ED-SWE: Event detection based on scoring and word embedding in online social networks for the internet of people

Online social media networks are gaining attention worldwide, with an increasing number of people relying on them to connect, communicate and share their daily pertinent event-related information. Event detection is now increasingly leveraging online social networks for highlighting events happening around the world via the Internet of People. In this paper, a novel Event Detection model based on Scoring and Word Embedding (ED-SWE) is proposed for discovering key events from a large volume of data streams of tweets and for generating an event summary using keywords and top-k tweets. The proposed ED-SWE model can distill high-quality tweets, reduce the negative impact of the advent of spam, and identify latent events in the data streams automatically. Moreover, a word embedding algorithm is used to learn a real-valued vector representation for a predefined fixed-sized vocabulary from a corpus of Twitter data. In order to further improve the performance of the Expectation-Maximization (EM) iteration algorithm, a novel initialization method based on the authority values of the tweets is also proposed in this paper to detect live events efficiently and precisely. Finally, a novel automatic identification method based on the cosine measure is used to automatically evaluate whether a given topic can form a live event. Experiments conducted on a real-world dataset demonstrate that the ED-SWE model exhibits better efficiency and accuracy than several state-of-art event detection models.     

Hybridizing adaptive large neighborhood search with kernel search: a new solution approach for the nurse routing problem with incompatible services and minimum demand

The average age of the population has grown steadily in recent decades along with the number of people suffering from chronic diseases and asking for treatments. Hospital care is expensive and often unsafe, especially for older individuals. This is particularly true during pandemics as the recent SARS-CoV-2. Hospitalization at home has become a valuable alternative to face efficiently a huge increase in treatment requests while guaranteeing a high quality of service and lower risk to fragile patients. This new model of care requires the redefinition of health services organization and the optimization of scarce resources (e.g., available nurses). In this paper, we study a Nurse Routing Problem that tries to find a good balance between hospital costs reduction and the well-being of patients, also considering realistic operational restrictions like maximum working times for the nurses and possible incompatibilities between services jointly provided to the same patient. We first propose a Mixed Integer Linear Programming formulation for the problem and use some valid inequalities to strengthen it. A simple branch-and-cut algorithm is proposed and validated to derive ground benchmarks. In addition, to efficiently solve the problem, we develop an Adaptive Large Neighborhood Search hybridized with a Kernel Search and validate its performance over a large set of different realistic working scenarios. Computational tests show how our matheuristic approach manages to find good solutions in a reasonable amount of time even in the most difficult settings. Finally, some interesting managerial insights are discussed through an economic analysis of the operating context.     

Failure load prediction and optimisation for adhesively bonded joints enabled by deep learning and fruit fly optimisation

Adhesively bonded joints have been extensively employed in the aeronautical and automotive industries to join thin-layer materials for developing lightweight components. To strengthen the structural integrity of joints, it is critical to estimate and improve joint failure loads effectually. To accomplish the aforementioned purpose, this paper presents a novel deep neural network (DNN) model-enabled approach, and a single lap joint (SLJ) design is used to support research development and validation. The approach is innovative in the following aspects: (i) the DNN model is reinforced with a transfer learning (TL) mechanism to realise an adaptive prediction on a new SLJ design, and the requirement to re-create new training samples and re-train the DNN model from scratch for the design can be alleviated; (ii) a fruit fly optimisation (FFO) algorithm featured with the parallel computing capability is incorporated into the approach to efficiently optimise joint parameters based on joint failure load predictions. Case studies were developed to validate the effectiveness of the approach. Experimental results demonstrate that, with this approach, the number of datasets and the computational time required to re-train the DNN model for a new SLJ design were significantly reduced by 92.00% and 99.57% respectively, and the joint failure load was substantially increased by 9.96%.     

一种按拼音首字母对数据库中的汉字进行检索的方法研究

根据SQL Server的排序规则,在不改变查询表结构的条件下,探讨并研究了在SQL Server的数据库服务器端直接按汉字的拼音首字母对汉字进行快速检索的方法。     

Heuristics for solving continuous berth allocation problem considering periodic balancing utilization of cranes

This study investigates a berth allocation problem considering the periodic balancing utilization of quay cranes in container terminals. The proposed model considers that the quay cranes allocated to a work shift should be fully used and other real-world considerations, such as the continuous quay line, the penalties for early arrivals and departure delays. To solve the model, several heuristics are developed: the model for large problems is decomposed into sub-models that are solved by rolling-horizon heuristics; neighborhood search heuristics are used for optimizing a berthing order of vessels; parallel computing is used to improve the algorithmic performance. The method performs well when applied to real-world large-scale instances with promising computation time that is linearly related to the number of vessels.     

浅析有效交互技术基础上的网络远程教学

本文主要简单的介绍了网络远程教学的内容,对有效交互技术的相关内容和特点进行了分析,研究将有效交互技术引入网络远程教学中的重要性,探讨网络远程教学中交互技术应用和设计的原则,以思考在交互技术上实施网络远程教学活动的有效措施,从而保障网络远程教学质量。据此,有利于培养学生对网络远程学习的兴趣,充分发挥交互技术的作用,以提高学生的学习效果,实现网络远程教学效益最大化。     

A multi-objective approach to optimal placement and sizing of multiple active power filters using a music-inspired algorithm

This paper proposes a new multi-objective framework for optimal placement and sizing of the active power filters (APFs) with satisfactory and acceptable standard levels. total harmonic distortion (THD) of voltage, harmonic transmission line loss (HTLL), motor load loss function (MLLF), and total APFs currents are the four objectives considered in the optimization, while harmonic distortions within standard level, and maximum allowable APF size, are modeled as constraints. The proposed model is one of non-convex optimization problem having a non-linear, mixed-integer nature. Since, a new modified harmony search algorithm (MHSA) is used and followed by a min–max technique in order to obtain the final optimal solution. The harmony search algorithm is a recently developed optimization algorithm, which imitates the music improvisation process. In this process, the Harmonists improvise their instrument pitches searching for the perfect state of harmony. The newly developed method has been applied on the IEEE 18-bus test system and IEEE 30-bus test system by different scenarios and cases to demonstrate the feasibility and effectiveness of the proposed method. The detailed results of the case studies are presented and thoroughly analyzed. The obtained results illustrate the sufficiency and profitableness of the newly developed method in the placement and sizing of the multiple active power filters, when compared with other methods.     

用土力学的新概念解读和修正经典饱和土力学

论述了应该用有效应力的新概念代替经典有效应力原理。总应力压缩模量与渗流水等效压缩模量的曲线相似;有效应力压缩模量起加劲作用,而不是起决定性作用。土的压缩变形计算中应用有效应力原理是错误的。对于起始水力坡降,引入饱和粘性土的自由水压力衰减概念。在饱和粘性土中,自由水通道率折减不大,相对自由水压力通过一定厚度后衰减为零。所以,新概念土力学的算法接近我国规范:"对粘性土宜按水土合算计算"。还解读了地下室浮力折减、流沙陷阱等等。     

Searching for triangles: An extension to food & packaging

Two laboratory-based visual search experiments (Experiments 1 and 2) and an online survey (Experiment 3) were conducted in order to investigate the visual search for triangular foods. The results of Experiment 1 revealed that the visual search for a downward pointing triangular target was faster than when the same target pointed upward, regardless of whether the stimuli were simple geometric figures or photos of food. Experiment 2 replicated these results using images of both food and non-food packaging. Experiment 3 revealed that the same triangular stimuli were generally rated as less pleasant, less liked, and less familiar when they pointed downward than when they pointed upward. Taken together, these results therefore suggest that the cognitive processing of food images is influenced by incidental aspects of their visual appearance, and that such a pattern of results can also be extended to the case of food packaging.     

Role of activated carbon on micropollutans degradation by ionizing radiation

The objective of this study was to analyze the influence of the presence of activated carbon on the degradation of the triiodinated contrast medium diatrizoate (DTZ) by the simultaneous use of gamma radiation and activated carbon. Four commercial activated carbons (Ceca, Witco, Sorbo, and Merck) with different textural and chemical characteristics were used for this purpose. The percentage DTZ removal obtained was considerably higher with the gamma radiation/activated carbon (GM/AC) system than with radiolysis in the absence of activated carbon, and it depended on the specific activated carbon employed. First, we optimized the amount of activated carbon required to maximize the amount of DTZ removed by the GM/AC system (0.06 g). The degradation constants were higher with the GM/AC system than with radiolysis alone, evidencing a synergic effect that favors pollutant removal. This synergic effect is independent of the textural but not the chemical characteristics of the activated carbon, observing a higher synergic activity for carbons with a higher surface content of oxygen, specifically quinone groups. We also highlight that the synergic effect of the activated carbon requires adsorbent–adsorbate electrostatic interaction and is absent when this interaction is hindered.