Miracle-dz/UniFAR-FTUs huggingface dataset:
Traffic-based reconfiguration for logical topologies in large-scale WDM optical networks

Wavelength-division multiplexing (WDM) technology has emerged as a promising technology for backbone networks. The optical layer based on WDM technology provides optical routing services to the upper layers such as the packet-switching layer and the time-division multiplexing (TDM) layer over the generalized multiprotocol label-switching (GMPLS) paradigm. The set of all-optical communication channels (lightpaths) in the optical layer defines the logical topology for the upper layer applications. Since the traffic demand of upper layer applications fluctuates from time to time, it is required to reconfigure the underlying logical topology in the optical layer accordingly. However, the reconfiguration for the logical topology is reluctantly disruptive to the network since some lightpaths should be torn down and some traffic has to be buffered or rerouted during the reconfiguration process. Therefore, it needs to have an efficient transition method to shift the current logical topology to the new one so as to minimize the effect of the reconfiguration on the upper layer traffic. This paper proposes several heuristic algorithms that move the current logical topology efficiently to the given target logical topology in large-scale wavelength-routed optical networks. In the proposed algorithms, the performance improvement/degradation of data transmission [transmission delay or distance between a source-destination (s-d) pair] caused by a new lightpath is considered as benefit for establishing the new lightpath. The proposed algorithms construct the new logical topology starting from a lightpath with the largest benefit to the user traffic. Simulation experiments have been performed to evaluate the proposed algorithms in comparison with existing algorithms in a National Science Foundation Network (NSFNET)-like network model with 16 nodes and 25 links. The results show that the proposed algorithms yield much better performance (shorter average packet hot distance) than previous algorithms mostly with comparable computation time.
Let's enforce a simple visualization rule in Software Architecture

Many software architecture books have been written during the past decade. Taylor et al. have made their latest attempt to settle a standard in their large volume book, Software Architecture: Foundations, Theory, and Practice. As a software development practitioner, the author of this paper, who worked on many software-centric systems in both Aerospace and Telecommunication industries, will provide a unique analysis of software architecture roles in the software development life cycle. Based on the view that the essential purpose of software architecture is to communicate the design of the software to its stakeholders, this paper proposes a simple approach to visualization in software architecture as a rule of thumb to achieve an effective communication in software development.
Characterization of n-Vertex Graphs with Metric Dimension n-3

For an ordered set $W=\{w_1,w_2,. ,w_k\}$ of vertices and a vertex $v$ in a connected graph $G$, the ordered $k$-vector $r(v|W):=(d(v,w_1),d(v,w_2),. ,d(v,w_k))$ is called the (metric) representation of $v$ with respect to $W$, where $d(x,y)$ is the distance between the vertices $x$ and $y$. The set $W$ is called a resolving set for $G$ if distinct vertices of $G$ have distinct representations with respect to $W$. The minimum cardinality of a resolving set for $G$ is its metric dimension. In this paper, we characterize all graphs of order $n$ with metric dimension $n-3$.
HARP: Harnessing inactive threads in many-core processors

SIMT accelerators are equipped with thousands of computational resources. Conventional accelerators, however, fail to fully utilize available resources due to branch and memory divergences. This underutilization is manifested in two underlying inefficiencies: pipeline width underutilization and pipeline depth underutilization. Width underutilization occurs when SIMD execution units are not entirely utilized due to branch divergences. This affects lane activity and results in SIMD inefficiency. Depth underutilization takes place when the pipeline runs out of active threads and is forced to leave pipeline stages idle. This work addresses both inefficiencies by harnessing inactive threads available to the pipeline. We introduce Harnessing inActive thReads in many-core Processors (or simply HARP) to improve width and depth utilization in accelerators. We show how using inactive yet ready threads can enhance performance. Moreover, we investigate implementation details and study microarchitectural changes needed to build a HARP-enhanced accelerator. Furthermore, we evaluate HARP under a variety of microarchitectural design points. We measure the area overhead associated with HARP and compare to conventional alternatives. Under Fermi-like GPUs, we show that HARP provides 10p speedup on average (maximum of 1.6X) at the cost of 3.5p area overhead. Our analysis shows that HARP performs better under narrower SIMD and shorter pipelines.
A New first class algebra, homological perturbation and extension of pure spinor formalism for superstring

Based on a novel first class algebra, we develop an extension of the pure spinor (PS) formalism of Berkovits, in which the PS constraints are removed. By using the homological perturbation theory in an essential way, the BRST-like charge Q of the conventional PS formalism is promoted to a bona fide nilpotent charge , the cohomology of which is equivalent to the constrained cohomology of Q. This construction requires only a minimum number (five) of additional fermionic ghost-antighost pairs and the vertex operators for the massless modes of open string are obtained in a systematic way. Furthermore, we present a simple composite ``b-ghost" field B(z) which realizes the important relation T(z) = {,B(z)}, with T(z) the Virasoro operator, and apply it to facilitate the construction of the integrated vertex. The present formalism utilizes U(5) parametrization and the manifest Lorentz covariance is yet to be achieved.
Design of the simulation platform for networked control systems based on DTHMM

In order to achieve the application of discrete-time hidden Markov model (DTHMM) in modeling and controlling the networked control system (NCS) with the network-induced delays in the forward channel, a simulation platform was designed and implemented in this paper by using TrueTime 1.5, which is a Matlab/Simulink-based simulator. There were one network module and four kernel modules (sensor, controller, actuator and interference nodes) on this simulation platform, and the composition and the main Matlab codes of each module were presented. On the simulation platform designed, the Expectation Maximization (EM) algorithm was achieved to derive the parameters of the DTHMM and the Viterbi algorithm was achieved to predict the controller-to-actuator delay (C-A delay) in the current sampling period. Based on the derived DTHMM and the predicted delays, a state-feedback controller to stabilize the NCS was also implemented on the simulation platform and used to solve the linear matrix inequalities. Taking a damped compound pendulum as the plant in the NCS, after 500 sampling periods the effectiveness of the modeling and controlling methods was carried out, and demonstrated the efficiency and easy operation of the simulation platform.
Logic Synthesis and Place-and-Route Environment for ORGAs

We have continued development of Optically Reconfigurable Gate Arrays (ORGAs) to realize larger virtual gate count VLSIs than currently available VLSIs. The grain and structure of ORGAs must be changed depending on their dynamically reconfigurable applications. Therefore, an ORGA development tool must be easily customizable for changes of the grain and structure. This paper presents an easily-customizable logic synthesis, and a place-and-route environment of ORGAs using appropriate software tools (Design Compiler and Apollo; Synopsys Inc.).
Hybrid dynamical systems

Several aspects of model consistency are addressed. The discussion is put in the context of a particular hybrid system, the disk controller. This multilayer hybrid dynamical system is extended to include two other layers: a user layer at the top to define more complex tasks, and a sequencer between the supervisor and the servo layer to permit synchronous control. <<ETX>>
Tentative Detection of Galaxy Spin Correlations in the Tully Catalog

We report a tentative detection of spin correlations in the Tully catalog of nearby galaxies. We define a simple but nontrivial spin correlation function and find an analytic estimate of it in the frame of the linear perturbation theory. Then we present the observed spin correlation signal from the Tully galaxies with error bars. The three-dimensional spin correlation turns out to be significant at the 97% confidence level, detected out to a few h-1 Mpc. This observed correlation is consistent with the theoretical prediction based on the gravitational instability picture of galaxy formation. An analysis of systematic errors is also presented. The observed strength of correlation may be sufficient to significantly affect the blank field of weak-lensing searches.
Homological mirror symmetry is T-duality for P

In this paper, we apply the idea of T-duality to projective spaces. From a connection on a line bundle on P, a Lagrangian in the mirror Landau–Ginzburg model is constructed. Under this correspondence, the full strong exceptional collection OPn(−n − 1), . , OPn(−1) is mapped to standard Lagrangians in the sense of [23]. Passing to constructible sheaves, we explicitly compute the quiver structure of these Lagrangians, and find that they match the quiver structure of this exceptional collection of P. In this way, T-duality provides quasi-equivalence of the Fukaya category generated by these Lagrangians and the category of coherent sheaves on P, which is a kind of homological mirror symmetry.
Performance Comparison of IRIS Recognition System

Classification of iris templates based on their texture patterns is one of the most effective methods in iris recognition systems. This paper proposes a novel algorithm for automatic iris classification based on fractal dimensions of Haar wavelet transforms is presented. Fractal dimensions obtained from multiple scale features are used to characterize the textures completely. Haar wavelet is applied in order to extract the multiple scale features at different resolutions from the iris image. Fractal dimensions are estimated from these patterns and a classifier is used to recognize the given image from a data base. Performance comparison was made among different classifiers. I. Introduction Two phases are involved during authentication process using a biometric system, enrollment and authentication. During enrollment features sets are extracted from iris textures and saved in database. During authentication the features are extracted from query iris template and classified against the database. Current iris recognition systems perform exhaustive matching with high computational complexity as large databases are to be considered. Thus this new iris recognition system will play a vital role in reducing both the search time and computational complexity by classifying into different categories. Iris texture exhibits a rich source of visual information-about the nature and three dimensional shapes of physical objects. Textures are complex visual patterns composed of entities, or sub patterns that have characteristic brightness, color, slope, size. Thus texture can be regarded as a similarity grouping in an image. The local sub-pattern properties give rise to the perceived lightness of the texture as a whole. Van Gool and Reed and Buf present a detailed survey of the various texture methods used in the image analysis studies. The recognition ability of classifiers depends on the quality of features used as well as the amount of training data available to them. Image features are mostly extracted on shape and texture of segmented objects. Karu defines a methodology for automatically identifying textured regions within an image so that feature extraction algorithms are used only where texture can be quantified. Julesz (1975) found that for a large class of textures " no texture pair can be discriminated if they agree in their second order statistics ". Therefore the major statistical method used in texture analysis is the one based on the definition of the joint probability distributions of pairsof pixels. Weska compared the Fourier spectrum, second order gray levels statistics, cooccurrence statistics and gray level run length …
Automatically Integrating Life Science Data Sources

Data integration in the life sciences is currently implemented by very costly manually curated projects or by schemadriven approaches that require knowledge of the data sources and knowledge about schema integration techniques. We propose Aladin ‐ an entirely dierent, almost automatic approach based on the database instances and domain knowledge on life science data sources. We focus on two main tasks in Aladin ‐ detecting intraschema relationships and detecting inter-schema relationships. For the first task, we present our algorithm Spider for detecting inclusion dependencies (INDs) as a precondition for foreign keys. Spider analyzes a 2.8GB database in 24min and a 32GB database in 6h, up to an order of magnitude faster than previous approaches. We use INDs in two ways: (i) as hint for semantically correct foreign keys and (ii) for identification of a “primary relation” ‐ a domain-specific schema construct intended to help in further integration. For the second task, we describe ideas and first results on detecting cross-references between life science data sources and on detecting duplicate objects.
Biomusic: An Auditory Interface for Detecting Physiological Indicators of Anxiety in Children

For children with profound disabilities affecting communication, it can be extremely challenging to identify salient emotions such as anxiety. If left unmanaged, anxiety can lead to hypertension, cardiovascular disease, and other psychological diagnoses. Physiological signals of the autonomic nervous system are indicative of anxiety, but can be difficult to interpret for non-specialist caregivers. This paper evaluates an auditory interface for intuitive detection of anxiety from physiological signals. The interface, called “Biomusic,” maps physiological signals to music (i.e., electrodermal activity to melody; skin temperature to musical key; heart rate to drum beat; respiration to a “whooshing” embellishment resembling the sound of an exhalation). The Biomusic interface was tested in two experiments. Biomusic samples were generated from physiological recordings of typically developing children (n = 10) and children with autism spectrum disorders (n = 5) during relaxing and anxiety-provoking conditions. Adult participants (n = 16) were then asked to identify “anxious” or “relaxed” states by listening to the samples. In a classification task with 30 Biomusic samples (1 relaxed state, 1 anxious state per child), classification accuracy, sensitivity, and specificity were 80.8% [standard error (SE) = 2.3], 84.9% (SE = 3.0), and 76.8% (SE = 3.9), respectively. Participants were able to form an early and accurate impression of the anxiety state within 12.1 (SE = 0.7) seconds of hearing the Biomusic with very little training (i.e., < 10 min) and no contextual information. Biomusic holds promise for monitoring, communication, and biofeedback systems for anxiety management.
QoE-based Cross-Layer Design of Mobile Video Systems: Challenges and Concepts

This conceptual paper focuses on revealing challenges and offering concepts associated with the incorporation of the quality of experience (QoE) paradigm into the design of mobile video systems. The corresponding design framework combines application, middleware and networking layer in a unique cross-layer approach, in which all layers shall jointly analyse the quality of the video and its delivery in face of volatile conditions. Particular ingredients of the framework are efficient video processing, advanced realtime scheduling, and reduced-reference metrics on application and network layer.
CONTENT-BASED VIDEO COPY DETECTION USING MULTIMODAL ANALYSIS

CONTENT-BASED VIDEO COPY DETECTION USING MULTIMODAL ANALYSIS Onur Kucuktunc M.S. in Computer Engineering Supervisors: Prof. Dr. Ozgur Ulusoy and Assoc. Prof. Dr. Uǧur Gudukbay July, 2009 Huge and increasing amount of videos broadcast through networks has raised the need of automatic video copy detection for copyright protection. Recent developments in multimedia technology introduced content-based copy detection (CBCD) as a new research field alternative to the watermarking approach for identification of video sequences. This thesis presents a multimodal framework for matching video sequences using a three-step approach: First, a high-level face detector identifies facial frames/shots in a video clip. Matching faces with extended body regions gives the flexibility to discriminate the same person (e.g., an anchor man or a political leader) in different events or scenes. In the second step, a spatiotemporal sequence matching technique is employed to match video clips/segments that are similar in terms of activity. Finally the non-facial shots are matched using low-level visual features. In addition, we utilize fuzzy logic approach for extracting color histogram to detect shot boundaries of heavily manipulated video clips. Methods for detecting noise, frame-droppings, picture-in-picture transformation windows, and extracting mask for still regions are also proposed and evaluated. The proposed method was tested on the query and reference dataset of CBCD task of TRECVID 2008. Our results were compared with the results of top-8 most successful techniques submitted to this task. Experimental results show that the proposed method performs better than most of the state-of-the-art techniques, in terms of both effectiveness and efficiency.
Characterizing Traffic Density and Its Evolution through Moving Object Trajectories

Managing and mining data derived from moving objects have become an important issue in recent years. In this paper, we are interested in mining trajectories of moving objects, such as vehicles in the road network. We propose a method for discovering dense routes by clustering similar road sections according to both traffic and location in each time period. The traffic estimation is based on the collected spatiotemporal trajectories. We also propose a characterization approach of the temporal evolution of dense routes by a graph connecting dense routes over consecutive time periods. This graph is labeled by a degree of evolution. We have implemented and tested the proposed algorithms, which have shown their effectiveness and efficiency.
Trajectory planning based on latitude for painting on spherical surface

A latitude method for the trajectory planning of spraying on spherical surface is presented. The latitude method is used to optimize the time and coating thickness in the spray painting. The start curve, the velocity of the spray gun and the width between neighboring paths are the main factors to affect the final coating quality. Spray painting time is determined by the start curve of the gun, while selection of the velocity and width contribute to the coating thickness together. Based on the paint deposition model of flat surface, the deposition model on the cylindrical surface is derived. The start curve on the spherical surface is derived from the Bounding-Box method. The spray gun velocity and the width between neighboring paths are determined through the optical function in which the coating thickness is the optimized target. The simulation shows that the latitude method presented in this paper can solve the problem of the trajectory planning on spherical surface.
TEMPORAL PATTERN ANALYSIS OF WAVELET-FILTERED MODIS EVI TO DETECT LAND USE CHANGE IN JAVA ISLAND, INDONESIA

Recently, land use and cover change is recognized as a one of major drivers of global change. Consequently, an updated and accurate database concerning their distribution is essential for global change research. This study investigated a land use change based on change of temporal pattern which applied to the wavelet-filtered MODIS EVI from 2000 to 2009. The temporal pattern analysis was able to detect the actual timing of change event in Java, either by conversion or vegetation growth; however, such capability was limited on global scale analysis. We identified several types of significant change pattern; those have contributed into the land use change. Nevertheless, the change detection based on temporal pattern became complicated in several sites of agricultural land, since they were detected as a land use change, even if they were not. Such phenomena were affected by the climate pattern issues, e.g. ElNino. The use of multi-temporal data sets will be necessary to develop methodologies that utilize information on inter-annual variations to increase the accuracy of the land surface characterization.
Comparative Visualization for Parameter Studies of Dataset Series

This paper proposes comparison and visualization techniques to carry out parameter studies for the special application area of dimensional measurement using 3D X-ray computed tomography (3DCT). A dataset series is generated by scanning a specimen multiple times by varying parameters of an industrial 3DCT device. A high-resolution series is explored using our planar-reformatting-based visualization system. We present a novel multi-image view and an edge explorer for comparing and visualizing gray values and edges of several datasets simultaneously. Visualization results and quantitative data are displayed side by side. Our technique is scalable and generic. It can be effective in various application areas like parameter studies of imaging modalities and dataset artifact detection. For fast data retrieval and convenient usability, we use bricking of the datasets and efficient data structures. We evaluate the applicability of the proposed techniques in collaboration with our company partners.
Longitudinal and lateral control for autonomous ground vehicles

Robust and stable control is a requirement for navigation of self-driving cars. Some approaches in the literature depend on a high number of parameters that are often difficult to estimate. A poor selection of these parameters often reduces considerably the efficiency of the control algorithms. In this paper we propose a simplified control system for autonomous vehicles that depends on a reduced number of parameters that can be easily set. This control system is composed of longitudinal and lateral controllers. The longitudinal controller is responsible for regulating the vehicle's cruise velocity while the lateral controller steers the vehicle's wheels for path tracking. Simulated and experimental tests have been carried out with the CaRINA II platform in the university campus with positive results.