Estimation of colloidal deposition from heterogeneous populations

This paper reports a study of size-heterogeneous colloid filtration in a new bed using different types of colloids under different conditions of flow and solution chemistry. Depth-wise variation of the particle-size-distributions f_i(x), and the total liquid-phase colloid concentration, C(x) are measured which are used to estimate the depth-wise variation of the liquid-phase concentration for each distinct section of the heterogeneous population, C_i(x). It is observed that log C_i(x) is linear with depth, for some systems, while it shows deviation from linearity, with the slope decreasing with depth, for others. Deposition-rates for these distinct sections of the heterogeneous population, k_i, are estimated from the slopes of the log C_i(x) data. These deposition-rates were then compared with predicted homogeneous-population deposition-rates from Colloid Filtration Theory (CFT), which shows agreement between the CFT-based-deposition-rates and heterogeneous-population-data based deposition-rates, for low flow velocities. At higher flow velocities a gap between the CFT-based and Data-based deposition-rates is observed. Deposition-rates from CFT are then used in a heterogeneous-colloid-filtration model, to examine if heterogeneous colloid deposition can be expressed as the sum of its parts. It is observed that, the sum-of-parts model provides a reasonable estimate of colloidal deposition from heterogeneous populations. Based on these results, it is possible to make predictions of colloidal deposition from complex heterogeneous suspensions. A new method for studying heterogeneous colloid filtration is also proposed.     

Laccase-membrane reactors for decolorization of an acid azo dye in aqueous phase: Process optimization

In the present investigation, performance of various laccase-membrane reactor configurations including direct enzyme contact, enzyme impregnated, immobilized enzyme and a reactor system based on laccase immobilization in chitosan membranes for decolorization of azo dye (acid black 10 BX) were examined using laccase enzyme purified from white rot fungi Pleurotus ostreatus 1804. A five-step laccase purification procedure was employed, which improved the enzymatic activity by 8.27 folds. Laccase was confirmed by comparing with the standard marker using SDS-PAGE electrophoresis, which showed molecular weight of 63 kDa. Experimental data showed that laccase has great potential for color removal without addition of external redox mediators. Various process parameters viz. aqueous phase of pH 6.0, enzyme concentration of 1.75 U/ml, dye concentration of 20 mg/L, temperature of 30 °C and reaction time of 120 min were optimized to achieve maximum decolorization efficiencies. Moreover, different laccase-membrane reactor configurations were tested to determine the efficacy of repeated application of laccase on dye decolorization process. Among the different reactor configurations employed, laccase encapsulated in chitosan membrane showed advantages such as short-term contact period and reusability of enzyme for a number of cycles.     

Discrete Modeling of Growth of Hairy Roots in a Mist Bioreactor

Hairy root culture is a promising route for large‐scale secondary metabolite production. A discrete model is developed to study the kinetic growth of these valuable roots in a reactor. The growth process is defined to occur in three sequential phases. The elongation rate is modeled as exponential growth with the growth coefficient being dependent on mass transfer coefficient, nutrient concentration difference, and distribution of nutrients in growth and sustenance requirements. Results indicate that the primary root growth is reduced by one‐fifth of its initial growth rate due to the branching process, and the growth of new branches is significantly faster than its primary root growth due to internal transport of nutrients. The model is successfully validated against experimental findings. Its integration with spatio‐temporal variation of nutrients in a reactor will be a crucial input to large‐scale production of hairy roots.     

Evading stepping-stone detection under the cloak of streaming media with SNEAK

Network-based intrusions have become a serious threat to the users of the Internet. To help cover their tracks, attackers launch attacks from a series of previously compromised systems called stepping stones. Timing correlations on incoming and outgoing packets can lead to detection of the stepping stone and can be used to trace the attacker through each link. Prior work has sought to counter the possibility of the attacker employing chaff packets and randomized delays. To date, however, researchers have not accounted for the full range of techniques that a sophisticated attacker could apply. In this work, we show that such an attacker could avoid detection by the best known stepping-stone detection methods. We propose a simple buffering technique that could be used by an attacker on a stepping stone to evade detection. This technique makes the timing of packets in the output flow of the stepping stone entirely independent of the timing of packets from the input flow, thereby eliminating the timing link that makes existing stepping-stone detection methods possible. To accomplish this, we only require buffering at the stepping stone and enough chaff packets to generate a constant-rate flow. This traffic has the characteristics of a multimedia stream, such as Voice over IP (VoIP), which is quite common on the Internet today. To test the effectiveness of our technique, we implemented it in a prototype stepping-stone application and tested its performance on the DETER testbed and the PlanetLab testbed. Our prototype successfully evades watermark-based detection and provides reasonable performance for shell commands over at least three stepping stones.     

QoS-Aware Admission Control and Dynamic Resource Provisioning Framework in Ubiquitous Multimedia Computing Environments

A ubiquitous service deployment is emerging in the multimedia, networking, and wireless mobile computing area. Therefore, there has been an increasing demand for ubiquitous computing environments to support a certain degree of quality of service (QoS) to meet various service requirements from different computing and networking applications, and to better utilize the computing resources. However, supporting QoS in the ubiquitous computing environments has also raised great concerns regarding the applicability of any QoS solution. Management of such ubiquitous multimedia applications requires new mechanisms, i.e., Soft-QoS framework, to be developed for admission control, negotiation, allocation, and scheduling. In this paper, we present a novel negotiated admission control algorithm that exploits the degradability property of applications to improve the performance of the system. The algorithm is based on setting aside a portion of the resources as reserves and managing it intelligently, so that the total utility of the system can be maximized. The mixed greedy and predictive strategy leads to an efficient protocol that also improves the system performance. We use the constructs of application benefit functions and resource demand functions in the integrated admission control and negotiation protocol. We applied our Soft-QoS framework to the admission controlling and resource scheduling for ubiquitous multimedia devices such as Continuous Media (CM) or Video-On-Demand (VOD) servers, where multimedia applications can generally tolerate certain variations on QoS parameters by providing multiple classes with consistently proportional rather than absolute QoS. Extensive simulation experiments are presented in the paper to evaluate the performance of the novel mechanisms and compare it against some other methods used in the past.This work was in part funded by DARPA through the SPAWARSYSCEN under Contract Number N66001-97-C-8525 and SK Telecom, Korea, under Contract Number (KU-R0405721).     

Tag-Splitting: Adaptive Collision Arbitration Protocols for RFID Tag Identification

Tag identification is an important tool in RFID systems with applications for monitoring and tracking. A RFID reader recognizes tags through communication over a shared wireless channel. When multiple tags transmit their IDs simultaneously, the tag-to-reader signals collide and this collision disturbs a reader's identification process. Therefore, tag collision arbitration for passive tags is a significant issue for fast identification. This paper presents two adaptive tag anticollision protocols: an Adaptive Query Splitting protocol (AQS), which is an improvement on the query tree protocol, and an Adaptive Binary Splitting protocol (ABS), which is based on the binary tree protocol and is a de facto standard for RFID anticollision protocols. To reduce collisions and identify tags efficiently, adaptive tag anticollision protocols use information obtained from the last process of tag identification. Our performance evaluation shows that AQS and ABS outperform other tree-based tag anticollision protocols.     

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Tag identification is an important tool in RFID systems with applications for monitoring and tracking. A RFID reader recognizes tags through communication over a shared wireless channel. When multiple tags transmit their IDs simultaneously, the tag-to-reader signals collide and this collision disturbs a reader's identification process. Therefore, tag collision arbitration for passive tags is a significant issue for fast identification. This paper presents two adaptive tag anticollision protocols: an adaptive query splitting protocol (AQS), which is an improvement on the query tree protocol, and an adaptive binary splitting protocol (ABS), which is based on the binary tree protocol and is a de facto standard for RFID anticollision protocols. To reduce collisions and identify tags efficiently, adaptive tag anticollision protocols use information obtained from the last process of tag identification. Our performance evaluation shows that AQS and ABS outperform other tree-based tag anticollision protocols     

Enhancing the applicability of near infrared spectroscopy for estimating specific gravity of green timber from Eucalyptus tereticornis by developing composite calibration using both radial and tangential face of wood

Specific gravity is a very important factor in determining the economics of wood and wood products. This study is aimed to apply the near infrared spectroscopy technique with integrating sphere and fiber optic probe accessories for fast prediction of specific gravity of green timber (moisture content 27–30 %) of Eucalyptus tereticornis from 10 to 12 year old plantation. Specific gravity (basic density) was determined by conventional method (oven dry wt/green volume) and correlated with near infrared spectra using partial least square (PLS) regression. Calibrations using radial face, tangential face and composite face (both radial and tangential) were developed and compared. Coefficient of determination of cross validation ( $ {\text{r}}_{\text{cv}}^{ 2} $ ) for radial-longitudinal, tangential-longitudinal solid strips samples and composite face (both radial and tangential) was between 0.74–0.77 and 0.64–0.77 using integrating sphere and fiber optic probe, respectively. The coefficient of determination of prediction ( $ {\text{r}}_{\text{p}}^{ 2} $ ) was between 0.73–0.85 (with integrating sphere) and 0.69–0.83 (with fiber optic probe). The ratio of performance deviation (RPD) ranges from 2.06 to 2.46 for all models. Root mean square error of prediction (RMSEP) was higher than root mean square error of cross validation (RMSECV). For composite models with radial and tangential face $ {\text{r}}_{\text{cv}}^{ 2} $ / $ {\text{r}}_{\text{p}}^{ 2} $ was 0.74/0.76 using integrating sphere and 0.71/0.83 with fiber optic probe with Quant 2 automatic factors optimization process. The results indicate that the composite model is just as good as the radial and tangential face models and can adequately address the problem where it is difficult to obtain perfect radial or tangential surface, particularly in small girth plantation timber or where surface recognition is difficult.     

Improving bagging performance through multi-algorithm ensembles

Working as an ensemble method that establishes a committee of classifiers first and then aggregates their outcomes through majority voting, bagging has attracted considerable research interest and been applied in various application domains. It has demonstrated several advantages, but in its present form, bagging has been found to be less accurate than some other ensemble methods. To unlock its power and expand its user base, we propose an approach that improves bagging through the use of multi-algorithm ensembles. In a multi-algorithm ensemble, multiple classification algorithms are employed. Starting from a study of the nature of diversity, we show that compared to using different training sets alone, using heterogeneous algorithms together with different training sets increases diversity in ensembles, and hence we provide a fundamental explanation for research utilizing heterogeneous algorithms. In addition, we partially address the problem of the relationship between diversity and accuracy by providing a non-linear function that describes the relationship between diversity and correlation. Furthermore, after realizing that the bootstrap procedure is the exclusive source of diversity in bagging, we use heterogeneity as another source of diversity and propose an approach utilizing heterogeneous algorithms in bagging. For evaluation, we consider several benchmark data sets from various application domains. The results indicate that, in terms of F1-measure, our approach outperforms most of the other state-of-the-art ensemble methods considered in experiments and, in terms of mean margin, our approach is superior to all the others considered in experiments.     

Transaction recovery in federated autonomous databases

Transaction management for federated database systems (FDBSs), where each participating DBMS is autonomous, supports global transactions that can access more than one database. A number of concurrency control algorithms exist for the failure-free environment. Handling transaction failure, due to concurrency control or site related reasons, becomes especially difficult in the presence of autonomy. Due to local autonomy, carrying out 2-phase commit may not be possible. This can be simulated by providing a server on top of the pre-existing DBMS at each site, which is responsible for submitting the local operations to the associated DBMS and communicating with the transaction's originating site. In this paper we formalize the problem of ensuring transaction consistency in an FDBS environment in the presence of failure. The key problem is that due to autonomy, the local DBMS and FDBS may have different views of an execution sequence generated at a site.Local recoverability is identified as the property of local execution sequences necessary for correctness. The other main problem is of guaranteeing that the various locally recoverable histories are consistent with each other. These identified properties are necessary and sufficient conditions for the correctness of FDBS recovery algorithms, and can be used to evaluate the correctness of the proposed algorithms. This paper also presents an FDBS recovery algorithm that has been proved to be correct. Formal proofs of all properties and a comparison of different algorithms are provided. Recommended by: Y. BreitbartThis work was supported in part by sub-contract #B09530013 from Honeywell SSDC, under contract #F30602-91-C-0128 from Rome Laboratory of the US Air Force.On leave from Computer Science Department, Heilongjiang University, People's Republic of China.