37111410
Performance Comparison Between Backpropagation, Neuro-Fuzzy Network, and SVM
In this study, we compare the performance of well-known neural networks, namely, back-propagation (BP) algorithm, Neuro-Fuzzy network and Support Vector Machine (SVM) using the standard three database sets: Wisconsin breast cancer, Iris and wine data. Since such database have been useful for evaluating performance of a group of machine learning algorithms, a series of experiments have been carried out for three algorithms using the cross validation method. Results suggest that SVM outperforms the others and the Neuro-Fuzzy network is better than the BP algorithm for this data set.
33400437
Facial Expression Recognition Using Active Appearance Model
This paper describes a facial expression recognition system based upon Active Appearance Model (AAM), which has been typically used for the face recognition task. Given that AAM has been also used in tracking the moving object, we thought it could be effective in recognizing the facial expressions of humans. Our results show that the performance of the facial expression recognition using AAM is reliably high when it combined with an enhanced Fisher classification model.
44579377
Head Detection and Tracking for the Car Occupant's Pose Recognition
This paper describes a Vision-based Occupant Pose Recognition (VOPR) system, which can ensure a safe airbag deployment. Head detection and its tracking are necessary for occupant’s pose recognition in the car, since the position of occupant’s head provides valuable information, such as his pose, size, position, and so on. We use the stereo cameras to extract a disparity map. Against variable lighting conditions including the night drive, we adopt infrared illumination as well as normal one. Results suggest that VOPR system is reliable and performs reasonably well.
14346631
Remote Software-Based Attestation for Wireless Sensors
Wireless sensor networks are envisioned to be deployed in mission-critical applications. Detecting a compromised sensor, whose memory contents have been tampered, is crucial in these settings, as the attacker can reprogram the sensor to act on his behalf. In the case of sensors, the task of verifying the integrity of memory contents is difficult as physical access to the sensors is often infeasible. In this paper, we propose a software-based approach to verify the integrity of the memory contents of the sensors over the network without requiring physical contact with the sensor. We describe the building blocks that can be used to build a program for attestation purposes, and build our attestation program based on these primitives. The success of our approach is not dependent on accurate measurements of the execution time of the attestation program. Further, we do not require any additional hardware support for performing remote attestation. Our attestation procedure is designed to detect even small memory changes and is designed to be resistant against modifications by the attacker.
14743541
SCAI TREC-8 Experiments
This working note reports our experiences with TREC-8 on four tracks: Ad Hoc, Filtering, Web, and QA. The Ad Hoc retrieval engine, SCAIR, has been used for the Web and QA experiments, and the ltering experiments were based on it's own engine. As a second entry to TREC, we focused this year on exploring possibilities of applying machine learning techniques to TREC tasks. The Ad Hoc track employed a cluster-based retrieval method where the scoring function used cluster information extracted from a collection of precompiled documents. Filtering was based on naive Bayes learning supported by an EM algorithm. In the Web track, we compared the performance of using link information to that of not using the information. In the QA track, some passage extraction techniques have been tested using the baseline SCAIR retrieval engine.
205099619
Simulated annealing and genetic algorithms for scheduling products with multi-level product structure
We consider a short-term production scheduling problem in a manufacturing system producing products with multi-level product structure, and their components and subassemblies. The problem is to schedule production of components, subassemblies, and final products with the objective of minimizing the weighted sum of tardiness and earliness of the items. We consider due dates of final products, precedence relationships among items, and processing capacity of the manufacturing system. The scheduling problem is solved with simulated annealing and genetic algorithms, which are search heuristics often used for global optimization in a complex search space. To compare the performance of these algorithms with the finite loading method, which is often used in practice, computational experiments are carried out using randomly generated test problems and results are reported.
1181632
Group key agreement efficient in communication
In recent years, collaborative and group-oriented applications and protocols have gained popularity. These applications typically involve communication over open networks; security thus is naturally an important requirement. Group key management is one of the basic building blocks in securing group communication. Most prior research in group key management focused on minimizing computation overhead, in particular minimizing expensive cryptographic operations. However, continued advances in computing power have not been matched by a decrease in network communication delay. Thus, communication latency, especially in high-delay long-haul networks, increasingly dominates the key setup latency, replacing computation delay as the main latency contributor. Hence, there is a need to minimize the size of messages and, especially, the number of rounds in cryptographic protocols. Since most previously proposed group key management techniques optimize computational (cryptographic) overhead, they are particularly impacted by high communication delay. In this work, we discuss and analyze a specific group key agreement technique which supports dynamic group membership and handles network failures, such as group partitions and merges. This technique is very communication-efficient and provably secure against hostile eavesdroppers as well as various other attacks specific to group settings. Furthermore, it is simple, fault-tolerant, and well-suited for high-delay networks.
16063207
Using motion-compensated frame-rate conversion for the correction of 3: 2 pulldown artifacts in video sequences
Currently, the most popular method of converting 24 frames per second (fps) film to 60 fields/s video is to repeat each odd-numbered frame for 3 fields and each even-numbered frame for 2 fields. This method is known as 3:2 pulldown and is an easy and inexpensive way to perform 24 fps to 60 fields/s frame-rate conversion. However, the 3:2 pulldown introduces artifacts, which are especially visible when viewing on progressive displays and during slow-motion playback. We have developed a motion-compensated frame-rate conversion algorithm to reduce the 3:2 pulldown artifacts. By using frame-rate conversion with interpolation instead of field repetition, mean square error and blocking artifacts are reduced significantly. The techniques developed here can also be applied to the general frame-rate conversion problem.