title: Establishment of a simple system to analyse the molecular interaction in the agglutination ofSaccharomyces cerevisiae

abstract: Saccharomyces cerevisiaea-agglutinin, which is involved in mating and covalently anchoring to the cell wall, consists of two components, Aga1p and Aga2p, whose syntheses are individually regulated. To facilitate the analysis of the protein–protein interaction on agglutination between a- and α-agglutinins, the construction of a yeast strain (MATa) with the functional protein prepared by genetic fusion of Aga1p- and Aga2p-encoding genes and by the expression system using the UPR–ICL promoter derived from the n-alkane-assimilating yeast, Candida tropicalis, which is functional under the condition of lower glucose concentration was tried and the agglutination ability of the constructed strain was evaluated with a yeast strain (MATa) which expressed AGα1 encoding α-agglutinin under the control of the same promoter. The genes were integrated into the yeast chromosomes. Cell agglutination between both (MATa) strains was observed microscopically when these two strains were mix-cultured to a glucose-decreased concentration. The agglutination was further confirmed by the sedimentation test and by the quantification using a filter. These results proved that the constructed Aga1p–Aga2p fusion protein was enoughly functional for the interaction with the Agα1 protein, and that this phenomenon occurred dependent on glucose concentration, but independent of the peptide pheromones secreted by the cells of the opposite mating types. Using this system, the role of two disulphide linkages between Aga1p and Aga2p on the binding activity between Aga2p and Aga1p was first evaluated. Under the treatment by the SH-compound (dithiothreitol), in which Agα2p is easily released into the medium from the intact cell surface, the Aga1p and Aga2p fusion protein was a good tool to make clear the role of the disulphide linkages. As a result, the linkages had a significant effect on not only the assembly but also the binding activity. The novel and simple system described here may further facilitate the study of molecular interaction in agglutination. Copyright © 2000 John Wiley & Sons, Ltd.


title: Exploratory Relation Extraction in Large Text Corpora

abstract: In this paper, we propose and demonstrate Exploratory Relation Extraction (ERE), a novel approach to identifying and extracting relations from large text corpora based on user-driven and data-guided incremental exploration. We draw upon ideas from the information seeking paradigm of Exploratory Search (ES) to enable an exploration process in which users begin with a vaguely defined information need and progressively sharpen their definition of extraction tasks as they identify relations of interest in the underlying data. This process extends the application of Relation Extraction to use cases characterized by imprecise information needs and uncertainty regarding the information content of available data. We present an interactive workflow that allows users to build extractors based on entity types and human-readable extraction patterns derived from subtrees in dependency trees. In order to evaluate the viability of our approach on large text corpora, we conduct experiments on a dataset of over 160 million sentences with mentions of over 6 million FREEBASE entities extracted from the CLUEWEB09 corpus. Our experiments indicate that even non-expert users can intuitively use our approach to identify relations and create high precision extractors with minimal effort.


title: Computer-Aided Cobb Measurement Based on Automatic Detection of Vertebral Slopes Using Deep Neural Network

abstract: Objective. To develop a computer-aided method that reduces the variability of Cobb angle measurement for scoliosis assessment. Methods. A deep neural network (DNN) was trained with vertebral patches extracted from spinal model radiographs. The Cobb angle of the spinal curve was calculated automatically from the vertebral slopes predicted by the DNN. Sixty-five in vivo radiographs and 40 model radiographs were analyzed. An experienced surgeon performed manual measurements on the aforementioned radiographs. Two examiners used both the proposed and the manual measurement methods to analyze the aforementioned radiographs. Results. For model radiographs, the intraclass correlation coefficients were greater than 0.98, and the mean absolute differences were less than 3°. This indicates that the proposed system showed high repeatability for measurements of model radiographs. For the in vivo radiographs, the reliabilities were lower than those from the model radiographs, and the differences between the computer-aided measurement and the manual measurement by the surgeon were higher than 5°. Conclusion. The variability of Cobb angle measurements can be reduced if the DNN system is trained with enough vertebral patches. Training data of in vivo radiographs must be included to improve the performance of DNN. Significance. Vertebral slopes can be predicted by DNN. The computer-aided system can be used to perform automatic measurements of Cobb angle, which is used to make reliable and objective assessments of scoliosis.


title: A Learned Representation For Artistic Style

abstract: The diversity of painting styles represents a rich visual vocabulary for the construction of an image. The degree to which one may learn and parsimoniously capture this visual vocabulary measures our understanding of the higher level features of paintings, if not images in general. In this work we investigate the construction of a single, scalable deep network that can parsimoniously capture the artistic style of a diversity of paintings. We demonstrate that such a network generalizes across a diversity of artistic styles by reducing a painting to a point in an embedding space. Importantly, this model permits a user to explore new painting styles by arbitrarily combining the styles learned from individual paintings. We hope that this work provides a useful step towards building rich models of paintings and offers a window on to the structure of the learned representation of artistic style.


title: Warp: Lightweight Multi-Key Transactions for Key-Value Stores

abstract: Traditional NoSQL systems scale by sharding data across multiple servers and by performing each operation on a small number of servers. Because transactions on multiple keys necessarily require coordination across multiple servers, NoSQL systems often explicitly avoid making transactional guarantees in order to avoid such coordination. Past work on transactional systems control this coordination by either increasing the granularity at which transactions are ordered, sacrificing serializability, or by making clock synchronicity assumptions. ::: This paper presents a novel protocol for providing serializable transactions on top of a sharded data store. Called acyclic transactions, this protocol allows multiple transactions to prepare and commit simultaneously, improving concurrency in the system, while ensuring that no cycles form between concurrently-committing transactions. We have fully implemented acyclic transactions in a document store called Warp. Experiments show that Warp achieves 4 times higher throughput than Sinfonia's mini-transactions on the standard TPC-C benchmark with no aborts. Further, the system achieves 75% of the throughput of the non-transactional key-value store it builds upon.


title: Physical exercise intervention in depressive disorders: meta-analysis and systematic review.

abstract: Previous meta-analyses investigating the effect of exercise on depression have included trials where the control condition has been categorized as placebo despite the fact that this particular placebo intervention (e.g., meditation, relaxation) has been recognized as having an antidepressant effect. Because meditation and mindfulness-based interventions are associated with depression reduction, it is impossible to separate the effect of the physical exercise from the meditation-related parts. The present study determined the efficacy of exercise in reducing symptoms of depression compared with no treatment, placebo conditions or usual care among clinically defined depressed adults. Of 89 retrieved studies, 15 passed the inclusion criteria of which 13 studies presented sufficient information for calculating effect sizes. The main result showed a significant large overall effect favoring exercise intervention. The effect size was even larger when only trials that had used no treatment or placebo conditions were analyzed. Nevertheless, effect size was reduced to a moderate level when only studies with high methodological quality were included in the analysis. Exercise may be recommended for people with mild and moderate depression who are willing, motivated, and physically healthy enough to engage in such a program.


title: Measurement of capacitive sensor with Arduino

abstract: This paper presents a measurement system with capacitive sensor connected to an open-source electronic platform Arduino Uno. A simple code was modified in the project, which ensures that the platform works as interface for the sensor. The code can be modified and upgraded at any time to fulfill other specific applications. The simulations were carried out in the platform's own environment and the collected data are represented in graphical form. Accuracy of developed measurement platform is 0.1 pF.


title: Vertical handoffs in fourth-generation multinetwork environments

abstract: Revolutionary drivers for 4G include a push toward universal wireless access and ubiquitous computing through seamless personal and terminal mobility. One of the major challenges for seamless mobility is the criterion of a vertical handoff protocol: a handoff protocol for users that move between different types of networks. Traditional operations for handoff detection policies, decision metrics, and radio link transfer are not able to adapt to dynamic handoff criteria or react to user inputs and changing network availabilities. Nor are they able to deliver context-aware services or ensure network interoperability. Thus, new techniques are needed to manage user mobility between different types of networks. This article presents a tutorial on the design and performance issues for vertical hand-off in an envisioned multinetwork fourth-generation environment. Various network architectures and technologies for 3G and beyond are described, including wireless LANs, cellular, satellite, and Mobile IP. Then the problem of vertical handoff is defined in the context of such a diverse network environment. Finally, research efforts to resolve the open problems are explored, including new techniques for dynamic handoff decision and detection algorithms and context-aware radio link transfer.


title: A 3.1 mW 8b 1.2 GS/s Single-Channel Asynchronous SAR ADC With Alternate Comparators for Enhanced Speed in 32 nm Digital SOI CMOS

abstract: An 8b 1.2 GS/s single-channel Successive Approximation Register (SAR) ADC is implemented in 32 nm CMOS, achieving 39.3 dB SNDR and a Figure-of-Merit (FoM) of 34 fJ per conversion step. High-speed operation is achieved by converting each sample with two alternate comparators clocked asynchronously and a redundant capacitive DAC with constant common mode to improve the accuracy of the comparator. A low-power, clocked capacitive reference buffer is used, and fractional reference voltages are provided to reduce the number of unit capacitors in the capacitive DAC (CDAC). The ADC stacks the CDAC with the reference capacitor to reduce the area and enhance the settling speed. Background calibration of comparator offset is implemented. The ADC consumes 3.1 mW from a 1 V supply and occupies 0.0015 mm2.


title: On Tendon-Driven Robotic Mechanisms with Redundant Tendons

abstract: In this paper, several basic issues are discussed regarding tendon redundancy and joint stiffness adjustability for a robotic mechanism driven with redundant tendons. After briefly discussing tendon- controllability, the authors define local maximum sets of tendons that are redundant simultaneously (local maximum redundant tendon sets) and obtain an irreducible description of a redundant tendon in terms of the others. The authors obtain conditions under which the joint stiffness is adjustable using the tendons' nonlinear elasticity.


IOT DECK : A DIGITAL CARD-BASED IDEATION GAME TO INSPIRE INTERNET OF THINGS DESIGN


title: Blind Spatial Subtraction Array for Speech Enhancement in Noisy Environment

abstract: We propose a new blind spatial subtraction array (BSSA) consisting of a noise estimator based on independent component analysis (ICA) for efficient speech enhancement. In this paper, first, we theoretically and experimentally point out that ICA is proficient in noise estimation under a non-point-source noise condition rather than in speech estimation. Therefore, we propose BSSA that utilizes ICA as a noise estimator. In BSSA, speech extraction is achieved by subtracting the power spectrum of noise signals estimated using ICA from the power spectrum of the partly enhanced target speech signal with a delay-and-sum beamformer. This ldquopower-spectrum-domain subtractionrdquo procedure enables better noise reduction than the conventional ICA with estimation-error robustness. Another benefit of BSSA architecture is ldquopermutation robustness". Although the ICA part in BSSA suffers from a source permutation problem, the BSSA architecture can reduce the negative affection when permutation arises. The results of various speech enhancement test reveal that the noise reduction and speech recognition performance of the proposed BSSA are superior to those of conventional methods.


title: A compact nonlinear-transmission-line-based mm-Wave SFCW imaging radar

abstract: This paper presents the results of initial measurements collected using a compact 60 GHz stepped-frequency continuous-wave (SFCW) imaging radar based on nonlinear transmission lines (NLTLs), and driving a pair of dual-waveguide-fed horn antennas. A range resolution of 2.22 cm is achieved using a bandwidth of over 6.5 GHz, and synthetic focusing is applied to achieve an azimuth resolution of 1 cm with mechanical scanning. The system demonstrates imaging of multiple targets obscured by a large non-metallic interface (cardboard).


title: Inner activity

abstract: Inner Activity is a multi-sensory virtual reality experience presented as a physical art installation. It combines interaction design and game technologies, sound healing and vibro-acoustic therapy techniques, physical set design, and concepts from meditation and spirituality. It utilizes the Oculus Rift and the SubPac, a tactile bass system for achieving whole body stimulation through synchronized audiovisual, haptic and olfactory feedback. This experience is a preliminary exploration into potential applications for using immersive virtual reality entertainment in healthcare, therapy and medicine.


title: Development of a 7DOF soft manipulator arm for the compliant humanoid robot COMAN

abstract: This paper presents the design and implementation of an intrinsically soft arm system for the COMpliant huMANoid COMAN robot. The two arms (left and right) use state-of-the-art technologies on actuator design that combine both active and passive compliance principles. Robustness of the arms is ensured by integrating intrinsic Series Elastic Actuation (SEA) into the joints to protect the arm at the initial time of the impacts while impedance control based on joint torque sensing and feedback permits the regulation of arm stiffness and damping properties and provides enhanced physical interaction performance. The tuning of the intrinsic stiffness level of the compliant joints is performed by a systematic method to obtain desired performance. A rich sensing system is developed to allow implementation of advanced control algorithms. The functionality of the arms was validated in several tasks requiring high payload, rich sensing ability, and compliant interaction.


title: 3D object detection with multiple kinects

abstract: Categorizing and localizing multiple objects in 3D space is a challenging but essential task for many robotics and assisted living applications. While RGB cameras as well as depth information have been widely explored in computer vision there is surprisingly little recent work combining multiple cameras and depth information. Given the recent emergence of consumer depth cameras such as Kinect we explore how multiple cameras and active depth sensors can be used to tackle the challenge of 3D object detection. More specifically we generate point clouds from the depth information of multiple registered cameras and use the VFH descriptor [20] to describe them. For color images we employ the DPM [3] and combine both approaches with a simple voting approach across multiple cameras. ::: ::: On the large RGB-D dataset [12] we show improved performance for object classification on multi-camera point clouds and object detection on color images, respectively. To evaluate the benefit of joining color and depth information of multiple cameras, we recorded a novel dataset with four Kinects showing significant improvements over a DPM baseline for 9 object classes aggregated in challenging scenes. In contrast to related datasets our dataset provides color and depth information recorded with multiple Kinects and requires localizing and categorizing multiple objects in 3D space. In order to foster research in this field, the dataset, including annotations, is available on our web page.


title: Stacked Deconvolutional Network for Semantic Segmentation

abstract: Recent progress in semantic segmentation has been driven by improving the spatial resolution under Fully Convolutional Networks (FCNs). To address this problem, we propose a Stacked Deconvolutional Network (SDN) for semantic segmentation. In SDN, multiple shallow deconvolutional networks, which are called as SDN units, are stacked one by one to integrate contextual information and guarantee the fine recovery of localization information. Meanwhile, inter-unit and intra-unit connections are designed to assist network training and enhance feature fusion since the connections improve the flow of information and gradient propagation throughout the network. Besides, hierarchical supervision is applied during the upsampling process of each SDN unit, which guarantees the discrimination of feature representations and benefits the network optimization. We carry out comprehensive experiments and achieve the new state-of-the-art results on three datasets, including PASCAL VOC 2012, CamVid, GATECH. In particular, our best model without CRF post-processing achieves an intersection-over-union score of 86.6% in the test set.


title: Deep Learning for solar power forecasting — An approach using AutoEncoder and LSTM Neural Networks

abstract: Power forecasting of renewable energy power plants is a very active research field, as reliable information about the future power generation allow for a safe operation of the power grid and helps to minimize the operational costs of these energy sources. Deep Learning algorithms have shown to be very powerful in forecasting tasks, such as economic time series or speech recognition. Up to now, Deep Learning algorithms have only been applied sparsely for forecasting renewable energy power plants. By using different Deep Learning and Artificial Neural Network algorithms, such as Deep Belief Networks, AutoEncoder, and LSTM, we introduce these powerful algorithms in the field of renewable energy power forecasting. In our experiments, we used combinations of these algorithms to show their forecast strength compared to a standard MLP and a physical forecasting model in the forecasting the energy output of 21 solar power plants. Our results using Deep Learning algorithms show a superior forecasting performance compared to Artificial Neural Networks as well as other reference models such as physical models.


title: The effectiveness of postmortem multidetector computed tomography in the detection of fatal findings related to cause of non-traumatic death in the emergency department

abstract: Objectives ::: To investigate the diagnostic performance of postmortem multidetector computed tomography (PMMDCT) for the detection of fatal findings related to causes of non-traumatic death in the emergency department (ED).


title: Synthesis, characterization of biodegradable dextran-allyl isocyanate-ethylamine/polyethylene glycol-diacrylate hydrogels and their in vitro release of albumin

abstract: Abstract Based on dextran–allyl isocyanate–ethylamine (Dex-AE) and polyethylene glycol–diacrylate (PEGDA), a pH sensitive biodegradable hydrogel with improved protein release was prepared through UV photo-crosslinking. The Dex-AE precursor was prepared through a two-step chemical modification and characterized by FT-IR and 1 H NMR. The effects of reaction conditions on the synthesis of Dex-AE were studied. The interior morphology data by scanning electron microscopy (SEM) revealed that an increase in Dex-AE content led to an initial decrease in pore size of the microstructure of the Dex-AE/PEGDA hydrogels, but a further increase in Dex-AE content resulted in a relatively looser network structure. The swelling data indicated that the swelling ratio depended on the precursor feed ratio and was correlated to the morphology of the microporous network structure. The pH sensitive property of the Dex-AE/PEGDA hydrogels was studied in different pH buffer solutions and was found that these hydrogels were pH sensitive due to the presence of ample pendant amino groups. The ionic strength data demonstrated that the Dex-AE/PEGDA hydrogels exhibit the highest swelling ratio in pure water, but the swelling ratio became lower as the ionic strength of the media increased. The in vitro albumin release from these hydrogels was examined in different pH (3.0, 7.4) buffer solutions. Both the protein loading and release data indicated that the Dex-AE/PEGDA hydrogels had more protein loading and sustained release capability than pure PEGDA hydrogel, and this ability increased as the Dex-AE composition increased; the Dex-AE/PEGDA hydrogel also showed a faster BSA release in a lower pH than a higher pH medium.


title: Preparation of poly(N-normalpropyl- acrylamide) gel beads

abstract: The gel beads of N-normal-propylacrylamide are prepared by the radical copolymerization of N-normalpropylacrylamide and N,N′-methylene-bis-acrylamide in water. The optimum reaction conditions to obtain the gel beads are revealed from the phase diagram of the reaction system together with the scanning electron microscopy of the reaction products. The scanning electron microscopy of the reaction products also indicates the formation of the spherical gel beads of sub-micron size ranging from 250 to 500 nm in diameter. The viscosity measurements of the suspension of the gel beads indicate that the concentration dependence of the viscosity of the suspension is well described by Einstein’s theory of the viscosity of colloidal particles. The intrinsic viscosity of the suspension of gel beads is then determined. The density of the gel beads, which was obtained from the intrinsic viscosity of the suspension, indicates that the gel beads are in the swollen state at a temperature of 20 °C.


title: A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model

abstract: We propose a new multiphase level set framework for image segmentation using the Mumford and Shah model, for piecewise constant and piecewise smooth optimal approximations. The proposed method is also a generalization of an active contour model without edges based 2-phase segmentation, developed by the authors earlier in T. Chan and L. Vese (1999. In Scale-Space'99, M. Nilsen et al. (Eds.), LNCS, vol. 1682, pp. 141–151) and T. Chan and L. Vese (2001. IEEE-IP, 10(2):266–277). The multiphase level set formulation is new and of interest on its own: by construction, it automatically avoids the problems of vacuum and overlaps it needs only log n level set functions for n phases in the piecewise constant cases it can represent boundaries with complex topologies, including triple junctionss in the piecewise smooth case, only two level set functions formally suffice to represent any partition, based on The Four-Color Theorem. Finally, we validate the proposed models by numerical results for signal and image denoising and segmentation, implemented using the Osher and Sethian level set method.


title: Fusion of color and infrared video for moving human detection

abstract: We approach the task of human silhouette extraction from color and thermal image sequences using automatic image registration. Image registration between color and thermal images is a challenging problem due to the difficulties associated with finding correspondence. However, the moving people in a static scene provide cues to address this problem. In this paper, we propose a hierarchical scheme to automatically find the correspondence between the preliminary human silhouettes extracted from synchronous color and thermal image sequences for image registration. Next, we discuss strategies for probabilistically combining cues from registered color and thermal images for improved human silhouette detection. It is shown that the proposed approach achieves good results for image registration and human silhouette extraction. Experimental results also show a comparison of various sensor fusion strategies and demonstrate the improvement in performance over non-fused cases for human silhouette extraction.


title: A Unified Approach to the Synchronous Performance Analysis of Single and Poly-Phase Line-Fed Interior Permanent Magnet Motors

abstract: Interior permanent magnet motors equipped with a squirrel-cage rotor are receiving lately an increased interest. Defined as line-start, line-fed or hybrid synchronous-induction motors, such machines combine the advantage of the brushless permanent magnet motors, i.e. high efficiency, constant torque for variable speed, with the high starting capability of the induction motors connected directly to the supply system. This paper proposes a unified analysis of these motors, with an emphasis on how any possible configuration may be described by using symmetrical components and two equivalent fictitious machines: positive and negative sequences. The analysis is validated on a single-phase unbalanced and on a three-phase balanced line-fed interior permanent magnet motors.


title: RDF data exploration and visualization

abstract: We present Paged Graph Visualization (PGV), a new semi-autonomous tool for RDF data exploration and visualization. PGV consists of two main components: a) the "PGV explorer" and b) the "RDF pager" module utilizing BRAHMS, our high per-formance main-memory RDF storage system. Unlike existing graph visualization techniques which attempt to display the entire graph and then filter out irrelevant data, PGV begins with a small graph and provides the tools to incrementally explore and visualize relevant data of very large RDF ontologies. We implemented several techniques to visualize and explore hot spots in the graph, i.e. nodes with large numbers of immediate neighbors. In response to the user-controlled, semantics-driven direction of the exploration, the PGV explorer obtains the necessary sub-graphs from the RDF pager and enables their incremental visualization leaving the previously laid out sub-graphs intact. We outline the problem of visualizing large RDF data sets, discuss our interface and its implementation, and through a controlled experiment we show the benefits of PGV.


title: A field study on organizational commitment, professional commitment and peer mentoring

abstract: This study investigates attitudes and citizenship behaviors of IS workers in the software industry by examining relationships among various facets of organizational commitment, professional commitment, and a particular organizational citizenship behavior (OCB) called peer mentoring. Results revealed that one facet of organizational commitment, affective commitment, was positively associated with peer mentoring, while a second facet, normative commitment, was negatively associated with peer mentoring. A third facet of organizational commitment, continuance commitment, had no significant relationship with peer mentoring while professional commitment was positively associated with peer mentoring. Our results also found a positive and significant interaction between professional commitment and affective commitment, and a negative and significant interaction between professional commitment and normative commitment in predicting OCBs, suggesting that managers of software professionals can foster OCBs by focusing on specific facets of commitment


title: Internet addiction: A structured literature review and future research directions

abstract: Internet Addiction (IA) has been a significant topical area for research since 1996. Considerable research has been done on IA across many nations around the world. Hence, there currently exists a rich body of literature addressing various aspects of IA. The study described in this report seeks to analyze the key findings expressed in the existing IA literature. In doing so, this study addresses four specific concerns relating to: a) reviewing various definitions of IA, b) growth of IA research over time in different parts of the world, c) the major themes identified in the literature, and d) future opportunities for research into IA. These concerns were addressed using a rigorous literature analysis involving 64 studies on IA selected from various scholarly sources. The outcomes of literature analysis are discussed in detail and some useful observations and insightful reflections are made. The findings reported in this study are useful because it offers a number of important recommendations for future research in this area.


title: Chatbots: Are they Really Useful?

abstract: Chatbots are computer programs that interact with users using natural lan- guages. This technology started in the 1960’s; the aim was to see if chatbot systems could fool users that they were real humans. However, chatbot sys- tems are not only built to mimic human conversation, and entertain users. In this paper, we investigate other applications where chatbots could be useful such as education, information retrival, business, and e-commerce. A range of chatbots with useful applications, including several based on the ALICE/AIML architecture, are presented in this paper.


title: Aspect Ranking: Identifying Important Product Aspects from Online Consumer Reviews

abstract: In this paper, we dedicate to the topic of aspect ranking, which aims to automatically identify important product aspects from online consumer reviews. The important aspects are identified according to two observations: (a) the important aspects of a product are usually commented by a large number of consumers; and (b) consumers' opinions on the important aspects greatly influence their overall opinions on the product. In particular, given consumer reviews of a product, we first identify the product aspects by a shallow dependency parser and determine consumers' opinions on these aspects via a sentiment classifier. We then develop an aspect ranking algorithm to identify the important aspects by simultaneously considering the aspect frequency and the influence of consumers' opinions given to each aspect on their overall opinions. The experimental results on 11 popular products in four domains demonstrate the effectiveness of our approach. We further apply the aspect ranking results to the application of document-level sentiment classification, and improve the performance significantly.


title: A Broadband Circularly Polarized Crossed-Dipole Antenna

abstract: A unidirectional broadband circularly polarized (CP) crossed-dipole antenna is presented in this communication. This antenna has a simple feeding structure, which uses an unequal power network. It can simply realize 90° phase shift and four equal power divisions. The study of the antenna performance with different geometric parameters has been conducted. Working band of designed antenna covers the BeiDou Navigation Satellite System, GPS, and GLNOSS bands. An optimized antenna is designed and measured, the measured results agree well with the simulated results. The results show good performance of impendence bandwidth is approximately 66.2% (1.01–2.01 GHz), the 3-dB axial-ratio bandwidth (ARBW) of approximately 41.3% (1.21–1.97 GHz). Moreover, the measured bore-sight antenna gain is stable and varying not too much, which average value is 6.0 dBic with less than 1.5-dB variation within the 3-dB ARBW.


title: Testing a TPACK-Based Technology Integration Assessment Rubric

abstract: Although there is ever-increasing emphasis on integrating technology in teaching, there are few well-tested and refined assessments to measure the quality of this integration. The few measures that are available tend to favor constructivist approaches to teaching, and thus do not accurately assess the quality of technology integration across a range of different teaching approaches. We have developed a more “pedagogically inclusive” instrument that reflects key TPACK concepts and that has proven to be both reliable and valid in two successive rounds of testing. The instrument’s interrater reliability coefficient (.857) was computed using both Intraclass Correlation and a score agreement (84.1%) procedure. Internal consistency (using Cronbach’s Alpha) was .911. Test-retest reliability (score agreement) was 87.0%. Five TPACK experts also confirmed the instrument’s construct and face validities. We offer this new rubric to help teacher educators to more accurately assess the quality of technology integration in lesson plans, and suggest exploring its use in project and unit plans. Developing and Assessing TPACK New understanding of the complex, situated, and interdependent nature of teachers’ technology integration knowledge—termed “technological pedagogical content knowledge,” or TPACK (Mishra & Koehler, 2006; Koehler & Mishra, 2008)—has led to inevitable questions about how this knowledge can be both developed and assessed. As the summaries below demonstrate, there is considerably more variety at present among TPACK development approaches than among assessment strategies. Koehler & Mishra (2005) recommend a learning-by-design approach to TPACK development in which educators, content experts, and technology specialists design instruction collaboratively, building TPACK as they do so (Koehler, Mishra & Yahya 2007). Other researchers promote immersive, content-based approaches, such as instructional modeling (Niess, 2005), collaborative lesson study with university researchers (Groth, Spickler, Bergner, & Bardzell, 2009), and meta-cognitive exploration of “deictic” TPACK that emerges as curricula and technologies change (Hughes & Scharber, 2008). Still others promote active, professional reflection and inquiry. Dawson (2007) and Pierson (2008), for example, suggest TPACK as a focus for teachers’ action research. Mouza & Wong (2009) propose a TPACK-based case development strategy in which teachers learn from their practice. Two approaches focus TPACK development within teachers’ planning. Roblyer & Doering (2010) recommend TPACK self-assessment as the first step in each stage of instructional decision-making. Harris and Hofer (2006; 2009) draw upon research about teachers’ planning practices to suggest a learning activities-based approach to selecting and combining curriculum-keyed teaching/learning strategies and complementary educational technologies. By contrast, published instruments that assess TPACK development and that have been tested for reliability and validity are of one type only: the self-report survey. Schmidt, Baran, Thompson, Koehler, Shin, & Mishra (2009) and Archambault & Crippen (2009) developed self-report instruments with multiple items keyed to each of the seven types of knowledge represented in the TPACK construct: technological (T), pedagogical (P), content (C), technological pedagogical (TP), technological content (TC), pedagogical content (PC), and technological pedagogical content knowledge (TPACK). Schmidt et al.’s survey was designed for repeated use by preservice teachers as they progress through their teacher education programs. It was also found to be reliable and valid for use at the beginning and end of shorter-duration summer courses in technology integration. Archambault and Crippen’s survey instrument was designed to be used by inservice instructors, and was found to be reliable and valid with a nationally representative sample of approximately 600 K-12 online teachers. Though the testing of these two instruments proved them to be quite robust measures, the challenges inherent in accurately estimating teachers’ knowledge via self-reports—in particular, that of inexperienced teachers—are well-documented. Unfortunately, research has shown that measured gains in teachers’ self-assessed knowledge over time are more reflective of their increased confidence regarding a particular professional development topic than their actual increased knowledge in practice (Lawless & Pellegrino, 2007; Schrader & Lawless, 2004). Self-report data should therefore be triangulated with external assessments of teachers’ TPACK knowledge. Since no instrument had been developed and published to date (to our knowledge) that supported this type of performance-based evaluation of TPACK, we decided to create and test one.


title: Automatic Driving on Ill-defined Roads: An Adaptive, Shape-constrained, Color-based Method

abstract: Autonomous following of ill-defined roads is an important part of visual navigation systems. This paper presents an adaptive method that uses a statistical model of the color of the road surface within a trapezoidal shape that approximately corresponds to the projection of the road on the image plane. The method does not perform an explicit segmentation of the images but instead expands the shape sideways until the match between shape and road worsens, simultaneously computing the color statistics. Results show that the method is capable of reactively following roads, at driving speeds typical of the robots used, in a variety of situations while coping with variable conditions of the road such as surface type, puddles, and shadows. We extensively evaluate the proposed method using a large number of datasets with ground truth available from http://www.aber.ac.uk/en/cs/research/ir/dss/. We moreover evaluate many color spaces in the context of road following, and we find that the color spaces that separate luminance from color information perform best, especially if the luminance information is discarded.


Comparative Study of Knowledge in Crop Diseases Using Machine Learning Techniques


title: Compact low-voltage power-efficient operational amplifier cells for VLSI

abstract: Compact low-voltage power-efficient operational amplifiers are described that are very suitable as very-large-scale-integration library cells because of the small die area of 0.08 mm/sup 2/ and the minimum supply voltage of 1.8 V. A key part of the circuit is the rail-to-rail class-AB output stage with folded mesh feedback control that combines power efficiency with operation down to 1.8 V and allows sufficient gain in a compact two-stage topology. A version with rail-to-rail input stage features a rail-to-rail input range for supply voltages down to 2.5 V. The dc gain of the op amps is more than 80 db while driving 10 k/spl Omega/, and the unity-gain frequency is 4 MHz with phase margin of 67/spl deg/ while driving 5 pF. The equivalent input noise voltage is 38 nV//spl radic/(Hz) at a frequency of 100 kHz. The amplifiers have been implemented in a standard digital 1.6-/spl mu/m complementary metal-oxide-semiconductor process.


title: Unsupervised Spectral–Spatial Feature Learning via Deep Residual Conv–Deconv Network for Hyperspectral Image Classification

abstract: Supervised approaches classify input data using a set of representative samples for each class, known as training samples . The collection of such samples is expensive and time demanding. Hence, unsupervised feature learning, which has a quick access to arbitrary amounts of unlabeled data, is conceptually of high interest. In this paper, we propose a novel network architecture, fully Conv–Deconv network, for unsupervised spectral–spatial feature learning of hyperspectral images, which is able to be trained in an end-to-end manner. Specifically, our network is based on the so-called encoder–decoder paradigm, i.e., the input 3-D hyperspectral patch is first transformed into a typically lower dimensional space via a convolutional subnetwork (encoder), and then expanded to reproduce the initial data by a deconvolutional subnetwork (decoder). However, during the experiment, we found that such a network is not easy to be optimized. To address this problem, we refine the proposed network architecture by incorporating: 1) residual learning and 2) a new unpooling operation that can use memorized max-pooling indexes. Moreover, to understand the “black box,” we make an in-depth study of the learned feature maps in the experimental analysis. A very interesting discovery is that some specific “neurons” in the first residual block of the proposed network own good description power for semantic visual patterns in the object level, which provide an opportunity to achieve “free” object detection. This paper, for the first time in the remote sensing community, proposes an end-to-end fully Conv–Deconv network for unsupervised spectral–spatial feature learning. Moreover, this paper also introduces an in-depth investigation of learned features. Experimental results on two widely used hyperspectral data, Indian Pines and Pavia University, demonstrate competitive performance obtained by the proposed methodology compared with other studied approaches.


One Intelligent Agent to Rule Them All Bachelor Thesis


title: Effect of Calcium and Vitamin D Supplementation on Bone Density in Men and Women 65 Years of Age or Older

abstract: Background Inadequate dietary intake of calcium and vitamin D may contribute to the high prevalence of osteoporosis among older persons. Methods We studied the effects of three years of dietary supplementation with calcium and vitamin D on bone mineral density, biochemical measures of bone metabolism, and the incidence of nonvertebral fractures in 176 men and 213 women 65 years of age or older who were living at home. They received either 500 mg of calcium plus 700 IU of vitamin D3 (cholecalciferol) per day or placebo. Bone mineral density was measured by dual-energy x-ray absorptiometry, blood and urine were analyzed every six months, and cases of nonvertebral fracture were ascertained by means of interviews and verified with use of hospital records. Results The mean (±SD) changes in bone mineral density in the calcium–vitamin D and placebo groups were as follows: femoral neck, +0.50±4.80 and -0.70±5.03 percent, respectively (P = 0.02); spine, +2.12±4.06 and +1.22±4.25 percent (P = 0.04); and total body,...


title: Deployment of UAV-mounted access points according to spatial user locations in two-tier cellular networks

abstract: We envision small cells mounted on unmanned aerial vehicles, to complement existing macrocell infrastructure. We demonstrate through numerical analysis that clustering algorithms can be used to position the airborne access points and select users to offload from the macrocells. We compare the performance of these deployments against equivalent simulated picocell deployments. We demonstrate that due to their ability to position themselves around exact user locations while maintaining a direct line-of-sight link the airborne access points provide a significantly improved received signal strength than the static picocell alternatives. We also find that the airborne access points provide superior service quality even in the presence of user and access point positioning errors.


title: Current-Mode Transceiver for Silicon Interposer Channel

abstract: An energy-efficient 3 Gb/s current-mode interface scheme is proposed for on-chip global interconnects and silicon interposer channels. The transceiver core consists of an open-drain transmitter with one-tap pre-emphasis and a current sense amplifier load as the receiver. The current sense amplifier load is formed by stacking a PMOS diode stage and a cross-coupled NMOS stage, providing an optimum current-mode receiver without any bias current. The proposed scheme is verified with two cases of transceivers implemented in 65 nm CMOS. A 10 mm point-to-point data-only channel shows an energy efficiency of 9.5 fJ/b/mm, and a 20 mm four-drop source-synchronous link achieves 29.4 fJ/b/mm including clock and data channels.


title: WordNet Affect: an Affective Extension of WordNet

abstract: In this paper we present a linguistic resource for the lexical representation of affective knowledge. This resource (named WORDNETAFFECT) was developed starting from WORDNET, through a selection and tagging of a subset of synsets representing the affective


title: Labia minora reconstruction using clitoral hood flaps, wedge excisions, and YV advancement flaps.

abstract: BACKGROUND ::: Labia minora reduction (labioplasty, labiaplasty) is the most common female genital aesthetic procedure. The majority of labia reductions are performed by trimming the labial edges. Many of these women present with (1) asymmetry; (2) scalloping of the labial edges with wide, occasionally painful scars; and (3) abrupt termination and distortion of the clitoral hood at its normal junctions with the clitoral frenula and the upper labium. Reconstruction can usually be performed with wedge excisions, labial YV advancement, and touch-up trimming. Reconstruction of a labial amputation, however, required the development of a new clitoral hood flap. ::: ::: ::: METHODS ::: Twenty-four clitoral hood flaps were performed on 17 patients from June of 2006 through May of 2010. An island clitoral hood flap randomly based on the dartos fascia of the lower clitoral hood and medial labium majus is transposed to the ipsilateral labial defect to reconstruct a labium. Of the 10 patients with unilateral flaps, nine of the patients had previous bilateral labial reductions. Reconstruction of the opposite side in these nine women was performed using one or a combination of the following: wedge excisions, YV advancement flaps, or controlled touch-up trimming. ::: ::: ::: RESULTS ::: All 24 flaps survived, with four minor complications. Five patients underwent revision of a total of seven flaps, but only two were for complications. As experience increased, revisions for aesthetic improvement became less common. ::: ::: ::: CONCLUSION ::: Reconstruction of labia minora defects secondary to trimming labia reductions is very successful using a combination of clitoral hood flaps, wedge excisions, and YV advancements.


title: Wearable Performance Devices in Sports Medicine

abstract: Context:Wearable performance devices and sensors are becoming more readily available to the general population and athletic teams. Advances in technology have allowed individual endurance athletes, sports teams, and physicians to monitor functional movements, workloads, and biometric markers to maximize performance and minimize injury. Movement sensors include pedometers, accelerometers/gyroscopes, and global positioning satellite (GPS) devices. Physiologic sensors include heart rate monitors, sleep monitors, temperature sensors, and integrated sensors. The purpose of this review is to familiarize health care professionals and team physicians with the various available types of wearable sensors, discuss their current utilization, and present future applications in sports medicine.Evidence Acquisition:Data were obtained from peer-reviewed literature through a search of the PubMed database. Included studies searched development, outcomes, and validation of wearable performance devices such as GPS, accelerom...


title: Design of Last-Level On-Chip Cache Using Spin-Torque Transfer RAM (STT RAM)

abstract: Because of its high storage density with superior scalability, low integration cost and reasonably high access speed, spin-torque transfer random access memory (STT RAM) appears to have a promising potential to replace SRAM as last-level on-chip cache (e.g., L2 or L3 cache) for microprocessors. Due to unique operational characteristics of its storage device magnetic tunneling junction (MTJ), STT RAM is inherently subject to a write latency versus read latency tradeoff that is determined by the memory cell size. This paper first quantitatively studies how different memory cell sizing may impact the overall computing system performance, and shows that different computing workloads may have conflicting expectations on memory cell sizing. Leveraging MTJ device switching characteristics, we further propose an STT RAM architecture design method that can make STT RAM cache with relatively small memory cell size perform well over a wide spectrum of computing benchmarks. This has been well demonstrated using CACTI-based memory modeling and computing system performance simulations using SimpleScalar. Moreover, we show that this design method can also reduce STT RAM cache energy consumption by up to 30% over a variety of benchmarks.


title: The Wheels on the Bot Go Round and Round: Robotics Curriculum in Pre-Kindergarten.

abstract: clers” that they constructed using parts from LEGO ® Education WeDo™ Robotics Construction Sets. The Robot Recyclers were designed to help carry, push, and/or sort recyclable materials found in the classroom. Researchers were participant-observers in the robotics lessons over the course of curriculum implementation. Each lesson was taught by the researchers, with classroom teachers present in order to facilitate classroom management and assist with small group work. A combination of interviews, video, photographs, and classroom observations were used to document the students’ experiences. Classroom teachers were also interviewed and asked to complete anonymous pre and post surveys. Results from this study provide preliminary evidence that PreKindergarten children can design, build, and program a robot after just one week of concentrated robotics work. Additionally, results indicate that teachers were able to successfully integrate robotics work into their classrooms that included foundational math and literacy concepts while also engaging children in the arts. However, this study also highlights the difficulties and challenges that must be considered before implementing a robotics curriculum into a PreKindergarten classroom, including opportunities for one-to-one adult assistance during building and programming activities.


title: Essential Oils in Food Preservation: Mode of Action, Synergies, and Interactions with Food Matrix Components

abstract: Essential oils are aromatic and volatile liquids extracted from plants. The chemicals in essential oils are secondary metabolites, which play an important role in plant defense as they often possess antimicrobial properties. The interest in essential oils and their application in food preservation has been amplified in recent years by an increasingly negative consumer perception of synthetic preservatives. Furthermore, food-borne diseases are a growing public health problem worldwide, calling for more effective preservation strategies. The antibacterial properties of essential oils and their constituents have been documented extensively. Pioneering work has also elucidated the mode of action of a few essential oil constituents, but detailed knowledge about most of the compounds’ mode of action is still lacking. This knowledge is particularly important to predict their effect on different microorganisms, how they interact with food matrix components, and how they work in combination with other antimicrobial compounds. The main obstacle for using essential oil constituents as food preservatives is that they are most often not potent enough as single components, and they cause negative organoleptic effects when added in sufficient amounts to provide an antimicrobial effect. Exploiting synergies between several compounds has been suggested as a solution to this problem. However, little is known about which interactions lead to synergistic, additive, or antagonistic effects. Such knowledge could contribute to design of new and more potent antimicrobial blends, and to understand the interplay between the constituents of crude essential oils. The purpose of this review is to provide an overview of current knowledge about the antibacterial properties and antibacterial mode of action of essential oils and their constituents, and to identify research avenues that can facilitate implementation of essential oils as natural preservatives in foods.


The Remaking of Reading : Data Mining and the Digital Humanities


title: Oracle Database In-Memory: A dual format in-memory database

abstract: The Oracle Database In-Memory Option allows Oracle to function as the industry-first dual-format in-memory database. Row formats are ideal for OLTP workloads which typically use indexes to limit their data access to a small set of rows, while column formats are better suited for Analytic operations which typically examine a small number of columns from a large number of rows. Since no single data format is ideal for all types of workloads, our approach was to allow data to be simultaneously maintained in both formats with strict transactional consistency between them.


title: An Algorithm for Calculating the QR and Singular Value Decompositions of Polynomial Matrices

abstract: In this paper, a new algorithm for calculating the QR decomposition (QRD) of a polynomial matrix is introduced. This algorithm amounts to transforming a polynomial matrix to upper triangular form by application of a series of paraunitary matrices such as elementary delay and rotation matrices. It is shown that this algorithm can also be used to formulate the singular value decomposition (SVD) of a polynomial matrix, which essentially amounts to diagonalizing a polynomial matrix again by application of a series of paraunitary matrices. Example matrices are used to demonstrate both types of decomposition. Mathematical proofs of convergence of both decompositions are also outlined. Finally, a possible application of such decompositions in multichannel signal processing is discussed.


title: Detecting money laundering and terrorist financing via data mining

abstract: Using import-export information to improve financial transaction security.


title: Role mining with ORCA

abstract: With continuously growing numbers of applications, enterprises face the problem of efficiently managing the assignment of access permissions to their users. On the one hand, security demands a tight regime on permissions; on the other hand, users need permissions to perform their tasks. Role-based access control (RBAC) has proven to be a solution to this problem but relies on a well-defined set of role definitions, a role concept for the enterprise in question. The definition of a role concept (role engineering) is a difficult task traditionally performed via interviews and workshops. However, often users already have the permissions that they need to do their jobs, and roles can be derived from these permission assignments using data mining technology, thus giving the process of role concept definition a head-start.In this paper, we present the ORCA role mining tool and its algorithm. The algorithm performs a cluster analysis on permission assignments to build a hierarchy of permission clusters and presents the results to the user in graphical form. It allows the user to interactively add expert knowledge to guide the clustering algorithm. The tool provides valuable insights into the permission structures of an enterprise and delivers an initial role hierarchy for the definition of an enterprise role concept using a bottom-up approach.


title: Identifying Topics By Position

abstract: This paper addresses the problem of identifying likely topics of texts by their position in the text. It describes the automated training and evaluation of an Optimal Position Policy, a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities of discourse structure. This method can be used in applications such as information retrieval, routing, and text summarization.


title: A wireless soil moisture sensor powered by solar energy

abstract: In a variety of agricultural activities, such as irrigation scheduling and nutrient management, soil water content is regarded as an essential parameter. Either power supply or long-distance cable is hardly available within field scale. For the necessity of monitoring soil water dynamics at field scale, this study presents a wireless soil moisture sensor based on the impedance transform of the frequency domain. The sensor system is powered by solar energy, and the data can be instantly transmitted by wireless communication. The sensor electrodes are embedded into the bottom of a supporting rod so that the sensor can measure soil water contents at different depths. An optimal design with time executing sequence is considered to reduce the energy consumption. The experimental results showed that the sensor is a promising tool for monitoring moisture in large-scale farmland using solar power and wireless communication.


title: Beyond Customer Churn: Generating Personalized Actions to Retain Customers in a Retail Bank by a Recommender System Approach

abstract: Customer churn may be a critical issue for banks. The extant literature on statistical and machine learning for customer churn focuses on the problem of correctly predicting that a customer is about to switch bank, while very rarely consid-ers the problem of generating personalized actions to improve the customer retention rate. However, these decisions are at least as critical as the correct identification of customers at risk. The decision of what actions to deliver to what customers is normally left to managers who can only rely upon their knowledge. By looking at the scientific literature on CRM and personalization, this research proposes a number of models which can be used to generate marketing ac-tions, and shows how to integrate them into a model embracing both the analytical prediction of customer churn and the generation of retention actions. The benefits and risks associated with each approach are discussed. The paper also describes a case of application of a predictive model of customer churn in a retail bank where the analysts have also generated a set of personalized actions to retain customers by using one of the approaches presented in the paper, namely by adapting a recommender system approach to the retention problem.


title: Diffusion Variational Autoencoders

abstract: A standard Variational Autoencoder, with a Euclidean latent space, is structurally incapable of capturing topological properties of certain datasets. To remove topological obstructions, we introduce Diffusion Variational Autoencoders with arbitrary manifolds as a latent space. A Diffusion Variational Autoencoder uses transition kernels of Brownian motion on the manifold. In particular, it uses properties of the Brownian motion to implement the reparametrization trick and fast approximations to the KL divergence. We show that the Diffusion Variational Autoencoder is capable of capturing topological properties of synthetic datasets. Additionally, we train MNIST on spheres, tori, projective spaces, SO(3), and a torus embedded in R3. Although a natural dataset like MNIST does not have latent variables with a clear-cut topological structure, training it on a manifold can still highlight topological and geometrical properties.


Elucidating Conceptual Properties from Word Embeddings


title: Control of Tendon-Driven Soft Foam Robot Hands

abstract: This paper presents a series of control strategies for soft compliant manipulators. We provide a novel approach to control multi-fingered tendon-driven foam hands using a CyberGlove and a simple ridge regression model. The results achieved include complex posing, dexterous grasping and in-hand manipulations. To enable efficient data sampling and a more intuitive design process of foam robots, we implement and evaluate a finite element based simulation. The accuracy of this model is evaluated using a Vicon motion capture system. We then use this simulation to solve inverse kinematics and compare the performance of supervised learning, reinforcement learning, nearest neighbor and linear ridge regression methods in terms of their accuracy and sample efficiency.


Bridging HMMs and RNNs through Architectural Transformations


Mood Detection: Implementing a facial expression recognition system


title: Value Directed Exploration in Multi-Armed Bandits with Structured Priors

abstract: Multi-armed bandits are a quintessential machine learning problem requiring the balancing of exploration and exploitation. While there has been progress in developing algorithms with strong theoretical guarantees, there has been less focus on practical near-optimal finite-time performance. In this paper, we propose an algorithm for Bayesian multi-armed bandits that utilizes value-function-driven online planning techniques. Building on previous work on UCB and Gittins index, we introduce linearly-separable value functions that take both the expected return and the benefit of exploration into consideration to perform n-step lookahead. The algorithm enjoys a sub-linear performance guarantee and we present simulation results that confirm its strength in problems with structured priors. The simplicity and generality of our approach makes it a strong candidate for analyzing more complex multi-armed bandit problems.


title: Thickening freeform surfaces for solid fabrication

abstract: Purpose – Given an intersection-free mesh surface S, the paper introduces a method to thicken S into a solid H located at one side of S. By such a surface-to-solid conversion operation, industrial users are able to fabricate a designed (or reconstructed) surface by rapid prototyping. Design/methodology/approach – The paper first investigates an implicit representation of the thickened solid H according to an extension of signed distance function. After that, a partial surface reconstruction algorithm is proposed to generate the boundary surface of H, which retains the given surface S on the resultant surface. Findings – Experimental tests show that the thickening results generated by the method give nearly uniform thickness and meanwhile do not present shape approximation error at the region of input surface S. These two good properties are important to the industrial applications of solid fabrication. Research limitations/implications – The input polygonal model is assumed to be intersection-free, where ...


title: A Cognitive radio approach for usage of virtual unlicensed spectrum

abstract: While essentially all of the frequency spectrum is allocated to different applications, observations provide evidence that usage of the spectrum is actually quite limited, particularly in bands above 3 GHz. In this paper we present a Cognitive Radio approach for usage of Virtual Unlicensed Spectrum (CORVUS), a vision of a Cognitive Radio (CR) based approach that uses allocated spectrum in a opportunistic manner to create "virtual unlicensed bands" i.e. bands that are shared with the primary (often licensed) users on a non-interfering basis. Dynamic spectrum management techniques are used to adapt to immediate local spectrum availability. We define the system requirements for this approach, as well as the general architecture and basic physical and link layer functions of CORVUS.


title: Computer Science Pedagogical Content Knowledge: Characterizing Teacher Performance

abstract: Computer science education efforts are expanding across the globe to equip students with the necessary computing skills for today’s digital world. However, preparing students to become literate in computing activities requires the training of tens of thousands of teachers in computer science. The discrepancy between student needs and teacher preparation in computer science has raised questions of quality teachers, particularly for teachers who do not possess adequate content or pedagogical knowledge to teach computer science efficiently. To address this issue, we designed an instrument to measure knowledge needed to teach computer science (i.e., computer science pedagogical content knowledge). Results exhibited that our instrument measured aspects of teachers’ computer science pedagogical content knowledge; however, teachers’ prior background in teaching did not influence their performance. We discuss implications for future research and practice.


title: Parallel Simulations of Manufacturing Processing using Simpy, a Python-Based Discrete Event Simulation Tool

abstract: SimPy is a Python-based, interpreted simulation tool that offers the power and convenience of Python. It is able to launch processes and sub-processes using generators, which act autonomously and may interact using interrupts. SimPy offers other advantages over competing commercial codes in that it allows for modular development, use of a version control system such as CVS, can be made self-documenting with PyDoc, and is completely extensible. The convenience of an interpreted language, however, is offset for large models by slower than desired run times. This disadvantage can be compensated for by parallelizing the system using PyMPI, from the Lawrence Livermore National Laboratory. This work was performed under the auspices of the U.S. Department of Energy by University of California, Lawrence Livermore National Laboratory under Contract W-7405-Eng-48.


title: Model reference adaptive system-based speed estimators for sensorless control of interior permanent magnet synchronous machines

abstract: In this work, speed estimators are designed based on a model reference adaptive system (MRAS) for sensorless control of interior permanent magnet synchronous machines (IPMSMs). To provide better filtering performance and reduce the noise contents in the estimated speed, an adaptive line enhancer is proposed to work with a sliding-mode observer to provide an improved reference model for speed estimation. In addition, a heterodyning speed adaption scheme is proposed to replace the conventional speed adaption mechanism. The proposed MRAS-based speed estimator has two different operating modes, which are suitable for generator- and motor-type applications, respectively. The effectiveness of the proposed speed estimators are verified by simulation using real-word vehicle data logged from a test vehicle. Furthermore, experimental results on a test stand for a heavy-duty IPMSM are also provided.


title: Mechanical Parameter Estimation of Permanent-Magnet Synchronous Machines With Aiding From Estimation of Rotor PM Flux Linkage

abstract: This paper proposes a combined parameter estimation for permanent-magnet synchronous machines (PMSMs), by which the rotor permanent-magnet (PM) flux linkage and mechanical parameters, such as the combined moment of inertia and viscous friction coefficient, are estimated without the aid from nominal machine parameter values. The proposed estimation of rotor PM flux linkage is based on the addition of position offsets and does not need the information of other machine parameters or injection of currents. With the aid from estimated rotor PM flux linkage, the electromagnetic torque can be consequently calculated for the estimation of mechanical parameters at no-load condition, and a two-step method is employed to achieve a higher ratio of signal to noise. This combined parameter estimation is finally validated on a surface-mounted PMSM (SPMSM) and an interior PMSM (IPMSM), respectively. It is found that the estimation error of combined moment of inertia with reference to its nominal value can be less than 10 $\%$ even if it (the combined moment of inertia) is lower than $1\times 10^{-3}\ \hbox{kg}\cdot \hbox{m}^{2} $ , while the estimation error will be further decreased to less than 3 $\%$ if it is higher than $7\times 10^{-3}\ \hbox{kg}\cdot \hbox{m}^{2}$ .


title: Fully-automatic recognition of various parking slot markings in Around View Monitor (AVM) image sequences

abstract: This paper proposes a novel fully-automatic method for recognizing various parking slot markings in image sequences acquired by an Around View Monitor (AVM) system which is gaining popularity as a parking-aid product. The proposed method utilizes an approach which finds parking slots in AVM image sequences using a simple detector and combines sequentially acquired slots rather than using a sophisticated heavy detector in order to achieve the robustness against diverse practical situations. Parking slots are first detected in the current image using the hierarchical tree structure based approach presented in our previous paper [1]. Then, the current positions of previously detected parking slots are predicted using a transformation between consecutive images, and the parking slots detected in the current image and predicted from previous images are combined. The resulting parking slots are clustered according to their types and orientations, and the clusters which contain more than a predetermined number of slots are selected as final parking slots. The proposed method was evaluated using 10 AVM image sequences that include 134 parking slots, and demonstrated a detection rate of 95% with only three false detections.


title: PaperPhone: understanding the use of bend gestures in mobile devices with flexible electronic paper displays

abstract: Flexible displays potentially allow for interaction styles that resemble those used in paper documents. Bending the display, e.g., to page forward, shows particular promise as an interaction technique. In this paper, we present an evaluation of the effectiveness of various bend gestures in executing a set of tasks with a flexible display. We discuss a study in which users designed bend gestures for common computing actions deployed on a smartphone-inspired flexible E Ink prototype called PaperPhone. We collected a total of 87 bend gesture pairs from ten participants and their appropriateness over twenty actions in five applications. We identified six most frequently used bend gesture pairs out of 24 unique pairs. Results show users preferred bend gestures and bend gesture pairs that were conceptually simpler, e.g., along one axis, and less physically demanding. There was a strong agreement among participants to use the same three pairs in applications: (1) side of display, up/down (2) top corner, up/down (3) bottom corner, up/down. For actions with a strong directional cue, we found strong consensus on the polarity of the bend gestures (e.g., navigating left is performed with an upwards bend gesture, navigating right, downwards). This implies that bend gestures that take directional cues into account are likely more natural to users.


title: Smartphone-based mobile gunshot detection

abstract: The ability to detect gunshots can provide someone with invaluable information in various circumstances. For the military and public servants, detecting gunshots can help save lives and potentially target offenders. People participating in shooting sports as beginners or professionals can also benefit from the use of sensors for improving their reaction and self control during training. Most current methods for gunshot detection require expensive devices that are purpose built or developed and often only examine one or two features of the gunshots such as the sound, recoil, or visible flash. Using the current sensors built into smartphones, 15 samples utilizing 10 different sensors are used examine how gunshot detection can be performed through the use of simple sensors. This extension of human activity recognition resulted in gunshot classification accuracy ranging from 0.0% – 99.7% with an average of 86.6%. Understanding how simple sensors respond to gunshots can provide simple and easy accessibility to new detection methods and ample opportunities to improve this potential field for various personal and smart city applications such as crime detection, policing, gunshot violence monitoring and control in the community.


Theory of Shielding and Grounding of Control Cables to Reduce Surges


title: Review on cyber-physical systems

abstract: Cyber-physical systems U+0028 CPS U+0029 are complex systems with organic integration and in-depth collaboration of computation, communications and control U+0028 3C U+0029 technology. Subject to the theory and technology of existing network systems and physical systems, the development of CPS is facing enormous challenges. This paper first introduces the concept and characteristics of CPS and analyzes the present situation of CPS researches. Then the development of CPS is discussed from perspectives of system model, information processing technology and software design. At last it analyzes the main obstacles and key researches in developing CPS.


title: Agile & Kanban In Coordination

abstract: Iterative development and Kanban are not mutually exclusive competing methodologies; in essence they are complementary processes that when used together can facilitate higher performance in large development teams. This paper is a walkthrough of the Network Gaming team's implementation of Iterative Agile alongside Lean Kanban here at WMS Gaming. The intent is to cover the processes created and the improvements achieved with this coordinated Agile / Lean system.


title: Survey on routing in data centers: insights and future directions

abstract: Recently, a series of data center network architectures have been proposed. The goal of these works is to interconnect a large number of servers with significant bandwidth requirements. Coupled with these new DCN structures, routing protocols play an important role in exploring the network capacities that can be potentially delivered by the topologies. This article conducts a survey on the current state of the art of DCN routing techniques. The article focuses on the insights behind these routing schemes and also points out the open research issues hoping to spark new interests and developments in this field.


title: Electrical modeling and characterization of through-silicon vias (TSVs) for 3-D integrated circuits

abstract: The integration of chips in the third dimension has been explored to address various physical and system level limitations currently undermining chip performance. In this paper, we present a comprehensive analysis of the electrical properties of through silicon vias and microconnects with an emphasis on single via characteristics as well as inter-TSV capacitive and inductive coupling in the presence of either a neighboring ground tap or a grounded substrate back plane. We also analyze the impact of technology scaling on TSV electrical parasitics, and investigate the power and delay trend in 3-D interstratum IO drivers with those of global wire in 2-D circuits over various technology nodes. We estimate the global wire length necessary to produce an equivalent 3-D IO delay, a metric useful in early stage design tools for 3D floorplanning that considers the electrical characteristics of 3D connections with TSVs and microconnects.


title: Blockchain-Based Publishing Layer for the Keyless Signing Infrastructure

abstract: A Keyless Signing Infrastructure (KSI) provides users with a means to timestamp documents on a per-second basis. The KSI consists of a global infrastructure with several server layers, by using Merkle hash trees, the root hash can be used to verify the integrity, timestamp of a document. Regular publication of root hashes, e.g., once per month, allows a document to be verified without support of the servers, but the previously proposed publication channels have several limitations. In this paper we address these limitations, show how a blockchain can be used as an additional publication layer on top of a KSI. Using the scripting capabilities in transactions, new features are introduced to the publication of root hashes. This includes faster publication, proof of origin for the publisher, the possibility for third parties to explicitly verify root hashes before they are published. These improvements will allow the verification of documents to be simpler, more flexible, more secure.


title: Millimeter-wave Wireless LAN and its Extension toward 5G Heterogeneous Networks

abstract: Millimeter-wave (mmw) frequency bands, especially 60 GHz unlicensed band, are considered as a promising solution for gigabit short range wireless communication systems. IEEE standard 802.11ad, also known as WiGig, is standardized for the usage of the 60 GHz unlicensed band for wireless local area networks (WLANs). By using this mmw WLAN, multi-Gbps rate can be achieved to support bandwidth-intensive multimedia applications. Exhaustive search along with beamforming (BF) is usually used to overcome 60 GHz channel propagation loss and accomplish data transmissions in such mmw WLANs. Because of its short range transmission with a high susceptibility to path blocking, multiple number of mmw access points (APs) should be used to fully cover a typical target environment for future high capacity multi-Gbps WLANs. Therefore, coordination among mmw APs is highly needed to overcome packet collisions resulting from un-coordinated exhaustive search BF and to increase the total capacity of mmw WLANs. In this paper, we firstly give the current status of mmw WLANs with our developed WiGig AP prototype. Then, we highlight the great need for coordinated transmissions among mmw APs as a key enabler for future high capacity mmw WLANs. Two different types of coordinated mmw WLAN architecture are introduced. One is the distributed antenna type architecture to realize centralized coordination, while the other is an autonomous coordination with the assistance of legacy Wi-Fi signaling. Moreover, two heterogeneous network (HetNet) architectures are also introduced to efficiently extend the coordinated mmw WLANs to be used for future 5 Generation (5G) cellular networks.


title: Mobile Emitter Geolocation and Tracking Using TDOA and FDOA Measurements

abstract: This paper considers recursive tracking of one mobile emitter using a sequence of time difference of arrival (TDOA) and frequency difference of arrival (FDOA) measurement pairs obtained by one pair of sensors. We consider only a single emitter without data association issues (no missed detections or false measurements). Each TDOA measurement defines a region of possible emitter locations around a unique hyperbola. This likelihood function is approximated by a Gaussian mixture, which leads to a dynamic bank of Kalman filters tracking algorithm. The FDOA measurements update relative probabilities and estimates of individual Kalman filters. This approach results in a better track state probability density function approximation by a Gaussian mixture, and tracking results near the Cramer-Rao lower bound. Proposed algorithm is also applicable in other cases of nonlinear information fusion. The performance of proposed Gaussian mixture approach is evaluated using a simulation study, and compared with a bank of EKF filters and the Cramer-Rao lower bound.


title: Weakly Supervised Facial Attribute Manipulation via Deep Adversarial Network

abstract: Automatically manipulating facial attributes is challenging because it needs to modify the facial appearances, while keeping not only the person's identity but also the realism of the resultant images. Unlike the prior works on the facial attribute parsing, we aim at an inverse and more challenging problem called attribute manipulation by modifying a facial image in line with a reference facial attribute. Given a source input image and reference images with a target attribute, our goal is to generate a new image (i.e., target image) that not only possesses the new attribute but also keeps the same or similar content with the source image. In order to generate new facial attributes, we train a deep neural network with a combination of a perceptual content loss and two adversarial losses, which ensure the global consistency of the visual content while implementing the desired attributes often impacting on local pixels. The model automatically adjusts the visual attributes on facial appearances and keeps the edited images as realistic as possible. The evaluation shows that the proposed model can provide a unified solution to both local and global facial attribute manipulation such as expression change and hair style transfer. Moreover, we further demonstrate that the learned attribute discriminator can be used for attribute localization.


title: A novel human-computer collaboration: combining novelty search with interactive evolution

abstract: Recent work on novelty and behavioral diversity in evolutionary computation has highlighted the potential disadvantage of driving search purely through objective means. This paper suggests that leveraging human insight during search can complement such novelty-driven approaches. In particular, a new approach called novelty-assisted interactive evolutionary computation (NA-IEC) combines human intuition with novelty search to facilitate the serendipitous discovery of agent behaviors in a deceptive maze. In this approach, the human user directs evolution by selecting what is interesting from the on-screen population of behaviors. However, unlike in typical IEC, the user can now request that the next generation be filled with novel descendants. The experimental results demonstrate that combining human insight with novelty search not only finds solutions significantly faster and at lower genomic complexities than fully-automated processes guided purely by fitness or novelty, but it also finds solutions faster than the traditional IEC approach. Such results add to the evidence that combining human users and automated processes creates a synergistic effect in the search for solutions.


title: Key challenges and opportunities in hull form design optimisation for marine and offshore applications

abstract: New environmental regulations and volatile fuel prices have resulted in an ever-increasing need for reduction in carbon emission and fuel consumption. Designs of marine and offshore vessels are more demanding with complex operating requirements and oil and gas exploration venturing into deeper waters and hasher environments. Combinations of these factors have led to the need to optimise the design of the hull for the marine and offshore industry. The contribution of this paper is threefold. Firstly, the paper provides a comprehensive review of the state-of-the-art techniques in hull form design. Specifically, it analyses geometry modelling, shape transformation, optimisation and performance evaluation. Strengths and weaknesses of existing solutions are also discussed. Secondly, key challenges of hull form optimisation specific to the design of marine and offshore vessels are identified and analysed. Thirdly, future trends in performing hull form design optimisation are investigated and possible solutions proposed. A case study on the design optimisation of bulbous bow for passenger ferry vessel to reduce wave-making resistance is presented using NAPA software. Lastly, main issues and challenges are discussed to stimulate further ideas on future developments in this area, including the use of parallel computing and machine intelligence.


title: A new class of nature-inspired algorithms for self-adaptive peer-to-peer computing

abstract: We present, and evaluate benefits of, a design methodology for translating natural phenomena represented as mathematical models, into novel, self-adaptive, peer-to-peer (p2p) distributed computing algorithms (protocols). Concretely, our first contribution is a set of techniques to translate discrete sequence equations (also known as difference equations) into new p2p protocols called sequence protocols. Sequence protocols are self-adaptive, scalable, and fault-tolerant, with applicability in p2p settings like Grids. A sequence protocol is a set of probabilistic local and message-passing actions for each process. These actions are translated from terms in a set of source sequence equations. Individual processes do not simulate the source sequence equations completely. Instead, each process executes probabilistic local and message passing actions, so that the emergent round-to-round behavior of the sequence protocol in a p2p system can be probabilistically predicted by the source sequence equations. The article's second contribution is the design and evaluation of a set of sequence protocols for detection of two global triggers in a distributed system: threshold detection and interval detection. This article's third contribution is a new self-adaptive Grid computing protocol called HoneyAdapt. HoneyAdapt is derived from sequence equations modeling adaptive bee foraging behavior in nature. HoneyAdapt is intended for Grid applications that allow Grid clients, at run-time, a choice of algorithms for executing chunks of the application's dataset. HoneyAdapt tells each Grid client how to adaptively select at run-time, for each chunk it receives, a good algorithm for computing the chunk—this selection is based on continuous feedback from other clients. Finally, we design a variant of HoneyAdapt, called HoneySort, for application to Grid parallelized sorting settings using the master-worker paradigm. Our evaluation of these contributions consists of mathematical analysis, large-scale trace-based simulation results, and experimental results from a HoneySort deployment.


title: A control engineer's guide to sliding mode control

abstract: Presents a guide to sliding mode control for practicing control engineers. It offers an accurate assessment of the so-called chattering phenomenon, catalogs implementable sliding mode control design solutions, and provides a frame of reference for future sliding mode control research.


title: Designing Organizational Models for Service Integration in a Multi-sourcing Context

abstract: With the persistent shift towards multi-sourcing, the complexity of service delivery is continuously increasing. This presents new challenges for clients who now have to integrate interdependent services from multiple providers. As other functions, service integration is subject to make-or-buy decisions: clients can either build the required capabilities themselves or delegate service integration to external functions. To define detailed organizational models, one requires understanding of specific tasks and how to allocate them. Based on a qualitative and quantitative expert study, we analyze generic organizational models, and identify key service integration tasks. The allocation of these tasks to clients or their providers generates a set of granular organizational structures. We analyze drivers for delegating these tasks, and develop typical allocations in practice. Our work contributes to expanding the theoretical foundations of service integration. Moreover, our findings will assist clients to design their service integration organization, and to build more effective multi-sourcing solutions.


title: Advances in computational facial attractiveness methods

abstract: Attractiveness of a face plays an important role in many social endeavors. It influences careers like digital entertainment, modeling and acting, as well as person's career prospect, financial status, and personal relationships. Computational approaches to exploring the nature and components of face attractiveness have been proposed, and have become an emerging topic in facial analysis research. Integrating techniques from image processing, computer vision and machine learning, this subarea aims to develop computational methods to quantify and investigate the attractiveness of a face. This paper summarizes the most recent advances in four related aspects of face attractiveness: (a) facial attractiveness prediction, (b) facial attractiveness enhancement, (c) lateral facial attractiveness and (d) 3D facial attractiveness. The motivations, innovative techniques, and significant results are summarized and discussed. The open problems in these areas and directions for future work are also briefly stated.


title: Interpretable Transformations with Encoder-Decoder Networks

abstract: Deep feature spaces have the capacity to encode complex transformations of their input data. However, understanding the relative feature-space relationship between two transformed encoded images is difficult. For instance, what is the relative feature space relationship between two rotated images? What is decoded when we interpolate in feature space? Ideally, we want to disentangle confounding factors, such as pose, appearance, and illumination, from object identity. Disentangling these is difficult because they interact in very nonlinear ways. We propose a simple method to construct a deep feature space, with explicitly disentangled representations of several known transformations. A person or algorithm can then manipulate the disentangled representation, for example, to re-render an image with explicit control over parameterized degrees of freedom. The feature space is constructed using a transforming encoder-decoder network with a custom feature transform layer, acting on the hidden representations. We demonstrate the advantages of explicit disentangling on a variety of datasets and transformations, and as an aid for traditional tasks, such as classification.


The best-sofar selection in Artificial Bee Colony algorithm


title: Monocular Visual-Inertial SLAM-Based Collision Avoidance Strategy for Fail-Safe UAV Using Fuzzy Logic Controllers

abstract: In this paper, we developed a novel Cross-Entropy Optimization (CEO)-based Fuzzy Logic Controller (FLC) for Fail-Safe UAV to expand its collision avoidance capabilities in the GPS-denied environments using Monocular Visual-Inertial SLAM-based strategy. The function of this FLC aims to control the heading of Fail-Safe UAV to avoid the obstacle, e.g. wall, bridge, tree line et al, using its real-time and accurate localization information. In the Matlab Simulink-based training framework, the Scaling Factor (SF) is adjusted according to the collision avoidance task firstly, and then the Membership Function (MF) is tuned based on the optimized Scaling Factor to further improve the control performances. After obtained the optimal SF and MF, 64 % of rules has been reduced (from 125 rules to 45 rules), and a large number of real see-and-avoid tests with a quadcopter have done. The simulation and experiment results show that this new proposed FLC can precisely navigates the Fail-Safe UAV to avoid the obstacle, obtaining better performances compared to only SF optimization-based FLC. To our best knowledge, this is the first work to present the optimized FLC using Cross-Entropy method in both SF and MF optimization, and apply it in the UAV.


title: Relational Aggression, Gender, and Social‐Psychological Adjustment

abstract: Prior studies of childhood aggression have demonstrated that, as a group, boys are more aggressive than girls. We hypothesized that this finding reflects a lack of research on forms of aggression that are relevant to young females rather than an actual gender difference in levels of overall aggressiveness. In the present study, a form of aggression hypothesized to be typical of girls, relational aggression, was assessed with a peer nomination instrument for a sample of 491 third-through sixth-grade children. Overt aggression (i.e., physical and verbal aggression as assessed in past research) and social-psychological adjustment were also assessed. Results provide evidence for the validity and distinctiveness of relational aggression. Further, they indicated that, as predicted, girls were significantly more relationally aggressive than were boys. Results also indicated that relationally aggressive children may be at risk for serious adjustment difficulties (e.g., they were significantly more rejected and reported significantly higher levels of loneliness, depression, and isolation relative to their nonrelationally aggressive peers). Language: en


title: Parenting stress among parents of children with Neurodevelopmental Disorders

abstract: In recent years, studies have shown that parents of children with Neurodevelopmental Disorders (NDDs) experience more parenting stress than parents of typically developing children, but the relation between the type of disorders and parenting stress is far from clear. The purpose of this study was to compare the parenting stress experienced by parents of 239 children with Specific Learning Disorders (SpLD), Language Disorders (LD), Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and typical development (TD). Parents of children with NDDs experience more parenting stress than those of children who have TD. Although, parents of children with ASD or ADHD report the most high scores of parenting stress, also the parents of children with SpLD or LD report higher parental stress compared with parent of children without NDDs. Another interesting finding was that IQ level or emotional and behavioral problems are associated with the higher levels of parenting stress. This study suggest that parent, both mothers and fathers, of children with different type of NDDs should be provided with interventions and resources to empower them with the knowledge and skills to reduce their stress and to enhance their quality of life.


title: A Climate-Based Malaria Transmission Model with Structured Vector Population

abstract: In this paper, we present a malaria transmission model with periodic birth rate and age structure for the vector population. We first introduce the basic reproduction ratio for this model and then show that there exists at least one positive periodic state and that the disease persists when $\mathcal{R}_0>1$. It is also shown that the disease will die out if $\mathcal{R}_0<1$, provided that the invasion intensity is not strong. We further use these analytic results to study the malaria transmission cases in KwaZulu-Natal Province, South Africa. Some sensitivity analysis of $\mathcal{R}_0$ is performed, and in particular, the potential impact of climate change on seasonal transmission and populations at risk of the disease is analyzed.


Biology and Host Range of the Gall Midge Species Cystiphora taraxaci under Growth Chamber Conditions (Diptera: Cecidomyiidae)


title: Effects of Microplastic on Fitness and PCB Bioaccumulation by the LugwormArenicola marina(L.)

abstract: It has been speculated that marine microplastics may cause negative effects on benthic marine organisms and increase bioaccumulation of persistent organic pollutants (POPs). Here, we provide the first controlled study of plastic effects on benthic organisms including transfer of POPs. The effects of polystyrene (PS) microplastic on survival, activity, and bodyweight, as well as the transfer of 19 polychlorinated biphenyls (PCBs), were assessed in bioassays with Arenicola marina (L.). PS was pre-equilibrated in natively contaminated sediment. A positive relation was observed between microplastic concentration in the sediment and both uptake of plastic particles and weight loss by A. marina. Furthermore, a reduction in feeding activity was observed at a PS dose of 7.4% dry weight. A low PS dose of 0.074% increased bioaccumulation of PCBs by a factor of 1.1–3.6, an effect that was significant for ΣPCBs and several individual congeners. At higher doses, bioaccumulation decreased compared to the low dose, whic...


title: Developing and evaluating computational models of musical style

abstract: Stylistic composition is a creative musical activity, in which students as well as renowned composers write according to the style of another composer or period. We describe and evaluate two computational models of stylistic composition, called Racchman-Oct2010 (random constrained chain of Markovian nodes, October 2010) and Racchmaninof-Oct2010 (Racchman with inheritance of form). The former is a constrained Markov model, and the latter embeds this model in an analogy based design system. Racchmaninof-Oct2010 applies a pattern discovery algorithm called SIACT and a perceptually validated formula for rating pattern importance, to guide the generation of a new target design from an existing source design. A listening study is reported concerning human judgments of music excerpts that are, to varying degrees, in the style of mazurkas by Frederic Chopin (1810–1849). The listening study acts as an evaluation of the two computational models and a third, benchmark system, called Experiments in Musical Intelligence. Judges’ responses indicate that some aspects of musical style, such as phrasing and rhythm, are being modeled effectively by our algorithms. Judgments are also used to identify areas for future improvements. We discuss the broader implications of this work for the fields of engineering and design, where there is potential to make use of our models of hierarchical repetitive structure.


title: Active Contour Models for Extracting Ground and Forest Canopy Curves from Discrete Laser Altimeter Data

abstract: The importance of finding efficient ways of quantifying terrestrial carbon stocks at a global scale has increased due to the concerns about global climate change. Exchange of carbon between forests and the atmosphere is a vital component of the global carbon cycle (Nelson et al. 2003). Recent advances in remote sensing technology have facilitated rapid and inexpensive measurements of topography over large areas (Zhang et al. 2003).