Effects of discrete-electrode configuration on traveling-wave electrohydrodynamic pumping

Traveling-wave electrohydrodynamic (EHD) micropumps can be incorporated into the package of an integrated circuit chip to provide active cooling. They can also be used for fluid delivery in microdevices. The pump operates in the presence of a thermal gradient through the fluid layer such that a gradient in electrical conductivity is established allowing ions to be induced. These ions are driven by a traveling electric field. Such a traveling electric field can be realized in practice only via discrete electrodes upon which the required voltages are imposed. The impact of using discrete electrodes to create the traveling wave on the flow rates generated is explored through numerical modeling. The change in performance from an ideal sinusoidal voltage boundary condition is quantified. The model is used to explore the widths of electrodes and the intervening isolation regions that lead to optimized pumping. The influence of the choice of working fluid on the performance of the pump is determined using an analytical model.     

Microproteomics: analysis of protein diversity in small samples

Proteomics, the large-scale study of protein expression in organisms, offers the potential to evaluate global changes in protein expression and their post-translational modifications that take place in response to normal or pathological stimuli. One challenge has been the requirement for substantial amounts of tissue in order to perform comprehensive proteomic characterization. In heterogeneous tissues, such as brain, this has limited the application of proteomic methodologies. Efforts to adapt standard methods of tissue sampling, protein extraction, arraying, and identification are reviewed, with an emphasis on those appropriate to smaller samples ranging in size from several microliters down to single cells. The effects of miniaturization on these analyses are highlighted using neuroscience-related examples, as are statistical issues unique to the high-dimensional datasets generated by proteomic experiments.     

Efficient tag detection in RFID systems

Recent technological advances have motivated large-scale deployment of RFID systems. However, a number of critical design issues relating to efficient detection of tags remain unresolved. In this paper, we address three important problems associated with tag detection in RFID systems: (i) accurately detecting RFID tags in the presence of reader interference (reader collision avoidance problem); (ii) eliminating redundant tag reports by multiple readers (optimal tag reporting problem); and (iii) minimizing redundant reports from multiple readers by identifying a minimal set of readers that cover all tags present in the system (optimal tag coverage problem). The underlying difficulties associated with these problems arise from the lack of collision detection mechanisms, the potential inability of RFID readers to relay packets generated by other readers, and severe resource constraints on RFID tags. In this paper we present a randomized, distributed and localized Reader Collision Avoidance (RCA) algorithm and provide detailed probabilistic analysis to establish the accuracy and the efficiency of this algorithm. Then, we prove that the optimal tag coverage problem is NP-hard even with global knowledge of reader and tag locations. We develop a distributed and localized Redundant Reader Elimination (RRE) algorithm, that efficiently identifies redundant readers and avoids redundant reporting by multiple readers. In addition to rigorous analysis of performance and accuracy, we provide results from elaborate simulations for a wide range of system parameters, demonstrating the correctness and efficiency of the proposed algorithms under various scenarios.     

Performance analysis in a probabilistic re-entrant for an environmental stress testing operation

This paper presents an extended approximation model based on mean value analysis (MVA) technique for a probabilistic re-entrant line. The objective is to develop a solution method to determine the total cycle time and mean throughput of the environmental stress testing (EST) operation for a given number of lots loaded into the system. Further work was done to determine the maximum number of lots that can be loaded into the system and the target cycle time. This paper also looks at alternative ways to assign human resources within the operation in the event of large number of lots required. Using analytical and simulation methods, comparison results were made for a five-stage queuing system with re-entrant lines into the second stage under various probabilistic routing conditions. The method proposed can be used by operation managers to determine their lots’ cycle times, maximum number of lots and the operator assignments.     

Diabetic Retinopathy Detection from Fundus Images Using Machine Learning Techniques : A Review

Diabetic retinopathy is one of the leading causes of blindness in today’s world. One of the major causes of Diabetic retinopathy is diabetes and also this occurs due to hereditary reasons. DR is classified into proliferative, non-proliferative and diabetic maculopathy. This paper approaches to one of the signs of non-proliferative DR called as exudates (commonly called hard exudates) and several methods which is introduced to detect them in retina. The work includes the algorithms, outcomes, datasets used and other results related with it. The results are compared by tabulating the evaluations and procedures.

     

Correction to: The Impact of Memory‑Efficient Bots on IoT‑WSN Botnet Propagation

Wireless Personal Communications - The Acknowledgements section in the initial online publication was incomplete. The original article has been corrected.     

A meta‐heuristic Bayesian network classification for intrusion detection

Software‐defined networking (SDN) is an innovative network paradigm much in demand today in academics and industry. In this network, the SDN controller must be able to observe and examine traffic flow through the network systems. However, intrusion‐based data packets affect the whole system is a major drawback. To overcome this issue, we propose a Novel Agent Program (NAP) framework for preventing switches from the external compromised attacks. A Meta‐Heuristic Bayesian Network Classification (MHBNC) algorithm for intrusion detection is proposed in this paper. The proposed algorithm follows certain procedures for preprocessing, feature selection, feature optimization, and classification. Normal and anomaly‐based data packets are classified successfully with its improved detection capabilities based on the optimization technique. The simulation results of the proposed ID_MBC (intrusion detection based on meta‐heuristic Bayesian classifier) technique is compared with existing techniques such as the association rule, PSO+GA, and the GA+RVM. The proposed MHBNC classifier performs better than existing methods.     

A novel sampling-based visual topic models with computational intelligence for big social health data clustering

The Journal of Supercomputing - Twitter is a popular social network for people to share views or opinions on various topics. Many people search for health topics through Twitter; thus, obtaining a...     

An Optimal Lempel Ziv Markov Based Microarray Image Compression Algorithm

In the recent years, microarray technology gained attention for concurrent monitoring of numerous microarray images. It remains a major challenge to process, store and transmit such huge volumes of microarray images. So, image compression techniques are used in the reduction of number of bits so that it can be stored and the images can be shared easily. Various techniques have been proposed in the past with applications in different domains. The current research paper presents a novel image compression technique i.e., optimized Linde–Buzo–Gray (OLBG) with Lempel Ziv Markov Algorithm (LZMA) coding technique called OLBG-LZMA for compressing microarray images without any loss of quality. LBG model is generally used in designing a local optimal codebook for image compression. Codebook construction is treated as an optimization issue and can be resolved with the help of Grey Wolf Optimization (GWO) algorithm. Once the codebook is constructed by LBG-GWO algorithm, LZMA is employed for the compression of index table and raise its compression efficiency additionally. Experiments were performed on high resolution Tissue Microarray (TMA) image dataset of 50 prostate tissue samples collected from prostate cancer patients. The compression performance of the proposed coding esd compared with recently proposed techniques. The simulation results infer that OLBG-LZMA coding achieved a significant compression performance compared to other techniques.     

Evaluation of power extraction circuits on piezo‐transducers operating under low‐frequency vibration‐induced strains in bridges

The concept of piezoelectric energy harvesting (PEH) provides a promising solution for perpetually running low‐power electronic devices such as wireless sensor networks by harvesting ambient vibrations generated from civil structures such as long span bridges, city flyovers, elevated metro corridors, which are constantly under dynamic loads. However, its successful industrial‐scale deployment on civil structures is still not realised because of the low‐frequency of vibrations (typically <5 Hz) encountered there, coupled with the low levels of voltage generation. The vast majority of PEH‐related studies have only focused on PEH configurations and geometries, Often entailing secondary structures. d₃₁ mode, which is the most natural mode of excitation, has not been investigated in depth for piezo‐patches directly bonded on the main structure. Studies, which have focused on electronic conditioning circuitry, have been restricted to typically high‐voltage and high‐frequency scenarios only. This paper focuses on systematically studying the issues inflicting energy harvesting from the ambient vibrations induced flexural strains civil structures, such as city flyovers, using piezo elements in d₃₁ mode. Vibration measurements are first undertaken from a typical city flyover consisting of steel girders supporting a reinforced concrete (RC) deck. The basic site measurements are employed to perform a laboratory‐based parametric study to investigate the influence of parameters such as vibration frequency, voltage, and circuit components like diodes on PEH. On the basis of the experimental results, it can be concluded that power in microwatts range can be typically harvested from these civil structures through directly bonded piezo patches in d₃₁ mode. However, there are still issues associated with electronic circuitry accompanying harvesters, such as diodes and storage elements. The same are summarised and future directions envisioned.