Small amphiphilic organics, coordination extended solids, and constant curvature structures

In this Account, we explore the role constant curvature structures play in amphiphilic small molecule crystals and extended coordination solids. A constant curvature structure is one in which there is a surface or interface that has the same curvature throughout its surface. Simple examples of such structures contain spheres (micelles), columns, or layers. Yet another family are cubic as is found in the gyroid topology. For amphiphilic systems, there are two domains, one generally hydrophobic and the other hydrophilic. We find that the interfaces between these two domains in small molecule structures resemble those in larger scale systems and adopt topologies related to constant curvature structures. The hydrophobic-to-total volume ratio, a molecular parameter, can be used to predict which type of constant curvature structure is adopted. In the case of three coordinate extended solids, constant curvature plays a role both in the extended net topology and in the hydrophobic-to-hydrophilic interface.     

Enhanced Dynamic Authentication Scheme (EDAS)

With non-stop growth in network environments, communication security is necessary. A strong protocol guarantees that users and service providers are secure against many kinds of attacks, such as impersonation and replay attack. Sood et al. proposed an authentication scheme based on dynamic identity to prevent transactions from being intercepted by malicious users. Although they claimed that their scheme has advantages over previous schemes with the same approach, we prove that their scheme is vulnerable to impersonation attack and stolen verification attack, and can be affected by clock synchronization. Therefore we propose a novel authentication scheme to enhance security and overcome limitations existing in Sood’s scheme. Our security analysis shows that our proposed method can efficiently resist known types of attacks. Experimental results also show that the method can be implemented and processed in real-time thus applicable for not only regular computers but also mobile devices.     

Faceless identification based on temporal strips

This paper first presents a novel approach for modelling facial features, Local Directional Texture (LDT), which exploits the unique directional information in image textures for the problem of face recognition. A variant of LDT with privacy-preserving temporal strips (TS) is then considered to achieve faceless recognition with a higher degree of privacy while maintaining high accuracy. The TS uses two strips of pixel blocks from the temporal planes, XT and YT, for face recognition. By removing the reliance on spatial context (i.e., XY plane) for this task, the proposed method withholds facial appearance information from public view, where only one-dimensional temporal information that varies across time are extracted for recognition. Thus, privacy is assured, yet without impeding the facial recognition task which is vital for many security applications such as street surveillance and perimeter access control. To validate the reliability of the proposed method, experiments were carried out using the Honda/UCSD, CK+, CAS(ME)² and CASME II databases. The proposed method achieved a recognition rate of 98.26% in the standard video-based face recognition database, Honda/UCSD. It also offers a 81.92% reduction in the dimension length required for storing the extracted features, in contrast to the conventional LBP-TOP.

     

Page segmentation using minimum homogeneity algorithm and adaptive mathematical morphology

Document layout analysis or page segmentation is the task of decomposing document images into many different regions such as texts, images, separators, and tables. It is still a challenging problem due to the variety of document layouts. In this paper, we propose a novel hybrid method, which includes three main stages to deal with this problem. In the first stage, the text and non-text elements are classified by using minimum homogeneity algorithm. This method is the combination of connected component analysis and multilevel homogeneity structure. Then, in the second stage, a new homogeneity structure is combined with an adaptive mathematical morphology in the text document to get a set of text regions. Besides, on the non-text document, further classification of non-text elements is applied to get separator regions, table regions, image regions, etc. The final stage, in refinement region and noise detection process, all regions both in the text document and non-text document are refined to eliminate noises and get the geometric layout of each region. The proposed method has been tested with the dataset of ICDAR2009 page segmentation competition and many other databases with different languages. The results of these tests showed that our proposed method achieves a higher accuracy compared to other methods. This proves the effectiveness and superiority of our method.     

A Nom historical document recognition system for digital archiving

A Nom historical document recognition system is being developed for digital archiving that uses image binarization, character segmentation, and character recognition. It incorporates two versions of off-line character recognition: one for automatic recognition of scanned and segmented character patterns (7660 categories) and the other for user handwritten input (32,695 categories). This separation is used since including less frequently appearing categories in automatic recognition increases the misrecognition rate without reliable statistics on the Nom language. Moreover, a user must be able to check the results and identify the correct categories from an extended set of categories, and a user can input characters by hand. Both versions use the same recognition method, but they are trained using different sets of training patterns. Recursive X–Y cut and Voronoi diagrams are used for segmentation; k–d tree and generalized learning vector quantization are used for coarse classification; and the modified quadratic discriminant function is used for fine classification. The system provides an interface through which a user can check the results, change binarization methods, rectify segmentation, and input correct character categories by hand. Evaluation done using a limited number of Nom historical documents after providing ground truths for them showed that the two stages of recognition along with user checking and correction improved the recognition results significantly.     

Enhanced security in internet voting protocol using blind signature and dynamic ballots

In this paper, we introduce an internet voting protocol which satisfies desired security requirements of electronic voting. In the newly proposed protocol, we allow the adversaries to get more power than in any previous works. They can be coercers or vote buyers outside, and corrupted parties inside our system. These adversaries also have ability to collude with each other to ruin the whole system. Our main contribution is to design an internet voting protocol which is unsusceptible to most of sophisticated attacks. We employ the blind signature technique and the dynamic ballots instead of complex cryptographic techniques to preserve privacy in electronic voting. Moreover, we also aim at the practical system by improving the blind signature scheme and removing physical assumptions which have often been used in the previous works.     

Development of a quadruped walking robot AiDIN-III using biologically inspired kinematic analysis

This paper presents a bio-inspired mechanism design for a quadruped walking robot. The approach is derived from the observation on the behaviors of quadruped locomotion, skeletal structure, and the study on the stability of walking based on morphological analysis. In the first, we define the design parameters such as the dimensions of the body and limbs, the center of mass position, and locomotion mechanisms based on surveys on the literatures from biologists. Then, by using the parameters, we propose an useful framework for determining the design parameters of a quadruped walking robot. For implementations, we manufacture a dog-type self-contained quadruped walking robot, named AiDIN-III (Artificial Digitigrade for Natural Environment version III) and the effectiveness of the proposed idea is validated via experimental works.     

Electromyographic evaluation of a bed assistive device for abdominal surgery patients in postoperative care

OBJECTIVE: Muscle activity with and without the use of commercially available patient assistive devices during bed rising and lowering was quantified. BACKGROUND: Limited research is available in understanding or evaluating the physical benefits of assistive devices for patient use following major abdominal surgery. METHODS: Twenty healthy participants (9 men, 11 women) took part in a laboratory study to test the effects of device configuration (five levels) and bed elevation angle (0 degree and 30 degrees) on mean and peak upper and lower rectus abdominis and external oblique concentric and eccentric muscle activity. RESULTS: Reduced muscle activity was associated with the use of an assistive device, as compared with manual bed rising (unassisted). Positioning the devices at a higher anchor height and/or increasing the bed elevation angle further reduced muscle activity. Objective and subjective differences between the two assistive devices evaluated in the study were found. CONCLUSION: These results suggest that self-assistive devices may speed recovery because of reduced loads on damaged tissues. APPLICATION: Potential applications of this research include the assessment of other commercially available lift aids or comparisons of self-assistive lift aids with hospital-housed lift aids used to speed recovery rates.