Application of an integrated approach MissionTo the left of the resource diagram Prompts

Create an image of different types of organizations clustered around a business initiative in the middle

make a 3D infographic that illustrates software integration, with the writing: “architecture”, “components” and “data”, with a high-tech design. Show the software in the form of a HOLOGRAPHIC cube in the center with program codes. Around it, insert computers, screens, servers, server clouds and computer chips.

make a 3D image illustrating software integration, with the writing: “architecture”, “components” and “data”, with a high-tech design. Show the software in the form of a HOLOGRAPHIC cube in the center with program codes. Around it, insert computers, screens, servers, server clouds and computer chips.

make a 3D image illustrating software integration, with the writing: “architecture”, “components” and “data”, with a high-tech design. Show the software in the form of a HOLOGRAPHIC cube in the center with program codes. Around it, insert computers, screens, servers, server clouds and computer chips.

make a futuristic 3D infographic that illustrates software integration through elements: “architecture”, “components” and “data”, with a high-tech design. Show the software in the shape of a HOLOGRAPHIC cube in the center with program codes

Currently client is struggling with the current process where they need to manually manage the excel sheets, reporting process and tools not situated in one application. There is No clear visibility of resource allocation, reporting, budget, collaboration, reporting, project management, task management, time consuming. we came up with the proposed solution to improve productivity by eliminating manual work and bringing all project-related processes into one unified PPM tool which will Include key features such as project and task management, resource allocation, budget tracking, reporting and team collaboration- all within a single platform and the tool will replace manual excel-based processes and disconnected tools currently in use. please create the system architecture diagram for proposed system

Realistic infographic A4 size (landscape), using the following data: Заголовок: "Стратегия ЕАБР 2022–2026" Напишите заголовок крупными буквами вверху страницы A4. Интеграционная роль (Интеграция): Нарисуйте иконку банка развития в центре страницы, например, большой стилизованный здание банка. Ниже иконки банка напишите "Уникальная роль банка развития." Инвестиции: Рядом с иконкой банка, нарисуйте круговую диаграмму, где каждый сектор будет представлять один из приоритетных направлений (инфраструктура, экология, энергетика, цифровая инфраструктура). Разделите диаграмму на секторы и подпишите их названиями. Под диаграммой укажите сумму инвестиций: "10,9 млрд долл. США." Инвестиционные мегапроекты (Мегапроекты): Рядом с диаграммой инвестиций, нарисуйте стрелку, идущую вправо и обозначающую "Европу ― Западный Китай". На конце стрелки нарисуйте иконку товаропроводящей сети и водно-энергетического комплекса. Рядом с иконками напишите стоимость инвестиций: "около 1,2 млрд долл. США." Активизация в странах миноритарных акционеров (Миноритарные акции): Ниже диаграммы инвестиций и мегапроектов, нарисуйте несколько маленьких флагов разных стран и проведите стрелки от каждого флага к банку. Под каждой стрелкой напишите "Стратегии для [название страны-участницы]" и сумму инвестиций: "500 млн долл. США." Развитие цифровых компетенций (Цифровые решения): Ниже предыдущих блоков, нарисуйте иконку компьютера и смартфона. Под иконками напишите "Поддержка цифрового развития стран-участниц" и "Реализация цифровых решений." Кадровая трансформация (Команда): Рядом с блоком цифровых решений, изобразите несколько человечков с креативными шляпами. Под изображением напишите "Формирование высококвалифицированных кадров" и "Специализация на межгосударственных проектах." Консолидация инвестиционных ресурсов (Консолидация): Ниже предыдущего блока, нарисуйте несколько больших долларовых знаков и проведите стрелки, указывающие на банк. Напишите "Организация финансирования и интеграция инвестиций" и "Мультипликативный эффект." Ресурсная база ЕАБР (Ресурсы): Рядом с предыдущим блоком, разместите круговую диаграмму, представляющую источники ресурсов (заимствования и акционерный капитал). Под диаграммой укажите цель кредитного рейтинга "А." Применение комплексного подхода (Миссия): Слева от диаграммы ресурсов, нарисуйте земной шар с стрелкой, указывающей на рыночную экономику и торгово-экономические связи. Под стрелкой напишите "Содействие рыночной экономике и торгово-экономическим связям" и "Уникальная интеграционная роль." Цель трансформации (Цель): Справа от диаграммы ресурсов, напишите "Обновленная стратегия ЕАБР к 2026 году."

Currently client is struggling with the current process where they need to manually manage the excel sheets, reporting process and tools not situated in one application. No clear visibility of resource allocation, reporting, budget, collaboration, reporting, project management, task management, time consuming. we came up with the proposed solution to improve productivity by eliminating manual work and bringing all project-related processes into one unified PPM tool which will Include key features such as project and task management, resource allocation, budget tracking, reporting and team collaboration- all within a single platform and the tool will replace manual excel-based processes and disconnected tools currently in use. please create the system architecture diagram for proposed system

Create a BioRender-style, publication-ready vector infographic titled “研究内容框架图” for a grant proposal. Use clean flat BioRender vectors, thick outlines, minimal shadows, consistent spacing, and a readable sans-serif font (Microsoft YaHei). Use a 16:10 landscape canvas (taller than 16:9). All text inside boxes must be Chinese exactly as specified. Do not include any mathematical letters, symbols, or formulas. Layout The figure has two main sections: Section A (left/center): Research Content Framework (main flowchart) A large framed panel with a top-down or left-to-right flow of four major blocks (Step 1 → Step 2 → Step 3 → Step 4). Each block is a rounded rectangle with a short title plus 2–4 bullet points. Add clear arrows between steps. Add a small triangle badge near Step 3 showing the trade-off. Section B (right side): Three embedded mini-schematics aligned vertically, each framed, with titles: “闭环控制框架（流程图）” “耦合误差示意（维恩图）” “深度递归神经网络示意（时间展开）” Use thin dashed connectors from the main Step 1–3 blocks to the corresponding mini-schematics to show correspondence. Icons (flat, minimal) Multi-agent network graph (nodes + edges), drones and mobile robots, wireless signal, clock/bell for event-triggering, sample-and-hold icon, neural network/RNN icon, Lyapunov/stability icon, and a balance scale icon (performance vs communication vs energy). Keep icons minimal and consistent. Chinese text to place in boxes (exact) Title (top center) “学习辨识—事件触发耦合下非线性多智能体系统分布式一致性控制与收敛性/有界性分析：研究内容框架图” Section A: Main research content framework (4 steps) Step 1 (Block 1) Title: “一致性误差机理刻画” Bullets: “建立统一闭环误差建模框架” “刻画学习误差、触发保持误差与拓扑耦合误差的交叉作用” “解释收敛退化、触发频繁与性能下降的成因” “覆盖无领导一致、领导跟随一致与协同跟踪场景” Step 2 (Block 2) Title: “低保守收敛性与有界性分析” Bullets: “显式利用触发区间信息构造分析工具” “建立收敛性与有界性判据并降低保守性” “推导误差上界、无有限时间无限触发条件与触发间隔下界” “刻画触发间隔与拓扑、触发参数、辨识精度的定量关系” Step 3 (Block 3) Title: “协同设计与权衡机制” Bullets: “协同设计学习辨识器、动态事件触发与分布式控制协议” “保证学习参数与内部递归状态有界” “揭示学习率、触发参数、拓扑特征与一致性性能的定量关系” “建立一致性性能—通信次数—能耗开销的可计算权衡” Add-on icon near Step 3: A small triangular trade-off badge with vertex labels (Chinese): “一致性性能 / 通信次数 / 能耗开销” Caption next to triangle: “可计算权衡” Step 4 (Block 4) Title: “仿真分析与实验验证” Bullets: “搭建含未知非线性、扰动与通信约束的仿真平台” “对比不同触发规则、拓扑与学习精度下的性能与通信开销” “在多无人机与多机器人平台开展验证” “形成可推广的低通信、高可靠、可验证方法” Section B: Three mini-schematics (right side) Mini-panel 1: “闭环控制框架（流程图）” Draw a left-to-right flowchart with rounded blocks and arrows: Blocks (in order, Chinese text exact): “非线性多智能体系统” → “局部/邻域信息获取” → “一致性误差计算” → “学习辨识器（深度递归神经网络）” → “分布式控制器” → “动态事件触发器” → “网络传输与采样保持” → Back arrow to “非线性多智能体系统” Add two dashed feedback arrows from “一致性误差计算” to: “学习辨识器（深度递归神经网络）” (label: “误差驱动更新”) “动态事件触发器” (label: “误差驱动更新”) Add small notes: Under “动态事件触发器”: “按需通信/按需更新” Near “网络传输与采样保持”: “触发保持误差” Add a small timeline icon with ticks labeled in Chinese: “触发时刻…下一次触发时刻” and label “触发间隔”. Mini-panel 2: “耦合误差示意（维恩图）” Draw a three-circle Venn diagram with semi-transparent circles: Circle labels (Chinese): “学习辨识误差” (with RNN icon) “触发保持误差” (with clock + sample-and-hold icon) “拓扑耦合误差” (with network graph icon) Pairwise overlap labels: “学习更新×非均匀更新” “异步通信×拓扑传播” “分布式辨识×邻域耦合” Center overlap (bold): “耦合项集合” Under it: “影响一致性误差演化” Arrow from center to a right-side box titled “结果表征” with bullets: “收敛退化（渐近→最终有界）” “触发频繁/触发间隔变小” “稳态误差界增大/性能下降” Mini-panel 3: “深度递归神经网络示意（时间展开）” Draw a time-unrolled recurrent network schematic along a horizontal timeline labeled in Chinese: “上一时刻 → 当前时刻 → 下一时刻” At each time slice, show stacked recurrent blocks: Input label: “本体状态与邻域信息” → Middle label: “递归记忆状态” → Output label: “未知非线性与不确定项的在线辨识输出” Connect time slices with arrows labeled: “共享参数” Add a side arrow from “一致性误差” into a small box: “参数更新（投影/正则化/学习率调度）” Then arrow into: “学习参数更新” Style constraints BioRender clean scientific infographic, no photorealism, no clutter, high readability. Strict rule: do not include any math symbols, letters, equations, or subscripts. Negative prompt: Avoid photorealistic style, avoid dense paragraphs, avoid handwritten fonts, avoid low resolution, avoid formulas, avoid math letters.

place both models together

Create a BioRender-style, publication-ready vector infographic titled “研究内容框架图” for a grant proposal. Use clean flat BioRender vectors, thick outlines, minimal shadows, consistent spacing, and a readable sans-serif font (Microsoft YaHei). Use a 16:10 landscape canvas (taller than 16:9). All text inside boxes must be Chinese exactly as specified. Do not include any mathematical letters, symbols, or formulas. Layout The figure has two main sections: Section A (left/center): Research Content Framework (main flowchart) A large framed panel with a top-down or left-to-right flow of four major blocks (Step 1 → Step 2 → Step 3 → Step 4). Each block is a rounded rectangle with a short title plus 2–4 bullet points. Add clear arrows between steps. Add a small triangle badge near Step 3 showing the trade-off. Section B (right side): Three embedded mini-schematics aligned vertically, each framed, with titles: “闭环控制框架（流程图）” “耦合误差示意（维恩图）” “深度递归神经网络示意（时间展开）” Use thin dashed connectors from the main Step 1–3 blocks to the corresponding mini-schematics to show correspondence. Icons (flat, minimal) Multi-agent network graph (nodes + edges), drones and mobile robots, wireless signal, clock/bell for event-triggering, sample-and-hold icon, neural network/RNN icon, Lyapunov/stability icon, and a balance scale icon (performance vs communication vs energy). Keep icons minimal and consistent. Chinese text to place in boxes (exact) Title (top center) “学习辨识—事件触发耦合下非线性多智能体系统分布式一致性控制与收敛性/有界性分析：研究内容框架图” Section A: Main research content framework (4 steps) Step 1 (Block 1) Title: “一致性误差机理刻画” Bullets: “建立统一闭环误差建模框架” “刻画学习误差、触发保持误差与拓扑耦合误差的交叉作用” “解释收敛退化、触发频繁与性能下降的成因” “覆盖无领导一致、领导跟随一致与协同跟踪场景” Step 2 (Block 2) Title: “低保守收敛性与有界性分析” Bullets: “显式利用触发区间信息构造分析工具” “建立收敛性与有界性判据并降低保守性” “推导误差上界、无有限时间无限触发条件与触发间隔下界” “刻画触发间隔与拓扑、触发参数、辨识精度的定量关系” Step 3 (Block 3) Title: “协同设计与权衡机制” Bullets: “协同设计学习辨识器、动态事件触发与分布式控制协议” “保证学习参数与内部递归状态有界” “揭示学习率、触发参数、拓扑特征与一致性性能的定量关系” “建立一致性性能—通信次数—能耗开销的可计算权衡” Add-on icon near Step 3: A small triangular trade-off badge with vertex labels (Chinese): “一致性性能 / 通信次数 / 能耗开销” Caption next to triangle: “可计算权衡” Step 4 (Block 4) Title: “仿真分析与实验验证” Bullets: “搭建含未知非线性、扰动与通信约束的仿真平台” “对比不同触发规则、拓扑与学习精度下的性能与通信开销” “在多无人机与多机器人平台开展验证” “形成可推广的低通信、高可靠、可验证方法” Section B: Three mini-schematics (right side) Mini-panel 1: “闭环控制框架（流程图）” Draw a left-to-right flowchart with rounded blocks and arrows: Blocks (in order, Chinese text exact): “非线性多智能体系统” → “局部/邻域信息获取” → “一致性误差计算” → “学习辨识器（深度递归神经网络）” → “分布式控制器” → “动态事件触发器” → “网络传输与采样保持” → Back arrow to “非线性多智能体系统” Add two dashed feedback arrows from “一致性误差计算” to: “学习辨识器（深度递归神经网络）” (label: “误差驱动更新”) “动态事件触发器” (label: “误差驱动更新”) Add small notes: Under “动态事件触发器”: “按需通信/按需更新” Near “网络传输与采样保持”: “触发保持误差” Add a small timeline icon with ticks labeled in Chinese: “触发时刻…下一次触发时刻” and label “触发间隔”. Mini-panel 2: “耦合误差示意（维恩图）” Draw a three-circle Venn diagram with semi-transparent circles: Circle labels (Chinese): “学习辨识误差” (with RNN icon) “触发保持误差” (with clock + sample-and-hold icon) “拓扑耦合误差” (with network graph icon) Pairwise overlap labels: “学习更新×非均匀更新” “异步通信×拓扑传播” “分布式辨识×邻域耦合” Center overlap (bold): “耦合项集合” Under it: “影响一致性误差演化” Arrow from center to a right-side box titled “结果表征” with bullets: “收敛退化（渐近→最终有界）” “触发频繁/触发间隔变小” “稳态误差界增大/性能下降” Mini-panel 3: “深度递归神经网络示意（时间展开）” Draw a time-unrolled recurrent network schematic along a horizontal timeline labeled in Chinese: “上一时刻 → 当前时刻 → 下一时刻” At each time slice, show stacked recurrent blocks: Input label: “本体状态与邻域信息” → Middle label: “递归记忆状态” → Output label: “未知非线性与不确定项的在线辨识输出” Connect time slices with arrows labeled: “共享参数” Add a side arrow from “一致性误差” into a small box: “参数更新（投影/正则化/学习率调度）” Then arrow into: “学习参数更新” Style constraints BioRender clean scientific infographic, no photorealism, no clutter, high readability. Strict rule: do not include any math symbols, letters, equations, or subscripts. Negative prompt: Avoid photorealistic style, avoid dense paragraphs, avoid handwritten fonts, avoid low resolution, avoid formulas, avoid math letters.

spoke and wheel with the center word "Program" and the outer words "Implementation", "Platform", etc.

make a 3D image that illustrates software integration through elements: “architecture”, “components” and “data”, with a high-tech design. Show the software in the form of a HOLOGRAPHIC cube in the center with program codes. Around it, insert computers, screens, servers, server clouds and computer chips.

together

Diagram illustration, symmetrical, flat icon design

Create a BioRender-style vector infographic. Place the panel header “研究目标” as a small caption in the upper-left corner (not a large title). Set its font size to ~80% of the main box titles, use regular weight (not bold), and keep it visually subtle. Use a clean professional layout, flat colors, thick outlines, minimal shadows, and consistent sans-serif font (Microsoft YaHei). Canvas: 16:9 or 16:10 landscape. The figure should be non-technical (no equations), focusing on goals hierarchy. All text inside boxes must be Chinese exactly as provided. Layout Split the figure into two parts: Left Part (Overall Goals Pyramid): Draw a 3-layer stacked pyramid (or three stacked rounded rectangles) labeled from top to bottom: “理论目标”, “方法目标”, “应用目标”. Use subtle distinct colors for each layer. Add a small left-side label “总体目标” above the pyramid. Right Part (Three Specific Objectives Cards): Place three numbered rounded-rectangle cards vertically aligned (G1, G2, G3). Each card contains the specific objective text. Draw thin arrows from each card to the related pyramid layer(s): G1 arrows to “理论目标” (primary) and slightly to “方法目标” (secondary) G2 arrows to “方法目标” (primary) and slightly to “理论目标” (secondary) G3 arrows to “应用目标” (primary) and slightly to “方法目标” (secondary) Bottom Bar (One-line Summary): Add a wide rounded rectangle at the bottom spanning the width, labeled “预期形成：低通信、高可靠、可验证的一致性控制理论与方法体系”. Icons (small, minimal, optional) Next to “理论目标”: a Lyapunov/analysis icon (V(x)) Next to “方法目标”: a neural network + event-trigger clock icon Next to “应用目标”: drone + robot icons Next to bottom bar: a balance scale icon labeled “性能—通信—能耗” Chinese text to place (exact) Overall Goals (left pyramid): Top layer title: “理论目标” Text: “建立一致性误差动力学描述与统一的收敛/有界性分析框架；给出误差判据、误差上界、无Zeno与IET下界等可验证结论。” Middle layer title: “方法目标” Text: “提出以DRNN为核心的学习辨识器、动态事件触发机制与分布式控制协议协同设计方法；揭示触发参数、拓扑、辨识误差与一致性性能的定性—定量关系；建立‘一致性性能—通信资源与能耗开销’权衡机制。” Bottom layer title: “应用目标” Text: “依托多无人机与多机器人平台开展仿真与实验验证；形成可推广的低通信、高可靠、可验证协同控制方法；服务无人系统集群、网络化制造单元及分布式能源等场景。” Right cards (specific objectives): Card 1 header: “具体目标1（G1）” Body: “构造显式利用触发区间信息的looped-functional型Lyapunov分析工具，降低收敛性与有界性结论的保守性；推导误差上界、无Zeno条件与IET下界；刻画IET与拓扑结构、触发参数及系统状态之间的定性—定量关系。” Card 2 header: “具体目标2（G2）” Body: “建立基于DRNN学习辨识的分布式事件触发一致性控制框架；研究学习误差、触发误差与拓扑耦合误差对闭环性能的影响；设计权值更新律与触发机制，实现对未知非线性/不确定项的在线补偿并提升鲁棒性。” Card 3 header: “具体目标3（G3）” Body: “面向模型信息不完备与参数不确定等情形，研究模型弱依赖的学习辨识–事件触发一致性控制方法；给出一致性误差收敛性与有界性条件，以及DRNN权值与内部递归状态的有界性结论；提升方法的工程可实施性与适用范围。” Bottom bar text: “预期形成：低通信、高可靠、可验证的一致性控制理论与方法体系” Negative prompt Avoid photorealism, avoid dense paragraphs, avoid tiny illegible text, avoid complex mathematical derivations, avoid cluttered decorative elements.

company business process management in a drawing as a schema without text

place both together

Mix the images, in the middle an red arrow on right direction

Mix the images, in the middle an red arrow on right direction

a hand made business process model

Create a BioRender-style vector infographic. Place the panel header “研究目标” as a small caption in the upper-left corner (not a large title). Set its font size to ~80% of the main box titles, use regular weight (not bold), and keep it visually subtle. Use a clean professional layout, flat colors, thick outlines, minimal shadows, and consistent sans-serif font (Microsoft YaHei). Canvas: 16:9 or 16:10 landscape. The figure should be non-technical (no equations), focusing on goals hierarchy. All text inside boxes must be Chinese exactly as provided. Layout Split the figure into two parts: Left Part (Overall Goals Pyramid): Draw a 3-layer stacked pyramid (or three stacked rounded rectangles) labeled from top to bottom: “理论目标”, “方法目标”, “应用目标”. Use subtle distinct colors for each layer. Add a small left-side label “总体目标” above the pyramid. Right Part (Three Specific Objectives Cards): Place three numbered rounded-rectangle cards vertically aligned (G1, G2, G3). Each card contains the specific objective text. Draw thin arrows from each card to the related pyramid layer(s): G1 arrows to “理论目标” (primary) and slightly to “方法目标” (secondary) G2 arrows to “方法目标” (primary) and slightly to “理论目标” (secondary) G3 arrows to “应用目标” (primary) and slightly to “方法目标” (secondary) Bottom Bar (One-line Summary): Add a wide rounded rectangle at the bottom spanning the width, labeled “预期形成：低通信、高可靠、可验证的一致性控制理论与方法体系”. Icons (small, minimal, optional) Next to “理论目标”: a Lyapunov/analysis icon (V(x)) Next to “方法目标”: a neural network + event-trigger clock icon Next to “应用目标”: drone + robot icons Next to bottom bar: a balance scale icon labeled “性能—通信—能耗” Chinese text to place (exact) Overall Goals (left pyramid): Top layer title: “理论目标” Text: “建立一致性误差动力学描述与统一的收敛/有界性分析框架；给出误差判据、误差上界、无Zeno与IET下界等可验证结论。” Middle layer title: “方法目标” Text: “提出以DRNN为核心的学习辨识器、动态事件触发机制与分布式控制协议协同设计方法；揭示触发参数、拓扑、辨识误差与一致性性能的定性—定量关系；建立‘一致性性能—通信资源与能耗开销’权衡机制。” Bottom layer title: “应用目标” Text: “依托多无人机与多机器人平台开展仿真与实验验证；形成可推广的低通信、高可靠、可验证协同控制方法；服务无人系统集群、网络化制造单元及分布式能源等场景。” Right cards (specific objectives): Card 1 header: “具体目标1（G1）” Body: “构造显式利用触发区间信息的looped-functional型Lyapunov分析工具，降低收敛性与有界性结论的保守性；推导误差上界、无Zeno条件与IET下界；刻画IET与拓扑结构、触发参数及系统状态之间的定性—定量关系。” Card 2 header: “具体目标2（G2）” Body: “建立基于DRNN学习辨识的分布式事件触发一致性控制框架；研究学习误差、触发误差与拓扑耦合误差对闭环性能的影响；设计权值更新律与触发机制，实现对未知非线性/不确定项的在线补偿并提升鲁棒性。” Card 3 header: “具体目标3（G3）” Body: “面向模型信息不完备与参数不确定等情形，研究模型弱依赖的学习辨识–事件触发一致性控制方法；给出一致性误差收敛性与有界性条件，以及DRNN权值与内部递归状态的有界性结论；提升方法的工程可实施性与适用范围。” Bottom bar text: “预期形成：低通信、高可靠、可验证的一致性控制理论与方法体系” Negative prompt Avoid photorealism, avoid dense paragraphs, avoid tiny illegible text, avoid complex mathematical derivations, avoid cluttered decorative elements.

A circular diagram illustrating 'Etki Yatırımı' with three distinct sections. The first section is orange, labeled 'Sosyal Etki,' and features a building icon. The second section is green, labeled 'Çevresel Etki,' and includes a leaf icon. The third section is blue, labeled 'Finansal Etki,' and has a dollar icon. At the center of the diagram is the bold text 'Etki Yatırımı' in Turkish. The overall design is modern, clean, professional, and visually balanced, suitable for educational and professional presentations.

place both together