Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamic relay selection for MAC-level retransmission in Vehicular Ad Hoc Networks

Communication in Vehicular Ad Hoc Networks (VANETs) is frequently disrupted by highly dynamic, noisy and interference-prone links. This paper proposes a novel algorithm, named Cross-Layer Tree Formation (CLTF), for medium access. CLTF enables the formation of the tree architecture that connects the receiver node with the cooperative relay node in Medium Access Control (MAC)-level retransmission. The proposed algorithm uses cooperative communication to increase the throughput and decrease the average delay in the network. Each relay node in the network serves a neighboring destination node. The simulation results show that CLTF incurs a significant gain in terms of throughput, which is at least 50% better under bad channel conditions.
Compressive Inverse Light Transport

This paper explores the possibility of acquiring inverse li ght transport directly. The current strategy of obtaining an inverse light transport ma trix involves two steps: First, acquire the forward light transport matrix (f-LTM) and then calculate the inverse of the f-LTM. Both steps of the strategy requires considerable computational power. In addition to computational cost, the measurement error incurred at the first step inevitably propagates to or potentially gets amplified in the matrix inv ersion step. In this paper, we propose a sensing strategy that acquires the inverse light transport matrix (i-LTM) directly, without reconstructing the f-LTM. Our direct strategy reduces both computational error and cost of acquiring i-LTM. For that, we propose a compressive inverse theory. Following the compressible property of i-LTM, a reconstruction condition for i-LTM is introduced. This new framework implies a trade-off between two factors: condition numbers of submatrices of f-LTM and the isometry constant of the illumination pattern. Our direct i-LTM reconstruction method is then demonstrated with a 2nd-bounce separation experiment on an M-shaped panel scene. Finally by quantitatively comparing our method with the existing two-stage approach, our method shows higher accuracy with lower complexity. The proofs of main theorem/lemma are contained in the supplementary material. The compressive inverse theory is general and potentially useful for wider application.
Distribution of Ink-jet Ink Components via ToF-SIMS and Optical Image Analysis

In this work the methodology is developed to study spreading and penetration of a custom ink-jet ink formulation, containing hydrophobic cationic crystal violet dye, ethoxylated surfactant, and ink solvent marked by lithium salt. With a new technique utilizing Time-of-Flight Secondary Ion Mass Spectrometry imaging, the ink component distribution and its effect on print quality of uncoated and coated papers are evaluated. High spatially resolved images obtained by ToF-SIMS illustrate differentiation of individual ink components, with ink solvent spreading more than the dye in all paper samples. Uncoated papers show greater and more irregular spreading leading to poor edge definition and poor print quality. Large separation of the dye from the solvent in the vertical direction of multipurpose and photo glossy ink-jet paper suggests a step-wise progression of ink penetration: ink flows through a more porous structure in the xdirection before advancing to the next sublayer in the z-direction of paper.
Asymmetric-frequency clustering: a power-aware back-end for high-performance processors

We introduce asymmetric frequency clustering (AFC), a micro-architectural technique that reduces the dynamic power dissipated by a processor's back-end while maintaining high performance. We present a dual-cluster, dual-frequency machine comprising a performance oriented cluster and a power-aware one. The power-aware cluster operates at half the frequency of the performance oriented cluster and uses a lower voltage supply. We show that this organization significantly reduces back-end power dissipation by executing non-performance-critical instructions in the power-aware cluster. AFC localizes the two frequency/voltage domains. Consequently, it mitigates many of the complexities associated with maintaining multiple supply voltage and frequency domains on the same chip. Key to the success of this technique are methods that assign as many instructions as possible to the slower/lower power cluster without impacting overall performance. We evaluate our techniques using a subset of SPEC2000 and SPEC95. AFC provides a 16% back-end power reduction with 1.5% performance loss compared to a conventional, dual-clustered processor where each cluster has schedulers of the same width and length.
Microtubules provide directional information for core PCP function

Planar cell polarity (PCP) signaling controls the polarization of cells within the plane of an epithelium. Two molecular modules composed of Fat(Ft)/Dachsous(Ds)/Four-jointed(Fj) and a ‘PCP-core’ including Frizzled(Fz) and Dishevelled(Dsh) contribute to polarization of individual cells. How polarity is globally coordinated with tissue axes is unresolved. Consistent with previous results, we find that the Ft/Ds/Fj-module has an effect on a MT-cytoskeleton. Here, we provide evidence for the model that the Ft/Ds/Fj-module provides directional information to the core-module through this MT organizing function. We show Ft/Ds/Fj-dependent initial polarization of the apical MT-cytoskeleton prior to global alignment of the core-module, reveal that the anchoring of apical non-centrosomal MTs at apical junctions is polarized, observe that directional trafficking of vesicles containing Dsh depends on Ft, and demonstrate the feasibility of this model by mathematical simulation. Together, these results support the hypothesis that Ft/Ds/Fj provides a signal to orient core PCP function via MT polarization. DOI: http://dx.doi. org/10.7554/eLife.02893. 001
Designing for the eye: design parameters for dwell in gaze interaction

Eye gaze tracking provides a natural and fast method of interacting with computers. Many click alternatives have been proposed so far, each with their own merits and drawbacks. We focus on the most natural selection method, i.e. the dwell, with which a user can select an on-screen object by just gazing at it for a pre-defined dwell time. We have looked at three design parameters of the dwell click alternative, namely dwell time, button size and placement of content. Two experiments, with similar user interfaces, were designed and conducted with 21 and 15 participants, respectively. Different combinations of dwell times and button sizes were tested in each experiment for each participant. One experiment had content placed on the buttons to be gazed at, while the other had content placed above the buttons. One important finding is that moving the content outside the clickable areas avoids accidental clicking, i.e. the Midas Touch problem. In such a design, a combination of big buttons and short dwell times are most suited for maximizing accuracy and ease of use, due to a phenomenon identified as the 'gaze-hold' problem.
Techniques for Automatic Music Transcription

The scheme of the monophonic transcription system implemented here, is illustrated in figure 1. If the fundamental frequency of a harmonic signal is calculated, and the resulting track is visualised, it can be noticed that, for most of the duration of the notes, the pitch remains approximately constant. This relation, so clear to the eye, requires some comment. In order to implement some grouping criteria and rules for sounds, emphasis should be given to the similarity in human perception between image and sound [2]. Important clues can be obtained by observing carefully the plot of the pitch track.
Development of Flexible and Optically Transparent Composite Film with Wheat Straw Nanofibres

Cellulose is a potential source of nano-material not only because it possesses excellent mechanical and optical properties, but also because it is environmentally benign. In this study, nanofibres derived from wheat straw, an agriculture residue, was utilized in producing flexible and optically transparent nanocompostie films. The composites were produced using a bi-phase impregnation technique that coats the dried nanofibre films with clear polyurethane acrylate resins using UV radiation induced curing. The nanocomposite films thus produced possess excellent tensile properties (161MPa in strength and 9GPa in Young’s Modulus), superior thermal stability (above 300°C), low coefficient of thermal expansion (8-9ppm/K), good light transparency (80%), excellent flexibility and abrasion resistance. These nanocomposite films are aimed to replace the conventional glass substrates made in batches to a polymer based substrates that can be efficiently produced in a roll-to-roll process for the base of the future flexible flat panel displays.
Nodule-Specific Regulation of Phosphatidylinositol Transfer Protein Expression in Lotus japonicus

Phosphatidylinositol transfer proteins (PITPs) modulate signal transduction pathways and membrane-trafficking functions in eukaryotes. Here, we describe the characterization of a gene family from Lotus japonicus that encodes a novel class of plant PITP-like proteins (LjPLPs) and that is regulated in an unusual nodule-specific manner. Members of this gene family were identified based on their nucleotide sequence homology with a previously described cDNA, LjNOD16, which encodes the L. japonicus late nodulin Nlj16. Nlj16 or highly related amino acid sequences are shown to constitute C-terminal domains of LjPLPs and are suggested to function as specific plasma membrane targeting modules. The expression patterns of one member of this gene family (LjPLP-IV) revealed that LjNOD16 mRNA synthesis in nodules is the result of the transcriptional activity of a nodule-specific promoter located in an intron of the LjPLP-IV gene. This intron-borne bidirectional promoter also generates nodule-specific antisense transcripts derived from the N-terminal PITP domain coding region of the LjPLP-IV gene. We propose that Nlj16 protein synthesis and LjPLP-IV antisense transcript generation are components of an elaborate mechanism designed to control LjPLP synthesis and/or functioning in nodules.
Reversing Transitions in Bounded Petri Nets

Reversible computation deals with mechanisms for undoing the effects of actions executed by a dynamic system. This paper is concerned with reversibility in the context of Petri nets which are a general formal model of concurrent systems. A key construction we investigate amounts to adding ‘reverse’ versions of selected net transitions. Such a static modification can severely impact on the behaviour of the system, e.g., the problem of establishing whether the modified net has the same states as the original one is undecidable. We therefore concentrate on nets with finite state spaces and show, in particular, that every transition in such nets can be reversed using a suitable finite set of new transitions.
Network management through graphs in Software Defined Networks

Software Defined Networks (SDN) is an emergent architecture that is dynamic, flexible, manageable, low cost, consistent with the dynamics of the modern applications. This paper shows a network representation model using a graph as the control plane of an SDN controller. The graph approach provides a globally consistent view of the network in real time. Our experiments show that graphs are a reliable representation of the real network, simplifying management in Software Defined Networking.
MCMC Shape Sampling for Image Segmentation with Nonparametric Shape Priors

Segmenting images of low quality or with missing data is a challenging problem. Integrating statistical prior information about the shapes to be segmented can improve the segmentation results significantly. Most shape-based segmentation algorithms optimize an energy functional and find a point estimate for the object to be segmented. This does not provide a measure of the degree of confidence in that result, neither does it provide a picture of other probable solutions based on the data and the priors. With a statistical view, addressing these issues would involve the problem of characterizing the posterior densities of the shapes of the objects to be segmented. For such characterization, we propose a Markov chain Monte Carlo (MCMC) sampling-based image segmentation algorithm that uses statistical shape priors. In addition to better characterization of the statistical structure of the problem, such an approach would also have the potential to address issues with getting stuck at local optima, suffered by existing shape-based segmentation methods. Our approach is able to characterize the posterior probability density in the space of shapes through its samples, and to return multiple solutions, potentially from different modes of a multimodal probability density, which would be encountered, e.g., in segmenting objects from multiple shape classes. We present promising results on a variety of data sets. We also provide an extension for segmenting shapes of objects with parts that can go through independent shape variations. This extension involves the use of local shape priors on object parts and provides robustness to limitations in shape training data size.
The Application of Kinetic Friction Energy for Ceramics Metallisation

The paper presents the problem of ceramics metallisation using the friction method based on the mechanism of joint formation, where the ener- gy of kinetic friction is directly transformed into heat and supplied in specified amounts directly to the joint formed between the layer and the substrate. The paper also presents friction-utilising ceramic metallisation process developed by the authors as well as shows the results of microstructural examination of metallised layers obtained.
A New Rigid Rod Model for the Discrete Element Method to Analyze the Dynamic Behavior of Needle-shaped Powder

Numerous studies of the dynamic behavior of powders have been performed by Discrete Element Method (DEM). The behavior of powders can be analyzed using the DEM assuming that the powder is composed of spherical particles. Moreover, the assumption of spherical particle reduces the computing time significantly. However, the biggest problem with this assumption is the real shape of the particles. Some types of particles, such as calcium carbonate and colloidal copper, are needle shaped. Thus, analysis based on spherical particles can produce errors because of the incorrect assumption. In this research, we developed a new model to simulate needle-shaped particles using the DEM. In the model, a series of particles are connected and regarded as a rod. There is no relative motion among the particles. Thus, the behavior of the rod is rigid motion. To validate the developed model, we carried out the drop-and-bounce test with different initial angles. The results showed negligible error of less than 2%.
Peak temperature control in thermal-aware behavioral synthesis through allocating the number of resources

High temperature adversely impacts on reliability, performance, and leakage power of ICs. In behavioral synthesis, both resource usage allocation and resource binding influence the final thermal profile. Previous thermal-aware behavioral syntheses only focused on binding, ignoring allocation. This paper proposes thermal-aware behavioral synthesis with resource usage allocation. According to power density and feedbacks from thermal simulation, we allocate the number of resources under area constraint. Our flow effectively controls peak temperature and creates even power densities among resources of “different” and “same” types. Compared to classic behavioral synthesis of peak temperature control, our technique reduces peak temperature by 11.1 °C on average with no area overhead and only 1.2 more steps latency overhead.
Aerosol radiative properties in the semiarid Western United States

Characterization of aerosol optical properties, such as aerosol optical depth, Angstrom exponent, and volume size distribution at the semiarid site of Tombstone Arizona (31823VN, 110805VW, 1408 m) will be presented for one annual cycle. In this region, extensive observations of selected optical parameters such as aerosol optical depth (AOD) have been made in the past and reported on in the literature. Less is known about other optical characteristics that are important in climate modeling and remote sensing. New observational techniques and inversion methods allow for the expansion of the earlier information. Observations have been taken with a state of the art sun photometer for a 1-year period and their analysis will be presented here. Monthly mean AODs at 500 nm were found to be in the range of 0.03–0.12; the monthly mean Angstrom exponent ranged from 0.9 to 1.6, being higher in spring and summer and lower in late fall and winter. Volume size distributions exhibit clear dominance of smaller particles, with a gradual increase in size from winter to spring and into summer. Annual variation of the radii of the smaller and the larger particles ranged between 0.05–0.4 and 4–8 Am, respectively. Radiance measurements at 940 nm were used to estimate precipitable water. The retrieved values compared within limits of uncertainty with independently derived estimates from the National Center for Environmental Prediction (NCEP) regional weather forecast model. An interesting outcome from
Preventing versus curing: avoiding conflicts in transactional memories

Transactional memories are typically speculative and rely on contention managers to cure conflicts. This paper explores a complementary approach that prevents conflicts by scheduling transactions according to predictions on their access sets. We first explore the theoretical boundaries of this approach and prove that (1) a TM scheduler with an accurate prediction can be 2-competitive with an optimal offline TM scheduler, but (2) even a slight inaccuracy in prediction makes the competitive ratio of the TM scheduler in the order of the number of transactions. We then show that, in practice, there is room for a pragmatic approach with good average case performance. We present Shrink, a scheduler that (1) bases its prediction of transactional accesses on the access patterns of the past transactions from the same thread, and (2) uses a novel heuristic, which we call serialization affinity, to schedule transactions with a probability proportional to the current amount of contention. Shrink obtains roughly 70% accurate read and write access predictions on STMBench7 and STAMP. In our experimental evaluation, Shrink significantly improves STM performance in cases the number of executing threads is higher than the number of available CPU cores. For SwissTM, Shrink improves the performance by up to 55% on STMBench7, and up to 120% on STAMP. For TinySTM, Shrink drastically improves the performance on STMBench7 and STAMP benchmarks.
Apriori approach to graph-based clustering of text documents

This thesis report introduces a new technique of do cument clustering based on frequent senses. The developed system, named GDClus t (Graph-Based Document Clustering) [1], works with frequent senses rather than dealing with frequent keywords used in traditional text mining techniques. GDClust presents text documents as hierarchical document-graphs and uses an Apriori pa adigm to find the frequent subgraphs, which reflect frequent senses. Discovere d frequent subgraphs are then utilized to generate accurate sense-based document clusters. W propose a novel multilevel Gaussian minimum support strategy for candidate sub graph generation. Additionally, we introduce another novel mechanism called Subgraph-E xtension mining that reduces the number of candidates and overhead imposed by the tr aditional Apriori-based candidate generation mechanism. GDClust utilizes an English l anguage thesaurus (WordNet [2]) to construct document-graphs and exploits graph-based data mining techniques for sense discovery and clustering. It is an automated system and requires minimal human interaction for the clustering purpose.
Design and analysis of a wrist-hand manipulator for rehabilitation of upper limb dexterous function

Dexterous distal arm functions are crucial for execution of activities of daily living (ADLs). However, it remains difficult for patients with neurological deficits, such as stroke, to recover the lost manipulation capabilities. In this paper, a modular approach has been proposed to design a wrist-hand manipulator to be employed in the rehabilitation training of the upper limb dexterous function. Consisting of the installation module, the forearm module, the in-parallel wrist module, and the hand module, the end-effector based manipulator encourages the patient to voluntary coordinate motion of individual joints of the upper limb. Further, it is compact, stiff, and can be easily installed on desk, wall or other systems. Various hand modules can be attached on the manipulator for patients of different paretic levels. Parameter optimization has been performed for the in-parallel wrist module about workspace capability and manipulability. Condition number over the entire workspace is taken as the manipulability measure. Finally, the design and optimization parameters are validated by kinematic simulation with MATLAB/Simulink SimMechanics toolbox.
Correlation-based load balancing for network intrusion detection and prevention systems

In large-scale enterprise networks, multiple network intrusion detection and prevention systems are used to provide high quality protections. In this context, keeping load evenly distributed among the systems is crucial. This is because even load distributions provide protection to the networks and improve the networks' quality of service. A challenging problem, however, is to maintain the load balancing of the systems while minimizing the loss of correlation information due to distributing traffic. Since anomaly- based detection and prevention of some intrusions, such as distributed denial of service (DDoS) attacks and port scans, require a single system to analyze correlated flows of the attacks, this loss of correlation information might severely affect the accuracy of the detections and preventions. In this paper, we address this challenging problem by first formalizing the load balancing problem as an optimization problem, considering both the systems' load variance and the correlation information loss. We then present our Benefit-based Load Balancing (BLB) algorithm as a solution to the optimization problem. We have implemented a prototype load-balancer which uses the BLB algorithm. We evaluated the load-balancer against various port scans and DDoS attacks. The evaluation results show that our load-balancer significantly improves the detection accuracy of these attacks while keeping the systems' load close within a desired bound.
Building Production Systems with Realistic Spiking Neurons

We present a novel cognitive architecture built from realistic spiking neurons that exhibits basic production system capabilities. It uses Holographic Reduced Representations to encode structured information and the Neural Engineering Framework to create detailed neuro-biologically plausible networks of spiking neurons for storing and manipulating these representations. We demonstrate this system's abilities to encode IF-THEN rules and manipulate its own representations in response to the current state. This leads to predictions about the sorts of rules that would be difficult for neurons to encode, and the maximum complexity of such rules. Our system bridges the gap between high-level cognitive architectures (including ACT-R) and modern neuroscience research, allowing details such as the numbers, types, and connections of neurons to be related to cognitive behaviour.