Logical Image Acquisition and Analysis of Android Smartphones

Android smartphones largely dominate the smartphone market. For this reason, it is very important to examine these smartphones in terms of digital forensics since they are often used as evidence in trials. It is possible to acquire a physical or logical image of these devices. Acquiring physical and logical images has advantages and disadvantages compared to each other. Creating the logical image is done at the file system level. Analysis can be made on this logical image. Both logical image acquisition and analysis of the image can be done by software tools. In this study, the differences between logical image and physical image acquisition in Android smartphones, their advantages and disadvantages compared to each other, the difficulties that may be encountered in obtaining physical images, which type of image contributes to obtaining more useful and effective data, which one should be preferred for different conditions, and the benefits of having root authority are discussed. The practice of getting the logical image of the Android smartphones and making an analysis on the image is also included. Although root privileges are not required for logical image acquisition, it has been observed that very limited data will be obtained with the logical image created without root privileges. Nevertheless, logical image acquisition has advantages too against physical image acquisition.

Discuss on High Speed Data Acquisition and Signal Processing

In order to realize the high speed data acquisition and fast Fourier analysis, the paper put forward a kind of high speed data acquisition and analysis system based on FPGA, the system uses Cyclone series FPGA with high-speed A/D converter, and use the fast Fourier custom analysis nucleation of Altera company, using the standard TCP/IP protocol communication with PC, match up the master machine based on Matlab GUI analysis software. We experiment high speed data acquisition and fast Fourier analysis for a plurality of groups of high frequency analog signals, at the same time the results display on the computer. The experimental results validate the fast Fourier analysis theory, and has realized the low cost, high performance data acquisition and analysis of the complete system design.

A DATA ACQUISITION SYSTEM FOR ACCELERATOR MASS SPECTROMETRY

A single and dual parameter data acquisition, ion beam measurements and control system for accelerator mass spectrometry is described. The system hardware has been constructed with the advantage of the lower cost and higher reliability. It is provided with varieties of functions such as selecting acquisition mode carrying out the multiple display, analyzing data and especially viewing isometric spectrum at different directions. It can also be used for ordinary nuclear spectrum system.

MODEL MEASUREMENT AND ANALYSIS OF ROTOR BEARING SYSTEM OF OE-SPINNING

This paper describes a CAD compatible software which can conduct model measurementand analysis on a dedicated computer system.This system which can provide modal testing andanalysis capability is also demonstrated briefly.It addresses four main tasks:(1)modal testingand data acquisition,(2)data analysis and correlation,(3)output of modal analysis results,(4)predictions of modal parameters using Structural Dynamic Modification (SDM)software.

Preliminary build and application of a data analysis platform for coiled tubing steel strips

To solve the problems in the quality control and improvement of coiled tubing steel strips production, such as scattered and inefficient production data, difficult performance fluctuation factor analysis, complex multivariate statistical analysis, and low accuracy and difficulty in mechanical property prediction, an industrial data analysis platform for coiled tubing steel strips production has been preliminarily developed.As the premise and foundation of analysis, industrial data collection, storage, and utilization are realized by using multiple big data technologies.With Django as the agile development framework, data visualization and comprehensive analyses are achieved.The platform has functions including overview survey, stability analysis, comprehensive analysis(such as exploratory data analysis, correlation analysis, and multivariate statistics),precise steel strength prediction, and skin-passing process recommendation.The platform is helpful for production overviewing and prompt responding, laying a foundation for an in-depth understanding of product characteristics and improving product performance stability.

Integration system research and development for three-dimensional laser scanning information visualization in goaf

An integration processing system of three-dimensional laser scanning information visualization in goaf was developed. It is provided with multiple functions, such as laser scanning information management for goaf, cloud data de-noising optimization, construction, display and operation of three-dimensional model, model editing, profile generation, calculation of goaf volume and roof area, Boolean calculation among models and interaction with the third party soft ware. Concerning this system with a concise interface, plentiful data input/output interfaces, it is featured with high integration, simple and convenient operations of applications. According to practice, in addition to being well-adapted, this system is favorably reliable and stable.

Mergers and Acquisitions: An Efficiency Evaluation

This article sheds light on how synergies arise through mergers and acquisitions (M&A). Enterprises go through the process of Mergers and Acquisitions (M&A) with the goal of improving performance, increasing efficiency and obtaining business synergy. Prior literature suggests that synergies could arise due to taxes, market power or efficiency improvements. This study evaluates the efficiency of M&A in Brazil among publicly-traded companies. We used models with multiple objectives from Goal Programming and Data Envelopment Analysis (GPDEA), employing accounting indicators as input and output variables, and thus evaluated the emergence of synergy gains. These models allow us to analyze and classify the M&A according to the efficiency obtained in such processes. Some of the M&A cases analyzed were mistakenly considered efficient when used traditional models. And, as expected, the GPDEA was proved to be superior to classical models;however it was noticed that few of the cases investigated were proved to be effective. We presented a new application for multi-objective approach that can be used to assess mergers and acquisitions. The dualapplication of GPDEA provided a greater understanding of efficiency generation in synergy creation by means of M&A.

Empirical Study on the Measurement of the High-Tech Industry Efficiency in China--Based on the Data of China＇s 31 Provinces （Including Municipalities and Autonomous Regions）

To evaluate the relative effectiveness of the input and output of the high-tech industry in China＇s 31 provinces （including municipalities and autonomous regions）, DEA evaluation model was constructed using data envelopment analysis （DEA）, and DEA evaluation model was solved using Deap2.1 software, for the purpose of obtaining the DEA efficiency and the non-DEA efficiency in all the provinces （including municipalities and autonomous regions）. Then, the comprehensive efficiency, technical efficiency, scale efficiency, scale return, and projection analysis were analyzed. Finally, the provinces of the non-DEA efficiency are sorted according to three efficiencies, and also a goal of improvement is proposed for the purpose of expanding technology investment in the provinces of the DEA efficiency.

Improved Symbiotic Organism Search with Deep Learning for Industrial Fault Diagnosis

Developments in data storage and sensor technologies have allowed the cumulation of a large volume of data from industrial systems.Both structural and non-structural data of industrial systems are collected,which covers data formats of time-series,text,images,sound,etc.Several researchers discussed above were mostly qualitative,and ceratin techniques need expert guidance to conclude on the condition of gearboxes.But,in this study,an improved symbiotic organism search with deep learning enabled fault diagnosis(ISOSDL-FD)model for gearbox fault detection in industrial systems.The proposed ISOSDL-FD technique majorly concentrates on the identification and classification of faults in the gearbox data.In addition,a Fast kurtogram based time-frequency analysis can be used for revealing the energy present in the machinery signals in the time-frequency representation.Moreover,the deep bidirectional recurrent neural network(DBiRNN)is applied for fault detection and classification.At last,the ISOS approach was derived for optimal hyperparameter tuning of the DL method so that the classification performance will be improvised.To illustrate the improvised performance of the ISOSDL-FD algorithm,a comprehensive experimental analysis can be performed.The experimental results stated the betterment of the ISOSDLFD algorithm over current techniques.

The Study of the Operating Performance of Marine Industry in the Blue Economic Zone: An Empirical Analysis Based on DEA and Tobit Model

The marine industry plays an important role in promoting the development of the blue economic zone,and the study of the operating performance of marine industry is of important practical significance. Using DEA method,this article measures the operating performance of marine industry in the blue economic zone. On this basis,using Tobit model,it analyzes the factors influencing the operating performance of marine industry. The results show that the industries of high carbon emission performance are basically the industries of high energy consumption,high emission and high pollution; the level of economic development and the number of important technological achievements can both significantly increase the pure technical efficiency; the sustainable environmental carrying capacity and the number of employees are conducive to improving the technological progress index and overall efficiency; the level of social infrastructure plays a role in promoting the overall efficiency,but the role is not obvious.

面向工业互联网数据分析的机器学习工作流推荐方法

工业大数据具有多模态和强关联等特性,这给数据分析与应用带来了新的挑战。如何根据工业应用需求的特点实施有效的数据分析过程通常是一项非常复杂、耗时耗力的任务。针对该问题,提出一种面向工业互联网数据分析的机器学习工作流推荐方法。该方法以已有解决方案为起点,将其所使用的数据集和机器学习工作流作为推荐参考,基于Doc2vec模型与最大平均差异方法计算文本描述相似度与数据分布特征相似度,可根据当前数据分析任务需求,推荐合适的已有解决方案中的机器学习工作流。仿真实验说明了该方法的有效性。

汽车制造业绿色供应链管理对环境绩效的影响研究

从绿色供应链管理和大数据分析能力视角探讨制度压力对企业环境绩效的影响机理,揭示绿色供应链管理和大数据分析能力在企业环境绩效形成过程的作用。研究结果表明:制度压力对绿色供应链管理实施与大数据分析能力有显著影响;绿色供应链管理与大数据分析能力对企业环境绩效提升有显著影响;大数据分析能力对企业绿色供应链管理实施有显著影响;在制度压力对环境绩效的影响中,大数据分析能力与绿色供应链管理存在部分中介效应。研究结果能够为汽车制造企业重视大数据分析能力建设和绿色供应链管理实践,提高环境绩效提供一定的参考价值。

基于AIGC协同工业设计流程的气道廓清辅具设计研究与实践

目的设计领域引入蓬勃发展的AIGC技术以期提高效率,在此基础上结合大数据技术和双钻模型,以提高AIGC应用于复杂产品工业设计的质量。方法提出了一种AIGC协同的“1+2”钻工业设计流程模型,通过三次发散、三次收敛来提高AIGC协同工业设计的流程效率与方案质量。首先,在ChatGPT和Python大数据爬取辅助下发散需求问题,在Python高频词分析、竞品分析、专家评审下收敛设计目标;其次,运用Midjourney的Stop参数模糊生图进行创意发散,通过对项目人员问卷调查收敛设计方向;最后,联合使用DALL·E、StableDiffusion和Midjourney发散设计细节,通过焦点小组收敛以确定最终方案并建模渲染。结果实现全面、专业、准确的长期卧床老人气道廓清的需求分析,且辅具设计方案的在用户友好程度、造型美观度、技术可行性和功能可用性方面获得了设计与工程双方专业人员的认可。结论AIGC、大数据与传统工业设计方法相结合的“1+2”钻设计流程,能够通过人工控制AIGC的参考内容、处理AIGC的生成内容,以及阶段性专家评估有效地提升AIGC协同的工业设计方案质量,为规范化的AIGC协同工业设计流程提供思路。

计算机数据采集技术在智慧畜禽养殖场中的应用

随着计算机数据采集技术的不断成熟,畜禽养殖行业迎来了新的发展机遇。因为畜禽养殖直接关系到市场中肉蛋奶等动物源性食品的稳定供给,一直受到社会的广泛关注。与传统养殖模式相比,智慧畜禽养殖具有智能化的特点,能有效提升畜禽养殖效能,降低饲料成本,从而保障养殖场的经济效益。本文从计算机数据采集技术的角度对智慧畜禽养殖中的优势进行分析,并强调了计算机数据采集技术在智慧畜禽养殖场中的应用策略,力求借助更科学、更精确的控制措施不断提高饲养管理水平和养殖经济效益,有效助推畜禽养殖行业的转型升级。

基于xDeepFM模型的关键核心技术识别及竞争态势分析——以通信设备制造产业为例

[研究目的]基于“逆变”情景,通过对通信产业的关键核心技术进行识别,以探寻逆变动力源及其竞争态势演化。[研究方法]梳理关键核心技术的定义、特征及识别方法,选取诺基亚、爱立信、华为及中兴4家通信设备企业自1984年起在全球申请的百万条专利为样本,构建基于因子分解机的深度预测神经网络模型(xDeepFM),实现关键核心技术识别与竞争态势分析。[研究结论]基于xDeepFM构建的识别模型能够有效在浩繁的专利数据中完成关键核心技术识别。通过对识别后的关键核心技术进行主题分析,评估通信产业关键核心技术竞争态势,为识别关键核心技术特征、打赢关键核心技术攻坚战提供情报支持。

我国工业机器人领域技术热点及发展趋势分析——基于CiteSpace文献专利融合分析

工业机器人是国家现代化工业技术实力的重要体现,也是国际科技竞争的关键战略领域。获取相关的技术发展动态数据并进行深入分析对于及时识别该领域存在的挑战和机会,具有重要意义。以工业机器人领域的最新期刊文献以及专利数据为样本进行数据融合分析,综合运用文献计量方法以及可视化工具,构建我国工业机器人领域创新知识图谱从科学和技术多维度展开分析。研究表明,我国工业机器人领域研究和发展总体呈现快速增长趋势,但同时也存在研究合作规模较小、知识和技术转化率低等问题,未来通过加强跨地区交流、促进产学研合作、改善技术结构等策略不断推动该领域新的发展。

“双碳”背景下钢铁新产线选址的环境结合度评价——以中国宝武为例

为准确测度“双碳”(即碳达峰、碳中和的合称)背景下具体工业门类选址与环境体系的结合发展实效,通过研究钢铁新产线的选址取向及环境关切转变,提出新产线选址的环境结合度评价框架。通过数据包络分析(Data Envelopment Analysis,DEA)模型计算环境-经济效率,通过动态综合评价模型揭示时间序列上效率的变化特征,以构建一套钢铁新产线选址的环境结合度评价方法,进而对中国宝武钢铁集团部分生产基地开展实证分析。评价结果为上海宝山基地的环境结合度最高。研究表明:环境结合度是“双碳”背景下钢铁新产线向既有基地选址时主要的环境关切,而环境结合度的评价框架和评价方法可有效表征连续时间序列上既有基地与所在城市环境体系的互促共进态势,对大型钢企未来选址新产线具有一定指导作用。

基于多文本分析的中国战略性新兴产业态势分析与发展研究

发展战略性新兴产业对推动我国经济转型升级具有重大作用。文章从学术热度和技术热度出发,基于主题聚类和突变词分析研究我国战略性新兴产业的研究热点和研究趋势,基于专利情报分析研究专利量、法律状态、专利类型、申请人类型以及重要经济门类,特别是“超高价值专利”以及重要申请人,并分别进行四大经济区域、三大经济圈以及主要省份的多区域比较研究,还分析了相关专利运营情况,最后提出促进战略性新兴产业发展的详细建议。

纸张生产质量检测系统的数值模拟与工业部署

为实现针对纸张生产质量的实时监测,提出了一种基于特征选择方案的在线软测量系统。该系统搭载有纸张生产质量软测量模型。软测量模型以托辊瞬时流量、毛布排放泵出口流量、断尾纤维百分比等纸张生产实时数据为基础建立运行参数体系。为验证该模型的有效性,通过数值模拟的方式对模型精度进行测试,最后提出了整个系统的部署思路并以参数设置功能模块为例展示了该操作界面的设计效果。经试验研究发现,纸张生产质量检测系统各项精度测试指标较为理想,操作界面设计友好直观,具有一定的应用价值。

大数据背景下的冰雪运动产品服务平台App设计研究

随着大数据技术的蓬勃发展,冰雪运动行业也面临着新的机遇和挑战。大数据可以帮助冰雪运动企业更好地了解客户需求,优化产品和服务,提高运营效率。文章首先对大数据技术进行概述。其次对冰雪运动产品服务平台App进行了设计分析,提出了冰雪运动产品服务平台App设计的策略,最后赋予设计实践。以期为冰雪运动企业提供一个高效、便捷、智能的产品服务平台,帮助企业更好地服务客户,提高竞争力。