The term of Hidden Champions was first put forward by Simon (1996a) in his book and has already been a well-studied subject all over the world. The purpose of this dissertation is to figure out what are the main factors underlying Chinese Hidden Champions. The literature part is composed of earlier research on Hidden Champions and theories on several factors that have been identified by authors, which form an analytical framework for analyzing empirical data. Conducting a qualitative approach, the empirical data was collected through semi-structured telephone interviews with the senior personnel of two Chinese companies. Secondary data, such as public reports, also played a complementary role. The findings of this study showed the factors of clear goal, excellent entrepreneur, focused strategy, sustained innovation, globalization and customer orientation immensely affect the success of Chinese Hidden Champions. It was also pointed out that there remain some views that are different from concepts of Simon’s.

In this work, we mostly concentrate on the hidden shift problem for non-injective functions. It is worthwhile to know that the query complexity of the non-injective hidden shift problem is exponential in the worst case by the well known bounds on the unstructured search problem. Hence, we can make this problem more tractable by imposing additional constraints on the problem. Perhaps the first constraint that comes to mind is to address the average case problem. In this work, we show that the average case non-injective hidden shift problem can be reduced to the injective hidden shift problem by giving one such reduction. The reduction is based on a tool we developed called injectivization. The result is strong in the sense that the underlying group can be any finite group and that the non-injective functions for which we have defined the hidden shift problem can have range in an arbitrary finite set. Using this tool, we simplify the main result of a recent paper by about the hidden shift problem for Boolean-valued functions by reducing that problem to Simon's problem. They also posed an open question which is subject to personal interpretation. We answer the seemingly most general interpretation of the question. However, we use our own techniques in doing so (the authors ask if their techniques can be used for addressing that problem). Another constraint that one can consider is to have a promise on the structure of the functions. In this work we consider the hidden shift problem for c-almost generalized bent functions. A class of functions which we defined that includes the generalized bent functions. Then we turn our attention toward the generalized hidden shift problem which is easier than injective hidden shift problem and hence more tractable. We state some of our observations about this problem. Finally we show that the average classical query complexity of the non-injective hidden shift problem over groups of form (Z/mZ)^n when m is a constant is exponential, which also immediately implies that the classical average query complexity of the non-injective hidden shift problem is exponential. We also show that the worst-case classical query complexity of the generalized injective hidden shift problem over the same group is high, which implies that the classical query complexity of the hidden shift problem is high.

The first impression of a person or an object relies hugely on the appearance. When it comes to the judgment of an object, whether it is attractive or not, the appearance becomes crucial although many audiences, especially in the field of art, are aware of the fact that looks can be deceiving. An object that is fabricated well on the surface can disappoint the audience once the outer layer is breached; but on the other hand, something that appears to be boring at first glance can surprise you with its hidden real quality. I became fascinated with the latter and decided to explore the relationship between the exterior and the interior of an object; what is hidden and what is not. / GDI Master / Storytelling 2009

Cloud computing provides business new working paradigm with the benefit of cost reduce and resource sharing. Tasks from different users may be performed on the same machine. Therefore, one primary security concern is whether user data is secure in cloud. On the other hand, hacker may facilitate cloud computing to launch larger range of attack, such as a request of port scan in cloud with virtual machines executing such malicious action. In addition, hacker may perform a sequence of attacks in order to compromise his target system in cloud, for example, evading an easy-to-exploit machine in a cloud and then using the previous compromised to attack the target. Such attack plan may be stealthy or inside the computing environment, so intrusion detection system or firewall has difficulty to identify it. The proposed detection system analyzes logs from cloud to extract the intensions of the actions recorded in logs. Stealthy reconnaissance actions are often neglected by administrator for the insignificant number of violations. Hidden Markov model is adopted to model the sequence of attack performed by hacker and such stealthy events in a long time frame will become significant in the state-aware model. The preliminary results show that the proposed system can identify such attack plans in the real network.

We present a new detection model include monitoring network perimeter and hosts logs to counter the new method of attacking involve different hosts source during an attacking sequence. The new attacking sequence we called ¡§Scout and Intruder¡¨ involve two separate hosts. The scout will scan and evaluate the target area to find the possible victims and their vulnerability, and the intruder launch the precision strike with login activities looked as same as authorized users. By launching the scout and assassin attack, the attacker could access the system without being detected by the network and system intrusion detection system. In order to detect the Scout and intruder attack, we correlate the netflow connection records, the system logs and network data dump, by finding the states of the attack and the corresponding features we create the detection model using the Hidden Markov Chain. With the model we created, we could find the potential Scout and the Intruder attack in the initial state, which gives the network/system administrator more response time to stop the attack from the attackers.

A Mandarin keyword spotting system based on LPC, VQ, discrete-time HMM and Viterbi algorithm is proposed in the thesis. Joining with a dialogue system, this keyword spotting platform is further refined to a prototype of Taiwan Railway Natural Language Reservation System. In the reservation process, five questions: name and ID number, departure station, destination station, train type and number of tickets, and time schedule are asked by the computer-dialogue attendant. Following by the customer¡¦s speech confirmation, electronic tickets can be correctly issued and printed within 90 seconds in a laboratory environment.

In this thesis, we discuss the subject into four parts. Firstly, we introduce the telematics for automotive. Secondary, we study the effects of locations of the hidden antenna. Thirdly, we discuss the effects of the windshield to the hidden antenna as we place the antenna on the windshield, then, the window film is attached to the windshield. We conduct implementation and measurement to analyze the effect of the film to the antenna. Finally, we find that the antenna gain is degraded in certain receiving angle due to the car body as we place the antenna at the corner of the windshield. In order to improve this, we design an EBG structure and place it between the antenna and the car body. The simulation result indicates that the EBG structure not only improves the gain in certain receiving angles but also reduces the induced current intensity on the car body.

We propose a novel medium access control scheme which borrows ideas from the dual busy tone approach and the IEEE 802.11e standard for improving quality of services in wireless networks. In the field of medium access control in Wireless LAN, there are two notorious problems, which have been studied for a long time. They are the hidden terminal problem and the exposed terminal problem. To avoid the collisions caused by hidden terminals, the RTS/CTS approach is widely adopted. However, RTS and CTS frames themselves are still subject to collisions. The Transmit Busy Tone and the Receive Busy Tone were proposed to further mitigate the hidden terminal problem and the exposed terminal problem. The transmit busy tone provides protection for the RTS packets and thus, increase the probability of successful RTS reception at the intended receiver. The receive busy tone acknowledges the RTS packet and provide continuous protection for the subsequent data packets. We use computer simulations to justify the usage of our proposal. We show that the proposed scheme outperforms the IEEE 802.11e standard.

Thesis (Th. M.)--Dallas Theological Seminary, 2003. / Includes bibliographical references (leaves 102-113).

Existing methods for image-based location estimation generally attempt to recognize every photo independently, and their resulting reliance on strong visual feature matches makes them most suited for distinctive landmark scenes. We observe that when touring a city, people tend to follow common travel patterns---for example, a stroll down Wall Street might be followed by a ferry ride, then a visit to the Statue of Liberty or Ellis Island museum. We propose an approach that learns these trends directly from online image data, and then leverages them within a Hidden Markov Model to robustly estimate locations for novel sequences of tourist photos. We further devise a set-to-set matching-based likelihood that treats each ``burst" of photos from the same camera as a single observation, thereby better accommodating images that may not contain particularly distinctive scenes. Our experiments with two large datasets of major tourist cities clearly demonstrate the approach's advantages over traditional methods that recognize each photo individually, as well as a naive HMM baseline that lacks the proposed burst-based observation model. / text