An efficient solution for privacy-preserving, secure remote access to sensitive data

Sharing data that contains personally identifiable or sensitive information, such as medical records, always has privacy and security implications. The issues can become rather complex when the methods of access can vary, and accurate individual data needs to be provided whilst mass data release for specific purposes (for example for medical research) also has to be catered for. Although various solutions have been proposed to address the different aspects individually, a comprehensive approach is highly desirable. This paper presents a solution for maintaining the privacy of data released en masse in a controlled manner, and for providing secure access to the original data for authorized users. The results show that the solution is provably secure and maintains privacy in a more efficient manner than previous solutions.

Spam filtering based on preference ranking

When the average number of spam messages received is continually increasing exponentially, both the Internet service provider and the end user suffer. The lack of an efficient solution may threaten the usability of the email as a communication means. In this paper we present a filtering mechanism applying the idea of preference ranking. This filtering mechanism will distinguish spam emails from other email on the Internet. The preference ranking gives the similarity values for nominated emails and spam emails specified by users, so that the ISP/end users can deal with spam emails at filtering points. We designed three filtering points to classify nominated emails into spam email, unsure email and legitimate email. This filtering mechanism can be applied on both middleware and at the client-side. The experiments show that high precision, recall and TCR (total cost ratio) of spam emails can be predicted for the preference based filtering mechanisms.

An algorithm to median shortest path problem (MSPP) in the design of urban transportation networks

This paper proposes an efficient solution algorithm for realistic multi-objective median shortest path problems in the design of urban transportation networks. The proposed problem formulation and solution algorithm to median shortest path problem is based on three realistic objectives via route cost or investment cost, overall travel time of the entire network and total toll revenue. The proposed solution approach to the problem is based on the heuristic labeling and exhaustive search technique in criteria space and solution space of the algorithm respectively. The first labels each node in terms of route cost and deletes cyclic and infeasible paths in criteria space imposing cyclic break and route cost constraint respectively. The latter deletes dominated paths in terms of objectives vector in solution space in order to identify a set of Pareto optimal paths. The approach, thus, proposes a non-inferior solution set of Pareto optimal paths based on non-dominated objective vector and leaves the ultimate decision to decision-makers for purpose specific final decision during applications. A numerical experiment is conducted to test the proposed algorithm using artificial transportation network. Sensitivity analyses have shown that the proposed algorithm is advantageous and efficient over existing algorithms to find a set of Pareto optimal paths to median shortest paths problems.

Collaboration in 3D shared spaces using X3D and VRML

We propose a framework for visual and haptic collaboration in 3D shared virtual spaces. Virtual objects can de declared as shared objects which visual and physical properties are rendered synchronously on each client computer. We introduce virtual tools which are shared objects associated with interactive and haptic devices. We implement the proposed ideas as new pilot versions of BS Collaborate server and BS Contact VRML/X3D viewer. In our collaborative framework, two pipelines-visual and haptic-complement each other to provide a simple and efficient solution to problem requiring collaboration in shared virtual spaces on the Web. We discuss two implementation frameworks based on the strong and thin server concepts.

A framework for visual and haptic collaboration in shared virtual spaces

We propose a framework for visual and haptic collaboration in X3D/VRML shared virtual spaces. In this collaborative framework, two pipelines— visual and haptic—complement each other to provide a simple and efficient solution to problem requiring collaboration in shared virtual spaces on the web. We consider shared objects defined as virtual object with their visual and physical properties rendered synchronously on each client computer. We introduce virtual tools which are shared objects associated with interactive and haptic devices. We implemented the proposed ideas as a server-client framework with a dedicated viewer. We discuss two implementation frameworks based on the strong and thin server concepts.

Type-aware task placement in geo-distributed data centers with low OPEX using data center resizing

With the rising demands on cloud services, the electricity consumption has been increasing drastically as the main operational expenditure (OPEX) to data center providers. The geographical heterogeneity of electricity prices motivates us to study the type-aware task placement problem over geo-distributed data centers. With the consideration of the diversity of user requests and server clusters in modern data centers, we formulate an optimization problem that minimizes OPEX while guaranteeing the quality-of-service, i.e., the expected response time of tasks. Furthermore, an efficient solution is designed for this formulated problem. The experimental results show that our proposal achieves much higher cost-efficiency than the greedy algorithm and much approaches the optimal results. © 2014 IEEE.

A general communication cost optimization framework for big data stream processing in geo-distributed data centers

With the explosion of big data, processing large numbers of continuous data streams, i.e., big data stream processing (BDSP), has become a crucial requirement for many scientific and industrial applications in recent years. By offering a pool of computation, communication and storage resources, public clouds, like Amazon's EC2, are undoubtedly the most efficient platforms to meet the ever-growing needs of BDSP. Public cloud service providers usually operate a number of geo-distributed datacenters across the globe. Different datacenter pairs are with different inter-datacenter network costs charged by Internet Service Providers (ISPs). While, inter-datacenter traffic in BDSP constitutes a large portion of a cloud provider's traffic demand over the Internet and incurs substantial communication cost, which may even become the dominant operational expenditure factor. As the datacenter resources are provided in a virtualized way, the virtual machines (VMs) for stream processing tasks can be freely deployed onto any datacenters, provided that the Service Level Agreement (SLA, e.g., quality-of-information) is obeyed. This raises the opportunity, but also a challenge, to explore the inter-datacenter network cost diversities to optimize both VM placement and load balancing towards network cost minimization with guaranteed SLA. In this paper, we first propose a general modeling framework that describes all representative inter-task relationship semantics in BDSP. Based on our novel framework, we then formulate the communication cost minimization problem for BDSP into a mixed-integer linear programming (MILP) problem and prove it to be NP-hard. We then propose a computation-efficient solution based on MILP. The high efficiency of our proposal is validated by extensive simulation based studies.

Stabilizing l1-norm prediction models by supervised feature grouping

Emerging Electronic Medical Records (EMRs) have reformed the modern healthcare. These records have great potential to be used for building clinical prediction models. However, a problem in using them is their high dimensionality. Since a lot of information may not be relevant for prediction, the underlying complexity of the prediction models may not be high. A popular way to deal with this problem is to employ feature selection. Lasso and l1-norm based feature selection methods have shown promising results. But, in presence of correlated features, these methods select features that change considerably with small changes in data. This prevents clinicians to obtain a stable feature set, which is crucial for clinical decision making. Grouping correlated variables together can improve the stability of feature selection, however, such grouping is usually not known and needs to be estimated for optimal performance. Addressing this problem, we propose a new model that can simultaneously learn the grouping of correlated features and perform stable feature selection. We formulate the model as a constrained optimization problem and provide an efficient solution with guaranteed convergence. Our experiments with both synthetic and real-world datasets show that the proposed model is significantly more stable than Lasso and many existing state-of-the-art shrinkage and classification methods. We further show that in terms of prediction performance, the proposed method consistently outperforms Lasso and other baselines. Our model can be used for selecting stable risk factors for a variety of healthcare problems, so it can assist clinicians toward accurate decision making.

A non-fullerene electron acceptor based on central carbazole and terminal diketopyrrolopyrrole functionalities for efficient, reproducible and solution-processable bulk-heterojunction devices

A novel, solution-processable non-fullerene electron acceptor, 6,6′-((9-(heptadecan-9-yl)-9H-carbazole-2,7-diyl)bis(thiophene-5,2-diyl))bis(2,5-bis(2-ethylhexyl)-3-(thiophen-2-yl)-2,5-dihydropyrrolo[3,4-c]pyrrole-1,4-dione) (coded as N7), based on central carbazole and terminal diketopyrrolopyrrole building blocks was designed, synthesized and characterized. N7 displayed excellent solubility, thanks to its design allowing incorporation of numerous lipophilic chains, thermal stability, and afforded a 2.30% power conversion efficiency with a high open-circuit voltage (1.17 V) when tested with the conventional donor polymer poly(3-hexylthiophene) in solution-processable bulk-heterojunction devices. To our knowledge, not only is N7 the first reported chromophore based on carbazole and diketopyrrolopyrrole functionalities but the open-circuit voltage reported here is among the highest values for a single junction bulk-heterojunction device that has been fabricated using a simple device architecture, with reproducible outcomes and with no special treatment.

Naphthalene diimide-based non-fullerene acceptors for simple, efficient, and solution-processable bulk-heterojunction devices

Two solution processable, non-fullerene electron acceptors, 2,2′-(((2,7-dioctyl-1,3,6,8-tetraoxo-1,2,3,6,7,8-exahydrobenzo[lmn][3,8]phenanthroline-4,9-diyl)bis(thiophene-5,2-diyl))bis(methanylylidene))dimalononitrile (R1) and (2Z,2′Z)-3,3′-((2,7-dioctyl-1,3,6,8-tetraoxo-1,2,3,6,7,8-hexahydrobenzo[lmn][3,8]phenanthroline-4,9-diyl)bis(thiophene-5,2-diyl))bis(2-(4-nitrophenyl) acrylonitrile) (R2), comprised of central naphthalene diimide and two different terminal accepting functionalities, malononitrile and 2-(4-nitrophenyl)acetonitrile, respectively, were designed and synthesised. The central and terminal accepting functionalities were connected via a mild conjugated thiophene linker. Both of the new materials (R1 and R2) displayed high thermal stability and were found to have energy levels matching those of the archetypal electron donor poly(3-hexylthiophene). A simple, solution-processable bulk-heterojunction device afforded a promising power conversion efficiency of 2.24% when R2 was used as a non-fullerene electron acceptor along with the conventional donor polymer poly(3-hexylthiophene). To the best of our knowledge, the materials reported herein are the first examples in the literature where synchronous use of such accepting blocks is demonstrated for the design and development of efficient non-fullerene electron acceptors.

Cobalt carbonate hydroxide nanowire array on ti mesh: an efficient and robust 3D catalyst for on-demand hydrogen generation from alkaline naBH4 solution.

In this work, for the first time, a cobalt carbonate hydroxide (Co(CO3 )0.5 (OH)⋅0.11 H2 O) nanowire array on Ti mesh (CHNA/Ti) was applied to drive the dehydrogenation of alkaline NaBH4 solution for on-demand hydrogen production. Compared with other nanostructured Co-based catalyst systems, CHNA/Ti can be activated more quickly and separated easily from fuel solutions. This self-supported cobalt salt nanowire array catalyst works as an efficient and robust 3D catalyst for the hydrolysis reaction of NaBH4 with a hydrogen generation rate of 4000 mL min(-1)  gCo (-1) and a low apparent activation energy of 39.78 kJ mol(-1) and offers an attractive system for on-demand hydrogen generation.

Integrated governance: a possible solution for a sustainable private sector led development in Bangladesh?

In the quest for 'good governance', the developing countries have embarked on ambitious NPM style market-oriented reform policies mainly advocated by international development agencies (IDA) over the last two decades. Bangladesh has been pursuing decades of market-oriented reforms advocated by IDAs with the prime objectives of achieving an efficient, cost effective service delivery through increased involvement of the private sector. The shift towards marketisation has led to a complex, horizontal and networked structure of partnerships between state and non state actors. The private sector and NOOs are now delivering goods and services which were once the exclusive domain of the state. These changes have however, not been associated with changes in institutional arrangements, safeguards and regulation required to support the private sector led development, which is not sustained independently of the context in which it operates. Using the agriculture input sector as an exemplar, this paper explores the constraints of sustainable private sector led development. The paper argues that the main impediment to private sector led development in this sector centre on lack of good governance. In addition, lack of an integrated market structure, market information, capacity and awareness building are other factors that are inhibiting the private sector led development. We argue that a functional governance model is required in Bangladesh that engages the state, civil society and the private sector to work effectively in a participatory approach to deal with the constraints of private sector led development and for improving good governance.

Computational aspects of the numerical solution of SDEs

In the last 30 to 40 years, many researchers have combined to build the knowledge base of theory and solution techniques that can be applied to the case of differential equations which include the effects of noise. This class of ``noisy'' differential equations is now known as stochastic differential equations (SDEs). Markov diffusion processes are included within the field of SDEs through the drift and diffusion components of the Itô form of an SDE. When these drift and diffusion components are moderately smooth functions, then the processes' transition probability densities satisfy the Fokker-Planck-Kolmogorov (FPK) equation -- an ordinary partial differential equation (PDE). Thus there is a mathematical inter-relationship that allows solutions of SDEs to be determined from the solution of a noise free differential equation which has been extensively studied since the 1920s. The main numerical solution technique employed to solve the FPK equation is the classical Finite Element Method (FEM). The FEM is of particular importance to engineers when used to solve FPK systems that describe noisy oscillators. The FEM is a powerful tool but is limited in that it is cumbersome when applied to multidimensional systems and can lead to large and complex matrix systems with their inherent solution and storage problems. I show in this thesis that the stochastic Taylor series (TS) based time discretisation approach to the solution of SDEs is an efficient and accurate technique that provides transition and steady state solutions to the associated FPK equation. The TS approach to the solution of SDEs has certain advantages over the classical techniques. These advantages include their ability to effectively tackle stiff systems, their simplicity of derivation and their ease of implementation and re-use. Unlike the FEM approach, which is difficult to apply in even only two dimensions, the simplicity of the TS approach is independant of the dimension of the system under investigation. Their main disadvantage, that of requiring a large number of simulations and the associated CPU requirements, is countered by their underlying structure which makes them perfectly suited for use on the now prevalent parallel or distributed processing systems. In summary, l will compare the TS solution of SDEs to the solution of the associated FPK equations using the classical FEM technique. One, two and three dimensional FPK systems that describe noisy oscillators have been chosen for the analysis. As higher dimensional FPK systems are rarely mentioned in the literature, the TS approach will be extended to essentially infinite dimensional systems through the solution of stochastic PDEs. In making these comparisons, the advantages of modern computing tools such as computer algebra systems and simulation software, when used as an adjunct to the solution of SDEs or their associated FPK equations, are demonstrated.

Wool powders used as sorbents to remove Co2+ ions from aqueous solution

The Co2+ sorption of two wool powders was investigated using its radioisotope 57Co (T1/2=271.8 days and γ=122.1 and 136.5 keV) as a tracer. The effects of the type of buffer, the pH value, the contact time and the initial concentration of Co2+ on the sorption behaviour of wool powders were studied. The Co2+ releasing ability of wool powders and the re-use of wool powders to sorb Co2+ were also examined. The optimum sorption of Co2+ by the powders occurred at pH 8 in phosphate buffer and pH 10 in ammonium sulphate buffer. Fourier-transform infrared spectroscopy (FTIR) was used to study the changes in chemical structure of the wool after exposure to both buffer solutions. Compared to the untreated wool fibre, the fine wool powders showed rapid sorption rates and high sorption capacities for Co2+. Co2+ ions were recovered after exposing the Co2+ loaded wool to HCl (0.1 M) and buffer at pH 3 (glycine/sodium chloride). After releasing Co2+ ions from wool powders, the efficiency of wool powders re-used to sorb Co2+ was 80% of that of the fresh wool powders. It is concluded from this study that wool powder can be used as an efficient sorbent to remove and release Co2+ from solution.

Shear-enhanced solution precipitation : a simple process to produce short polymeric nanofibers

The growing interest in polymeric nanofibers has been increasing the push for the development of simple and efficient nanofiber-preparation techniques. We herein describe how a conventional solution process is readapted to suit the needs for fast and efficient production of short polymeric nanofibers. Poly(ethylene-co-acrylic acid) (PEAA), a semi-crystalline polymer, was used as model. When a PEAA solution was injected into an alcoholic non-solvent while simultaneously applying high shear to the non-solvent system, PEAA nanofibers were obtained with average diameter as thin as 113 nm and length as short as 4.5 _m. The fiber diameter and length were also adjustable by varying the operating parameters. This one-step technique advances the currently available nanofabrication tools by adjusting a widely accepted concept to the nano-scale. It may constitute a viable method for large-scale production of short polymeric nanofibers.