Evaluating and Addressing Interoperability Constraints in Health Information Systems for Enhanced Healthcare Delivery in Zimbabwe

Interoperability constraints in health information systems pose significant challenges to the seamless exchange and utilization of health data, hindering effective healthcare delivery. This paper aims to evaluate and address these constraints to enhance healthcare delivery. The study examines the current state of interoperability in health information systems, identifies the key constraints, and explores their impact on healthcare outcomes. Various approaches and strategies for addressing interoperability constraints are discussed, including the adoption of standardized data formats, implementation of interoperability frameworks, and establishment of robust data governance mechanisms. Furthermore, the study highlights the importance of stakeholder collaboration, policy development, and technical advancements in achieving enhanced interoperability. The findings emphasize the need for a comprehensive evaluation of interoperability constraints and the implementation of targeted interventions to promote seamless data exchange, improve care coordination, and enhance patient outcomes in healthcare settings.

High-resolution Remote Sensing Image Semi-global Matching Method Considering Geometric Constraints of Connection Points and Image Texture Information

Dense matching of remote sensing images is a key step in the generation of accurate digital surface models.The semi-global matching algorithm comprehensively considers the advantages and disadvantages of local matching and global matching in terms of matching effect and computational efficiency,so it is widely used in close-range,aerial and satellite image matching.Based on the analysis of the original semi-global matching algorithm,this paper proposes a semi-global high-resolution remote sensing image that takes into account the geometric constraints of the connection points and the image texture information based on a large amount of high-resolution remote sensing image data and the characteristics of clear image texture.123123The method includes 4 parts:①Precise orientation.Aiming at the system error in the image orientation model,the system error of the rational function model is compensated by the geometric constraint relationship of the connecting points between the images,and the sub-pixel positioning accuracy is obtained;②Epipolar image generation.After the original image is divided into blocks,the epipolar image is generated based on the projection trajectory method;③Image dense matching.In order to reduce the size of the cost space and calculation time,the image is pyramided and then semi-globally matched layer by layer.In the matching process,the disparity map expansion and erosion algorithm that takes into account the image texture information is introduced to restrict the disparity search range and better retain the edge characteristics of the ground objects;④Generate DSM.In order to test the matching effect,the weighted median filter algorithm is used to filter the disparity map,and the DSM is obtained based on the principle of forward intersection.Finally,the paper uses the matching results of WordView3 and Ziyuan No.3 stereo image to verify the effectiveness of this method.

High-resolution Remote Sensing Image Semi-global Matching Method Considering Geometric Constraints of Connection Points and Image Texture Information

Dense matching of remote sensing images is a key step in the generation of accurate digital surface models.The semi-global matching algorithm comprehensively considers the advantages and disadvantages of local matching and global matching in terms of matching effect and computational efficiency,so it is widely used in close-range,aerial and satellite image matching.Based on the analysis of the original semi-global matching algorithm,this paper proposes a semi-global high-resolution remote sensing image that takes into account the geometric constraints of the connection points and the image texture information based on the large amount of high-resolution remote sensing image data and the characteristics of clear image texture.The method includes 4 parts:(1)Precise orientation.Aiming at the system error in the image orientation model,the system error of the rational function model is compensated by the geometric constraint relationship of the connecting points between the images,and the sub-pixel positioning accuracy is obtained;(2)Epipolar image generation.After the original image is divided into blocks,the epipolar image is generated based on the projection trajectory method;(3)Image dense matching.In order to reduce the size of the cost space and calculation time,the image is pyramided and then semi-globally matched layer by layer.In the matching process,the disparity map expansion and erosion algorithm that takes into account the image texture information is introduced to restrict the disparity search range and better retain the edge characteristics of the ground objects;(4)Generate DSM.In order to test the matching effect,the weighted median filter algorithm is used to filter the disparity map,and the DSM is obtained based on the principle of forward intersection.Finally,the paper uses the matching results of WordView3 and Ziyuan No.3 stereo image to verify the effectiveness of this method.

Constraints of Women Farmer’s Access to Information and Communication Technologies (ICTs) for Agricultural Information in Oyo State, Nigeria

The study investigated constraints of women farmers access to ICTs for agricultural information in Oyo State.A total of 120 respondents were sampled.Data were retrieved using interview schedule and were analysed using descriptive and inferential statistics.Statistics reveal respondents average age,average household size and average monthly income as x=45.8,x=10.6 and x=₦7,800.34 respectively,majority(86.7%)were married,58.3%representing respondents with primary education.Mobile phone(x=0.98)was the most available among the respondents while poor ICTs infrastructure(x=1.55)and difficulty in the utilization of ICTs gadgets(x=1.62)ranked highest as constraints access to ICTs for agricultural information.Significant relationship existed between respondents average monthly income(r=0.492,p=0.000),educational level(χ^(2)=4.726,p=0.021)and the constraints access to ICTs for agricultural information.Scaling up the ICTs infrastructure base around farming clusters and capacity building like training on ICTs to access agricultural information retrieval is advocated for women farmers.

Flight parameter calculation method of multi-projectiles using temporal and spatial information constraint

The dynamic parameters of multiple projectiles that are fired using multi-barrel weapons in highfrequency continuous firing modes are important indicators to measure the performance of these weapons.The characteristics of multiple projectiles are high randomness and large numbers launched in a short period of time,making it very difficult to obtain the real dispersion parameters of the projectiles due to the occlusion or coincidence of multiple projectiles.Using six intersecting-screen testing system,in this paper,we propose an association recognition and matching algorithm of multiple projectiles using a temporal and spatial information constraint mechanism.We extract the output signal from each detection screen and then use the wavelet transform to process the output signal.We present a method to identify and extract the time values on which the projectiles pass through the detection screens using the wavelet transform modulus maximum theory.We then use the correlation of the output signals of three parallel detection screens to establish a correlation coefficient recognition constraint function for the multiple projectiles.Based on the premise of linear projectile motion,we establish a temporal and spatial constraint matching model using the projectile’s position coordinates in each detection screen and the projectile’s time constraints within the multiple intersecting-screen geometry.We then determine the time values of the multiple projectiles in each detection screen using an iterative search cycle registration,and finally obtain the flight parameters for the multiple projectiles in the presence of uncertainty.The proposed method and algorithm were verified experimentally and can solve the problem of uncertainty in projectiles flight parameter under different multiple projectile firing states.

Optimization of Supplier Switching with Asymmetric Information

The buyer-supplier relationship plays a great role in most economic systems. The buying firm usually tries to find a new supplier who provides products with satisfying quality and lower price. A broad branch of literature deals with the development of buyer-supplier relationships, but limited research is on the circumstances under which a buyer should terminate such a relationship and switch to a new supplier. In this paper, the incentive compatibility constraint (IC) which induces the entrant supplier to report his true cost is considered, and the participation constraint (PC) which ensures the entrant supplier to get at least reservation profit is taken into account. Then the supplier switching model is set up to minimize the buying firm's total procurement cost which includes the transfer payment to the incumbent supplier, the payment to the entrant supplier and the switching cost, and the buying firm's switching cost is considered as a function of the switching quantity. With the theoretical analysis of IC, PC and the proposed model, the optimal supplier switching strategy can be obtained. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the switching strategy.

A new method to solve the Reynolds equation including mass-conserving cavitation by physics informed neural networks(PINNs)with both soft and hard constraints

In this work,a new method to solve the Reynolds equation including mass-conserving cavitation by using the physics informed neural networks(PINNs)is proposed.The complementarity relationship between the pressure and the void fraction is used.There are several difficulties in problem solving,and the solutions are provided.Firstly,the difficulty for considering the pressure inequality constraint by PINNs is solved by transferring it into one equality constraint without introducing error.While the void fraction inequality constraint is considered by using the hard constraint with the max-min function.Secondly,to avoid the fluctuation of the boundary value problems,the hard constraint method is also utilized to apply the boundary pressure values and the corresponding functions are provided.Lastly,for avoiding the trivial solution the limitation for the mean value of the void fraction is applied.The results are validated against existing data,and both the incompressible and compressible lubricant are considered.Good agreement can be found for both the domain and domain boundaries.

Air combat decision-making of multiple UCAVs based on constraint strategy games

Game theory can be applied to the air combat decision-making problem of multiple unmanned combat air vehicles(UCAVs).However,it is difficult to have satisfactory decision-making results completely relying on air combat situation information,because there is a lot of time-sensitive information in a complex air combat environment.In this paper,a constraint strategy game approach is developed to generate intelligent decision-making for multiple UCAVs in complex air combat environment with air combat situation information and time-sensitive information.Initially,a constraint strategy game is employed to model attack-defense decision-making problem in complex air combat environment.Then,an algorithm is proposed for solving the constraint strategy game based on linear programming and linear inequality(CSG-LL).Finally,an example is given to illustrate the effectiveness of the proposed approach.

减税降费对企业投资效率的影响研究

减税降费政策是促进企业发展、提高市场活力的重要举措,对提高企业投资效率、推进供给侧改革具有重要意义。本文通过我国沪深A股上市公司2012-2020年的数据,对减税降费对企业投资效率的影响进行研究。研究结果表明:减税降费能够有效提升企业的投资效率;机制检验表明,减税降费可以通过缓解融资约束,减少企业投资不足的行为,通过降低信息不对称程度抑制过度投资的行为。通过进一步研究发现,减税降费对提高民营企业、低自由现金流企业投资效率的效果更为显著;政策对不同成长机会的企业影响效应有所区别;政策对市场化程度较高地区的企业投资不足的作用更加明显,而对市场化程度较低地区的企业过度投资的作用更为明显。本文还提出了推进减税降费政策,从而提高企业投资效率、促进企业高质量发展的政策建议。

数字普惠金融发展缓解融资约束研究——基于涉农企业的实证分析

伴随数字经济的蓬勃发展,数字普惠金融为缓解涉农企业融资约束提供了新的可能和路径。将北京大学数字普惠金融2011—2020年市级数据与中国涉农企业数据进行匹配,实证检验数字普惠金融发展对涉农企业融资约束的影响。研究表明:数字普惠金融发展可以显著缓解涉农企业融资约束,该结论在进行多种稳健性检验后依然成立。其中,数字普惠金融覆盖广度的影响效果优于使用深度和数字化程度;数字普惠金融发展能够通过降低融资成本、提高信息透明度等机制缓解涉农企业融资约束;数字普惠金融发展对非国有企业融资约束的缓解作用相对于国有企业更大,对加工服务业企业融资约束的缓解作用相对于养殖种植业企业更大。传统金融发展越好的地区,数字普惠金融发展对企业融资约束的缓解作用更强。总体而言,在缓解涉农企业融资约束异质性方面,数字普惠金融的“逐利性”大于其“普惠性”。文章为乡村振兴背景下解决涉农企业融资难题、助推农业经济发展提供理论参考和实践指引:第一,要继续推进数字普惠金融发展,为涉农企业提供数量众多、业态丰富的新型金融服务;第二,涉农企业要积极进行信息披露,减小与金融机构间的信息不对称程度,拓宽自身融资渠道;第三,要加大对落后地区和经营养殖种植业企业的扶持力度和资源倾斜,发挥数字普惠金融的应有之义。

以“数”谋“盈”:企业数字化转型对盈余持续性的影响研究

以2007-2021年沪深A股上市公司为研究样本,基于企业数字化转型的“治理效应”“信息效应”和“融资效应”,实证检验企业数字化转型对盈余持续性的影响及作用机制。研究发现,企业数字化转型可显著提高盈余持续性,其作用机制在于抑制真实盈余管理、提高信息透明度和缓解融资约束。从异质性视角来看,“底层技术运用”和“技术实践应用”均可显著提高盈余持续性;在非国有企业、成长性低的企业中,企业数字化转型对盈余持续性的影响更加显著。企业应该坚定实施数字化转型的信心,增强实施数字化转型的动力,以谋求持续稳定的收益。

复杂环境下基于自适应极线约束的AGV视觉SLAM算法

针对传统视觉同步定位与地图构建(SLAM)算法不能有效处理复杂环境中的动态及潜在动态目标而影响定位与建图性能的问题,提出一种基于Mask R-CNN神经网络以及ORB-SLAM3算法改进的视觉SLAM方法。针对动态目标,提出一种基于语义信息的运动一致性检验算法,使用自适应阈值的极线约束方法实现图像中动态特征点的精确剔除;针对潜在动态目标,提出一种改进的长期数据关联方法,通过增大关键帧选取密度及优化关键帧中的潜在动态目标信息,对算法的回环优化和地图融合过程进行改进,提高回环优化效果与地图复用性。在TUM数据集和真实场景中进行验证,实验结果表明与ORB-SLAM3算法相比,采用TUM数据集在低动态场景和高动态场景中的绝对轨迹均方根误差分别减小8.5%和65.6%;在真实场景下测试,所提算法的定位精度提高了62.5%。

数字金融赋能企业高质量发展的作用机制与实现路径

数字金融的快速发展对提升金融服务实体经济能力以及实现企业高质量发展都有着重要影响。以2013—2021年中国A股上市的实体企业为研究样本,通过构建地级市层面的数字金融发展指数以及企业层面的高质量发展指数,实证检验数字金融对企业高质量发展的作用机制与实现路径。研究发现,数字金融能够显著促进企业高质量发展,但这种促进作用在不同行业和不同区域存在一定差异。从作用机制看,数字金融的发展能够有效缓解信息不对称和融资约束等,并通过提升技术创新和企业效率等内部优化手段,显著促进实体企业高质量发展。从实现路径来看,目前数字金融推动企业高质量发展主要是通过企业创新发展、共享发展和协调发展这三个路径发挥作用,而绿色发展和开放发展路径的作用并未有效发挥。同时,有效的金融监管是数字金融赋能企业高质量发展路径实现的必要保障。因此,应加强对数字金融的政策支持,积极探索绿色发展和开放发展等潜在路径,充分发挥创新发展、共享发展和协调发展路径的积极作用,并以适度监管保障数字金融赋能企业高质量发展。

中国绿色信贷发展状况、基本特征与政策建议

绿色信贷市场是中国绿色金融体系中发展最早、规模最大的市场,在支持绿色领域融资、推动“双碳”目标实现的过程中将发挥举足轻重的作用。目前全球尚无绿色信贷的统一标准,国内外标准各有侧重。近年来中国的绿色信贷市场快速发展,其规模、增速及占总贷款的比重均持续攀升。从结构特征看,其资金主要投向绿色交通运输和清洁能源领域,参与机构从大型银行拓展到中小银行。从变化趋势看,其政策目标从号召引导过渡到制度规范,政策重点措施从限制性转变为鼓励性,产品类别从单一化发展到多样化,绿色信贷市场逐渐走向规范和完善。但是,当前中国绿色信贷市场在制度环境、激励约束、信息披露监管等方面仍存在一些缺陷。基于上述分析,提出促进中国绿色信贷市场发展的四点建议:促进绿色信贷制度的完善,加大政策激励与支持的力度,加快数据与信息披露体系建设,加强全流程的跟踪监管。

数字金融参与对农村居民创业决策的影响——基于CHFS2019数据的实证分析

农民创业为推进乡村振兴赋予了新动能,而数字金融为农民创业提供了契机。文章基于2019年中国家庭金融调查数据,采用Probit模型从微观视角分析了数字金融参与对农村居民创业决策的影响,并从信贷约束和信息约束两方面探究了数字金融参与影响农村居民创业决策的中间机制。研究结果显示,创业农村居民参与数字金融水平远远大于非创业农村居民;机制检验表明,数字金融参与通过缓解农村居民的信贷约束和增加信息可得性正向促进农村居民的创业决策;异质性结果表明,数字金融参与对东部地区、较高学历、身体状况健康的农村居民创业决策影响效果更大。鉴于此,提出通过普及农村居民的金融知识提升农村居民金融素养,加大中西部农村地区互联网基础设施建设,提高农村居民教育程度,为农村居民创业提供更加便捷可行的渠道。

地理知识图谱增强与多时空条件约束的轨迹预测

基于机器学习的轨迹预测方法通常依赖历史轨迹数据的数量和质量,而社交媒体签到数据更新频率低,形成的轨迹稀疏,在预测中易出现难学习、过拟合等问题。为突破低质量轨迹数据在预测任务中的限制,本文提出一种基于地理知识图谱增强与多时空约束条件建模的轨迹预测方法。将复杂异构的多源地理信息结构化为由若干三元组构成的地理知识图谱进行统一表达,并通过知识表示模型挖掘其中语义关联来增强轨迹序列的向量表征,同时采用具有多重时空约束条件的多头自注意力机制提取稀疏轨迹序列中的多重时空特征,从而提升轨迹预测精度。研究采用纽约市Foursquare社交媒体签到数据进行方法验证,试验结果表明:本文方法相较于其他表示学习方法和轨迹预测方法,在命中率和平均倒数排名两个评价指标上均有不同程度的提升,能够有效增强稀疏轨迹序列的表征,提取轨迹的多重时空特征,提高社交媒体用户签到轨迹的预测精度。

社会责任信息披露能否助力企业高质量发展--基于链式多重中介效应分析

基于信息不对称等理论,以我国2011—2021年沪深A股上市企业为研究对象,采用链式多重中介效应模型,探讨社会责任信息披露对企业高质量发展的作用机制。结果表明,社会责任信息披露可通过融资约束和绿色创新间接影响企业高质量发展,其并行、链式中介效应均表现为显著的促进效应;进一步通过异质性检验发现,社会责任信息披露对企业高质量发展的促进作用在重污染企业、民营企业、两职分离企业以及应规披露企业中更为显著;研究结果为社会责任信息披露是实现企业高质量发展的重要因素提供了证据,有助于增进对二者间作用关系的理解,丰富了企业高质量发展的路径研究。

融资约束、信息条件与企业绿色债务期限结构的选择

绿色融资期限的选择会直接影响绿色投资以及企业的财务稳定和可持续发展。本文从绿色项目投融资期限较长、风险较大且国内绿色项目融资中债务资金占比较大的事实出发,构建企业绿色债务融资三期模型,分析企业绿色债务期限决策与绿色资金市场和信息环境之间的密切关系,揭示绿色债务资金束紧和信息非对称对企业绿色债务期限结构选择的影响。研究发现,短期债务的再融资风险与长期债务成本水平是影响绿色融资期限决策的重要因素,企业绿色债务融资期限决策受到企业管理者权衡私人收益与损失的重要影响,企业绿色项目的信息不对称程度降低和融资约束缓解有助于企业绿色债务融资期限延长。企业绿色项目的自融规模、项目风险、内部激励、管理成本等因素变化也与企业绿色债务融资期限决策关系密切。据此,金融机构应加大绿色金融产品的创新力度,企业应着力改善绿色项目信息披露质量,政府应构建利于绿色金融发展的相关制度体系。

注册制改革与IPO公司投资效率

选取2019年7月22日至2021年12月31日注册制和核准制“共存”窗口期的首次公开募股(IPO)公司为样本,基于熵平衡匹配检验注册制改革对投资效率的影响。研究结果表明:注册制改革提高了IPO公司的投资效率,并通过缓解融资约束和提高信息披露质量提升投资效率;同时,对投资效率的提升效应在非国有企业、市场化程度较低地区的公司、外部监督较弱的公司中更显著。鉴于此,在注册制改革的进程中要强化信息披露质量监督,关注有较好投资机会公司的融资需求。

基于多重互信息约束的高表现力语音转换

随着语音转换在人机交互领域的广泛应用,对于获取高表现力语音的需求日益显著.当前语音转换主要通过解耦声学特征实现,侧重对内容和音色特征的解耦,很少考虑语音中混合的情感特性,导致转换音频情感表现力不足.为解决上述问题,本文提出一种基于多重互信息约束的高表现力语音转换模型(MMIC-EVC).在对内容和音色特征进行解耦的基础上,引入表现力模块分别对话语级韵律和节奏特征进行建模,以实现情感特性的传递;随后通过最小化各特征之间的多重互信息变分对数上界,约束各编码器专注于解耦对应的声学嵌入.在CSTR-VCTK和ESD语音数据集上的实验表明,本模型的转换音频语音自然度评分(MOS)达到3.78,梅尔倒谱失真为5.39 dB,最佳最差占比测试结果大幅领先于基线模型,MMIC-EVC能够有效解耦韵律和节奏特征,并实现高表现力语音转换,为人机交互带来更加出色和自然的用户体验.