Miracle-dz/UniFAR-FTUs huggingface dataset:
Analog/RF circuit design techniques for nanometerscale IC technologies

CMOS evolution introduces several problems in analog design. Gate-leakage mismatch exceeds conventional matching tolerances requiring active cancellation techniques or alternative architectures. One strategy to deal with the use of lower supply voltages is to operate critical parts at higher supply voltages, by exploiting combinations of thin- and thick-oxide transistors. Alternatively, low voltage circuit techniques are successfully developed. In order to benefit from nanometer scale CMOS technology, more functionality is shifted to the digital domain, including parts of the RF circuits. At the same time, analog control for digital and digital control for analog emerges to deal with current and upcoming imperfections.
A conceptual model of personal space for human-aware robot activity placement

This work proposes a conceptual model of personal space that can be used within symbolic knowledge-based robot architectures. The robot represents personal spaces in terms of affordance spaces attached to humans, i.e., portions of physical space that can be used for interactions. The model does not rely on numeric functions nor does it impose any restrictions upon the geometry of personal space. The approach is applied to human-aware robot activity placement planning: Given an activity type and a robot that is to perform an activity of this type, principles of personal space use determine the reasons pros and cons to place that particular activity at a particular affordance space. The symbolic representations of personal spaces enable robots to make choices and to communicate the reasons for their choices to humans.
Thread scheduling based on low-quality instruction prediction for simultaneous multithreaded processors

A simultaneous multithreaded (SMT) processor is capable of executing instructions from multiple threads in the same cycle. SMT in fact was introduced as a complementary architecture to superscalar to increase the throughput of the processor. Recently, several computer manufacturers have introduced their first generation SMT architecture. SMT permits multiple threads to compete simultaneously for shared resources. An example is the race for the fetch unit which is a critical logic responsible for thread scheduling decisions. When more threads than hardware execution contexts are available, the decision of choosing the best threads to fetch instructions from, will affect the processor's efficiency. In this paper the authors presented a new approach to choose the most useful threads among all available threads while they compete on a shared resource. The quality of instructions was identified based on the time they spend in the instruction queue. Low-quality instructions spend more time in the instruction queue. Accordingly threads with fewer number of low-quality instructions have a higher contribution to the entire processor throughput. In an experimental study, such low-quality instructions in each thread was identified to a maximum of 92% accuracy (average 72%). The authors exploited this to increase the overall processor throughput by giving higher priority to threads with lesser number of low-quality instructions. Overall an average of 11% performance improvement was achieved over the traditional algorithm that schedules threads in a round-robin fashion.
Approximate Stochastic Models for Chemically Reacting Systems

In the stochastic formulation of chemical reactions, the time evolution of the first M order statistical moments for the number of molecules of the different species involved is generally not closed, in the sense that they depend on moments of order higher than M. For analysis purposes, the time evolution of the first M order moments is often made to be closed by approximating the higher order moments as nonlinear functions of moments up to order M, which we refer to as the moment closure functions. Recent work has introduced the technique of derivativematching, where the moment closure functions are obtained by matching time derivatives of the exact (not closed) moment equations with that of the approximate (closed) equations for some initial time and set of initial conditions. However, for multispecies reactions these results have been restricted to a second order of truncation, i.e. M = 2. This paper extends these results by providing explicit formulas to construct moment closure functions for any arbitrary order of truncation M. Striking features of these moment closure functions are that they are independent of the reaction parameters (reaction rates and stoichiometry). Moreover, by increasing M, the closed moment equations provide more accurate approximations to the exact moment equations. We demonstrate the usefulness of our result by applying it to an example of stochastic focusing motivated from a gene cascade network, where the stochastic mean differs from the chemical rate equations. Moment estimates from the closed moment equations are compared with those obtained from a large number of Monte Carlo simulations.
Eecient 3-d Range Searching in External Memory

We present a new approach to designing data structures for the important problem of external-memory range searching in two and three dimensions. We construct data structures for answering range queries in O((log log log B N) log B N + K=B) I/O operations, where N is the number of points in the data structure, B is the I/O block size, and K is the number of points in the answer to the query. Our data structures answer a longstanding open problem by providing three dimensional results comparable to those provided by 8, 10] for the two dimensional case, though completely new techniques are used. Ours is the rst 3-D range search data structure that simultaneously achieves both a base-B logarithmic search overhead (namely, (log log log B N) log B N) and a fully blocked output component (namely, K=B). This gives us an overall I/O complexity extremely close to the well-known lower bound of (log B N + K=B). We base our data structures on the novel concept of B-approximate boundaries, which are manifolds that partition space into regions based on the output size of queries at points within the space.
Using invariant feature descriptors for an efficient image retrieval

In this paper, we study some feature descriptors and detectors based on invariants type and use the most stable and robust keypoints for an efficient object detection. From many points of view local descriptors are relatively different, the way of their extraction and the type of the invariance, the goal of this paper is to examine existing feature detectors and apply the most appropriate and efficient on our Content-based image retrieval engine (CBIR).
User-defined surface+motion gestures for 3d manipulation of objects at a distance through a mobile device

One form of input for interacting with large shared surfaces is through mobile devices. These personal devices provide interactive displays as well as numerous sensors to effectuate gestures for input. We examine the possibility of using surface and motion gestures on mobile devices for interacting with 3D objects on large surfaces. If effective use of such devices is possible over large displays, then users can collaborate and carry out complex 3D manipulation tasks, which are not trivial to do. In an attempt to generate design guidelines for this type of interaction, we conducted a guessability study with a dual-surface concept device, which provides users access to information through both its front and back. We elicited a set of end-user surface- and motion-based gestures. Based on our results, we demonstrate reasonably good agreement between gestures for choice of sensory (i.e. tilt), multi-touch and dual-surface input. In this paper we report the results of the guessability study and the design of the gesture-based interface for 3D manipulation.
Fixed-Wing UAV Attitude Estimation Using Single Antenna GPS Signal Strength Measurements

This article considers a novel approach to using global positioning system (GPS) signal strength readings and estimated velocity vector for estimating the attitude of a small fixed-wing unmanned aerial vehicle (UAV). This approach has the benefit being able to estimate full position, velocity and attitude states of a UAV using only the data from a single GPS receiver and antenna. Two different approaches for utilizing GPS signal strength within measurement updates for UAV attitude in a nonlinear Kalman filter are discussed and assessed using recorded UAV flight data. Comparisons of UAV pitch and roll estimates against measurements from a high-grade mechanical gyroscope are used to show that approximately 5° error with respect to both mean and standard-deviation on both axes is achievable.
Leadership Process Models: A Review and Synthesis

In organizational research, studying “processes” is important for uncovering and understanding the underlying causal mechanisms in a predictor-mediator-outcome logic. Processes answer “how” and “why” questions and provide more complete explanations about phenomena. Our focus in this review is on studies of leadership processes, which we systematically analyze to report on the state of the science. In doing so, we present a two-dimensional target-centric taxonomy to integrate previous research: The taxonomy distinguishes the target’s level (i.e., individual follower, team, organizational, and extraorganizational) as well as the type of leadership processes that affect either the target’s development or leverage of resources. Our review indicates that the predominantly studied leadership “meta” process model looks at the effect of leader traits or behaviors on performance-related outcomes through cognitive, affective, or behavioral leveraging factors. This “meta” model points to several important and understudied processes, including a leader’s influence on the target’s development or work context. We also identify two largely overlooked yet critical issues for leadership process research: modeling the role of time and that of multiple processes through which leadership effects manifest themselves in organizations. Using our taxonomy, we provide several reflection points that can guide the development of genuine and thoughtful leadership process theories. We conclude by urging future leadership process research to embrace multiprocess, multilevel, and time-sensitive models.
MILEF: an efficient approach to mixed level automatic test pattern generation

Automatic test pattern generation in CMOS circuits from gate-level net lists is efficient, but has shortcomings with respect to fault coverage in complex and irregular CMOS gates and networks. An approach relying on the transistor structure only is inefficient and virtually impossible for larger circuits. The authors describe the gate level part of a tool for dynamically coupled gate-level and switch-level test generation. Acceptable performance and high fault coverage for non-trivial transistor networks are combined. Patterns generated in this way are inherently capable of detecting interrupt types of faults and transition faults. In combination with local overcurrent detectors, stuck-on and bridging faults can be identified. <<ETX>>
Email Analysis and Information Extraction for Enterprise Benefit

In spite of rapid advances in multimedia and interactive technologies, enterprise users prefer to battle with email spam and overload rather than lose the benefits of communicating, collaborating and solving business tasks over email. Many aspects of email have significantly improved over time, but its overall integra- tion with the enterprise environment remained practically the same. In this paper we describe and evaluate a light-weight approach to enterprise email communica- tion analysis and information extraction. We provide several use cases exploiting the extracted information, such as the enrichment of emails with relevant contex- tual information, social network extraction and its subsequent search, creation of semantic objects as well as the relationship between email analysis and information extraction on one hand, and email protocols and email servers on the other. The proposed approach was partially tested on several small and medium enterprises (SMEs) and seems to be promising for enterprise interoperability and collaboration in SMEs that depend on emails to accomplish their daily business tasks.
Resilience and migration: Experiences of same-sex binational couples in Canada

ABSTRACT A phenomenological research design was employed to investigate experiences of individuals in binational relationships who migrated to Canada with their partners due to discriminatory immigration laws that prevented them from remaining together legally in the United States. Participants (N = 17) were American (N = 7), British (N = 2), French (N = 2), Canadian (N = 1), Chinese (N = 1), Colombian (N = 1), Dutch (N = 1), and two with dual citizenship. This article centers on participants' experiences of resiliency throughout the migration process to Canada. Results revealed resilience in three overarching categories: building a life in Canada, re-careering in Canada, and creating social support networks. Implications for policy and practice are discussed.
Asymptotic symmetries of string theory on AdS3 × S3 with Ramond-Ramond fluxes

String theory on AdS3 space-times with boundary conditions that allow for black hole states has global asymptotic symmetries which include an infinite dimensional conformal algebra. Using the conformal current algebra for sigma-models on PSU(1,1|2), we explicitly construct the R-symmetry and Virasoro charges in the worldsheet theory describing string theory on AdS3 × S3 with Ramond-Ramond fluxes. We also indicate how to construct the full boundary superconformal algebra. The boundary superconformal algebra plays an important role in classifying the full spectrum of string theory on AdS3 with Ramond-Ramond fluxes, and in the microscopic entropy counting in D1-D5 systems.
The Dilution of Effort in Self-Evaluating Development Teams : Agile Loafing

Attempts to resolve the problems in software development have concentrated on the tools and methodologies used, despite an acceptance by many that it is a sociological problem. An example of this is the procedures and processes surrounding evaluations within projects, yet ultimately it depends on individuals more than process. This paper examines one of the sociological factors inherent in a software development team to determine its impact on evaluation within a project. Social loafing occurs where individual members of a team demonstrate a tendency not to work as hard as they could or should. This “slacking off” occurs because the team provides a degree of anonymity – the individual feels their lack of work will be hidden from evaluation within the overall output of the team. Some authors purport that Agile Software development teams have low incidences of social loafing (though these are opinions rather than research findings); the contrary can also be argued. An examination of the philosophy behind Agile Software Development, demonstrated by the Agile Manifesto, highlighted the possibility of occurrences of social loafing brought about by the Agile values. Agile espouses the importance of cohesive teams, the empowerment of these teams, and the collective ownership and selfevaluation of work by the team. These values map onto factors which are described as affecting social loafing. An investigation of two teams over an eight month period examined if the Agile values could lead to incidences of social loafing, specifically when their work is being evaluated The investigation determined that the opposite was actually the case. This paper then goes on to determine why the findings go against the initial hypothesis and to show the impact this can have on those evaluating software development projects.
Using linkage information to approximate the distribution of relevant documents in DIR

In this paper, a method for addressing the source selection problem in a distributed information retrieval environment is presented. The method proposes a solution to the source selection problem by making use of the outlink distribution extracted from a sampling collection in order to locate the most authoritative collections for a particular query. Experiments carried out with the algorithm show that its performance exceeds that of the uniform approach, with much more economical means. Specifically, the link-based method is much more efficient in terms of collection utilization than the uniform strategy, which can be applied under the same conditions. A key feature of the algorithm is that it can be combined and work in parallel with content-based source selection algorithms.
Evaluating PCJ library for graph problems - Graph500 in PCJ

In the paper we present evaluation of the PCJ (Parallel Computations in Java) library for graph problems, namely for the first kernel in Graph500 benchmark. PCJ is a library for parallel computations in Java based on PGAS (Partitioned Global Address Space) paradigm. PCJ hides communication details such as threads or network programming, which allows to develop distributed applications easily. In the library all variables are local to the program threads however some variables can be marked as shared, which makes them accessible from different tasks via one-sided communication. We used the PCJ library to implement the first kernel of Graph 500 benchmark. In the first kernel from the input tuples list an undirected graph is constructed and compressed into CSR (Compressed Sparse Row) structure. The Graph500 benchmark includes a scalable data generator (Kronecker generator) that we used to produce edge tuples containing the start vertex and end vertex for each edge. We present the evaluation of the performance of the PCJ library for the first kernel with division into data distribution, computation and data gathering. Computation and data gathering shows good scalability of the PCJ.
Energy-Efficient Time Synchronization in Wireless Sensor Networks via Temperature-Aware Compensation

Time synchronization is critical for wireless sensor networks (WSNs) because data fusion and duty cycling schemes all rely on synchronized schedules. Traditional synchronization protocols assume that wireless channels are available around the clock. However, this assumption is not true for WSNs deployed in intertidal zones. In this article, we present TACO, a synchronization scheme for WSNs with intermittent wireless channels and volatile environmental temperatures. TACO estimates the correlation of clock skews and temperatures by solving a constrained least squares problem and continuously adjusts the local time with the predicted clock skews according to temperatures. Our experiment conducted in an intertidal zone shows that TACO can greatly reduce the clock drift and prolong the resynchronization intervals.
Miniaturized fractal rat-race, branch-line, and coupled-line hybrids

In this paper, space-filling curves have been used to realize a family of miniaturized hybrids. The large surface area occupied by a conventional structure has been significantly reduced through the use of space-filling curves having the same electrical characteristics. Several space-filling curves have been studied and implemented in different designs. The second-iteration Moore rat-race coupler occupies only 12.6% of the conventional coupler's area, while the area of the second-iteration Sierpinski branch-line coupler is 24.7% of the conventional case. On the other hand, a nine-section Minkowski coupled-line balun is confined in 60% of the conventional balun's area. However, the effective size reduction depends on the used space-filling curve, compression ratio, and associated coupling between segments. The performance of the proposed space-filling hybrids is as good as that of the corresponding conventional structures, and even better in some cases. The design and simulation of the proposed space-filling hybrids have been performed using a moment-method-based full-wave electromagnetic simulator. Measurements of one fabricated coupler prototype are in good agreement with simulation results.
Stabilities of quantitative plasma culture for human immunodeficiency virus, RNA, and p24 antigen from samples collected in VACUTAINER CPT and standard VACUTAINER tubes

We evaluated the stability of human immunodeficiency virus (HIV) load markers from blood samples collected in VACUTAINER CPT or standard VACUTAINER brand tubes using sodium heparin or sodium citrate as anticoagulants. Quantitative plasma culture and p24 antigen concentrations were determined, and HIV RNA levels in plasma were measured by both reverse transcription-PCR-enzyme-linked immunosorbent assay (RT-PCR-ELISA) and branched DNA methods. All tubes were stored at room temperature for analysis at 2, 24, 48, and 72 h after the blood samples were drawn. No difference was seen between tube types with respect to the HIV titer in plasma or the positivity rate for all samples that demonstrated a fall in titer over time. Unbound p24 antigen levels in plasma decreased during the initial 48-h period in both tube types. Immune complex-dissociated p24 antigen levels decreased in CPT tubes but not in standard VACUTAINER tubes. The HIV RNA copy number in plasma measured by RT-PCR-ELISA was stable in most subjects and was significantly higher in CPT tubes than in standard VACUTAINER tubes at 24 and 72 h after the blood samples were drawn. The branched DNA probe assay detected a significant decline in HIV RNA equivalent in plasma over 72 h in both collection tubes, the decline being more dramatic in the standard VACUTAINER tube than the CPT tube. Overall, interday variability suggests that samples collected for a particular assay should be processed at the same time after blood is drawn and that a particular tube type be used throughout a given study.
An iterative algorithm for context selection in adaptive entropy coders

Context-based adaptive entropy coding is an essential feature of modern image compression algorithms; however, the design of these coders is non-trivial due to the balance that must be struck between the benefits associated with using a large number of conditioning classes, or contexts, and the penalties resulting from data dilution. The problem is especially severe when coding small sub-images where the amount of data available is small. In this paper, we propose an iterative algorithm that begins with a large number of conditioning classes and then uses a clustering procedure to reduce this number to a desired value. This method is in contrast to the more usual approach of defining contexts in an ad-hoc manner. Experiments are conducted on synthetic data sources having varying amounts of memory, as well as on the sub-images resulting from a wavelet decomposition of an image. The results show that our approach to context selection is effective and that the algorithm automatically learns the structure of the data. This technique could be applied to improve the performance of both image and video coders.
Office documents on a database kernel—filing, retrieval, and archiving

One of the main component of integrated office systems is the large central filing system. It efficiently stores, retrieves and searches office documents containing text, images, graphics, data and voice. We propose to implement a filing system on top of the Darmstadt database system (DASDBS), which is designed as a data management kernel for both standard and non-standard applications. This paper investigates the choice of appropriate storage structures for the filing system objects and the realization of the system by using the kernel. Furthermore we discuss the efficient retrieval support of office objects by signatures and introduce a new archival approach by using storage media like optical disks.