Miracle-dz/UniFAR-FTUs huggingface dataset:
6 Development of a CORBA-based Humanoid Robot and its Applications

Recently, the research on humanoid robots has attracted many researchers. The research spans from stability and optimal control, gait generation, human-robot and robot-robot communication. In addition, humanoid robots have been also used to understand better human motion. Among humanoid robot prototypes the most well known is Honda humanoid robot (Hirai et. al., 1998). This robot has the ability to move forward and backward, sideways to the right or the left, as well as diagonally. In addition, the robot can turn in any direction, walk up and down stairs continuously. Other example is the 35 dof (degrees of freedom) Saika humanoid robot (Inaba et al. 1998). This robot can perform a reach-and-grasp motion through coordinating legs and arms. The key idea of the system architecture of this robot is a remote brained approach. In addition, the Waseda humanoid robot group has also developed an anthropomorphic dynamic biped walking robot adapting to the humans' living floor (Takanishi et. al., 1990). Fujitsu also has developed a commercial 25 dof miniature humanoid robot, named HOAP-1, for research purposes. Weighing 6 kg and standing 0.48 m tall, the light and compact HOAP-1 and accompanying simulation software can be used for developing motion control algorithms in such areas as two-legged walking, as well as in research on human-to-robot communication interfaces. In our robotics laboratory at Yamagata University, we initialized the humanoid robot project. The goal of this project is to contribute to the research on humanoid robots. For this reason, we developed an anthropomorphic biped humanoid robot called Bonten-Maru. During the humanoid robot design, we tried to mimic as much as possible the human characteristics, from the viewpoints of links dimensions, body structure, as well as the number and configuration of the degrees of freedom. The high number of dofs helps the humanoid robot to realize complex motions in even and uneven terrains, like walking, going up and down stairs, crawling, etc. In this chapter, we present the development of Common Object Request Broker Architecture (CORBA) based humanoid robot control systems. Consequently, this chapter explains the application of real time generation of humanoid robot optimal gait by using soft computing techniques, and also teleoperation systems and its applications. Simulation and experimental results of the proposed system in
STUDIES OF AN OPTIMALLY UNBIASED MA FILTER INTENDED GPS-BASED TIMEKEEPING FOR

Abstract : In this paper, we examine one of the possible approaches to design an optimally unbiased moving average (MA) filter intended for the time error online estimating and synchronization in timekeeping. The approach is based on the slowly changing nature of a time error generated by the local clock and has led to a simple formula for the optimally unbiased MA filter, which does not require any a priori knowledge about the time error process. When filtering the various GPS-based time error processes, we found out that, of the filters with the same time constant, the designed filter demonstrates an error intermediate between the three-state and two-state Kalman filters. The filter has been examined for numerically simulated data and some practical situations of the GPS-based time errors generated with the crystal and rubidium oscillators.
High-speed network intrusion detection and prevention

Today more than ever, gaining unauthorized access to network resources is appetizing for malicious intruders. Network Intrusion Detection and Prevention Systems (NIDPSs) are vital against these intrusions. For NIDPS, Deep Packet Inspection (DPI)—comparing incoming packet payloads against known attack signatures—is the most time-consuming operation which is even more challenging for high-speed networks where a byte of data arrives at every 200 ps from each 40-Gbps link. Traditional DPI systems use either off-chip random-access or content-addressable memory, neither of which is up to the speed challenge. To increase throughput by reducing off-chip access, on-chip filters such as Bloom Filters (BF) are also used. However, in this thesis, we show that BFs have shortcomings when implemented on hardware. Hence, we propose Aggregated Bloom Filters (ABF) to increase the throughput and scalability of hardware BFs. ABF leverages the query mechanism for hardware BFs by removing redundant hash calculations and redundant on-chip memory accesses for higher throughput. ABF also improves scalability by aggregating small distributed BFs to a single BF for better on-chip memory utilization. ABF shows seven-fold improvement in the average query throughput and four times less memory usage compared to previous hardware BFs for NIDPS. In the second part of this thesis, we expand our focus to optimize the memory usage for the entire DPI and eliminate the off-chip memory, completely. We propose a new data structure called TriBiCa (Trie Bitmap Content Analyzer), a minimal perfect hashing scheme for hardware, to achieve this goal. We have designed the TriBiCa for Xilinx Virtex II Pro FPGA chip, achieving 10-Gbps NIDPS throughput. A proof-of-concept design is implemented and tested with 1-Gbps packet streams. By using today's state-of-the-art FPGAs, we believe a throughput of 40 Gbps is achievable. NIDPS can easily be evaded by fragmentation of attack packets. The straightforward defragmentation method is not applicable at high-speeds due to high memory requirement. In the final part of this thesis, this multi-packet signature detection problem is addressed using a defragmentation-free, space-efficient solution. A new data structure, Prefix Bloom Filters (PBFs), is proposed to significantly reduce the storage requirement of the problem.
IEngage: Using Technology to Enhance Students’ Engagement in a Large Classroom

This paper aims to answer how we can increase students’ engagement in a large class. We hypothesised that the use of KeyPad, an interactive student response system, can lead to enhanced student engagement in a large classroom. We tested a model of classroom technology integration enhancing the students’ engagement among first year undergraduate students (n=131). This study provides evidence of significant effect of positive attitude and social pressure on the intent to use KeyPads. In turn, the intent to use KeyPads leads to the actual use of KeyPads which is directly associated with the level of student engagement. In addition, we find evidence for the relationship between extraversion and level of engagement such that compared to extrovert students, introvert students felt more engaged.
An architecture for stream OLAP exploiting SPE and OLAP engine

Explosive increase of real-time data sources, so-called "data streams" (or just "steams") and increasing demands for real-time analysis over streams give rise to realtime analysis over streams. However, developing tailor-made systems for such applications is not always desirable due to high developing costs and long developing periods. To cope with this problem, this paper proposes a novel architecture for online analytical processing (OLAP) over streams exploiting off-the-shelf stream processing engine (SPE) combined with OLAP engine. It allows users to perform OLAP analysis over streams for the latest time period, called Interval of Interest (Iol). The system in the meantime processes multiple continuous query language (CQL) queries corresponding to different aggregation levels in cube lattice. To cover arbitrary aggregation levels using limited system's memory, we propose to partially deploy CQL queries for those with higher reference frequencies, whereas the results are dynamically calculated using existing aggregation results with the help of OLAP engine. For optimal CQL query deployment, we propose a cost-based optimization method that maximizes the performance. The experimental results show that the proposed architecture is feasible enough to realize stream OLAP by combining an SPE and an OLAP engine. Also, the proposed system significantly outperforms other comparative methods by generating optimized query deployment plans.
A Rapid and Reliable Method of Counting Neurons and Other Cells in Brain Tissue: A Comparison of Flow Cytometry and Manual Counting Methods

It is of critical importance to understand the numbers and distributions of neurons and non-neurons in the cerebral cortex because cell numbers are reduced with normal aging and by diseases of the CNS. The isotropic fractionator method provides a faster way of estimating numbers of total cells and neurons in whole brains and dissected brain parts. Several comparative studies have illustrated the accuracy and utility of the isotropic fractionator method, yet it is a relatively new methodology, and there is opportunity to adjust procedures to optimize its efficiency and minimize error. In the present study, we use 142 samples from a dissected baboon cortical hemisphere to evaluate if isotropic fractionator counts using a Neubauer counting chamber and fluorescence microscopy could be accurately reproduced using flow cytometry methods. We find greater repeatability in flow cytometry counts, and no evidence of constant or proportional bias when comparing microscopy to flow cytometry counts. We conclude that cell number estimation using a flow cytometer is more efficient and more precise than comparable counts using a Neubauer chamber on a fluorescence microscope. This method for higher throughput, precise estimation of cell numbers has the potential to rapidly advance research in post-mortem human brains and vastly improve our understanding of cortical and subcortical structures in normal, injured, aged, and diseased brains.
Ethernet Controller for Host Communication with Energy-Efficient Microprocessor

— It is evident that chips are getting bigger in capacity through progressing time, thus increasing the difficulty in testing their functionality. The most common testing approach involves the use of fully programmable gate arrays (FPGAs) to send test data from a host PC station to the chip and return the chip's reply back to the host. This paper presents several techniques utilized to model a more robust protocol and to also provide faster synchronization of data with the chip via Ethernet connection. The results of such investigations of the circuits optimized reveal minimal logic utilization of registers and LUTs for the advantage of processor and memory performance.
A Self-Organized Internal Models Architecture for Coding Sensory–Motor Schemes

Cognitive robotics research draws inspiration from theories and models on cognition, as conceived by neuroscience or cognitive psychology, to investigate biologically plausible computational models in artificial agents. In this field, the theoretical framework of Grounded Cognition provides epistemological and methodological grounds for the computational modeling of cognition. It has been stressed in the literature that \textit{simulation}, \textit{prediction}, and \textit{multi-modal integration} are key aspects of cognition and that computational architectures capable of putting them into play in a biologically plausible way are a necessity. Research in this direction has brought extensive empirical evidence suggesting that \textit{Internal Models} are suitable mechanisms for sensory-motor integration. However, current Internal Models architectures show several drawbacks, mainly due to the lack of a unified substrate allowing for a true sensory-motor integration space, enabling flexible and scalable ways to model cognition under the embodiment hypothesis constraints. We propose the Self-Organized Internal Models Architecture (SOIMA), a computational cognitive architecture coded by means of a network of self-organized maps, implementing coupled internal models that allow modeling multi-modal sensory-motor schemes. Our approach addresses integrally the issues of current implementations of Internal Models. We discuss the design and features of the architecture, and provide empirical results on a humanoid robot that demonstrate the benefits and potentialities of the SOIMA concept for studying cognition in artificial agents.
Crowd-Based Deduplication: An Adaptive Approach

Data deduplication stands as a building block for data integration and data cleaning. The state-of-the-art techniques focus on how to exploit crowdsourcing to improve the accuracy of deduplication. However, they either incur significant overheads on the crowd or offer inferior accuracy. This paper presents ACD, a new crowd-based algorithm for data deduplication. The basic idea of ACD is to adopt correlation clustering (which is a classic machine-based algorithm for data deduplication) under a crowd-based setting. We propose non-trivial techniques to reduce the time required in performing correlation clustering with the crowd, and devise methods to postprocess the results of correlation clustering for better accuracy of deduplication. With extensive experiments on the Amazon Mechanical Turk, we demonstrate that ACD outperforms the states of the art by offering a high precision of deduplication while incurring moderate crowdsourcing overheads.
Self-organizing and self-correcting classifications of biological data

MOTIVATION Rapid, automated means of organizing biological data are required if we hope to keep abreast of the flood of data emanating from sequencing, microarray and similar high-throughput analyses. Faced with the need to validate the annotation of thousands of sequences and to generate biologically meaningful classifications based on the sequence data, we turned to statistical methods in order to automate these processes. RESULTS An algorithm for automated classification based on evolutionary distance data was written in S. The algorithm was tested on a dataset of 1436 small subunit ribosomal RNA sequences and was able to classify the sequences according to an extant scheme, use statistical measurements of group membership to detect sequences that were misclassified within this scheme and produce a new classification. In this study, the use of the algorithm to address problems in prokaryotic taxonomy is discussed. AVAILABILITY S-Plus is available from Insightful, Inc. An S-Plus implementation of the algorithm and the associated data are available at http://taxoweb.mmg. msu.edu/datasets
The Milky Way Rotation Curve and Its Vertical Derivatives: Inside the Solar Circle

We measure the Galactic rotation curve and its first two vertical derivatives in the first and fourth quadrants of the Milky Way using the 21 cm VGPS and SGPS. We find tangent velocities of the atomic gas as a function of Galactic longitude and latitude by fitting an analytic line profile to the edges of the velocity profiles. The shape of the analytic profile depends only on the tangent velocity and the velocity dispersion of the gas. We use two complementary methods to analyze the tangent velocities: a global model to fit typical parameter values and a local fitting routine to examine spatial variations. We confirm the validity of our fitting routines by testing simple models. Both the global and local fits are consistent with a vertical falloff in the rotation curve of –22 ± 6 km s−1 kpc−1 within 100 pc of the Galactic midplane. The magnitude of the falloff is several times larger than what would be expected from the change in the potential alone, indicating some other physical process is important. The falloff we measure is consistent in magnitude with that measured in the halo gas of other galaxies.
Construction of the Offender in Child Sexual Abuse Prevention Training for Adults

Until recently, the media was Americans’ primary source of information about child sexual offenders. Today, however, millions of adults attend child sexual abuse prevention trainings sponsored by churches, schools, and other organizations. This paper draws on participant observation in 22 sessions of a popular Catholic program. It examines how the curriculum frames child sexual offenders and how group processes support or challenge that framing. While such trainings have the potential to challenge incorrect stereotypes, group and organizational pressures often coalesce to perpetuate fear, anger, and an inability to see offenders as anything but “others. ”
Blending CMM and Six Sigma to Meet Business Goals

Tata Consultancy Services (TCS) blended Six Sigma concepts with the various SW CMM key process areas, thereby creating a quality management system. This helped TCS improve its customer focus and sustain process improvement initiatives by explicitly linking them to business goals. The TCS team implemented the QMS on the lines of Level 2 and 3 requirements of SW CMM, using Six Sigma concepts to reinforce quantitative process and product measurements and analysis, process improvements for defect prevention, and process optimization. This article describes TCS's approach, highlighting the benefits gained by blending Six Sigma and CMM to provide quality deliverables to its customers.
An integrated scheme for automated video abstraction based on unsupervised cluster-validity analysis

Key frames and previews are two forms of a video abstract, widely used for various applications in video browsing and retrieval systems. We propose in this paper a novel method for generating these two abstract forms for an arbitrary video sequence. The underlying principle of the proposed method is the removal of the visual-content redundancy among video frames. This is done by first applying multiple partitional clustering to all frames of a video sequence and then selecting the most suitable clustering option(s) using an unsupervised procedure for cluster-validity analysis. In the last step, key frames are selected as centroids of obtained optimal clusters. Video shots, to which key frames belong, are concatenated to form the preview sequence.
A New Strategy for Selecting Subdivision Point in the Bernstein Approach to Polynomial Optimization

In the Bernstein approach to polynomial range finding, we propose a new rule for selection of the point where the domain subdivision is to be done. For a given direction of subdivision, instead of subdividing a box at its midpoint (as is done in the existing literature), we propose to subdivide the box at a point where the partial derivative of the polynomial (in the direction of subdivision) equals zero. The location of this point is estimated using the variation diminishing property of the derivative polynomial in the Bernstein form. We then compare the performance of the proposed rule for subdivision point with that of the existing midpoint subdivision rule, on nine polynomial problems of different dimensions varying from two to eight dimensions. We evaluate both the rules using three different existing subdivision direction selection rules, and find the proposed rule to be overall more efficient in computational time and number of subdivisions.
Modelling the runoff response in the Mulde catchment (Germany)

Abstract. The paper presents two different levels of regionalization used to represent the spatial distribution of landscape parameters for the hydrological modelling of the Mulde. The aim of this investigation was to find out how the discretisation level affects quality of modelling with the hydrological modelling system J2000. Furthermore we improved our understanding of the applicability and reliability of the distributed model J2000 on the macro-scale. Spatial information was aggregated in two different discretisation levels: subbasins (SB) and hydrological response polygons (HRP). A J2000 simulation was carried out for both discretisation levels based on a 1 year calibration and a 3 year validation period. Simulations performed well for both levels of spatial discretisation. The results seemed to be better in the more complex discretisation approach, where the Nash-Sutcliffe coefficient was higher. We can conclude that our first results show more accurate simulations produced by the HRP discretisation approach, the visual inspection shows a better application of the SB approach to the reproduction of the base flow.
The Impact of Employee Competence on Organizational Agility: the Mediating Role of IT Alignment

Scholars have proposed that IT enables organizational agility by extending the reach and richness of firm knowledge and processes. However, this relationship is still open to debate. Based on the dynamic capabilities perspective, this paper proposes a model to investigate how employee competence (i.e., IT competence of business people and business competence of IT professionals) affects organizational agility through IT alignment. Data analysis results show that IT alignment fully mediates the influence of IT competence of business people and partially mediates the influence of business competence of IT professionals on organizational agility. In addition, the two kinds of competence are also positively interacting with each other to enhance IT alignment. We summarize with implications and suggestions for future research.
Genetic Heterogeneity Reveals On-Going Speciation and Cryptic Taxonomic Diversity of Stream-Dwelling Gudgeons (Teleostei, Cyprinidae) in the Middle Danubian Hydrosystem (Hungary)

Although stream-dwelling gudgeons (Cyprinidae, genus: Gobio) are widespread in Central Europe, the taxonomy of this group and the distribution of its species are still unexplored in detail. The aims of our study are to ascertain taxonomic composition and distribution of the former Gobio gobio superspecies in the inner area of the Carpathian Basin. Since the presence of cryptic species is suspected in this area, we examined the taxonomic and phylogenetic relationships of Central European Gobio taxa by sequencing the mitochondrial DNA control region (mtCR). Additionally, we characterized the genetic structure of 27 stream-dwelling gudgeon populations of this area by Amplified Fragment Length Polymorphism (AFLP). Results of mtCR analysis proved the presence of three species already known as G. obtusirostris (dominant in NW-Hungary), G. gobio (sporadic) and G. carpathicus (sporadic). Additionally, the analysis revealed the existence of one doubtful taxon, G. sp1 (dominant in NE-Hungary), and a new isolated haplogroup (dominant in SW-Hungary). Although Network analysis showed significant detachment among haplogroups, their genetic distances were quite small. Therefore Bayesian phylogenetic analysis showed weak nodal support for the branching pattern both for newly described haplotypes, and for the already accepted species. AFLP data showed distinct population structure and a clear pattern of isolation was revealed by distance of stocks. At the same time, level of separation was not affected by the altitudinal position of sites. Moreover we found three major clusters of populations which were separated according to hydrographic regions, and corresponded to the findings of mtCR analysis. Our results suggest the on-going speciation of gudgeons in the Carpathian Basin, however the separation of haplogroups seems to only be an intermediate phase. The discovered natural pattern seems to be only slightly influenced by anthropogenic impacts. Additionally our results put into question the suitability of the recently accepted within Gobio genus taxonomy.