Analysis and Simulations of Open-Source Intelligence Process System Dynamics from User’s Perspective

In today’s society with advanced Internet,the amount of information increases dramatically with each passing day,which leads to increasingly complex processes of open-source intelligence.Therefore,it is more important to rationalize the operation mode and improve the operation efficiency of open-source intelligence under the premise of satisfying users’needs.This paper focuses on the simulation study of the process system of opensource intelligence from the user’s perspective.First,the basic concept and development status of open-source intelligence are introduced in details.Second,six existing intelligence operation process models are summarized and their advantages and disadvantages are compared in focus.Based on users’preference,the open-source intelligence system simulation theory model is constructed from four aspects:intelligence collection,intelligence processing,intelligence analysis,and intelligence delivery.Meanwhile,the dynamics model of the open-source intelligence process system is constructed based on the open-source intelligence system simulation theoretical model,which specifically includes five parts:determination of system boundary,construction of causal loop diagram,construction of stock flow diagram,writing ofmathematical equations,and system sensitivity test.Finally,the system simulation results were analyzed.It was found that improving the system of intelligence agencies,opening up government affairs,improving the professional level of intelligence personnel,strengthening the communication and cooperation among personnel of various intelligence departments,and expressing intelligence products through diverse forms can effectively improve the operational efficiency of the open-source intelligence process system.

Developing Lexicons for Enhanced Sentiment Analysis in Software Engineering:An Innovative Multilingual Approach for Social Media Reviews

Sentiment analysis is becoming increasingly important in today’s digital age, with social media being a significantsource of user-generated content. The development of sentiment lexicons that can support languages other thanEnglish is a challenging task, especially for analyzing sentiment analysis in social media reviews. Most existingsentiment analysis systems focus on English, leaving a significant research gap in other languages due to limitedresources and tools. This research aims to address this gap by building a sentiment lexicon for local languages,which is then used with a machine learning algorithm for efficient sentiment analysis. In the first step, a lexiconis developed that includes five languages: Urdu, Roman Urdu, Pashto, Roman Pashto, and English. The sentimentscores from SentiWordNet are associated with each word in the lexicon to produce an effective sentiment score. Inthe second step, a naive Bayesian algorithm is applied to the developed lexicon for efficient sentiment analysis ofRoman Pashto. Both the sentiment lexicon and sentiment analysis steps were evaluated using information retrievalmetrics, with an accuracy score of 0.89 for the sentiment lexicon and 0.83 for the sentiment analysis. The resultsshowcase the potential for improving software engineering tasks related to user feedback analysis and productdevelopment.

Limited Feedback Bit Allocation for Cooperative Multi-cell Systems with Multi- user MIMO

For the cooperative multi-cell systems with multi-user MIMO, a new limited feedback bit allocation scheme is proposed to minimize the rate loss caused by quantization error. In the proposed scheme, the Channel State Information (CSI) feedback of cell-edge user for the local service cell and the adjacent interference cell are separately quantized. Based on the upper bound of the rate loss of cell-edge user due to the limited feedback, the number of feedback bits for quantized CSI of the local service cell and the adjacent cell are optimized with the fixed total bits of the limited feedback. The simulation shows that our proposed scheme of feedback bits allocation efficiently decreases the interference and increases the rate of systems compared with that of equal bits allocation and those of other allocations.

User Fairness Scheme with Proportional Fair Scheduling in Multi-user MIMO Limited Feedback System

In Multi-user MIMO (MU-MIMO) downlink system, suitable user selection schemes can improve spatial diversity gain. In most of previous studies, it is always assumed that the base station (BS) knows full channel state information (CSI) of each user, which does not consider the reality. However, there are only limited feedback bits in real system. Besides, user fairness is often ignored in most of current user selection schemes. To discuss the user fairness and limited feedback, in this paper, the user selection scheme with limited feedback bits is proposed. The BS utilizes codebook precoding transmitting strategy with LTE codebook. Furthermore, this paper analyzes the influence of the number of feedback bits and the number of users on user fairness and system sum capacity. Simulation results show that in order to achieve better user fairness, we can use fewer bits for feedback CSI when the number of user is small, and more feedback bits when the number of users is large.

The Impact of Comment Style on Learners’ Essay Revisions

This paper investigates how the type of written feedback provided by teachers affects learners’ ability to revise essays. A total of 120 participants participated in two rounds of essay composition and feedback delivery. The findings indicate that learners who receive comments in the form of questions are more prone to make revisions compared to those receiving statements or imperatives. These results hold significant implications for educators and the ways they utilize written feedback to enhance learners’ writing skills.

基于T-S模糊模型的桥吊系统积分状态反馈控制

小车定位精度和负载摆角大小是桥式起重机控制系统的两个重要性能指标。采用状态反馈控制时小车位移会存在稳态误差,为了消除稳态误差,提高系统的定位精度,给出基于T-S模糊模型的积分状态反馈控制方法。在桥式起重机非线性动力学模型基础上,建立增维T-S模糊模型,基于所建模型设计并行结构的积分状态反馈控制器,通过线性矩阵不等式计算反馈增益矩阵,并对闭环系统的稳定性进行分析。实验结果表明积分状态反馈控制不仅可以提高系统的定位精度,减少定位时间,而且有较好的抗干扰能力。

On Teacher's Feedback from the Perspective of Communication

Classroom interaction involves many aspects,among which teacher's feedback is an important element.This paper aimes at studying teacher's feedback from the perspective of communication.It first discusses the definition of teacher's feedback and analyses the functions of teacher's feedback in the classroom interaction and then explores some strategies for effective feedback based on communication theory.

基于S-O-R理论的新型公共阅读空间用户流失行为分析——来自大众点评网用户评论

文章以大众点评网站中新型公共阅读空间的评论数据为对象,以S-O-R模型为理论基础,利用Python爬取其“中评”与“差评”的评论数据,运用内容分析法归纳得出新型公共阅读空间用户流失行为的主要因素,并构建新型公共阅读空间用户流失行为模型。在此基础上,提出提高新型公共阅读空间服务效能的相关建议,为提高新型阅读空间的服务质量,降低用户流失率提供参考。

基于L-M-NFSR结构的16比特S盒设计方法

S盒是分组密码算法的重要部件,为密码算法提供非线性变换,S盒的安全强度在一定程度上决定着密码算法的安全强度。为构造具有优良密码学性质的16比特S盒,设计一种以Lai-Massey结构和非线性反馈移位寄存器(NFSR)组件相结合的L-M-NFSR新结构。该结构以与高级加密标准(AES)算法S盒仿射等价的8比特S盒作为新结构的轮函数,减少设计的复杂性并提高结构的可变性;左右分支各增加一个迭代少量拍数即可符合严格雪崩特性的NFSR组件用于提高结构的扩散性;通过3轮迭代和遍历生成16比特S盒。进一步地,基于该结构,以AES算法S盒仿射等价新生成的8比特S盒替换轮函数中的8比特S盒,可方便地生成大量新的16比特密码S盒。为提高对所构造16比特S盒性质的评估效率,采用图形处理器(GPU)进行并行计算,测试结果表明,所生成的16比特S盒具有较优的密码学性质,均满足双射性,代数次数为15,非线性度最优为31992,差分均匀度最低为18,信噪比最低为146.712,具有较好地抵御数学攻击和差分功耗分析的安全性。

利用CNC多维约束的S型速度规划

经典控制模型中存在时间过耦合,而速度规划与实时轨迹控制都与时间关联,导致实时计算量、规划与控制协调性等不足的问题,提出利用CNC多维约束的S型速度规划方法.首先建立双重反馈的控制模型,内反馈继承经典控制模型将时间反馈到控制器,外反馈将非时间反馈到规划器;然后将影响速度规划的因素分为时间相关与时间无关,与时间相关因素在控制器中实时控制,与时间无关因素在规划器中进行非时间速度规划;在规划器中建立基于轨迹路径长度、轨迹几何特性、运动参数以及程序行号等信息的多维约束模型;最后以路径长度代替时间作为运动参考量,结合多维约束模型,考虑轨迹的几何特性与路径长度映射关系,使轨迹特性与非时间建立具有空间性关联.通过MATLAB仿真对控制模型的抗干扰能力进行验证,并通过CODESYS软件编程和实验的结果表明,所提方法是可行和有效的.

通信受限下T-S模糊网络控制系统L_(1)动态输出反馈控制

针对通信受限的非线性网络控制系统,为兼顾系统性能和节约利用网络资源,引入事件触发通信机制(ETCM),利用时延建模方法和并行分布补偿(PDC)技术,将连续控制系统建模为一个采样数据误差依赖的非线性网络化系统模型;构建保守性低的时滞依赖和模糊基依赖的Lyapunov-Krasovskii泛函,给出增广系统稳定性和鲁棒性结果,得到鲁棒控制器存在的充分条件,提出一种基于线性矩阵不等式(LMIs)的事件触发参数,以及全局模糊L 1动态输出反馈控制器参数的协同设计方法。采用永磁同步电动机模型仿真验证,结果表明该设计方法可减少网络资源占用,达到闭环控制系统的性能要求。

Angle-Based Beamforming in mmWave Massive MIMO Systems with Low Feedback Overhead Using Multi-Pattern Codebooks

The integration of millimeter-wave(mmWave)communications and massive multiple input multiple output(MIMO)techniques is a promising solution to dramatically increase the 5G network throughput.By using large antenna arrays,beamforming can be adopted to improve the 5G capacity by employing spatial domain resources.In a frequency division duplexing(FDD)based 5G mmWave MIMO system,beamforming operation requires timely downlink channel state information(CSI)feedback.However,the rapid channel variations caused by short wavelength of mmWave band,and the high-level feedback information required due to the large number of antennas in massive MIMO system lead to the significantly increased beamforming overhead.In this paper,by exploiting the higher angular stability of such channels,we propose an angle-based beamforming scheme to reduce the feedback frequency and the number of feedback bits.To facilitate this approach users are initially selected to reduce the intra-zone interference before beamforming.Besides,location related feedback,which is not affected by the number of antennas,is adopted to reduce overhead.The simulation results show that two proposed user selection algorithms can adapt to scenarios with diverse requirements,while the feedback overhead of proposed angle-based beamforming algorithm is sharply reduce compared with that of CSIbased beamforming algorithm.

Customization Product Design Based on User's Emotion and Needs

The paper presents a design method that ensures the ingenuity of the product form as well as the whole and exact expression of user’s needs. The key idea is to establish an automatic design system which can transform the user’s language needs into the product features in real-time. A rifle was taken as a research instance and soldiers were chosen as evaluation customers. The theory of fuzzy set and semantic difference are adopted to evaluate the relationship between user’s needs and product features as well as their alternatives. FAHP (fuzzy analytic hierarchy process) is utilized to judge the user’s satisfactory forms. This method can also be applied to other product form designs.

Use of methotrexate in inflammatory bowel disease in 2014: A User's Guide

Methotrexate has been used an immunomodulator in many autoimmune diseases,including inflammatory bowel disease. However,many physicians are unfamiliar or uncomfortable with its use in the management of inflammatory bowel disease. We summarize the data for use of methotrexate in common clinical scenarios:(1) steroid dependant Crohn's disease(CD);(2) maintenance of remission in steroid free CD;(3) azathioprine failures in CD;(4) in combination therapy with Anti-TNF agents in CD;(5) decreasing antibody formation to Anti-TNF therapy in CD;(6) management of fistulizing disease in CD; and(7) as well as induction and maintenance of remission in ulcerative colitis. An easy to use algorithm is provided for the busy clinician to access and safely prescribe methotrexate for their inflammatory bowel disease patients.

Information perception and feedback mechanism and key techniques of multi-modality human-robot interaction for service robots

With the increasing of the elderly population and the growing hearth care cost, the role of service robots in aiding the disabled and the elderly is becoming important. Many researchers in the world have paid much attention to heaRthcare robots and rehabilitation robots. To get natural and harmonious communication between the user and a service robot, the information perception/feedback ability, and interaction ability for service robots become more important in many key issues.

Frequent Itemset Mining of User’s Multi-Attribute under Local Differential Privacy

Frequent itemset mining is an essential problem in data mining and plays a key role in many data mining applications.However,users’personal privacy will be leaked in the mining process.In recent years,application of local differential privacy protection models to mine frequent itemsets is a relatively reliable and secure protection method.Local differential privacy means that users first perturb the original data and then send these data to the aggregator,preventing the aggregator from revealing the user’s private information.We propose a novel framework that implements frequent itemset mining under local differential privacy and is applicable to user’s multi-attribute.The main technique has bitmap encoding for converting the user’s original data into a binary string.It also includes how to choose the best perturbation algorithm for varying user attributes,and uses the frequent pattern tree(FP-tree)algorithm to mine frequent itemsets.Finally,we incorporate the threshold random response(TRR)algorithm in the framework and compare it with the existing algorithms,and demonstrate that the TRR algorithm has higher accuracy for mining frequent itemsets.

User’s Relevance of PIR System Based on Cloud Models

A new method to evaluate fuzzily user＇s relevance on the basis of cloud models has been proposed. All factors of personalized information retrieval system are taken into account in this method. So using this method for personalized information retrieval （PIR） system can efficiently judge multi-value relevance, such as quite relevant, comparatively relevant, commonly relevant, basically relevant and completely non-relevant, and realize a kind of transform of qualitative concepts and quantity and improve accuracy of relevance judgements in PIR system. Experimental data showed that the method is practical and valid. Evaluation results are more accurate and approach to the fact better.

Joint Source and Relay Precoding/Beamforming Algorithm for OFDM Multi-user Cooperative Relay Systems

In order to reduce the feedback load of multi-user orthogonal frequency division multiplexing （ OFDM ） -based wireless systems, a practiral limited bits feedback precoding algorithm is proposed with direct source-destination link based on amplify-and- forward cooperative relay network under frequency selective fading channels. Using joint minimum mean square error（MMSE） filter, the receiving decoding matrix is designed for each user in the paper. Source precoding （beamforming） matrix is optimized with convex function of weight mean square error （MSE）. Relay precoding matrix is obtained under MSE decomposition and convex optimization. The precoding matrix index is fed back for clustered subcarrier of OFDM with limited feedback. Then using interpolation algorithm, all precoding matrices are achieved at base station （BS） and relay nodes. Simulations indicate the effectiveness of the proposed limited feedback joint precoding and beam_formlng design. The proposed method can improve bit error rate （BER） performance and obtain better sum-rate performance in contrast to existing algorithms. It displays the BER performance is close to that of the unquantified precoding feedback method.

LMI-based output feedback fuzzy control of chaotic system with uncertainties

This paper studies the robust fuzzy control for nonlinear chaotic system in the presence of parametric uncertainties. An uncertain Takagi-Sugeno （T-S） fuzzy model is employed for fuzzy modelling of an unknown chaotic system. A sufficient condition formulated in terms of linear matrix inequality （LMI） for the existence of fuzzy controller is obtained. Then the output feedback fuzzy-model-based regulator derived from the LMI solutions can guarantee the stability of the closed-loop overall fuzzy system. The T-S fuzzy model of the chaotic Chen system is developed as an example for illustration. The effectiveness of the proposed controller design methodology is finally demonstrated through computer simulations on the uncertain Chen chaotic system.