literature Survey

Detection of illicit accounts over the Ethereum blockchain

Runtime Verification of Ethereum Smart Contracts

The Blockchain Oracle Problem in Decentralized Finance—A Multivocal Approach

Trusted Academic Transcripts on the Blockchain: A Systematic Literature Review