An Ethereum-based solution for energy trading in smart grids

The need for a flexible, dynamic, and decentralized energy market has rapidly grown in recent years. As a matter of fact, Industry 4.0 and Smart Grids are pursuing a path of automation of operations to insure all the steps among consumers and producers are getting closer. This leads towards solutions that exploit the paradigm of public blockchain, which represents the best platform to design flat and liquid markets for which providing trust and accountability to mutual interactions becomes crucial. On the other hand, one of the risks arising in this situation is that personal information is exposed to the network, with intolerable threats to privacy. In this paper, we propose a solution for energy trading, based on the blockchain Ethereum and Smart Contracts.The solution aims to be a concrete proposal to satisfy the needs of energy trading in smart grids, including the important feature that no information about the identity of the peers of the network is disclosed in advance.     

Tracing manufacturing processes using blockchain-based token compositions

Supply chain traceability is one of the most promising use cases to benefit from characteristics of blockchain, such as decentralization, immutability and transparency, not required to build prior trust relationships among entities. A plethora of supply chain traceability solutions based on blockchain has been proposed recently. However, current systems are limited to tracing simple goods that have not been part of the manufacturing process. We recommend a method that allows for the traceability of manufactured goods, including their components. Products are represented using non-fungible digital tokens that are created on a blockchain for each batch of manufactured products. To create a link between a product and the components that are needed to produce it, we propose “token recipes” that define the amount of tokenized goods required for minting a new token. As input tokens are automatically and transparently consumed when creating a product token, the physical process of producing a new item out of existing components is projected onto the ledger. This ultimately leads to the complete traceability of goods, including the origin of inputs. Evaluating the performance of the system, we show that a prototypical implementation for the Ethereum Virtual Machine (EVM) scales linearly with the amount of the input and goods tracked.     

Smart contract applications within blockchain technology: A systematic mapping study

With the advent of blockchain, smart contracts have become one of the most sought-after technologies because of the high customisability they add to transactions. This has given rise to many smart contract applications in areas ranging from financial services, life sciences and healthcare to energy resources and voting. However, due to their infancy, smart contracts still pose many challenges that encumber the stakeholders who interact with them: users, developers and the organisations that are built on top of smart contracts. This study aims to contribute to the body of knowledge of smart contracts within blockchain technology. Based on a systematic mapping study, we offer a broad perspective on their problems and corresponding solutions, present the research trends within the area and compile the 64 papers identified, grouped by top publication sources, channels, methods and approaches. We conclude that, since 2016, there has been an increasing trend towards the publication of blockchain-based smart contract articles at conferences and journals, mainly reflecting experiments and presenting methods, tools and models. According to the results, the most commonly discussed problems and solutions in the literature are related to the security, privacy and scalability of blockchain and the programmability of smart contracts.     

Research on optimal intelligent routing algorithm for IoV with machine learning and smart contract

The huge increase in the communication network rate has made the application fields and scenarios for vehicular ad hoc networks more abundant and diversified and proposed more requirements for the efficiency and quality of data transmission. To improve the limited communication distance and poor communication quality of the Internet of Vehicles (IoV), an optimal intelligent routing algorithm is proposed in this paper. Combined multi-weight decision algorithm with the greedy perimeter stateless routing protocol, designed and evaluated standardized function for link stability. Linear additive weighting is used to optimize link stability and distance to improve the packet delivery rate of the IoV. The blockchain system is used as the storage structure for relay data, and the smart contract incentive algorithm based on machine learning is used to encourage relay vehicles to provide more communication bandwidth for data packet transmission. The proposed scheme is simulated and analyzed under different scenarios and different parameters. The experimental results demonstrate that the proposed scheme can effectively reduce the packet loss rate and improve system performance.     

A secure spectrum auction scheme without the trusted party based on the smart contract

With the development of communication 5G networks and technologies, spectrum resources are increasingly scarce. The scarcity of the spectrum resource makes market-driven spectrum auction become an important means of spectrum allocation, and due to the complexity of the network environment, the security of spectrum auctions can not be ignored. Most existing secure spectrum auction schemes introduce a semi-honest agent to complete spectrum auction. However, the hypothetical semi-honest model does not guarantee the security of spectrum auction in the actual application scenario, which may lead to potential security threats: the agent may reveal the privacy of bidders, agent or auctioneer may collude with the bidder to manipulate the spectrum auction, and so on. In this paper, a secure spectrum auction scheme without a trusted party is proposed based on the smart contract technology, and the smart contract written into the blockchain replaces the traditional semi-honest agent to cooperate with the auctioneer server to complete the auction. In order to ensure the security of our scheme, a secure spectrum auction protocol is designed, in which the Software Guard Extensions (SGX) technology and Paillier cryptosystem are used to protect the privacy of bidders. Public verification is provided in our protocol by using extensive Pedersen commitment, which prevents the auctioneer server and the bidder from colluding with each other and verifies group bid sum values. Finally, the security analysis is given to propose several types of attacks that can be defended. Besides, theoretical analysis and simulation experiments of our protocol are also provided.     

Historicizing the smart cities: Genealogy as a method of critique for smart urbanism

This study explores the utility of genealogy as a method of critiquing the history of the present in the smart cities. Taking a South Korean smart city of Songdo as a point of departure, this paper offers a genealogical understanding of a smart city that situates the current technics and technologies of data-driven urban governance within the broader context of South Korean history. Given the scarcity of a historically informed understanding of a smart city in the existing literatures on smart urbanism, this paper argues that a genealogical method helps us to counter the sweeping binarism that obscures the complexity and diversity of actually existing smart cities today. Through genealogy, this study underscores the multifaceted nature of the smart city, which consists of a combination of multiple urban diagrams that grows out of distinct problems and objectives of urban management – mobility, security, environment, and futurity. This paper illustrates how a smart city emerged out of multiple strings of history and problematizations that are contingently interweaved at a given time and space in multiple and diffused forms.     

Clamp-and-Forget: A self-sustainable non-invasive wireless sensor node for smart metering applications

Measuring and managing the power consumption of household appliances, as well as that of industrial machineries, is becoming more and more important to improve the distribution and usage of the electrical energy and to reduce the energy bill. We present the design of a non-invasive wireless current meter which can measure AC current up to $60A_{\mathit{RMS}}$ exploiting a small clamp-on inductive sensor. The novelty of the design is a subsystem consisting of a harvesting circuit designed to extract energy from the same current transducer used for measurements. Experiments have been conducted to validate the approach, to assess the accuracy of the sensing system and deviations due to the energy harvester, and to determine the condition which permits us to achieve the energy neutrality and thus, a self-sustainable smart meter.     

Potential pitfalls of smart city development: A study on parking mobile applications (apps) in Hong Kong

Smart cities are built upon information and communication technologies (ICTs) to enable a broad range of advanced services. Through a comprehensive literature review, this study identified four pitfalls brought by the pervasive application of ICT, including information insecurity, privacy leakage, information islands, and digital divide. Therefore, a questionnaire survey together with 27 interviews was conducted in Hong Kong to investigate how the public perceived these pitfalls within the context of mobile apps providing real-time parking information which form a major part of smart mobility. System insecurity and privacy leakage were found to arouse worries among the app-users while their awareness of protecting personal data was found to have room for improvement. Islands of real-time parking information occur as a result of the lack of collaboration among private carpark operators. Digital divide existed widely among the disadvantaged groups and the problem cannot be solved by mere provision of ICT facilities. Overall, technologies alone cannot make a city smart or smarter. It is the suitable way in which ICTs are used to serve all citizens that matters.     

From smart cities to smart social urbanism: A framework for shaping the socio-technological ecosystems in cities

Advocated mostly by technology companies, the smart city concept promises participation, democratization and innovative urbanism. Tracking these promises and ideas, this paper explores “smart urbanism” in ten cities from all over Israel. Based on interviews with leading figures in municipalities, smart city consultants and key figures in technological companies (n = 40), the aims of this paper are to assess the efforts of cities to become smart by responding to the following questions: 1. What is guiding the decision-making process in developing technological initiatives? 2. Does context play a role in implementing technological initiatives? 3. How are the residents perceived, and what tools are being used to address residents' digital differences? The key argument of this paper is threefold: first, in the process of becoming a smart city, the roles of public and private actors are blurred, influencing the process of decision making. Second, despite contextual differences, cities adopt similar digital initiatives. Third, technological initiatives that focus on social needs and address inequality in the digital age are still at the margins. The final discussion suggests that most municipalities are still at an early stage of digitization implementation and have the ability to shape and form a vision for the cities as socio-technological ecosystems in a way that will serve their publics as a whole. The paper ends with a call for shifting the focus from the city to society in developing digital initiatives and cultivating smart social urbanism.     

The underlying factors of the perceived usefulness of using smart wearable devices for disaster applications

Smart wearable devices offer much potential to assist citizens in disasters. To the general public, however, using these devices for disaster applications is still a novel concept. In disasters, most people are reluctant to rely on unfamiliar technologies. Thus, for these devices to become truly useful in disasters, it is important to understand factors that affect their acceptance by the public. Previous studies show that perceived usefulness is a clear antecedent of people’s acceptance of smart wearable devices. However, the underlying factors that affect perceived usefulness itself are not clearly known. Thus, the aim of this study is to fill this gap, and by doing so, to derive some practical implications for solution developers and governments.This study used structural equation modelling to analyse survey data collected from 647 respondents in Japan. We found that the respondents’ perceived usefulness of the current applications of smart wearable devices was a strong predictor of their perceived usefulness of using these devices for disaster applications. Although indirect factors such as the ownership of ICT gadgets and the usage of social media also had some influences, most of their effects were mediated through increasing the respondents’ perceived usefulness of the current applications. In other words, through appreciating the functions of the current applications of smart wearable devices, people can visualise the usefulness of these devices in disaster situations. That being said, we found that in parallel, people also had concerns on the privacy issues of these devices. These findings shed light on the promotion and development of this fast growing technology for disaster applications.     

面向非平衡数据分类的概率过抽样过滤方法

利用非合作博弈理论为概率过抽样合成的少数类数据决定其最可能的类标签,将数据中的非本类合成数据进行过滤,减少概率过抽样合成数据过程中产生的重叠数据,得到更高质量的少数类数据进而改善数据倾斜状况。实验分别以CART和SVM分类器建立模型,将本文提出的面向非平衡数据分类的概率过抽样过滤方法RACOG+F与原始概率过抽样方法分别在8个KEEL非平衡数据集上进行对比。实验表明,本文提出的方法在评价指标F-measure、G-mean和AUC上获得了较好的分类性能。     

Semantic dictionary based method for short text classification

The traditional short-text classification's accuracy usually highly relies on statistical feature selection. Owing to the fact that short-text has inherent defects such as short length, weak signal and less features. It is hard to avoid noise words when doing feature extension which will highly influence the accuracy of classification. In order to solve the above problem, this paper proposes a semantic dictionary method for short-text classification. The method builds a set of domain dictionary by analyzing the specific characteristics in certain field. As each word's weight in the dictionary is designed according to the correlation between the word and the category, classification accuracy has improved to some extent. Then, in order to enhance dictionary vocabulary coverage, association rules are utilized to automatically extend semantic dictionary. Finally, an experiment based on micro-blog data is conducted which shows that the method has a good effect.     

基于轮廓线曲率特征的人脸分类及识别

文中提出一种人脸分类及识别方法。在对人脸图像进行预处理之后,提取出人脸的轮廓,再细化,去除边缘噪声,得到人脸的轮廓线。对此轮廓线逐点计算曲率得到曲率线。将不同的曲率线之间的互相关函数定义为曲率线之间的相似性,并由此对人脸进行分类和识别。由于曲率几何特征明显,具有位移和旋转不变性,所提出的方法有较好的鲁棒性,并且得到了良好的分类效果。     

Cross-layer progressive attention bilinear fusion method for fine-grained visual classification

Fine-grained visual classification (FGVC) is a critical task in the field of computer vision. However, FGVC is full of challenges due to the large intra-class variation and small inter-class variation of the classes to be classified on an image. The key in dealing with the problem is to capture subtle visual differences from the image and effectively represent the discriminative features. Existing methods are often limited by insufficient localization accuracy and insufficient feature representation capabilities. In this paper, we propose a cross-layer progressive attention bilinear fusion (CPABF in short) method, which can efficiently express the characteristics of discriminative regions. The CPABF method involves three components: 1) Cross-Layer Attention (CLA) locates and reinforces the discriminative region with low computational costs; 2) The Cross-Layer Bilinear Fusion Module (CBFM) effectively integrates the semantic information from the low-level to the high-level 3) Progressive Training optimizes the parameters in the network to the best state in a delicate way. The CPABF shows excellent performance on the four FGVC datasets and outperforms some state-of-the-art methods.     

一种用于雷达信号调制分类的特征评估方法

针对用于调制分类过程中雷达信号脉内特征参数评估问题,提出了一种多指标联合评估方法.该方法使用复杂性、可分离性和稳定性3个指标对特征参数的调制分类性能进行联合评估,克服了传统评估手段仅使用单一指标难以进行全面科学评估的缺陷,并可以根据应用需求获取相应的最合理的综合评分值.理论分析和计算机仿真结果表明,该方法可以有效评估特征的调制分类性能,具有较强的工程应用价值.     

一种快速低秩的判别子字典学习算法及图像分类

本文提出了一种快速低秩的判别子字典学习算法。在训练阶段,构造一个子字典的低秩约束项和拉普拉斯矩阵正则化项,加入判别字典学习的目标函数中。将原始样本映射到一个新的空间中,使同一类别的相邻点彼此靠近,同时增强子字典对同类样本的重构能力,针对每类样本的判别性特征,学习出相应的学习字典。在测试阶段,利用k NN分类器估计测试样本的类别标签。同时,将算法应用在3种数据集上,与其他的字典学习算法进行比较,取得了较好的分类结果。     

一种适应于非完备标签数据和标签关联性的多标签分类方法

多标签分类已在很多领域得到了实际应用,所用标签大多具有很强的关联性,甚至存在非完备标签或部分标签遗失。然而,现有的多标签分类算法难以同时处理这两种情况。基于此,提出一种新的概率模型处理方法,实现同时对具有标签关联性和遗失标签情况进行多标签分类。该方法可以自动获知和掌握多标签的关联性。此外,通过整合遗失的标签信息,该方法能够提供一个自适应策略来处理遗失的标签。在完备标签和非完备标签的数据上进行实验,结果表明,与现有的多标签分类算法相比,提出的方法得到了较好的分类预测评价值。     

基于属性权值多级分类的测试样本数据预处理方法

针对算法测试在工业生产实际操作应用中,经常面临样本数据迅速大量增加,测试执行时间过长、测试效率低下、算法改进周期过长的问题.文章提出一种精简测试样本的算法,快速实时处理新增样本,去除冗余数据.首先对新增的样本数据按照分类阈值分配到各子数据集中,然后在每一个子数据集中根据数据的重要程度属性计算相似度值,为减少计算量,先对子数据集进行排序处理,最后根据相似性的阈值判断去除冗余数据.实验利用所得样本库不断对算法进行回归测试,分析表明算法的测试效率及测试充分性都有明显提升,并提高了算法在工业生产实际应用过程中的稳定性和适应性,有力的保证了算法的质量.     

基于级联模型的输变电设备状态图像分类方法

对采集到的输变电设备状态图像进行智能化分析是一种实时有效的设备状态监测方式。传统机器学习算法在处理电力设备图像分类问题时,由于不考虑代价敏感和类别不平衡问题,效率较低。文中针对输变电设备状态图像的特点,提出一种基于级联模型的图像分类方法,并通过实验验证该方法的优越性。     

显控台的内涵和分类方法及型谱研究

探讨了显控台的内涵,提出了显控台的分类方法,阐述了显控台型谱.采用广义和狭义的概念明晰了显控台的基本内涵;采用特征分类法从多个角度对显控台进行了分类和类型识别;通过分析和介绍几种显控台型谱,表明在不同行业和领域中显控台的型谱不一定相同