Next time, let's invite our friends to enjoy this group of
Nowadays, more and more people like to travel outdoors, and they prefer to record their own roads and landscapes with cameras. In fact, if you can make some technical modifications to your photography later, and add some new elements, you may find different landscapes. For example, Victoria Siemer, a photographer, perfectly combines geometry with photography, bringing us a group of amazing reverse scenes.
Victoria Siemer is a graphic designer and photographer from Brooklyn, New York. He took a group of photos of natural scenery, and then added geometric elements to change people's visual space to achieve a shocking effect. During photo processing, Victoria Siemer used post technology to rearrange natural elements, such as mountains shrouded in clouds, quiet and peaceful forests, and vast sea, to create different levels, thus blurring the clear boundary between reality and fiction. In addition, the geometric shapes in this group of photos, like mirrors, reflect the scenery of another dimension, and put different landscapes of different dimensions into one picture, bringing people different visual enjoyment.
Next time, let's invite our friends to enjoy this group of photos with surrealism style along with Zhiding Expression!
Data collection: ETL tools are responsible for extracting data from distributed and heterogeneous data sources, such as relational data and flat data files, into the temporary middle layer, cleaning, converting and integrating them, and finally loading them into data warehouses or data marts, which become the basis of online analysis and data mining.
Access to data: relational database, NOSQL, SQL, etc.
Infrastructure: Cloud storage, distributed file storage, etc.
Data processing: NLP (NaturalLanguageProcessing) is a subject that studies the language problems of human-computer interaction. The key to natural language processing is to make computers "understand" natural language, so natural language processing is also called NLU (NaturalLanguage Understanding), also known as Computational Linguistics. On the one hand, it is a branch of language information processing; on the other hand, it is one of the core topics of artificial intelligence.
Statistics: hypothesis test, significance test, variance analysis, correlation analysis, t-test, variance analysis, chi-square analysis, partial correlation analysis, distance analysis, regression analysis, simple regression analysis, multiple regression analysis, stepwise regression, regression prediction and residual analysis, ridge regression, logistic regression analysis, curve estimation, factor analysis, cluster analysis, principal component analysis, factor analysis, fast clustering method and clustering method
Data mining: Classification, Estimation, Prediction, affinity grouping or association rules, Clustering, Description and Visualization, complex data type mining (Text, Web, graphics, video, audio, etc.)
Prediction: prediction model, machine learning, modeling and simulation.
Results: Cloud computing, tag cloud, diagram, etc.
To understand the concept of big data, we should first start with "big", which refers to the data scale. Big data generally refers to the amount of data above 10TB(1TB=1024GB). Big data is different from massive data in the past, and its basic characteristics can be summarized by four V’s (Vol-ume, Variety, Value and Veloc-ity), namely, large volume, diversity, low value density and high speed.
First, the data volume is huge. From TB level to PB level.
Secondly, there are many types of data, such as weblogs, videos, pictures, geographical location information, and so on.
Third, the value density is low. Take video as an example. During continuous monitoring, the data that may be useful is only one or two seconds.
Fourthly, the processing speed is fast. 1 second law. This last point is also fundamentally different from the traditional data mining technology. Internet of Things, cloud computing, mobile Internet, Internet of Vehicles, mobile phones, tablets, PCs, and various sensors all over the globe are all data sources or ways of carrying them.
Of course, this is not all the expenses that Zhu Ting needs to deduct. Zhu Ting also needs to pay 1.5%-3% of the agent fees and some miscellaneous expenses of the players’ union. Moreover, because of the talent cultivation, Zhu Ting also needs to pay part of the salary to the Henan mother team. After a full calculation, Zhu Ting’s 1.2 million euros will actually be deducted by nearly 50%, which means that Zhu Ting actually gets 600,000 euros (equivalent to about RMB 4.2 million). But now Zhu Ting obviously doesn’t care about this. To tell the truth, if she wants to make money, Zhu Ting will stay in China. Her annual salary is at least over $1 million, and her income is more than that of studying abroad. Moreover, at home, Zhu Ting has more time to attend business activities, which is also a large amount of income. But for 28-year-old Zhu Ting, she deserves her last chance to fight for her dream. Zhu Ting also knows that if she wants to lead the China women’s volleyball team out of the trough, she must become.
As the first world competition in the Paris Olympic Games cycle, China women’s volleyball team finished sixth, and once again missed the championship. Fortunately, our ultimate goal is not this year’s World Championships, but the Olympic Games two years later. Therefore, this World Championships can be regarded as an opportunity to train and test the team, discover and cultivate some players through competitions, and lay a solid foundation for the women’s volleyball team to return to the peak in the future! Through this World Women’s Volleyball Championship, four players have played their own value, and they can also lock in a place to stay in the women’s volleyball lineup, while three players may not be able to re-enter the women’s volleyball national team in the future through this World Championship.
First of all, let’s take a look at the four outstanding players. Li Yingying, as the core of the team, will not be mentioned. They are Wang Yun, Diao Linyu, Wang Mengjie and Yang Hanyu! Although Diao Linyu is a veteran in this national team, this world championship is the first one she participated in. Diao Linyu’s performance is also obvious to all, and she completely pushed Ding Xia to the bench. In the future, with the latter gradually fading out of the national team, Diao Linyu is definitely the first choice for the second pass position. Wang Yun’s words can be regarded as the biggest discovery of China women’s volleyball team. After that, even if Zhu Ting and Zhang Changning come back, she can still lock in the position of the fourth main attack of women’s volleyball team.
Last year’s Tokyo Olympic Games had a great influence on Wang Mengjie, and she was almost retired by fans. Fortunately, she persisted in the end, and seized the opportunity again at this year’s World Championships, becoming the first free agent of the women’s volleyball team again! Although young Yang Hanyu didn’t get as many opportunities as the previous three players in the World Championships, she was basically replaced when the team was in the most difficult time. However, even though there are few opportunities, Yang Hanyu has grasped them well, at least during his playing time, and has a very good performance. Coupled with the lack of strength and performance of Wang Yuanyuan, the starting assistant attacker, Yang Hanyu is likely to replace Wang Yuanyuan in future competitions, and become a candidate for the main assistant attacker of the women’s volleyball team.
After this World Championships, the three players who are likely to leave the national women’s volleyball team, perhaps including the aforementioned Wang Yuanyuan, can only "abuse vegetables". Once she meets an opponent who is stronger than herself, it is difficult to play. The other two players are Jin Ye, a major player, and Wang Weiyi, a free agent. These two players have one thing in common: they are not young. Jin Ye, 26, and Wang Weiyi, 27, can’t be used as future training objects of the team. Besides, they didn’t play very well in this World Championships, and their strength is far from the level of playing the World Series. They should leave their positions to younger and more potential players!
In order to improve the efficiency of imaging examination and better serve patients, the imaging department of Guzhen County People’s Hospital introduced artificial intelligence AI imaging diagnosis system to assist imaging doctors to provide faster and more accurate examination and diagnosis for the majority of patients.
Recently, the medical imaging department of Guzhen County People’s Hospital has introduced the world’s advanced artificial intelligence (AI) aided diagnosis system (pulmonary nodules, rib fractures, coronary arteries, head and neck vessels, stroke), which means that doctors have joined hands with "AI", and the medical imaging department has officially entered the era of intelligent medical care, providing more accurate, fast and efficient imaging diagnosis for the majority of patients, so that more patients can get timely diagnosis and treatment at an early stage.
AI artificial intelligence, leaving pulmonary nodules nowhere to hide
Early detection and treatment of lung cancer can greatly improve the quality of life and survival rate of patients. As the manifestation of early lung cancer, regular screening of pulmonary nodules is particularly important. Chest CT is the first choice for early screening of lung cancer. A chest CT examination will produce at least 400 CT images, which are great pressure and challenge to doctors’ eyesight, physical strength and endurance. However, naked eye screening is hard to avoid, especially for small pulmonary nodules close to blood vessels, which are prone to missed diagnosis. AI-aided diagnosis system for pulmonary nodules effectively solves this problem. It adopts advanced adaptive network technology and rule algorithm, and incorporates the deep learning and expert experience of a large number of selected cases. It can "carpet screen" every image scanned by chest CT in about 5 seconds, automatically mark suspicious parts, automatically detect the density, size and other related information of nodules, accurately locate the location of nodules and judge the types of nodules. It is highly sensitive and specific for the diagnosis of various pulmonary nodules, greatly improving the detection rate of tiny lesions, and generating a detection guide with one click.
AI artificial intelligence, sharp eyes detect small aneurysms
At present, the intelligent diagnosis of brain diseases includes cerebral hemorrhage, cerebral atherosclerosis, intracranial aneurysm and carotid vulnerable plaque evaluation. Intracerebral hemorrhage is a refractory disease with high mortality and disability rate in neurosurgery. AI+ head CT, based on machine vision and deep learning technology, bleeding volume, to determine whether there is cerebral hernia.
AI artificial intelligence, hidden fracture is no longer hidden.
AI can have a very high detection rate of rib fractures, especially occult fractures, based on chest CT data, and can accurately mark the accurate location and fracture type interpretation of rib fractures in patients with chest trauma.
AI artificial intelligence helps standardize the diagnosis and treatment of coronary heart disease
Artificial intelligence-assisted coronary CTA has high accuracy and sensitivity. It can automatically identify blood vessels, complete the identification of blood vessel segments, and at the same time, automatically complete the assessment of vascular stenosis and plaque properties, provide suggestions for plaque risk, improve the diagnostic efficiency, and promote the standardization of diagnosis and treatment of coronary heart disease.
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