提醒自己少走弯路的十条忠告

迈不过友情╰ 2022-05-25 13:50 252阅读 0赞

## [少走弯路的10条忠告][10] ##

如何在涉世之初少走弯路，有一个好的开端，开始一番成功的事业？以下是一些先行者积累的10条有益的涉世忠告。好好地遵循、把握这些忠告和建议吧，比起所学的课堂课程来，它毫不逊色！

## 1.1、买个闹钟，以便按时叫醒你 ##

贪睡和不守时，都将成为你工作和事业上的绊脚石，任何时候都一样。不仅要学会准时，更要学会提前。就如你坐车去某地，沿途的风景很美，你忍不住下车看一看，后来虽然你还是赶到了某地，却不是准时到达。“闹钟”只是一种简单的标志和提示，真正灵活、实用的时间，掌握在每个人的心中。

## 1.2、如果你不喜欢现在的工作，要么辞职不干，要么就闭嘴不言 ##

初出茅庐，往往眼高手低，心高气傲，大事做不了，小事不愿做。不要养成挑三拣四的习惯。不要雨天烦打伞，不带伞又怕淋雨，处处表现出不满的情绪。记住，不做则已，要做就要做好。

## 1.3、每个人都有孤独的时候 ##

要学会忍受孤独，这样才会成熟起来。年轻人嘻嘻哈哈、打打闹闹惯了，到了一个陌生的环境，面对形形色色的人和事，一下子不知所措起来，有时连一个可以倾心说话的地方也没有。这时，千万别浮躁，学会静心，学会忍受孤独。在孤独中思考，在思考中成熟，在成熟中升华。不要因为寂寞而乱了方寸，而去做无聊无益的事情，白白浪费了宝贵的时间。

## 1.4、走运时要做好倒霉的准备 ##

有一天，一只狐狸走到一个葡萄园外，看见里面水灵灵的葡萄垂涎欲滴。可是外面有栅栏挡着，无法进去。于是它一狠心绝食三日，减肥之后，终于钻进葡萄园内饱餐一顿。当它心满意足地想离开葡萄园时，发觉自己吃得太饱，怎么也钻不出栅栏了。相信任何人都不愿做这样的狐狸。退路同样重要。饱带干粮，晴带雨伞，点滴积累，水到渠成。有的东西今天似乎一文不值，但有朝一日也许就会身价百倍。

## 1.5、不要像玻璃那样脆弱 ##

有的人眼睛总盯着自己，所以长不高看不远；总是喜欢怨天尤人，也使别人无比厌烦。没有苦中苦，哪来甜中甜？不要像玻璃那样脆弱，而应像水晶一样透明，太阳一样辉煌，腊梅一样坚强。既然睁开眼睛享受风的清凉，就不要埋怨风中细小的沙粒。

## 1.6、管住自己的嘴巴 ##

不要谈论自己，更不要议论别人。谈论自己往往会自大虚伪，在名不副实中失去自己。议论别人往往陷入鸡毛蒜皮的是非口舌中纠缠不清。每天下班后和你的那些同事朋友喝酒聊天可不是件好事，因为，这中间往往会把议论同事、朋友当做话题。背后议论人总是不好的，尤其是议论别人的短处，这些会降低你的人格。

## 1.7、机会从不会“失掉”，你失掉了，自有别人会得到 ##

不要凡事在天，守株待兔，更不要寄希望于“机会”。机会只不过是相对于充分准备而又善于创造机会的人而言的。也许，你正为失去一个机会而懊悔、埋怨的时候，机会正被你对面那个同样的“倒霉鬼”给抓住了。没有机会，就要创造机会，有了机会，就要巧妙地抓住。

## 1.8、若电话老是不响，你该打出去 ##

很多时候，电话会给你带来意想不到的收获，它不是花瓶，仅仅成为一种摆设。交了新朋友，别忘了老朋友，朋友多了路好走。交际的一大诀窍就是主动。好的人缘好的口碑，往往助你的事业更上一个台阶。

## 1.9、千万不要因为自己已经到了结婚年龄而草率结婚 ##

想结婚，就要找一个能和你心心相印、相辅相携的伴侣。不要因为放纵和游戏而恋爱，不要因为恋爱而影响工作和事业，更不要因一桩草率而失败的婚姻而使人生受阻。感情用事往往会因小失大。

## 1.10、写出你一生要做的事情，把单子放在皮夹里，经常拿出来看 ##

人生要有目标，要有计划，要有提醒，要有紧迫感。一个又一个小目标串起来，就成了你一生的大目标。生活富足了，环境改善了，不要忘了皮夹里那张看似薄薄的单子。

\[1\] 葛彤 基于机器学习的室内wifi定位算法研究 北京邮电2017  
\[2\] 卞智. 基于机器学习算法的指纹匹配定位技术研究\[D\]. 北京邮电大学, 2017.  
\[3\] 覃玉清. 基于深度学习的WIFI定位算法\[D\]. 南京大学, 2014.  
\[4\] 刘万寿. 基于WiFi技术的室内无线定位方法研究\[D\]. 哈尔滨工程大学, 2015.  
\[5\] 王鹏. 基于机器学习的无线传感网络节点定位方法研究\[D\]. 浙江工业大学, 2011.  
\[6\] 李军, 何星, 蔡云泽,等. 基于K-means和Random Forest的WiFi室内定位方法\[J\]. 控制工程, 2017, 24(4):787-792.  
\[7\] 徐龙阳. 基于机器学习的室内定位方法综述\[J\]. 电脑知识与技术, 2018(1).  
\[8\] Cong C, Men X. An Innovative Indoor Location Algorithm Based on Supervised Learning and WIFI Fingerprint Classification\[C\]// International Conference On Signal And Information Processing, Networking And Computers. Springer, Singapore, 2017:238-246.  
\[9\] Elbasiony R, Gomaa W. WiFi Localization for Mobile Robots Based on Random Forests and GPLVM\[C\]// International Conference on Machine Learning and Applications. IEEE, 2015:225-230.  
\[10\] Hernández N, Ocaña M, Alonso J M, et al. WiFi-based indoor localization and tracking of a moving device\[C\]// Ubiquitous Positioning, Indoor Navigation & Location Based Services. IEEE, 2014:281-289.  
\[11\] Wang ， Qiaojun Kernel learning and applications in wireless localization  
\[12\] Wu H, Chen J, Wang C, et al. A Kernel-Based Localization Approach in Wireless Sensor Networks\[C\]// International Conference on Future Generation Communication and  
\[13\] Tran D A, Nguyen T. Localization In Wireless Sensor Networks Based on Support Vector Machines\[J\]. IEEE Transactions on Parallel & Distributed Systems, 2008, 19(7):981-994.NETWORKING. IEEE, 2008:31-34.  
\[14\] Jaroenkittichai P, Leelarasmee E. Utilizing Multiple Data Sources for Localization in Wireless Sensor Networks Based on Support Vector Machines\[J\]. Ieice Transactions on Fundamentals of Electronics Communications & Computer Sciences, 2013, E96.A(11):2081-2088.  
\[15\] Zhu F, Wei J. Localization Algorithm in Wireless Sensor Networks Based on Improved Support Vector Machine\[J\]. Journal of Nanoelectronics & Optoelectronics, 2016, 12(5):452-459.  
\[16\] Salamah A H, Tamazin M, Sharkas M A, et al. An enhanced WiFi indoor localization system based on machine learning\[C\]// International Conference on Indoor Positioning and Indoor Navigation. IEEE, 2016.  
\[17\] Zhao J, Wang J. WiFi indoor positioning algorithm based on machine learning\[C\]// IEEE International Conference on Electronics Information and Emergency Communication. IEEE, 2017:279-283.  
\[18\] Zhao J, Wang J. WiFi indoor positioning algorithm based on machine learning\[C\]// IEEE International Conference on Electronics Information and Emergency Communication. IEEE, 2017:279-283.  
\[19\] Pan J J, Yang Q, Pan S J. Online co-localization in indoor wireless networks by dimension reduction\[C\]// National Conference on Artificial Intelligence. AAAI Press, 2007:1102-1107.  
\[20\] Pan J J, Yang Q, Chang H, et al. A manifold regularization approach to calibration reduction for sensor-network based tracking\[C\]// National Conference on Artificial Intelligence and the Eighteenth Innovative Applications of Artificial Intelligence Conference, July 16-20, 2006, Boston, Massachusetts, Usa. DBLP, 2006:988–993.  
\[21\] Laine S, Aila T. Temporal Ensembling for Semi-Supervised Learning\[J\]. 2016.  
\[22\] Xiaojin Z. Semi-Supervised Learning Literature Sur-vey\[J\]. 2005, 37(1):63-77.  
\[23\] 黄涛涛, 顾晶晶, 庄毅. 基于半监督拉普拉斯映射的移动定位算法\[J\]. 计算机工程, 2018, 44(1):144-148.  
\[24\] 李昱. 半监督流形学习算法研究和应用\[D\]. 西安电子科技大学, 2010.  
\[25\] 刘海红, 周聪辉. 半监督拉普拉斯特征映射算法\[J\]. 计算机工程与设计, 2012, 33(2):601-606.  
\[26\] 杨剑, 王珏, 钟宁. 流形上的Laplacian半监督回归\[J\]. 计算机研究与发展, 2007, 44(7):1121-1127.  
\[27\] Yang B, Xu J, Yang J, et al. Localization algorithm in wireless sensor networks based on semi-supervised manifold learning and its application\[J\]. Cluster Computing, 2010, 13(4):435-446.  
\[28\] Zhou M, Tang Y, Nie W, et al. GrassMA: Graph-based Semi-supervised Manifold Alignment for Indoor WLAN Localization\[J\]. IEEE Sensors Journal, 2017, PP(99):1-1.  
\[29\] Belkin M, Niyogi P, Sindhwani V. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples\[M\]. JMLR.org, 2006.  
\[30\] Wang J, Luo J, Pan S J, et al. Learning-Based Outdoor Localization Exploiting Crowd-Labeled WiFi Hotspots\[J\]. IEEE Transactions on Mobile Computing, PP(99):1-1.  
\[31\] Pan J J, Yang Q, Pan S J. Online co-localization in indoor wireless networks by dimension reduction\[C\]// National Conference on Artificial Intelligence. AAAI Press, 2007:1102-1107.  
[https://blog.csdn.net/jrunw/article/details/79205322][https_blog.csdn.net_jrunw_article_details_79205322]  
[https://www.coursera.org/learn/machine-learning/home/welcome][https_www.coursera.org_learn_machine-learning_home_welcome]  
[https://blog.csdn.net/hamigua\_12/article/details/8695527][https_blog.csdn.net_hamigua_12_article_details_8695527]  
[https://blog.csdn.net/zb1165048017/article/details/51360362][https_blog.csdn.net_zb1165048017_article_details_51360362]  
[https://blog.csdn.net/jrunw/article/details/79205322][https_blog.csdn.net_jrunw_article_details_79205322]  
[http://wwv.cyzone.cn/a/20170422/310196.html][http_wwv.cyzone.cn_a_20170422_310196.html]  
[https://blog.csdn.net/sjtuai/article/details/75375578][https_blog.csdn.net_sjtuai_article_details_75375578]  
[https://www.cnblogs.com/tiandsp/archive/2013/03/06/2946310.html][https_www.cnblogs.com_tiandsp_archive_2013_03_06_2946310.html]  
\[1\] Wang J, Tan N, Luo J, et al. WOLoc: WiFi-only outdoor localization using crowdsensed hotspot labels\[C\]// INFOCOM 2017 - IEEE Conference on Computer Communications, IEEE. IEEE, 2017.  
\[2\] Wang J, Luo J, Pan S J, et al. Learning-Based Outdoor Localization Exploiting Crowd-Labeled WiFi Hotspots\[J\]. IEEE Transactions on Mobile Computing, PP(99):1-1.  
\[3\] Belkin M. Semi-supervised learning on manifolds\[J\]. Machine Learning, 2004, 56(1-3):209-239.  
\[4\] Zheng V W, Pan S J, Yang Q, et al. Transferring multi-device localization models using latent multi-task learning\[C\]// National Conference on Artificial Intelligence. AAAI Press, 2008:1427-1432.  
\[5\] Pan R, Zhao J, Zheng V W, et al. Domain-constrained semi-supervised mining of tracking models in sensor networks\[C\]// ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, California, Usa, August. DBLP, 2007:1023-1027.  
\[6\] Pan J J, Yang Q, Chang H, et al. A manifold regularization approach to calibration reduction for sensor-network based tracking\[C\]// National Conference on Artificial Intelligence and the Eighteenth Innovative Applications of Artificial Intelligence Conference, July 16-20, 2006, Boston, Massachusetts, Usa. DBLP, 2006:988–993.  
\[7\] Pan J J, Pan S J, Zheng V W, et al. Digital Wall: A Power-efficient Solution for Location-based Data Sharing\[C\]// IEEE International Conference on Pervasive Computing & Communications. IEEE Computer Society, 2008:645-650.  
\[8\] Pan S J, Kwok J T, Yang Q, et al. Adaptive localization in a dynamic WiFi environment through multi-view learning\[C\]// National Conference on Artificial Intelligence. AAAI Press, 2007:1108-1113.  
\[9\] Belkin M, Niyogi P. Semi-Supervised Learning on Riemannian Manifolds\[J\]. Machine Learning, 2004, 56(1-3):209-239.  
\[10\] Pan J J, Pan S J, Yin J, et al. Tracking mobile users in wireless networks via semi-supervised colocalization\[J\]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2012, 34(3):587.

\[1\] 黄涛涛, 顾晶晶, 庄毅. 基于半监督拉普拉斯映射的移动定位算法\[J\]. 计算机工程, 2018, 44(1):144-148.  
\[2\] 杨斌, 徐金梧, 阳建宏,等. 基于半监督流形学习的无线传感器网络定位方法及其应用\[J\]. 工程科学学报, 2010, 32(7):946-951.  
\[3\] 夏颖, 马琳, 张中兆,等. 基于半监督流形学习的 WLAN 室内定位算法\[J\]. 系统工程与电子技术, 2014(7):1422-1427.  
\[4\] 王成群. 基于学习算法的无线传感器网络定位问题研究\[D\]. 浙江大学, 2009.  
\[5\] 周牧, 唐云霞, 田增山,等. 基于流形插值数据库构建的WLAN室内定位算法\[J\]. 电子与信息学报, 2017, 39(8):1826-1834.  
\[6\] Yang B, Xu J, Yang J, et al. Localization algorithm in wireless sensor networks based on semi-supervised manifold learning and its application\[J\]. Cluster Computing, 2010, 13(4):435-446.  
\[7\] Belkin M, Niyogi P, Sindhwani V. Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples\[M\]. JMLR.org, 2006.

[10]: http://www.cnblogs.com/xdp-gacl/p/4102862.html
[https_blog.csdn.net_jrunw_article_details_79205322]: https://blog.csdn.net/jrunw/article/details/79205322
[https_www.coursera.org_learn_machine-learning_home_welcome]: https://www.coursera.org/learn/machine-learning/home/welcome
[https_blog.csdn.net_hamigua_12_article_details_8695527]: https://blog.csdn.net/hamigua_12/article/details/8695527
[https_blog.csdn.net_zb1165048017_article_details_51360362]: https://blog.csdn.net/zb1165048017/article/details/51360362
[http_wwv.cyzone.cn_a_20170422_310196.html]: http://wwv.cyzone.cn/a/20170422/310196.html
[https_blog.csdn.net_sjtuai_article_details_75375578]: https://blog.csdn.net/sjtuai/article/details/75375578
[https_www.cnblogs.com_tiandsp_archive_2013_03_06_2946310.html]: https://www.cnblogs.com/tiandsp/archive/2013/03/06/2946310.html