Miracle-dz/UniFAR-FTUs huggingface dataset:
The geometry of interaction machine

We investigate implementation techniques arising directly from Girard's Geometry of Interaction semantics for Linear Logic, specifically for a simple functional programming language (PCF). This gives rise to a very simple, compact, compilation schema and run-time system. We analyse various properties of this kind of computation that suggest substantial optimisations that could make this paradigm of implementation not only practical, but potentially more efficient than extant paradigms.
Prior Image Guided Undersampled Dual Energy Reconstruction with Piecewise Polynomial Function Constraint

Dual energy CT has the ability to give more information about the test object by reconstructing the attenuation factors under different energies. These images under different energies share identical structures but different attenuation factors. By referring to the fully sampled low-energy image, we show that it is possible to greatly reduce the sampling rate of the high-energy image in order to lower dose. To compensate the attenuation factor difference between the two modalities, we use piecewise polynomial fitting to fit the low-energy image to the high-energy image. During the reconstruction, the result is constrained by its distance to the fitted image, and the structural information thus can be preserved. An ASD-POCS-based optimization schedule is proposed to solve the problem, and numerical simulations are taken to verify the algorithm.
Visual place recognition for autonomous robots

The problem of place recognition is central to robot map learning. A robot needs to be able to recognize when it has returned to a previously visited place, or at least to be able to estimate the likelihood that it has been at a place before. Our approach is to compare images taken at two places, using a stochastic model of changes due to shift, zoom, and occlusion to predict the probability that one of them could be a perturbation of the other. We have performed experiments to gather the valve of a /spl chi//sup 2/ statistic applied to image matching from a variety of indoor locations. Image pairs gathered from nearby locations generate low /spl chi//sup 2/ values, and images gathered from different locations generate high values. The rate of false positive and false negative matches is low.
A remote health care system based on wireless sensor networks

A medical system based on wireless sensor network technology is established. Firstly, the structure of a two-tiered wireless sensor network based on embedded Web Server for collecting and analyzing medical examination data is presented. Then the designs of the software and hardware systems of the wireless physiological sensor node and the physiological base station (sink node) are presented. The wireless communication between the sensor nodes, the sink nodes and remote central server are connected in one of the following ways, including Internet, GSM(Global System of Mobile Communications) short message, and telephone modem. The idea of this work is to make an assistant tool for doctors to diagnose the diseases and help the patients easier. This system can be used at home or in hospitals to form a remote medical system among home, community and hospital.
tACS Phase Locking of Frontal Midline Theta Oscillations Disrupts Working Memory Performance

Background: Frontal midline theta (FMT) oscillations (4–8 Hz) are strongly related to cognitive and executive control during mental tasks such as memory processing, arithmetic problem solving or sustained attention. While maintenance of temporal order information during a working memory (WM) task was recently linked to FMT phase, a positive correlation between FMT power, WM demand and WM performance was shown. However, the relationship between these measures is not well understood, and it is unknown whether purposeful FMT phase manipulation during a WM task impacts FMT power and WM performance. Here we present evidence that FMT phase manipulation mediated by transcranial alternating current stimulation (tACS) can block WM demand-related FMT power increase (FMTΔpower) and disrupt normal WM performance. Methods: Twenty healthy volunteers were assigned to one of two groups (group A, group B) and performed a 2-back task across a baseline block (block 1) and an intervention block (block 2) while 275-sensor magnetoencephalography (MEG) was recorded. After no stimulation was applied during block 1, participants in group A received tACS oscillating at their individual FMT frequency over the prefrontal cortex (PFC) while group B received sham stimulation during block 2. After assessing and mapping phase locking values (PLV) between the tACS signal and brain oscillatory activity across the whole brain, FMT power and WM performance were assessed and compared between blocks and groups. Results: During block 2 of group A but not B, FMT oscillations showed increased PLV across task-related cortical areas underneath the frontal tACS electrode. While WM task-related FMTΔpower and WM performance were comparable across groups in block 1, tACS resulted in lower FMTΔpower and WM performance compared to sham stimulation in block 2. Conclusion: tACS-related manipulation of FMT phase can disrupt WM performance and influence WM task-related FMTΔpower. This finding may have important implications for the treatment of brain disorders such as depression and attention deficit disorder associated with abnormal regulation of FMT activity or disorders characterized by dysfunctional coupling of brain activity, e.g., epilepsy, Alzheimer’s or Parkinson’s disease (AD/PD).
A New Design of High-Performance Large-Scale GIS Computing at a Finer Spatial Granularity: A Case Study of Spatial Join with Spark for Sustainability

Sustainability research faces many challenges as respective environmental, urban and regional contexts are experiencing rapid changes at an unprecedented spatial granularity level, which involves growing massive data and the need for spatial relationship detection at a faster pace. Spatial join is a fundamental method for making data more informative with respect to spatial relations. The dramatic growth of data volumes has led to increased focus on high-performance large-scale spatial join. In this paper, we present Spatial Join with Spark (SJS), a proposed high-performance algorithm, that uses a simple, but efficient, uniform spatial grid to partition datasets and joins the partitions with the built-in join transformation of Spark. SJS utilizes the distributed in-memory iterative computation of Spark, then introduces a calculation-evaluating model and in-memory spatial repartition technology, which optimize the initial partition by evaluating the calculation amount of local join algorithms without any disk access. We compare four in-memory spatial join algorithms in SJS for further performance improvement. Based on extensive experiments with real-world data, we conclude that SJS outperforms the Spark and MapReduce implementations of earlier spatial join approaches. This study demonstrates that it is promising to leverage high-performance computing for large-scale spatial join analysis. The availability of large-sized geo-referenced datasets along with the high-performance computing technology can raise great opportunities for sustainability research on whether and how these new trends in data and technology can be utilized to help detect the associated trends and patterns in the human-environment dynamics.
It's Time for a Song - Transcribing Recordings of Bell-playing Clocks

The paper presents an algorithm for automatic transcription of recordings of bell-playing clocks. Bell-playing clocks are clocks containing a hidden bell-playing mechanism that is periodically activated to play a melody. Clocks from the eighteenth century give us unique insight into the musical taste of their owners, so we are interested in studying their repertoire and performances - thus the need for automatic transcription. In the paper, we first present an analysis of acoustical properties of bells found in bell-playing clocks. We propose a model that describes positions of bell partials and an algorithm that discovers the number of bells and positions of their partials in a given recording. To transcribe a recording, we developed a probabilistic method that maximizes the joint probability of a note sequence given the recording and positions of bell partials. Finally, we evaluate our algorithms on a set of recordings of bell-playing clocks.
Class library implementation of an open architecture knowledge support system

Abstract Object-oriented class libraries offer the potential for individual researchers to manage the large bodies of code generated in the experimental development of complex interactive systems. This article analyses the structure of such a class library that supports the rapid prototyping of a wide range of systems including collaborative networking, shared documents, hypermedia, machine learning, knowledge acquisition and knowledge representation, and various combinations of these technologies. The overall systems architecture is presented in terms of a heterogeneous collection of systems providing a wide range of application functionalities. Examples are given of group writing, multimedia and knowledge-based systems which are based on combining these functionalities. The detailed design issues of the knowledge representation server component of the system are analysed in terms of requirements, the current state of the art, and the underlying theoretical principles that lead to an effective object-oriented implementation. It is shown that modeling the server through intensional algebraic semantics leads naturally to an open-architecture class library into which new data types may be plugged as required without change to the basic deductive engine. It is concluded that the development of a principled class library targeted on complex interactive applications does empower the individual researcher in the rapid prototyping of experimental systems. However, it is noted that much of the power of the approach stems from the cumulative evolution of the class library through successive applications, and hence the results may not generalize to team projects where greater rigidity is required in the class library in order to facilitate project management and inter-member coordination.
Development of fast patient position verification software using 2D-3D image registration and its clinical experience

To improve treatment workflow, we developed a graphic processing unit (GPU)-based patient positional verification software application and integrated it into carbon-ion scanning beam treatment. Here, we evaluated the basic performance of the software. The algorithm provides 2D/3D registration matching using CT and orthogonal X-ray flat panel detector (FPD) images. The participants were 53 patients with tumors of the head and neck, prostate or lung receiving carbon-ion beam treatment. 2D/3D-ITchi-Gime (ITG) calculation accuracy was evaluated in terms of computation time and registration accuracy. Registration calculation was determined using the similarity measurement metrics gradient difference (GD), normalized mutual information (NMI), zero-mean normalized cross-correlation (ZNCC), and their combination. Registration accuracy was dependent on the particular metric used. Representative examples were determined to have target registration error (TRE) = 0.45 ± 0.23 mm and angular error (AE) = 0.35 ± 0.18° with ZNCC + GD for a head and neck tumor; TRE = 0.12 ± 0.07 mm and AE = 0.16 ± 0.07° with ZNCC for a pelvic tumor; and TRE = 1.19 ± 0.78 mm and AE = 0.83 ± 0.61° with ZNCC for lung tumor. Calculation time was less than 7.26 s.The new registration software has been successfully installed and implemented in our treatment process. We expect that it will improve both treatment workflow and treatment accuracy.
cAMP Increases Density of ENaC Subunits in the Apical Membrane of MDCK Cells in Direct Proportion to Amiloride-sensitive Na+ Transport

Antidiuretic hormone and/or cAMP increase Na+ transport in the rat renal collecting duct and similar epithelia, including Madin-Darby canine kidney (MDCK) cell monolayers grown in culture. This study was undertaken to determine if that increment in Na+ transport could be explained quantitatively by an increased density of ENaC Na+ channels in the apical membrane. MDCK cells with no endogenous ENaC expression were retrovirally transfected with rat α-, β-, and γENaC subunits, each of which were labeled with the FLAG epitope in their extracellular loop as described previously (Firsov, D., L. Schild, I. Gautschi, A.-M. Mérillat, E. Schneeberger, and B.C. Rossier. 1996. Proc. Natl. Acad. Sci. USA. 93:15370–15375). The density of ENaC subunits was quantified by specific binding of 125I-labeled anti-FLAG antibody (M2) to the apical membrane, which was found to be a saturable function of M2 concentration with half-maximal binding at 4–8 nM. Transepithelial Na+ transport was measured as the amiloride-sensitive short-circuit current (AS-I sc) across MDCK cells grown on permeable supports. Specific M2 binding was positively correlated with AS-I sc measured in the same experiments. Stimulation with cAMP (20 μM 8-p-chlorothio-cAMP plus 200 μM IBMX) significantly increased AS-I sc from 11.2 ± 1.3 to 18.1 ± 1.3 μA/cm2. M2 binding (at 1.7 nM M2) increased in direct proportion to AS-I sc from 0.62 ± 0.13 to 1.16 ± 0.18 fmol/cm2. Based on the concentration dependence of M2 binding, the quantity of Na+ channels per unit of AS-I sc was calculated to be the same in the presence and absence of cAMP, 0.23 ± 0.04 and 0.21 ±0.05 fmol/μA, respectively. These values would be consistent with a single channel conductance of ∼5 pS (typically reported for ENaC channels) only if the open probability is <0.02, i.e., less than one-tenth of the typical value. We interpret the proportional increases in binding and AS-I sc to indicate that the increased density of ENaC subunits in the apical membrane can account completely for the I sc increase produced by cAMP.
Buffer Filter: A Last-Level Cache Management Policy for CPU-GPGPU Heterogeneous System

There is a growing trend towards heterogeneous systems, which contain CPUs and GPGPUs in a single chip. Managing those various on-chip resources shared between CPUs and GPGPUs, however, is a big issue and the last-level cache (LLC) is one of the most critical resources due to its impact on system performance. Some well-known cache replacement policies like LRU and DRRIP, designed for a CPU, can not be so well qualified for heterogeneous systems because the LLC will be dominated by memory accesses from thousands of threads of GPGPU applications and this may lead to significant performance downgrade for a CPU. Another reason is that a GPGPU is able to tolerate memory latency when quantity of active threads in the GPGPU is sufficient, but those policies do not utilize this feature. In this paper we propose a novel shared LLC management policy for CPU-GPGPU heterogeneous systems called Buffer Filter which takes advantage of memory latency tolerance of GPGPUs. This policy has the ability to restrict streaming requests of GPGPU by adding a buffer to memory system and vacate LLC space for cache-sensitive CPU applications. Although there is some IPC loss for GPGPU but the memory latency tolerance ensures the basic performance of GPGPU's applications. The experiments show that the Buffer Filter is able to filtrate up to 50% to 75% of the total GPGPU streaming requests at the cost of little GPGPU IPC decrease and improve the hit rate of CPU applications by 2x to 7x.
Neural Network Models of Thermotaxis in the Nematode C . elegans

Acknowledgements I am most grateful to Dr. Shawn Lockery, whose instruction and guidance started me on this exciting journey. I have greatly benefited from my interactions with Gwen Frishkoff and Dr. Kathleen Sullivan, both of whom I hold in highest regard and shall strive to emulate in my own academic career. I am also personally indebted to Alicia Powers, and Rachel Wilkes for their substantial contributions to my sanity during the preparation of this document. Coleman 2003 2 1 Introduction Caenorhabditis elegans is a 1mm long soil nematode that has become the focus of much biological research. Its complete genome has been sequenced, and a vast array of genetic mutants and their resultant phenotypes have been cataloged. All 302 of its neurons have been identified and named, and their interconnections have been studied in such detail that a complete wiring diagram has been assembled (White, et. al., 1986). As such, C. elegans offers a unique opportunity to comprehend a complex multicellular organism to a far greater degree than ever before possible. Prior research has utilized computational techniques to explore the chemotaxis behavior, to develop neural network models capable of replicating the behavior (Ferree et. al., 1997), to develop computational rules capable of mimicking the behavior (Ferree & Lockery, 1999), and even to construct a mobile robot capable of chemotaxis-like locomotion (Morse et. al, 1997). This document hopes to apply this pre-established methodology to the more complex locomotive behavior of thermotaxis. In Section 2, a brief survey of pre-existing literature is conducted. The biology of C. elegans is discussed, with a specific focus on the structure and function of the thermotaxis circuit. Additionally, computer science approaches to thermotaxis-like tasks are reviewed in the hope that the cybernetic solutions may shed light on the biological solutions. Subsequent sections consist of original research involving the construction and analysis of neural network models of thermotaxis. Section 3 details the mathematical underpinnings of the thermotaxis behavior that are common to all models presented in Coleman 2003 3 this document. The thermotaxis assay environment is defined, a kinematic model for nematode locomotion is presented, and an operational definition of thermotaxis is used to develop a fitness function. In Section 4, a highly idealized time-delay neural network is constructed and trained to perform thermotaxis. In order to gain insight into the nature of the thermotaxis control problem, time-delay networks with varying numbers of neurons are each trained …
Adaptive and selective packet marking in communication networks

We propose a novel traceback approach that marks IP traffic by applying selective marking and reducing load mechanisms. Our technique is adaptive and is exploiting any specific properties that help characterizing an activity in communication traffic. It helps reducing problems such as processing overhead, bandwidth overload, detecting security attacks, and handling encrypted traffic. The selective character of our method reduces tremendously the performance cost observed with other marking approaches. The approach is applied to TCP traffic, for which an IP traceback has been implemented and integrated into what is called "Click software router". Finally, a comparative study is made with the Deterministic Packet Marking technique.
SDSecurity: A Software Defined Security experimental framework

The emerging Software Defined Systems (SDSys) is a recent paradigm, which has been introduced to reduce the overhead in the control and management operations of complex computing systems. The main concept behind this technology is around isolating the data plane from the control plane. Traditional security mechanisms are facing more challenges in providing sufficient levels of protection and efficiency. SDSys for security has been proposed to address these challenges. Software Defined Security (SDSec) provides a flexible and centralized security solution by abstracting the security mechanisms from the hardware layer to a software layer. In this paper we present a novel experimental framework to provide a novel virtualized testbed environment for SDSec systems. This work builds on the Mininet simulator, where its core components, the host, switch and the controller, are customized to build the proposed experimental simulation framework for SDSec. To the best of the authors' knowledge, this is the first experimental framework and simulator for SDSec solutions. The developed simulator, will not only support the development and testing of SDSecurity solutions, it will also serve as an experimentation tool for researchers and for benchmarking purposes. The developed simulator could also be used as an educational tool to train students and novice researchers.
Applications of remote controlled robotics in the intelligent space

As the concept of the Internet of Things (IoT) permeates the industry and our lives it becomes more and more advantageous to use its emerging services and capabilities. In this paper we explore the possibility of combining the data and services provided by the emerging IoT with remotely controlled robots using a concept of the so-called Intelligent Space (IS). We also provide an overview of infrastructure requirements and describe our own design of IS with some possible applications of such an approach.
Polarization Rotation in Silicon Waveguides: Analytical Modeling and Applications

The efficient use of optical nonlinearities in silicon is crucial for the implementation of silicon-based photonic devises. In this paper, we present an approximate analytical study of nonlinear polarization rotation in silicon-on-insulator (SOI) waveguides; the rotation is predominantly caused by the effects of self-phase modulation and cross-phase modulation, stemming from the anisotropic Kerr nonlinearity. In the first part of the paper, we analyze the transmittance of the Kerr shutter in the continuous-wave regime and address the problem of its optimization. It is essential for the generality of our conclusions that both free-carrier effects and two-photon absorption are properly accounted for in this study. We specifically show that the signal transmittance may be optimized by adjusting the waveguide length, the pump power, and the incident linear polarizations of pump and signal beams. In the second part of the paper, we examine the problem of power equalization with SOI waveguides. We validate the derived analytical solutions by comparing their predictions with the data from numerical simulations and illustrate the solutions by the examples of practical interest. The results of our work may prove useful for the design and optimization of SOI-based Kerr shutters, all-optical switches, and power equalizers.
Global Inflation Dynamics

This paper examines the dynamics of various measures of national, regional, and global inflation. The paper calculates the first two common factors for four measures of industrial country inflation rates: total CPI, core CPI, cyclical total CPI, and cyclical core CPI. The paper then demonstrates that the first common factor is sometimes helpful in forecasting national inflation rates. It also shows that the second common factor and the first common factor for cyclical inflation is sometimes helpful in forecasting national CPI inflation rates. Finally, the paper suggests that the commonality of industrial inflation rates reflects the commonality of the determinants of inflation.