Titlebook: Innovation Management in the Intelligent World; Cases and Tools Tugrul U. Daim,Dirk Meissner Book 2020 Springer Nature Switzerland AG 2020

迷住

Innovation Management Framework at a Medical Devices Companyagement. Foresighting innovation is among the central elements of long-term strategic planning, which results in dedicated roadmaps for all technology domains. The company uses a moderate share of external inputs for its innovation activities but emphasizes the importance of internal competences str

慢慢沖刷

比賽用背帶

Tesla Energychnologies to store that energy. For Tesla Energy, the greatest challenge with solar power is to develop products that can store solar power for use when the sun is not shining. Storage of solar power is what Tesla has today mastered, with a storage device that is simple to use, easy to install, rel

冒號(hào)

Future of Transportation: Hyperlooproughs and the arrival of “information anywhere” in this digital age, one could foresee the future of transport being massively networked, user-centric, interconnected, and also dynamically priced. As complex and challenging this might be, together with technological innovation, it is necessary for

flutter

partitions stream data into cells, derives statistical information of the cells, and then applies clustering on these much smaller statistical information without referring to the input data. Therefore, grid-based clustering is efficient and very suitable for high-throughput data streams, which are

鞏固

愉快嗎

Brian Barley,Ande Kitamura,Thomas Loar,Edwin Ramon-Samayoa,John Yuzon,Tugrul U. Daimy of the mining algorithm to survive the increasing size of the data. However, as the dimensionality of the data increases, not only the efficiency but also the effectiveness of traditional mining algorithms is compromised. For instance, clusters hidden in some subspaces are hard to be detected usin

Prostaglandins

Claris Leung,Andy Hsiao,Michael Hobernicht,Kevin Camp,Vanessa Kung,Tugrul U. Daimy of the mining algorithm to survive the increasing size of the data. However, as the dimensionality of the data increases, not only the efficiency but also the effectiveness of traditional mining algorithms is compromised. For instance, clusters hidden in some subspaces are hard to be detected usin

Anguish

M. Krishna Priya,Raj Srinivasan,G. Harshitha,Shraddha Zingade,Nihal Jeena,Tugrul U. Daim,Dirk Meissny of the mining algorithm to survive the increasing size of the data. However, as the dimensionality of the data increases, not only the efficiency but also the effectiveness of traditional mining algorithms is compromised. For instance, clusters hidden in some subspaces are hard to be detected usin

惡心

Aayushi Gupta,Binu Thomas,Fayez Alsoubaie,Harsita Gadiraju,Priyanka Patil,Tugrul U. Daim,Dirk Meissn-specific query. Recent neural TripRec methods with sequence-to-sequence models have achieved remarkable performance. However, alongside the exposure bias in general recommender systems, the selection bias caused by the lack of explicit feedback (e.g., ratings) from the trip data exacerbates the ten