A Voltage Control Method for a Distributed Line Feeder by means of Multiagent Approach

This paper proposes a method for the coordinated control of power factor by means of a multiagent approach. The proposed multiagent system consists of two types of agent: single feeder agent (F_AG) and bus agent (B_AG). In the proposed system, an F_AG plays as an important role, which decides the power factors of all distributed generators by executing the load flow calculations repeatedly. The voltage control strategies are implemented as the class definition of Java into the system. In order to verify the performance of the proposed method, it has been applied to a typical distribution model system. The simulation results show that the system is able to control very violent fluctuation of the demands and the photovoltaic (PV) generations.     

Looking ahead: Joint small group detection and tracking in crowd scenes

Small group detection and tracking in crowd scenes are basis for high level crowd analysis tasks. However, it suffers from the ambiguities in generating proper groups and in handling dynamic changes of group configurations. In this paper, we propose a novel delay decision-making based method for addressing the above problems, motivated by the idea that these ambiguities can be solved using rich temporal context. Specifically, given individual detections, small group hypotheses are generated. Then candidate group hypotheses across consecutive frames and their potential associations are built in a tree. By seeking for the best non-conflicting subset from the hypothesis tree, small groups are determined and simultaneously their trajectories are got. So this framework is called joint detection and tracking. This joint framework reduces the ambiguities in small group decision and tracking by looking ahead for several frames. However, it results in the unmanageable solution space because the number of track hypotheses grows exponentially over time. To solve this problem, effective pruning strategies are developed, which can keep the solution space manageable and also improve the credibility of small groups. Experiments on public datasets demonstrate the effectiveness of our method. The method achieves the state-of-the-art performance even in noisy crowd scenes.     

Distributed ledger technology in supply chains: a transaction cost perspective

With the emergence of distributed ledger technology (DLT), numerous practitioners and researchers have proclaimed its beneficial impact on supply chain transactions in the future. However, the vast majority of DLT initiatives are discontinued after a short period. With the full potential of DLT laying far down the road, especially managers in supply chain management (SCM) seek for short-term cost-saving effects of DLT in order to achieve long-term benefits of DLT in the future. However, the extant research has bypassed grounding long-term as well as short-term effects of DLT on supply chain transaction with empirical data. We address this shortcoming, following an abductive research approach and combining empirical data from a multiple case study design with the corresponding literature. Our study reveals that the effects of DLT on supply chain transactions are two-sided. We found six effects of DLT solutions that have a cost-reducing or cost avoidance impact on supply chain transactions. In addition, we found two effects that change the power distribution between buyers and suppliers in transactions and a single effect that reduces the dependency of supply chain transactions on third parties. While cost-reducing and avoidance as well as dependency-reducing effects are positive effects, the change in power distribution might come with disadvantages. With these findings, the paper provides the first empirical evidence of the impact of DLT on supply chain transactions, which will enable managers to improve their assessment of DLT usage in supply chains.     

Utilizing sensor data to model students’ creativity in a digital environment

While creativity is essential for developing students’ broad expertise in Science, Technology, Engineering, and Math (STEM) fields, many students struggle with various aspects of being creative. Digital technologies have the unique opportunity to support the creative process by (1) recognizing elements of students’ creativity, such as when creativity is lacking (modeling step), and (2) providing tailored scaffolding based on that information (intervention step). However, to date little work exists on either of these aspects. Here, we focus on the modeling step. Specifically, we explore the utility of various sensing devices, including an eye tracker, a skin conductance bracelet, and an EEG sensor, for modeling creativity during an educational activity, namely geometry proof generation. We found reliable differences in sensor features characterizing low vs. high creativity students. We then applied machine learning to build classifiers that achieved good accuracy in distinguishing these two student groups, providing evidence that sensor features are valuable for modeling creativity.     

Control theory for stochastic distributed parameter systems,an engineering perspective

The main purpose of this paper is to survey some recent progresses on control theory for stochastic distributed parameter systems, i.e., systems governed by stochastic differential equations in infinite dimensions, typically by stochastic partial differential equations. We will explain the new phenomenon and difficulties in the study of controllability and optimal control problems for one dimensional stochastic parabolic equations and stochastic hyperbolic equations. In particular, we shall see that both the formulation of corresponding stochastic control problems and the tools to solve them may differ considerably from their deterministic/finite-dimensional counterparts. More importantly, one has to develop new tools, say, the stochastic transposition method introduced in our previous works, to solve some problems in this field.     

A novel quasi-oppositional harmony search algorithm and fuzzy logic controller for frequency stabilization of an isolated hybrid power system

The intermittent wind power in isolated hybrid distributed generation (IHDG) may cause serious problems associated with frequency (f) and power (P) fluctuation. Energy storage devices such as battery, super capacitor, and superconducting magnetic energy storage (SMES) may be used to reduce these fluctuations associated with f and P. This paper presents a study of IHDG power system for improving both f and P deviation profiles with the help of SMES. The studied IHDG power system is consisted of wind turbine generator and diesel engine generator. Both f and P control problems of the studied power system model are addressed in presence or absence of SMES. Fuzzy logic based proportional–integral–derivative (PID) controller with SMES is used for the purpose of minimization of f and P deviations. The different tunable parameters of the PID controller and those of the SMES are tuned by a novel quasi-oppositional harmony search algorithm. Performance study of the IHDG power system model is carried out under different perturbation conditions. The results demonstrate minimum f and P deviations may be achieved by using the proposed fuzzy logic based PID controller along with SMES.     

Studying local liquid velocity in liquid–solid packed bed using the newly developed X-ray DIR technique

Combination of X-ray Digital Industrial Radiography (DIR) and Particle Tracking Velocimetry (PTV) techniques for local liquid velocity measurement (V_LL) has been newly developed and successfully applied for trickle bed reactor (TBR). The technique was validated against newly developed fiber optical probe technique. This work attempts to highlight the applicability of this newly developed technique on a liquid–solid packed bed reactor. In this work, liquid was represented by water and solids were represented by EPS beads. The EPS beads were chosen because of its low density property. Three superficial liquid velocities (V_SL) were applied to the system. The experiment was replicated four times. The digital industrial radiography (DIR) consists of a complementary metal oxide semiconductor (CMOS) digital detector and X-ray source. Results of this work suggest that the technique has been successfully applied and comparable with previous work that has been done in the literature. It also suggests that there will be a maximum measurable interstitial liquid velocity when it travel inside the packed bed. The measured V_LL can have a maximum range that is between 4 and 4.7 times that of its V_SL. For V_SL=0.42±±2%, the V_LL-Max is in between 1.7 cm/s and 1.9 cm/s, V_SL=0.84±±2%, the V_LL-Max is in between 3.6 cm/s and 4.0 cm/s, and for V_SL=1.11±±2%, the V_LL-Max is in between 4.3 cm/s and 4.8 cm/s.     

小型机载激光通信系统设计与验证

针对空空宽带高速通信的需求，设计了小型化机载激光通信系统。仿真分析了300 km、2.5 Gb/s无线激光链路性能，并通过运动仿真台模拟机动环境测试了系统的跟踪与通信性能，其中粗跟踪误差为533.2 μrad(1σ)，精跟踪误差为3.6 μrad(1σ)，测试数据传输240 s，通信误码率为2.82×10-9。仿真与实验验证了该系统用于远距离空空无线激光通信的可行性。     

基于分段加权的反向稀疏跟踪算法研究

为提高稀疏表示跟踪模型性能，提出一种分段加权的反向稀疏跟踪算法，将跟踪问题转化为在贝叶斯框架下寻找概率最高的候选对象问题，构造不同的分段权重函数来分别度量候选目标与正负模板的判别特征系数。通过池化来降低跟踪结果的不确定性干扰，选择正负模板加权系数差值最大的候选表示作为跟踪结果。实验表明，在光照变化、遮挡、快速运动、运动模糊情况下，所提出的算法可以确保跟踪结果的准确性和鲁棒性。     

基于查询的新闻多文档自动摘要技术研究

针对新闻文本领域,该文提出一种基于查询的自动文本摘要技术,更加有针对性地满足用户信息需求。根据句子的TF-IDF、与查询句的相似度等要素,计算句子权重,并根据句子指示的时间给定不同的时序权重系数,使得最近发生的新闻内容具有更高的权重,最后使用最大边界相关的方法选择摘要句。通过与基于TF-IDF、Text-Rank、LDA等六种方法的对比,该摘要方法ROUGE评测指标上优于其他方法。从结合评测结果及摘要示例可以看出,该文提出的方法可以有效地从新闻文档集中摘取核心信息,满足用户查询内容的信息需求。