一种新型智能COD仪的研制

近年来，GSM移动通信技术日趋成熟，它提供了强大可靠的短信息（SMS）服务和数据传输服务。基于GSM数据传输平台的各种应用也不断被开发。本文介绍GSM在污水COD监测方面的应用，并着重介绍COD监测终端的开发与研制。     

AN SVAD ALGORITHM BASED ON FNNKD METHOD

The capacity of mobile communication system is improved by using Voice Activity Detection (VAD) technology. In this letter, a novel VAD algorithm, SVAD algorithm based on Fuzzy Neural Network Knowledge Discovery (FNNKD) method is proposed. The performance of SVAD algorithm is discussed and compared with traditional algorithm recommended by ITU G.729B in different situations. The simulation results show that the SVAD algorithm performs better.     

多模式对连接权矩阵的一种神经网络学习算法

该文提出多模式对连接权矩阵的一种神经网络学习算法,并给出了严格的理论证明。该算法能够将多个模糊模式对可靠地编码存储到尽可能少的连接权矩阵中,从而大大地减少存储空间,而且容易实现,并举例验证了它的有效性。     

Creating awareness on bullying and cyberbullying among young people: Validating the effectiveness and design of the serious game Conectado

Serious games have proven to be educational tools with numerous positive effects, capable of promoting learning, changing behavior, or improving training and skills development, among other effects. Serious games can also be applied to address and prevent social problems. This study describes the experiments and analyses we have carried out to test the effectiveness of Conectado, a serious game created to prevent bullying and cyberbullying in schools by increasing awareness of the problem in players. We have used the results from these experiments to answer different research questions regarding the game’s acceptance and effectiveness, validating several characteristics of the game design. We have also studied the influence of players’ characteristics on the effect of the game, as well as the relationship between the in-game behaviors of players and their degree of awareness. We have verified a positive effect of the game in terms of an increase of awareness regarding bullying and cyberbullying for all target users, and have provided further insight into how this increase is related to different players’ characteristics and behaviors.     

一种新型基于环上带误差学习问题的认证密钥交换方案

利用格上判定带误差学习问题(Ring-DLWE)困难假设,该文基于Peikert的调和技术构造认证密钥交换方案。在标准模型下,该方案是CK模型中可证明安全的,并达到弱前向安全性(wPFS)。与现有的基于LWE的密钥交换方案相比,该方案使用平衡的密钥提取函数,因而保护共享会话密钥,同时因其基于格中困难问题,所以能抵抗量子攻击。     

Analog VLSI Circuits for Competitive Learning Networks

An investigation is made concerning implementations of competitive learning algorithms in analog VLSI circuits and systems. Analog and low power digital circuits for competitive learning are currently important for their applications in computationally-efficient speech and image compression by vector quantization, as required for example in portable multi-media terminals. A summary of competitive learning models is presented to indicate the type of VLSI computations required, and the effects of weight quantization are discussed. Analog circuit representations of computational primitives for learning and evaluation of distortion metrics are discussed. The present state of VLSI implementations of hard and soft competitive learning algorithms are described, as well as those for topological feature maps. Tolerance of learning algorithms to observed analog circuit properties is reported. New results are also presented from simulations of frequency-sensitive and soft competitive learning concerning sensitivity of these algorithms to precision in VLSI learning computations. Applications of these learning algorithms to unsupervised feature extraction and to vector quantization of speech and images are also described.     

LANN AND ITS HETEROASSOCIATIVE MEMORY PROPERTIES

This paper provides a new architecture of neural network, called loop architecture neural network(LANN), and its learning rules. One of its features distinguished from other network, such as Hopfield and bidirectional associative memories, is that it can perform the associative memory among multiple categories. Analysis and simulated results have proved that it is an effective network with excellent convergence.     

束流位置监测系统的研制及其在国家同步辐射实验室二期工程中的应用

 介绍一种储存环束流位置监测系统的标定装置。这套标定装置是为NSRL二期工程储存环注入段真空盒改造而研制的。系统的标定精度达±0.01mm。该装置已用于新增注入段真空管的束流位置探测器的定标，获得了探头定标值，并根据其拟合和计算结果对注入段真空管进行了筛选，被选中的真空管已装入储存环注入段。     

改进人工蜂群算法优化ELM分类模型

针对极限学习机(Extreme Learning Machine,ELM)参数优化问题,提出改进人工蜂群算法(Improvement Artificial bee colony, IABC)优化ELM分类模型。算法采用解更新策略池代替固定不变的更新策略,将邻域搜索自适应化;优化侦察蜂搜索方式,利用Kent映射产生均匀性更优的初始随机数序列。在分类数据集中,将IABC-ELM分类模型同ELM、PSO-ELM分类模型进行对比实验。实验中,IABC-ELM模型取得了最佳的分类结果,得到了最低的输出权重范数。结果表明,IABC-ELM模型分类效果显著优于对比模型,证实了IABC算法优化ELM分类模型的有效性和优越性。     

Assessment model of classroom acoustics criteria for enhancing speech intelligibility and learning quality

In this paper, a new classroom acoustics assessment model (CAAM) based on analytic hierarchy process (AHP) for enhancing speech intelligibility and learning quality is proposed. The model is based on five main criteria that affect the learning process and related to classrooms acoustical properties. These include classroom specifications, noise sources inside and outside the classroom, teaching style, and vocal effort. The priority and weights of these major criteria along with their alternatives are identified using the views of students, staff, education consultants, and expertise by using a developed questionnaire, and the AHP methodology. This model can be considered as a helpful framework enabling universities decision makers to take effective decisions on classroom acoustics treatment issues. It also provides colleges’ higher authorities the suitable guidelines that help for determining necessary requirements that help to raise the quality and efficiency of the educational environment; in order to reach an excellent learning environment; and hence increasing students learning outcomes.