MOTIVATION: Developments in biotechnology have enabled the in vitro evolution of binding proteins. The emerging limitations of antibodies in binding protein engineering have led to suggestions for other proteins as alternative binding protein scaffolds. Most of these proteins were selected based on human intuition rather than systematic analysis of the available data. To improve this strategy, we developed a computational framework for finding desirable binding protein scaffolds by utilizing protein structure and sequence information. RESULTS: For each protein, its structure and the sequences of evolutionarily-related proteins were analyzed, and spatially contiguous regions composed of highly variable residues were identified. A large number of proteins have these regions, but leucine rich repeats (LRRs), histidine kinase domains and immunoglobulin domains are predominant among them. The candidates suggested as new binding protein scaffolds include histidine kinase, LRR, titin and pentapeptide repeat protein. AVAILABILITY AND IMPLEMENTATION: The database and web-service are accessible via http://bcbl.kaist.ac.kr/LibBP CONTACT: [email protected] data: Supplementary data are available at Bioinformatics online.

Recent research has shown that range data acquired from consumer imaging devices are successfully used to build accurate 3D geometric models of surrounding environments very quickly. However, as the volume of modeling space grows, its processing time inevitably becomes huge when a simple linear data structure is used to handle a large range data set. The main difficulty is that pairwise scan matching among all pairs of input data requires quadratic computational complexity. The OBB-sphere tree presented in this paper accelerates the process by intelligently choosing a subset of related pair candidates. The proposed data structure is an enhanced sphere tree in which every leaf node contains a set of 3D points computed from a depth image and bounded by one sphere and one tighter-fitting shape, which is the oriented bounding box (OBB). This approach exploits the simplicity of spheres in hierarchical tree construction and the intersection test which is performed to reject objects that are far apart. The compactness of OBBs is used to refine the results of the intersection test. The number of possible pairs was reduced by more than half in some test datasets in the experiment.

Address resolution protocol (ARP) is widely used to maintain mapping between data link (e.g. MAC) and network (e.g. IP) layer addresses. Although most hosts rely on automated and dynamic management of ARP cache entries, current implementation is well-known to be vulnerable to spoofing or denial of service (DoS) attacks. There are many tools that exploit vulnerabilities of ARP protocols, and past proposals to address the weaknesses of the ‘original’ ARP design have been unsatisfactory. Suggestions that ARP protocol definition be modified would cause serious and unacceptable compatibility problems. Other proposals require customised hardware be installed to monitor malicious ARP traffic, and many organisations cannot afford such cost. This study demonstrates that one can effectively eliminate most threats caused by the ARP vulnerabilities by installing anti-ARP spoofing agent (ASA), which intercepts unauthenticated exchange of ARP packets and blocks potentially insecure communications. The proposed approach requires neither modification of kernel ARP software nor installation of traffic monitors. Agent uses user datagram protocol (UDP) packets to enable networking among hosts in a transparent and secure manner. The authors implemented agent software on Windows XP and conducted an experiment. The results showed that ARP hacking tools could not penetrate hosts protected by ASA.

We propose a novel method to enhance a family of ICP(iterative closest point) algorithms by updating velocity. Even though ICP algorithms play a dominant role in a model based tracking, it is difficult to avoid an accumulated tracking error during a continuous motion. It is because that typical ICP algorithms assumes that each of the point in one scan are measured simultaneously while most of the available rangefinders measure each point sequentially. Hence conventional ICP algorithms are prone to be erroneous under a fast motion and an accumulated error during the motion cannot be ignored in many cases. In our approach, we estimate a velocity of a rangefinder numerically over ICP iterations. As a result, distortion of a scan due to the motion can be compensated using estimated velocity. In addition, outliers are effectively rejected during the iteration of velocity update, which means that more accurate and robust motion is trackable. Also we verify a performance and an accuracy of our method by demonstrating simulation and real-world experiment results.