Said a window lock

在村庄中,两名农民被捆绑并送往庄园。另外两个喝醉的农民跟随着他们。不久,所需的所有马匹和货车都聚集在博古特查罗夫家的院子里。农民们匆忙地将主人的财物装上货车,而德龙,在玛丽亚公主的要求下从杂物间释放出来,正在院子里指挥男人们。一名高大的农民从女仆手中接过一个箱子,提醒其他人不要粗鲁对待,因为这东西很值钱。

About the village. The two peasants who were bound they took to the manor-house. The two drunken peasants followed them. Ay, now look at you! said one of them, addressing Karp. Do you suppose you can talk to the gentry like that? What were you thinking about? You are a fool, put in the other; a regular fool. Within two hours the horses and carts required were standing in the courtyard of the Bogutcharovo house.

 

The peasants were eagerly hurrying out and packing in the carts their owners' goods; and Dron, who had at Princess Marya's desire, been released from the lumber-room, where they had shut him up, was standing in the yard, giving directions to the men. Don't http://www.door-fitting.com/ pack it so carelessly, said one of the peasants, a tall man with a round, smiling face, taking a casket out of a housemaid's hands. It's worth money too, you may be sure.

 

Why, if you fling it down like that or put it under the cord, it will get scratched. I don't like to see things done so. Let everything be done honestly, according to rule, I say. There, like this, under the matting, and cover it up with hay; there, that's first-rate. Mercy on us, the books, the books, said another peasant, bringing out Prince Andrey's bookshelves. Mind you don't stumble! Ay, but it's heavy, lads; the books are stout and solid! Yes, they must have worked hard to write them! said a window lock

http://blog.oricon.co.jp/doorfitting/

http://rock.kg/node/337137

转载于:https://www.cnblogs.com/wt152/archive/2013/05/06/3062492.html

import threading import time from PyQt5 import QtWidgets, QtCore, QtGui import pyttsx3 import random class VoiceAssistant(QtCore.QObject): """语音响应模块 - 线程安全的语音播报类""" finished = QtCore.pyqtSignal() # 语音播报完成信号 error_occurred = QtCore.pyqtSignal(str) # 错误信号 def __init__(self, parent=None): super().__init__(parent) self.engine = None self.initialize_engine() self.lock = threading.Lock() self.speech_count = 0 self.max_speeches_before_restart = 50 # 每50次播报后重启引擎 # 多语言响应策略配置 self.response_strategies = { "welcome": { "zh": "欢迎{name}!", "en": "Welcome {name}!" }, "unknown": { "zh": "未识别到注册用户,请进行登记", "en": "Unknown user, please register" }, "low_confidence": { "zh": "识别置信度较低,请重新验证", "en": "Low confidence, please try again" } } def initialize_engine(self): """初始化语音引擎""" try: self.engine = pyttsx3.init() self.engine.setProperty('rate', 150) # 语速 (120-180为自然语速) self.engine.setProperty('volume', 0.9) # 音量 (0.0-1.0) # 设置中文语音(如果系统支持) voices = self.engine.getProperty('voices') if len(voices) > 1: self.engine.setProperty('voice', voices[1].id) # 通常索引0是英文,1是中文 except Exception as e: self.error_occurred.emit(f"语音引擎初始化失败: {str(e)}") def set_language(self, lang='zh'): """设置语音语言 :param lang: 'zh' 中文, 'en' 英文 """ if self.engine is None: self.initialize_engine() voices = self.engine.getProperty('voices') if lang == 'en' and voices: self.engine.setProperty('voice', voices[0].id) # 英文 elif len(voices) > 1: self.engine.setProperty('voice', voices[1].id) # 中文 def speak(self, text, lang='zh'): """线程安全的语音播报方法 :param text: 要播报的文本 :param lang: 语言代码 ('zh'/'en') """ def run(): try: # 添加200-500ms随机延迟 delay_ms = random.randint(200, 500) time.sleep(delay_ms / 1000.0) with self.lock: if self.engine is None: self.initialize_engine() self.set_language(lang) self.engine.say(text) self.engine.runAndWait() self.speech_count += 1 # 定期重启引擎防止资源泄漏 if self.speech_count >= self.max_speeches_before_restart: self.engine.stop() self.engine = None self.speech_count = 0 self.initialize_engine() self.finished.emit() except Exception as e: self.error_occurred.emit(f"语音播报错误: {str(e)}") # 启动语音线程 threading.Thread(target=run, daemon=True).start() def get_response(self, response_type, name="", lang='zh'): """获取自定义响应文本 :param response_type: 响应类型 ('welcome', 'unknown', 'low_confidence') :param name: 用户名 (用于欢迎词) :param lang: 语言代码 ('zh'/'en') """ strategy = self.response_strategies.get(response_type, {}).get(lang, "") return strategy.format(name=name) class MainWindow(QtWidgets.QMainWindow): """主窗口类 - 集成人脸识别和语音反馈""" def __init__(self): super().__init__() # 初始化UI组件 self.setup_ui() # 初始化语音助手 self.voice_assistant = VoiceAssistant() self.voice_assistant.finished.connect(self.on_speech_finished) self.voice_assistant.error_occurred.connect(self.on_speech_error) # 初始化人脸识别模块 (假设已实现) self.setup_face_recognition() # 当前语言设置 self.current_lang = 'zh' # 默认中文 def setup_ui(self): """设置用户界面""" self.setWindowTitle("人脸识别系统 - 语音增强版") self.setGeometry(100, 100, 800, 600) # 主布局 central_widget = QtWidgets.QWidget() self.setCentralWidget(central_widget) main_layout = QtWidgets.QVBoxLayout(central_widget) # 视频显示区域 self.video_label = QtWidgets.QLabel("摄像头画面") self.video_label.setAlignment(QtCore.Qt.AlignCenter) self.video_label.setStyleSheet("background-color: black;") main_layout.addWidget(self.video_label, 3) # 识别结果显示 self.result_label = QtWidgets.QLabel("等待识别...") self.result_label.setAlignment(QtCore.Qt.AlignCenter) self.result_label.setStyleSheet("font-size: 18px; font-weight: bold;") main_layout.addWidget(self.result_label) # 控制按钮 button_layout = QtWidgets.QHBoxLayout() self.start_btn = QtWidgets.QPushButton("开始识别") self.start_btn.clicked.connect(self.start_recognition) button_layout.addWidget(self.start_btn) self.stop_btn = QtWidgets.QPushButton("停止识别") self.stop_btn.clicked.connect(self.stop_recognition) button_layout.addWidget(self.stop_btn) self.lang_btn = QtWidgets.QPushButton("切换语言(中/英)") self.lang_btn.clicked.connect(self.toggle_language) button_layout.addWidget(self.lang_btn) main_layout.addLayout(button_layout) def setup_face_recognition(self): """初始化人脸识别模块 (伪代码)""" # 这里应包含人脸识别系统的初始化代码 # 参考引用[4]中百度AI接口集成部分 self.face_recognition_active = False print("人脸识别模块初始化完成") def start_recognition(self): """开始人脸识别""" self.face_recognition_active = True self.result_label.setText("识别中...") print("人脸识别已启动") # 在实际应用中,这里会启动摄像头和人脸检测线程 def stop_recognition(self): """停止人脸识别""" self.face_recognition_active = False self.result_label.setText("识别已停止") print("人脸识别已停止") def toggle_language(self): """切换语言设置""" self.current_lang = 'en' if self.current_lang == 'zh' else 'zh' lang_name = "中文" if self.current_lang == 'zh' else "English" self.result_label.setText(f"语言已切换至: {lang_name}") def on_face_recognized(self, name, confidence): """人脸识别结果处理 :param name: 识别出的用户名 :param confidence: 置信度 (0.0-1.0) """ # 显示识别结果 result_text = f"识别成功: {name} (置信度: {confidence:.2f})" self.result_label.setText(result_text) # 根据置信度选择语音响应策略 if confidence > 0.75: response_text = self.voice_assistant.get_response("welcome", name, self.current_lang) elif confidence > 0.5: response_text = self.voice_assistant.get_response("welcome", name, self.current_lang) else: response_text = self.voice_assistant.get_response("low_confidence", lang=self.current_lang) # 触发语音播报 self.voice_assistant.speak(response_text, self.current_lang) def on_speech_finished(self): """语音播报完成后的回调""" print("[语音] 播报完成") def on_speech_error(self, error_msg): """语音错误处理""" print(f"[语音错误] {error_msg}") QtWidgets.QMessageBox.warning(self, "语音错误", error_msg) def closeEvent(self, event): """关闭窗口时释放资源""" if self.voice_assistant.engine is not None: self.voice_assistant.engine.stop() super().closeEvent(event) if __name__ == "__main__": app = QtWidgets.QApplication(sys.argv) window = MainWindow() window.show() sys.exit(app.exec_()) 这俩程序的功能代码怎么合并到一起变成一个程序?可以给我完整的代码吗?
11-14
MATLAB主动噪声和振动控制算法——对较大的次级路径变化具有鲁棒性内容概要:本文主要介绍了一种在MATLAB环境下实现的主动噪声和振动控制算法,该算法针对较大的次级路径变化具有较强的鲁棒性。文中详细阐述了算法的设计原理与实现方法,重点解决了传统控制系统中因次级路径动态变化导致性能下降的问题。通过引入自适应机制和鲁棒控制策略,提升了系统在复杂环境下的稳定性和控制精度,适用于需要高精度噪声与振动抑制的实际工程场景。此外,文档还列举了多个MATLAB仿真实例及相关科研技术服务内容,涵盖信号处理、智能优化、机器学习等多个交叉领域。; 适合人群:具备一定MATLAB编程基础和控制系统理论知识的科研人员及工程技术人员,尤其适合从事噪声与振动控制、信号处理、自动化等相关领域的研究生和工程师。; 使用场景及目标:①应用于汽车、航空航天、精密仪器等对噪声和振动敏感的工业领域;②用于提升现有主动控制系统对参数变化的适应能力;③为相关科研项目提供算法验证与仿真平台支持; 阅读建议:建议读者结合提供的MATLAB代码进行仿真实验,深入理解算法在不同次级路径条件下的响应特性,并可通过调整控制参数进一步探究其鲁棒性边界。同时可参考文档中列出的相关技术案例拓展应用场景。
### 关于SAID模型的技术定义 在技术领域中,SAID模型通常指代一种特定的设计模式或者架构方法论。然而,在更广泛的语境下,“SAID”可能并非特指某单一概念,而是一个缩写形式,具体含义取决于上下文环境。如果将其拆解为通用原则,则可以理解为 **Specificity, Adaptation, Individualization, and Development (专一性、适应性、个体化以及发展)** 的集合体[^1]。 #### SAID模型的核心要素 - **Specificity(专一性)**: 这部分强调任何系统设计或解决方案都应针对具体的业务需求定制开发,而非采用一刀切的方式处理所有场景。 - **Adaptation(适应性)**: 此特性描述了如何通过灵活调整来应对不断变化的需求和技术条件。例如,在软件工程实践中,敏捷开发流程就是这种理念的具体体现之一[^2]。 - **Individualization(个体化)**: 面向不同用户提供个性化服务的能力至关重要。这不仅限于用户体验层面,还包括数据管理策略等方面——即根据不同用户的特征提供差异化的支持和服务选项。 - **Development(发展)**: 持续改进和优化的过程贯穿整个生命周期。无论是产品功能迭代还是性能调优,都需要基于反馈循环来进行长期演进和发展[^3]。 #### 在IT领域的实际应用场景分析 -SAID模型被广泛应用于现代信息技术项目当中,尤其是在涉及复杂系统的构建过程中显得尤为重要。比如云计算平台建设就需要充分考虑上述四个维度的要求;再如人工智能算法训练阶段也需要遵循类似的思路去规划实验框架并评估效果等等[^4]。 ```python def said_model_application(): specificity = "Design tailored solutions based on specific requirements." adaptation = "Implement flexible mechanisms to handle changing conditions." individualization = "Provide personalized services according to user characteristics." development = "Continuously improve through iterative processes." return { 'specificity': specificity, 'adaptation': adaptation, 'individualization': individualization, 'development': development } result = said_model_application() print(result) ```
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