Sulfur-impregnated, sandwich-type, hybrid carbon nanosheets with hierarchical porous structure for high-performance lithium-sulfur batteries

Sandwich-type hybrid carbon nanosheets (SCNMM) consisting of graphene and micro/mesoporous carbon layer are fabricated via a double template method using graphene oxide as the shape-directing agent and SiO2 nanoparticles as the mesoporous guide. The polypyrrole synthesized in situ on the graphene oxide sheets is used as a carbon precursor. The micro/mesoporous strcutures of the SCNMM are created by a carbonization process followed by HF solution etching and KOH treatment. Sulfur is impregnated into the hybrid carbon nanosheets to generate S@SCNMM composites for the cathode materials in Li-S secondary batteries. The microstructures and electrochemical performance of the as-prepared samples are investigated in detail. The hybrid carbon nanosheets, which have a thickness of about 10-25 nm, high surface area of 1588 m2 g-1, and broad pore size distribution of 0.8-6.0 nm, are highly interconnected to form a 3D hierarchical structure. The S@SCNMM sample with the sulfur content of 74 wt% exhibits excellent electrochemical performance, including large reversible capacity, good cycling stability and coulombic efficiency, and good rate capability, which is believed to be due to the structure of hybrid carbon materials with hierarchical porous structure, which have large specific surface area and pore volume.

Polymorphic malware detection using Hierarchical Hidden Markov Model

Binary signatures have been widely used to detect malicious software on the current Internet. However, this approach is unable to achieve the accurate identification of polymorphic malware variants, which can be easily generated by the malware authors using code generation engines. Code generation engines randomly produce varying code sequences but perform the same desired malicious functions. Previous research used flow graph and signature tree to identify polymorphic malware families. The key difficulty of previous research is the generation of precisely defined state machine models from polymorphic variants. This paper proposes a novel approach, using Hierarchical Hidden Markov Model (HHMM), to provide accurate inductive inference of the malware family. This model can capture the features of self-similar and hierarchical structure of polymorphic malware family signature sequences. To demonstrate the effectiveness and efficiency of this approach, we evaluate it with real malware samples. Using more than 15,000 real malware, we find our approach can achieve high true positives, low false positives, and low computational cost.

Modelling multilevel data in multimedia : A hierarchical factor analysis approach

Multimedia content understanding research requires rigorous approach to deal with the complexity of the data. At the crux of this problem is the method to deal with multilevel data whose structure exists at multiple scales and across data sources. A common example is modeling tags jointly with images to improve retrieval, classification and tag recommendation. Associated contextual observation, such as metadata, is rich that can be exploited for content analysis. A major challenge is the need for a principal approach to systematically incorporate associated media with the primary data source of interest. Taking a factor modeling approach, we propose a framework that can discover low-dimensional structures for a primary data source together with other associated information. We cast this task as a subspace learning problem under the framework of Bayesian nonparametrics and thus the subspace dimensionality and the number of clusters are automatically learnt from data instead of setting these parameters a priori. Using Beta processes as the building block, we construct random measures in a hierarchical structure to generate multiple data sources and capture their shared statistical at the same time. The model parameters are inferred efficiently using a novel combination of Gibbs and slice sampling. We demonstrate the applicability of the proposed model in three applications: image retrieval, automatic tag recommendation and image classification. Experiments using two real-world datasets show that our approach outperforms various state-of-the-art related methods.

A Bayesian nonparametric model for hierarchical sequence of images

 Scale features are useful for a great number of applications in computer vision. However, it is difficult to tolerate diversities of features in natural scenes by parametric methods. Empirical studies show that object frequencies and segment sizes follow the power law distributions which are well generated by Pitman-Yor (PY) processes. Based on mid-level segments, we propose a hierarchical sequence of images to obtain scale information stored in a hierarchical structure through the hierarchical Pitman-Yor (HPY) model which is expected to tolerate uncertainty of natural images. We also evaluate our representation by the application of segmentation.

An introduction to eRoadmapping : providing learning paths for students and empowering teachers

This paper reports on the development of an innovative teaching strategy: an eRoadmap.  Based on the theory of conceptual mapping, the eRoadmap provides an interactive, hierarchical structure for course delivery, using the readily accessible platform provided by Microsoft PowerPoint.  For the student, the eRoadmap provides a self-paced learning environment which encourages student engagement; for the teacher, it provides an environment for the development of a course framework, and the integration of teaching materials from a variety of sources.  Futher advantages of the eRoadmap from the perspectives of both students and teachers are discussed, and future directions for development, evaluation and research are outlined.

Understanding the impact of organisational downsizing on knowledge sharing

Careful consideration by managers of the potential impact of the popular strategy of economic restructuring (downsizing) on organisational structure and culture could improve the quality of organisational knowledge sharing, however this influence has not yet been addressed in the knowledge management literature. This paper explores how a strategy of downsizing may reshape organisational structure and culture and inhibit organisational knowledge sharing, drawing on an interpretive case study of knowledge sharing in an information technology services function at a large Australian education service provider. Key findings indicate that when specialised teams are downsized, subcultures may develop where teams become mistrustful and insular, and knowledge sharing is constrained across teams. Further, when a hierarchical structure is present and downsizing occurs, managers may become more cautious about sharing knowledge with subordinates. The study also suggests that Internet technologies may play a key role in helping to compensate for the shortfall in knowledge stock resulting from downsizing. In conclusion, this paper highlights an important need for companies to consider the potential negative influences of downsizing on organisationalknowledge sharing.

The pragmatics of text facilitation : the study of academic English of native and non-native writers

In this paper I describe the discursive strategies related to the writer–reader textual reciprocity. I focus on one way of achieving such reciprocity -- the employment by the writer of facilitative schematic structures and metalanguage where one text segment signposts information conveyed in the segment that follows. I refer to these facilitative schematic structures as "organising relational schemata". I see organising relations as the most explicit components of the rhetorical structure of texts: they illuminate the main message and aid the reader's cognitive processes in the orientation of how information is conveyed by text.
This paper discusses the way the choices of organising relations and associated metalanguage by the writers in different cultures and different discourse communities contribute to the communicative homeostasis in the world of text. It shows how the influence of a native culture and intellectual style together with the forces operating within the writer's international disciplinary community interact in the authorial guidance in the scholarly prose.
I introduce and exemplify three types of organising relational structures: Advance Organisers, Introducers and Enumerators. I trace the utilisation of these three types of relations in sociology research papers written in English and produced in "Anglo" and Polish academic discourse comunities by native English speaking and native Polish speaking scholars. The relational typology adopted is based on a study by Golebiowski (2002), which proposed a theoretical framework for the examination of discoursal structure of research papers, referred to as FARS – Framework for the Analysis of the Rhetorical Structure of Texts. FARS entails a relational taxonomy which displays a pattern of rhetorical relations utilised by the writer to achieve textual coherence.
I describe intertextual differences in the frequency of occurrence of organising relations, their degree of explicitness and their positioning in the hierarchical structure of texts. Differences in the mode of employment of textual organisers suggest that the rhetorical structure of English research prose produced by non-native speakers cannot escape being shaped by the characteristics and conventions of the authors’ first language. They are also attributed to cultural norms and conventions as well as educational systems prevailing within the discourse communities which constitute the social contexts of texts.

Modelling multi-criteria decision analysis for benchmarking management practices in project management

The link between management practices and worker’s motivations impacting construction productivity is being considered as significant among the research community. This research aimed to identify and analyse the underlying attributes impacting construction productivity from the site management perspective. This research presents a framework designed to analyse and quantify the relative relevance of different drivers in the determination of productivity levels and the degree of effectiveness of potential opportunities for improving performance of overall projects. Owing to the complexity of construction projects and underlying conflicting drivers influencing higher worker’s productivity, the Analytical Hierarchy Process (AHP) is employed to deal with interdependent relationships within a multi-criteria decision-making model. In the analytical approach, the large unstructured decision parameters are identified first and then are broken down into the manageable and measurable components using a top down hierarchical structure. This paper demonstrates an example to illustrate how to empirically analyse and prioritise a set of influencing parameters as selection criteria in devising appropriate management practices to ensure higher productivity vis-à-vis optimum performance of projects.

Integrated governance : a pre-requisite for sustainable market-orientated development in Bangladesh

Using agriculture input sector as an exemplar, this article assesses Bangladesh's efforts towards a market-oriented development approach. It examines the changing role of the state following the market-based reforms undertaken in this sector and assesses whether the outcomes of the reforms are sustainable. Findings reveal that, although the current move towards a market-oriented approach has led to a shift away from a state-dominated hierarchical structure, it has not been associated with adequate changes in institutional arrangements, safeguards, and regulation. As a result, despite notable achievements of the reforms, the sustainability of these successes is in question. To facilitate participatory, accountable, and sustainable, market-oriented development, the paper proposes an integrated governance model linking state, business, and civil society.

Middle managerial careers in the 21st century

Managerial careers no longer conform to traditional career paths, progressing within the hierarchical structure of one or two organisations. Instead, organisational restructuring and changed business practices have impacted middle managers' job security and the need to take personal responsibility for their careers. Concurrently. the nature ofmiddle managerial work has altered - bringing increasing intensity and a requirement to manage within new workplace practices such as flexibility initiatives and short-term managerial contracts. These changes have implications for how human resource professionals both attract and retain talented managers. This paper argues for a critical re-consideration ofthe distinct nature ofmiddle managerial careers.

Secure connectivity model in wireless sensor networks (WSN) using first order Reed-Muller codes

In this paper, we suggest the idea of separately treating the connectivity and communication model of a Wireless Sensor Network (WSN). We then propose a novel connectivity model for a WSN using first order Reed-Muller Codes. While the model has a hierarchical structure, we have shown that it works equally well for a Distributed WSN. Though one can use any communication model, we prefer to use the communication model suggested by Ruj and Roy [1] for all computations and results in our work. Two suitable secure (symmetric) cryptosystems can then be applied for the two different models, connectivity and communication respectively. By doing so we have shown how resiliency and scalability are appreciably improved as compared to Ruj and Roy [1].

Symbolic representation and distributed matching strategies for schematics

This paper describes object-centered symbolic representation and distributed matching strategies of 3D objects in a schematic form which occur in engineering drawings and maps. The object-centered representation has a hierarchical structure and is constructed from symbolic representations of schematics. With this representation, two independent schematics representing the same object can be matched. We also consider matching strategies using distributed algorithms. The object recognition is carried out with two matching methods: (1) matching between an object model and observed data at the lowest level of the hierarchy, and (2) constraints propagation. The first is carried out with symbolic Hopfield-type neural networks and the second is achieved via hierarchical winner-takes-all algorithms

A multi-agent incremental negotiation scheme for meetings scheduling

We present an agent-oriented approach to the meeting scheduling problem and propose an incremental negotiation scheme that makes use of a hierarchical structure of an individual agent's working knowledge. First, we formalise the meeting scheduling problem in a multi-agent context, then elaborate on the design of a common agent architecture of all agents in the system. As a result, each agent becomes a modularised computing unit yet possesses high autonomy and robust interface with other agents. The system reserves the meeting participants' privacy since there are no agents with dominant roles, and agents can communicate at an abstract level in their hierarchical structures

Hyaluronic acid–collagen network interactions during the dynamic compression and recovery of cartilage

A compression cell designed to fit inside an NMR spectrometer was used to investigate (i) the in situ dynamic strain response and structural changes of the internal pore network, and (ii) the diffusion and flow of interstitial water, in full thickness cartilage samples as they were mechanically deformed under a constant compressive load (pressure) and then allowed to recover (swell again) when the load was removed. Selective enzymatic digestion of the collagen fibril network and the glycopolysaccharide hyaluronic acid (HA) was performed to mimic some of the structural and compositional changes associated with osteoarthritis. Digestion of collagen gave rise to mechanical ‘dynamic softening’ and—perhaps more importantly—nearly complete loss in the ability to recover through swelling, both effects due to the disruption of the hierarchical structure and fibril interconnectivity in the collagen network which adversely affects its ability to deform reversibly and to properly regulate the pressurization and resulting rate and direction of interstitial fluid flow. In contrast, digestion of HA inside the collagen pore network caused the cartilage to ‘dynamically stiffen’ which is attributed to the decrease in the osmotic (entropic) pressure of the digested HA molecules confined in the cartilage pores that causes the network to contract and thereby become less permeable to flow. These digestioninduced changes in cartilage’s properties reveal a complex relationship between the molecular weight and concentration of the HA in the interstitial fluid, and the structure and properties of the collagen fibril pore network, and provide new insights into how changes in either could influence the onset and progression of osteoarthritis.