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A 50Gb/s all-digital adaptive noise-suppression (NS) feed-forward equalizer (AFFE) and adaptive decision feedback equalizer (ADFE) for 2-level pulse amplitude modulation (2-PAM) serial link systems is presented. Based on a parallel extended incremental coefficients-lookahead scheme (EICL), we propose a Dual Data-paths Self-Lookahead Filter (DD-SLF) for ADFE. DD-SLF architecture has better energy efficiency and hardware area than an original SLF architecture due to the number of delay elements in the feedback loop is reduced. Furthermore, gated clock technique with the design idea of register file architecture is used to replace the pipelined delay elements to save power. The whole equalizer which operates at 1GHz system clock rate with 50 parallelisms is implemented in 40nm CMOS technology with a 0.38mm2 core area. The equalizer with 50Gb/s throughput rate achieves 2.6pJ/bit energy efficiency under 0.81V supply measurement results.

A 50Gb/s all-digital adaptive noise-suppression (NS) feed-forward equalizer (AFFE) and adaptive decision feedback equalizer (ADFE) for 2-level pulse amplitude modulation (2-PAM) serial link systems with SNR based power management scheme is presented. Based on a parallel extended incremental coefficientslookahead scheme (EICL), we propose a reconfigurable Dual Datapaths Self-Lookahead Filter (DD-SLF) for ADFE. SNR-power management skill is adopted to adaptively adjust the hardware configuration in different channel environment and SNR to achieve optimum energy efficiency. The whole equalizer which operates at 1 GHz system clock rate with 50 parallelisms is implemented in 40nm CMOS technology with a core area 0.38mm2. The equalizer with 50Gb/s throughput rate achieves 2.6pJ/bit energy efficiency under 0.81V supply measurement results.

A 40Gb/s all-digital adaptive noise-suppression feed-forward filter/equalizer (AFFE) and adaptive decision feedback equalizer (ADFE) for 2-level pulse amplitude modulation (2-PAM) systems is presented. Batch mode coefficients update (BMCU) unit together with coefficients-lookahead scheme are proposed to achieve high parallelism architecture for ADFE. With these schemes, new extended incremental coefficients-lookahead filter architecture is proposed to provide high throughput rate and to reduce hardware complexity of parallel ADFE. Besides, feed-forward noise-suppression architecture is proposed for AFFE to provide better signal-to-noise ratio (SNR). The equalizer operates at 1 GHz system clock with 40 parallelisms is implemented in 40nm CMOS technology with a core area 0.23mm2. The measurement results verify the equalizer performance and the maximum throughput of 40Gb/s is achieved under 0.9V supply with 4.35pJ/bit energy efficiency.

This paper proposes a novel time series forecasting method based on a weighted self-constructing clustering technique. The training data patterns are processed incrementally. If a data pattern is not similar enough to an existing cluster, it forms a new cluster of its own. However, if a data pattern is similar enough to an existing cluster, it is added to the most similar cluster. During the clustering process, weights are learned for each cluster. For a given series of time-stamped data up to time t, we divide it into a set of training patterns. By using the weighted self-constructing clustering, the training patterns are grouped into a set of clusters. A radial basis function (RBF) network is then constructed, for which the obtained clusters are served as the basis functions of the hidden neurons. To forecast the value at time t + 1, the input pattern is fed into the resulting RBF network and the corresponding network output is taken as the estimation. Experimental results are shown to demonstrate the effectiveness of the proposed approach.

Focused ultrasound (FUS) with microbubbles (MBs) can enhance delivery of impermeable materials into cells for eliminating abnormal cells or enhancing gene transfection. Very few of the existing systems can precisely control cellular physiology. Chemically-inducible dimerization (CID) system has already gained widespread popularity as a tool in cell biology and has been used to address the diverse, yet fundamental biological questions. Although remotely triggering CID system by external stimuli such as light has been developed, it is still challenging to deliver light to the tissues deeper than just 2 mm without any invasive surgical procedures. This study proposed a new ultrasound-chemical hybrid system to trigger the CID system by FUS with MBs. With FUS, membrane impermeable chemical dimerizers can be introduced into cells to spatiotemporally control cellular physiology within timescale of minutes.

By learning from the past behaviors of user transaction records, recommender systems can help people to nd interesting products from many other products. In a collaborative ltering based recommender system, products are regarded as features. However, there are usually quite a lot of products to be considered. A recommender system would be very inefficient if such a large number of products are processed before making any recommendations. We propose a method which applies a self-constructing clustering technique to reduce the dimensionality related to the number of products. As a result, the processing time for making recommendations is much reduced without degrading the accuracy of recommendations.

This paper proposes a novel full-digital architecture of adaptive decision feedback equalizer (ADFE) for wireline 2-level pulse amplitude modulation (2-PAM) systems. It is well known that the feedback loop in DFE limits the greatest achievable speed. The proposed scheme begins by deriving coefficient-lookahead concept based on a reasonable assumption, whereupon a preliminary architecture can be implemented using the formula derived. Furthermore, according to channel characteristics, the formula derived can be simplified to break the feedback loop. Finally, the architecture can be easily pipelined and processed in parallel to achieve high throughput rate. Thus, the proposed design is a high speed design with parallel and pipeline architecture. This paper used a TSMC 40 nm CMOS process to fabricate the proposed design with a build-in self-test (BIST) circuit. The measured results show that the throughput rate is up to 16 Gbps.

In our previous work, our grouping mechanism based on edX online forum, which aims to help teachers form learning groups in SPOC context. We proposed the interaction as the main criterion and heterogeneous academic results as the supportive to do grouping. In the past experiment, we compared our method to student grouping by themselves, our method is better in learning performance but satisfactions is worse. In this paper, we continue the previous work, and make some changes for the experiment content, in order to carry out a second experiment. Moreover, in this paper a more in-depth analysis and comparison of experimental results twice. In the second experiment, we found that the results of the post-test is worse than the first experiment. We believe that the main reason may be that the participation of the online discussion board is reduced, leading to interactive information can be obtained also reduced. Eventually leading to less effective of our method. But the experimental group grade still higher than the control group and have the same satisfaction about grouping result in the second experiment.

Collaborative Learning (CL) along with the changing of the teaching environment, the way how students interact has also changed. The rise of Massive Open Online Courses (MOOCs) lets the teaching environment turn into online teaching. Deriving from MOOCs, Small Private Online Course (SPOC) incorporates the concept of Blended Learning (BL), which combines the advantage of MOOCs and face-to-face teaching. In this context, implies an enormous amount of consideration of group division factors and information volume when teachers organize groups. In the face of an unprecedented workload size, organizing groups manually is extremely time consuming and difficult for teachers. In this paper, we make use of the advantages of the conditions of SPOC, retrieving the social network of students on the online discussion board, then the heterogeneous division of groups based on academic results is the supplementary to do grouping. In addition, this paper makes use of edX, a representative platform of MOOCs, and develops the group division modules based on the format of the online discussion boards of the platform. Comparing with the way of grouping by students themselves in this context, the method which brought out by this paper do a better job in learning performance in spite of the satisfactions is worse.

This paper is dedicated to moving-object intrusion detection in all-weather conditions based on Retinex-enhanced approach. The proposed method mainly consists of image enhancement and intrusion detection for moving-objects. A Retinex-enhanced approach is developed for reducing the high-lighting's affection at nighttime environment. Then, the frame-difference and morphological processing are employed to remove noisy areas caused by high-lighting, shadow, and raindrops for generating the initial moving-object's mask. To extract a more complete moving-object, a refinement processing based on intensity analysis is introduced to remove ground-light (caused by car lights) areas generated in the raining situation. Finally, intrusion is judged by checking whether a moving object is crossing a predefined detection line or not. Experimental results show that the proposed method can provide an intrusion-detection rate of over 97% at daytime, over 90% at nighttime, and over 97% in the raining situation.

recently, big data computing in cloud systems is an important issue. Cloud computing tries to satisfy users' demands and provide services by sharing hardware and software resources. Therefore, using the virtualization technology to enhance system performance is an important goal. In practical, single cloud cannot provide unlimited services with limited physical resources. Therefore, this study proposes a vertical/horizontal resource scaling mechanism for federated clouds. When single virtual machine is unable to satisfy user requests, the proposed mechanism will allocate new resources in the federated clouds by vertical/horizontal scaling fashions. In general, horizontal scaling obtains more computing power by adding more virtual machines, and vertical scaling obtains more computing power by adding resources in the virtual machine. The vertical-scaling system not only enhances the system performance but also increases physics machine utilization. But the vertical- scaling system incurs the communication latency problem. Therefore, this study focuses on the vertical /horizontal scaling approach for reducing the minimum turnaround time and for improving the cost efficiency. Our study assessments the cloud computing capability by using cost efficiency (throughput/price per minute). Performance for NAS Parallel Benchmarks (for example, Parallel (EP), Conjugate Gradient (CG), Integer Sort (IS)) is evaluated. Experimental results show that our approach cloud reduce communication overhead and improve the resource utilization and throughput. Keywords - federated cloud, vertical scaling, horizontal scaling.

The development of cloud computing brings the revolution of information technology (IT). Because the resource in any physical cloud infrastructure is finite, resource outsourcing is an important issue in cloud computing. This study proposes a distributed scheduling approach based on game theory for the resource competition problem in the federated cloud. In this study, each job consists of one or more tasks, and has specific communication behavior between tasks. The proposed approach groups tasks according to communication behavior to minimize communication overhead. In the meantime, when multiple providers access the same resources, the resource-conflict occurs. This study also tries to achieve the Nash equilibrium to improve the benefit obtained from the federated clouds. This work evaluates some benchmarks over Taiwan Uni-Cloud. Experimental results demonstrate that the cloud provider could obtain extra profits by outsourcing resources while the federated cloud has enough remaining resources.

Pedestrian detection is important in the computer vision field. In the nighttime, pedestrian detection is even more valuable. In this paper, we address the issue of detecting pedestrians in video streams from a moving camera at nighttime. Most nighttime human detection approaches only use single feature extracted from images. The effective image features in daytime environment may suffer from textureless, high contrast and low light problems at night. To deal with these issues, we first segment the foreground by using the proposed Smart Region Detection approach to generate candidates. Then we design a nighttime pedestrian detection system based on the AdaBoost and the support vector machine (SVM) classifiers with contour and histogram of oriented gradients (HOG) features to effectively recognize pedestrians from those candidates. Combining different type of complementary features improve the detection performance. Results show that our pedestrian detection system is promising in the nighttime environment.

Traditional paper-and-pencil tests have always been a heavy burden for teachers. In recent years, computer technology has been widely applied to the education field, which makes quite an impact on traditional teaching activities. Teachers have to take more advantages of new technology in both tools and methodology to achieve a more effective assessment. In this paper, a web-based Chinese math word problem test system is proposed. The system is based on an automatic item generation (AIG) mechanism, which employs object-oriented technology to dynamically generate items that require little human review prior to administration. The teacher can organize a test by specifying the number of problems and their types. Students can take a test online within the valid period. Every student has different, but similar test items of the same difficulty levels, which brings the assessment more fairness and improves security. Moreover, students can use the system as a practice tool anytime and anywhere for learning purpose.

This study uses the time-evolved voltage holding ratio (VHR) to measure the influence of UV exposure on a nematic liquid-crystal cell. Apart from the real-time measurement during the exposure, the time-dependent recovery of VHR is also monitored after a certain amount of UV irradiation. Our experimental results show that the cell impregnated with an adequate content of the anatase TiO 2 as a nano-additive possesses a higher VHR, which unambiguously implies that the TiO 2 nanoparticles are capable of preventing the serious ion effect caused by the harmful UV. Achieving the "green" concept, this research suggests a new approach to reduce the ion effect and extend the life of LCD devices under sunlight.

Decision feedback equalizer (DFE) uses a feedback path to cancel post-cursor ISI, and this feedback path will also cause the limitation of its maximum throughput rate. This paper proposes a new lookahead method to break the feedback path for multi-gigabit DFE design. After lookahead computation, each paralleled sub-circuit has the same throughput rate as original one. Therefore, the total throughput rate is proportional to the parallelization factor. The computation complexity of the proposed architecture is lower than that of multiplexer-based lookahead DFE if the tap number of the feedback filter is large. It is shown that the new method saves 10% hardware complexity for an 8 taps feedback filter DFE and 98% hardware complexity for a 12 taps feedback filter DFE in comparison to a 10Gbps multiplexer-based lookahead DFE.

Microarray is widely used for the cancer research and identifies different expressions for specific genes. We present a computational method for constructing cancer and normal gene regulatory networks from micorarray data based on transcription factor analysis and independency test. The web service technology is used to wrap the bioinformatics toolkits of methods and databases to automatically extract the promoter regions of DNA sequences and predict the transcription factors that regulate gene expressions. After reconstructing the gene regulatory network, the network statistical measure and network motifs extract the potential genes to compare the sub-networks between the cancer and normal gene networks. We adopt the microarray datasets from Stanford microarray database of prostate cancer as a target application to evaluate the methods.

An all digital 3.5 Gbps blind adaptive decision feedback equalizer (ADFE) is designed for 10GBase-LX4 IEEE 802.3 ae standard. It uses 5 parallel equalization blocks each with 6 taps and 4 taps for each feed-forward equalizer (FFE) and feed-back equalizer (FBE). This concurrent ADFE has core area of 0.864times0.864 mm2 with operation up to 3.5 Gbps using 1.2-V supply in a 0.13 um CMOS process. It dissipates 94 mW when working at 3.125 Gbps.