Universal Band Pass Sampling Algorithm for Integration of Multiple Wireless Technologies Using Software Defined Radio Platform

Software Defined Radio (SDR) architecture allows us to integrate different mobile technologies using common hardware but with different software modules. To achieve this, we need to keep the signal in digital form for as much portion of the circuitry as possible, so that the implementation could be carried out by programmable digital processors. For this purpose, the incoming radio frequency (RF) signal is down converted to baseband spectrum using band pass sampling method. Research works carried out so far in this field have developed a few algorithms for band pass sampling. But, these algorithms are not much useful for most of the mobile communication systems and they use complex methodology for computing the sampling frequency values. In order to use the SDR platform to integrate all current wireless technologies, an efficient, cost effective and less complex algorithm that can be labelled as universal band pass sampling algorithm is developed in this paper for multiple mobile systems. This algorithm is based on a novel idea of inserting guard bands between the signals which reduces the design complexities of perfect ADC and sharp cut off filters. Using this algorithm, valid sampling frequency ranges and corresponding IF values are calculated for down converting RF signals. The algorithm is tested for six RF signals of different wireless technologies which are integrated and simultaneously down converted using SDR based front end receiver and thus the system multiplies the base station capacity by a factor of six. The simulation results are obtained and shown in this paper which proves that the algorithm developed works well for most of the wireless technologies.

Towards an Effective Communication in the Care of Patients with Long Term Disease in Kenya via Cybernetic—A Systematic Review

In this paper, to effectively treat chronic disorders and improve the standard of care, effective communication between patients and healthcare professionals was essential. The aim of the study was to review the literature on how good communication might improve treatment outcomes for Kenyan patients with chronic and terminal illnesses and to determine whether Cybernetic electronic communication can improve those outcomes even more. We uncovered the history of treatment outcomes for chronic and terminal diseases in this research study, both with and without communication at the core of the patient’s care plan. We discussed the importance of good communication in the treatment of patients with chronic and terminal illnesses and why it is a momentous endeavor comparable to medical diagnosis and treatment for the long-term health of patients. To locate pertinent material for the background literature study, we carried out a comprehensive literature search. Although the preliminary literature review was a continuation of the introduction research, it also highlighted the paucity of local Kenyan literature and suggested that improved communication might help patients with chronic and terminal illnesses have better treatment outcome. Methodology maintained the literature search, as a systematic literature review focused on core of the study, making separate sections of the same body necessary. This ensured that a methodological literature search section is as comprehensive as possible. We used an integrated PRISM model to limit a comprehensive literature search and a systematic literature review design as part of the overall process. Non-probability sampling and snowball approaches on literary papers over the previous 17 years were used in this arrangement. Since this was a multidisciplinary study, the four experts who also serve as authors were chosen from within their respective fields of expertise to design the study. They created search strategies, generated key words, looked up keywords in database engines, assessed the results of the literature using the PRISMA logical model, looked over successful literature, and triangulated their findings. The conclusions of the experts individually revealed a convergence of thoughts, beliefs, and practices across. The study concluded that even though there isn’t much research done in Kenya on the same subject;what is available illustrates how crucial good communication is for patients with chronic illnesses. The study’s findings also highlighted the positive effects of effective communication between patients and healthcare professionals on treatment plan adherence, patient satisfaction, and overall health outcomes. The results also noted that in order to improve patient care and outcome, Kenyan healthcare workers should underscore developing their communication skills. The study also found that the incorporation of cybernetics is crucial if a truly effective communication is required so as to enable centered care for patients with long-term diseases in Kenya. The goal of the Cybernetics is to activate genuinely effective communication in the care of Patients with long-term disease in Kenya. This study is organized to begin with an abstract, followed by keywords, an introduction, literature review, methodology, findings, discussion, and finally conclusions.

5-30 Establishment of Interface Communication between Terminal System and the Treatment Planning System

Treatment of terminal system is mainly through the interface communication protocol for treatment planningsystem to achieve the control of various kinds of medical equipments, including primary collimator, range shifter,scatterer, ridge type filter, multi-leaf collimator, etc. TPS was based on the radioactive source and the patientmodeling to simulate the plan implementation of radiotherapy. The basic structure of block diagram is shown inFig. 1.

Discussion on Network Multimedia Interface Design under the Perspective of Communication Study

Using multimedia writing tools ‘Author ware＇ for Windows 3.0b18, and making a multimedia interface for a simple interface generated by FoxPro 2.5B, mainly to solve how to connect an interface with Author ware and FoxPro database, namely the communication problem between two separate programs under the Windows environment and to generate the multimedia interface which is consistent with the status and requests for the management information system, namely the problem that how to establish multimedia interface design.

湿陷性黄土中可回收锚杆锚-土界面抗剪强度随机森林模型

为推进湿陷性黄土地区基坑工程中可回收锚杆的工程应用,以土体含水率(w)、土体干密度(ρ_(d))和锚固体直径(d)作为试验影响因素,开展了湿陷性黄土的湿陷试验以及可回收锚杆微段单元体拉拔试验,获得了黄土湿陷系数(δ_(s))和锚-土界面剪应力-剪切位移曲线随试验影响因素(w、ρ_(d)和d)的变化规律。试验结果表明:湿陷系数随干密度的增大呈减小趋势,随含水率的增大呈减小趋势;锚-土界面峰值剪切强度则随干密度的增大呈增大趋势,随含水率的增大呈减小趋势;单元体试样边界效应与土样软硬程度有关。最后,基于随机森林算法,选取土体含水率、土体干密度、湿陷系数和锚固体直径4个影响因素作为输入变量,建立了湿陷性黄土中可回收锚杆锚-土界面峰值剪切强度预测模型,其训练集和测试集的可决系数(R^(2))分别为0.971、0.915,表明所建立预测模型效果较好。

Prediction of corrosion rate for friction stir processed WE43 alloy by combining PSO-based virtual sample generation and machine learning

The corrosion rate is a crucial factor that impacts the longevity of materials in different applications.After undergoing friction stir processing(FSP),the refined grain structure leads to a notable decrease in corrosion rate.However,a better understanding of the correlation between the FSP process parameters and the corrosion rate is still lacking.The current study used machine learning to establish the relationship between the corrosion rate and FSP process parameters(rotational speed,traverse speed,and shoulder diameter)for WE43 alloy.The Taguchi L27 design of experiments was used for the experimental analysis.In addition,synthetic data was generated using particle swarm optimization for virtual sample generation(VSG).The application of VSG has led to an increase in the prediction accuracy of machine learning models.A sensitivity analysis was performed using Shapley Additive Explanations to determine the key factors affecting the corrosion rate.The shoulder diameter had a significant impact in comparison to the traverse speed.A graphical user interface(GUI)has been created to predict the corrosion rate using the identified factors.This study focuses on the WE43 alloy,but its findings can also be used to predict the corrosion rate of other magnesium alloys.

FloodNet： Coupling Adaptive Sampling with Energy Aware Routing in a Flood Warning System

We describe the design of FloodNet, a flood warning system, which uses a grid-based flood predictor model developed by environmental experts to make flood predictions based on readings of water level collected by a set of sensor nodes. To optimize battery consumption, the reporting frequency of sensor nodes is required to be adaptive to local conditions as well as the flood predictor model. We therefore propose an energy aware routing protocol which allows sensor nodes to consume energy according to this need. This system is notable both for the adaptive sampling regime and the methodology adopted in the design of the adaptive behavior, which involved development of simulation tools and very close collaboration with environmental experts.

Key Techniques in Adaptive Polarization Mode Dispersion Compensation: Sampling and Feedback Control

This paper presents the sampling and feedback control techniques, which are the kernel of our experiment on adaptive Polarization Mode Dispersion (PMD) compensation for optical fiber communication systems. Some key points on sampling and feedback techniques are discussed and practical resolutions for them are put forward.

全自动罐下取样系统V1.0设计与实现

根据GB/T 4756—2015《石油液体手工取样法》中规定的取样点(上部样、中部样、下部样),开发一套全自动的取样系统。本文主要内容介绍了全自动罐下取样系统的应用、概述、系统设计的原理和功能、可视化系统画面的开发以及系统应用的优点。

基于STM32的全自动样本分杯处理系统的设计

为简化手工对样本前处理的繁琐操作流程,提高样本前处理的质量,开发一套基于STM32的全自动样本分杯处理系统。该系统硬件主要包含STM32H750VBT6微处理器单元、运动控制单元和传感器检测单元;软件主要包含步进电机控制程序和在线移液检测,结合Microsoft Visual Studio软件作为人机界面。结果表明,该系统运行可靠、人机交互友好,能精确控制移液过程的样本,满足全自动样本分杯处理的要求。

Labeling Malicious Communication Samples Based on Semi-Supervised Deep Neural Network

The limited labeled sample data in the field of advanced security threats detection seriously restricts the effective development of research work.Learning the sample labels from the labeled and unlabeled data has received a lot of research attention and various universal labeling methods have been proposed.However,the labeling task of malicious communication samples targeted at advanced threats has to face the two practical challenges:the difficulty of extracting effective features in advance and the complexity of the actual sample types.To address these problems,we proposed a sample labeling method for malicious communication based on semi-supervised deep neural network.This method supports continuous learning and optimization feature representation while labeling sample,and can handle uncertain samples that are outside the concerned sample types.According to the experimental results,our proposed deep neural network can automatically learn effective feature representation,and the validity of features is close to or even higher than that of features which extracted based on expert knowledge.Furthermore,our proposed method can achieve the labeling accuracy of 97.64%~98.50%,which is more accurate than the train-then-detect,kNN and LPA methodsin any labeled-sample proportion condition.The problem of insufficient labeled samples in many network attack detecting scenarios,and our proposed work can function as a reference for the sample labeling tasks in the similar real-world scenarios.

A Method of Combination of Language Understanding with Touch-Based Communication Robots

Studies of robots which aim to entertain and to be conversational partners of the live-alone become very important. The robots are classified into DBC (Dialogue-Based Communication) robots and TBC (Touch-Based Communication) robots. DBC robots have an effect to be conversational partners. A typical application of TBC robots is Paro (a baby harp seal robot) which has an effect to entertain humans. The combination of DBC and TBC will be able to achieve both a conversational ability and an entertaining effect, but there is no study of combination of DBC and TBC. This paper proposes a response algorithm that can combine conversational information and touch information from humans. Criterions for estimation are defined as follows: FFV (Familiarity Factor Value), EFV (Enjoyment Factor Value), CR (Concentration Rate), ER (Expression Rate), and RR (Recognition Rate). FFV and EFV are total ratings for questionnaire related to familiarity and enjoyment factors, respectively. CR measures attention for humans. ER is the interest of communication with robots by representing Level 2 (laugh with opening one’s mouse), Level 1 (smile), and Level 0 (expressionless). RR is recognition ability for voices and touch actions. From the experiment for impressions of robot responses with 11 subjects, it turns out that the proposed method with combination of DBC and TBC is improved by 20.7 points in FFV, and by 12.6 points in EFV compared to only TBC. From the robot communication experiment, it turns out that the proposed method is improved by 8 points in the ER, by 5.3 points in the ER with Level 2, and by 24.5 points in the RR compared to only DBC.

Coupled maps serving the exchange processes on the environmental interfaces regarded as complex systems

We have defined the environmental interface through the exchange processes between media forming this interface. Considering the environmental interface as a complex system we elaborated the advanced mathematical tools for its modelling. We have suggested two coupled maps serving the exchange processes on the environmental interfaces spatially ranged from cellular to planetary level, i.e. 1) the map with diffusive coupling for energy exchange simulation and 2) the map with affinity, which is suitable for matter exchange processes at the cellular level. We have performed the dynamical analysis of the coupled maps using the Lyapunov exponent, cross sample as well as the permutation entropy in dependence on different map parameters. Finally, we discussed the map with affinity, which shows some features making it a promising toll in simulation of exchange processes on the environmental interface at the cellular level.

基于双接口分集和数据样本的脉冲噪声抑制算法

针对电力线与无线双接口通信中的电力线突发脉冲噪声(BIN)的干扰问题,提出一种基于分集信号抵消和自适应阈值估计(DSC-ATE)的BIN抑制算法。首先,利用电力线和无线并行信道传输相同的分集信号,接收端通过分集信号抵消获得脉冲噪声样本,降低峰平比对阈值估计的影响;然后利用噪声样本对非线性函数的最佳阈值进行估计;最后对脉冲噪声进行抑制处理。为了提高算法的鲁棒性和可扩展性,该文通过引入折扣因子和学习率来实现算法在复杂度和精度之间的有效折中。与已有的非线性处理算法相比,该方法不需要噪声的先验统计信息,并可根据信道环境的变化自适应地调整阈值。仿真结果表明,所提算法在可靠性和阈值精度方面均具有显著提升。

IUID Method-Mix: Towards a Systematic Approach for Intercultural User Interface Design (IUID)

A method-mix for intercultural user interface design (IUID) is explained and exemplified by application examples based on a hybrid approach covering cultural contexts in human-computer interaction (HCI) design using a model of culturally influenced HCI. Cultural influence on HCI is described using cultural variables for user interface design. Assumptions and empirical results regarding the influence of culture on HCI, considering the path of the information processing and the interaction style between Chinese and German users are explained based on cultural models. Subsequent indicators represent the relationship between culture and HCI (culturally imprinted by the user). Correlations adopted theoretically between cultural dimensions and variables for HCI design were investigated. These correlations represent relevant constituents of a model for culturally influenced HCI. Considerations applying this model and evidence for the proper application of the IUID method-mix are presented elucidating why and how cultural aspects play a role in HCI design and usability/UX engineering. The IUID method-mix serves to inspire HCI engineers in the requirement analysis phase as well as HCI designers in the design phase. The readers are thereby sensitized to the challenges of intercultural usability/UX engineering and intercultural HCI design and will be equipped with methodological knowledge relevant to the derivation of design recommendations for user interface design for and in their desired cultural contexts. Finally, implications for practitioners are shown, including HCI style scores and practical design recommendations, to prognosticate the effort and the expenditures for considering the cultural context in IUID.

Treatment of Imbalance Dataset for Human Emotion Classification

Developments in biomedical science, signal processing technologies have led Electroencephalography (EEG) signals to be widely used in the diagnosis of brain disease and in the field of Brain-Computer Interface (BCI). The collected EEG signals are processed using Machine Learning-Random Forest and Naive Bayes- and Deep Learning-Recurrent Neural Network (RNN), Neural Network (NN) and Long Short Term Memory (LSTM)-Algorithms to obtain the recent mood of a person. The Algorithms mentioned above have been imposed on the data set in order to find out what the person is feeling at a particular moment. The following thesis is conducted to find out one of the following moods (happy, surprised, disgust, fear, anger and sadness) of a person at an instant, with an aim to obtain the result with least amount of time delay as the mood differs. It is pretty obvious that the accuracy of the output varies depending upon the algorithm used, time taken to process the data, so that it is easy for us to compare the reliability and dependency of a particular algorithm to another, prior to its practical implementation. The imbalance data sets that were used had an imbalanced class and thus, over fitting occurred. This problem was handled by generating Artificial Data sets with the use of SMOTE Oversampling Technique.

Design and implementation of control system for superconducting RSFQ circuit

The superconducting rapid single flux quantum(RSFQ)integrated circuit is a promising solu-tion for overcoming speed and power bottlenecks in high-performance computing systems in the post-Moore era.This paper presents an architecture designed to improve the speed and power limitations of high-performance computing systems using superconducting technology.Since superconducting microprocessors,which operate at cryogenic temperatures,require support from semiconductor cir-cuits,the proposed design utilizes the von Neumann architecture with a superconducting RSFQ mi-croprocessor,cryogenic semiconductor memory,a room temperature field programmable gate array(FPGA)controller,and a host computer for input/output.Additionally,the paper introduces two key circuit designs:a start/stop controllable superconducting clock generator and an asynchronous communication interface between the RSFQ and semiconductor chips used to implement the control system.Experimental results demonstrate that the proposed design is feasible and effective,provi-ding valuable insights for future superconducting computer systems.

实验室煤与充填体组合试样变形破坏特征研究

随着充填开采在煤矿开采中的广泛应用,对于煤与充填体组合受巷道覆岩破坏控制理论难以满足工程技术实践发展的现状,导致煤体应力集中、片帮破坏、巷道煤体动力突出等灾害变得更加严重,探究其组合结构本身劣化过程及破坏特征,是解决这类灾害难题的前提。基于充填体能够有效控制煤体及巷道稳定性的实践经验,本文采用现场测试和实验室测试的方法,研究煤体与夹矸界面处的微观结构特征以及充填体厚度对组合试样的影响。研究结果表明,随着充填体厚度的增加,组合试样的抗压强度逐渐降低。当充填体厚度为15 mm时,组合试样整体抗压强度降低至5.74 MPa,相比标准煤样降幅达到77.2%。此降幅主要由于充填体分割煤样,导致组合试样的等效弹性模量降低、整体性弱化和承载能力下降。煤岩组合试样的破坏形式和力学特性也受充填体位置的影响。在单轴压缩过程中,煤与充填体组合试样经历四个阶段:一是在组合试样开始受压时,应变集中在煤样边缘和充填体接触界面处;二是随着承载能力增加,应变集中位置转移至煤样与充填体界面处;三是在加载到峰值前组合试样下部煤样应变集中程度增加并出现裂隙扩展;四是加载达到极限强度后组合试样发生破坏。此外,充填体位置对组合试样的破坏模式和裂纹扩展也有显著影响。充填体厚度为6 mm时,裂纹主要集中在充填体上部和下部。充填体厚度为10 mm时,充填体下部的破坏更加明显。而充填体厚度为15 mm时,裂纹主要发生在组合试样中部。研究成果可为我国地下工程煤岩体变形失稳控制等方面提供一定的理论参考,对推进充填承载控制理论及其工程设计理论的发展具有重要意义。

直接推进技术在有机污染场地调查中的应用研究

近年来,直接推进技术以其快速精确、经济高效、可装备先进探测器等优点,在国外污染场地调查中得到广泛推广与应用。文章在总结国内外相关研究成果基础上,对直接推进技术中的膜界面探测和连续钻进取样技术在污染场地调查中的功能和应用进行了论述,并在某有机污染场地调查中进行了试验研究。结果表明,利用膜界面探测技术首先半定量获取场地污染物的分布特征及范围,然后以此为指导采用直推式钻机钻进获取代表性样品,并进行实验室测试分析,可以快速、精确地刻画有机污染场地的污染物种类、浓度与分布范围,为后期采样计划和调查提供重要依据。

高速DSP图像处理系统的模拟视频输入接口设计

根据以TMS32 0C6 2 0 1为中心的高速DSP图像处理系统的要求 ,设计了由高速模拟视频前端 (AFE)和I2 C总线单片机所构成的模拟视频输入接口电路 ,分析其工作原理 ,探讨了与系统编程有关的几个重要问题。经实际应用表明 ,该接口电路构成简单、功能强、智能化程度高 ,且引入的系统噪声较小 ,从而为后级的视频数字滤波提供了较好的数据源。