Miracle-dz/UniFAR-FTUs huggingface dataset:
High Distortion and Non-Structural Image Matching via Feature Co-occurrence

We propose a novel approach for determining if a pair of images match each other under the effect of a high-distortion transformation or non-structural relation. The co-occurrence statistics between features across a pair of images are learned from a training set comprising matched and mismatched image pairs - these are expressed in the form of a cross-feature ratio table. The proposed method does not require feature-to-feature correspondences, but instead identifies and exploits feature co-occurrences that are able to provide discriminative result from the transformation. The method not only allows for the matching of test image pairs that have substantially different visual content as compared to those present in the training set, but also caters for transformations and relations that do not preserve image structure.
Symbolic Analysis of the Neuron Action Potential

We present a novel approach to investigating key behavioral properties of complex biological systems by first using automated techniques to learn a simplified Linear Hybrid Automaton model of the system under investigation, and then carrying out automatic reachability analysis on the resulting model. The specific biological system we consider is the neuronal Action Potential and the specific question of interest is bifurcation: the graded response of the neuron to stimulation of varying amplitude and duration. Reachability analysis in this case is performed using the d/dt analysis tool for hybrid systems. The results we so obtain reveal the precise conditions under which bifurcation manifests, when taking into consideration an infinite class of input stimuli of arbitrary shape, amplitude, and duration within given respective intervals. To the best of our knowledge, this represents the first time that formal (reachability) analysis has been applied to a computational model of excitable cells. The obvious advantage of symbolic reachability analysis over simulation - perhaps the only available analysis method when complex systems of coupled ODEs are used to model excitable-cell behavior, as has traditionally been the case - is that through the so-called reachable set computation, the system's reaction to an infinite set of possible inputs can be observed. Our results further demonstrate that Linear Hybrid Automata, as a formal language, is both expressive enough to capture interesting excitable-cell behavior, and abstract enough to render formal analysis possible.
Black holes and Calabi-Yau threefolds

We compute the microscopic entropy of certain 4 and 5 dimensional extermal black holes which arise for compactification of M-theory and type IIA on Calabi-Yau 3-folds. The results agree with macroscopic predictions, including some subleading terms. The macroscopic entropy in the 5 dimensional case predicts a surprising growth in the cohomology of moduli space of holomorphic curves in Calabi-Yau threefolds which we verify in the case of elliptic threefolds.
Objective testing of a cooperative intersection collision avoidance system for traffic signal and stop sign violation

Crashes in intersections caused by a violation of traffic signals or stop signs amount to a significant portion of all vehicle crashes. The percentage of fatal crashes that occur at intersections remains constant over the years at nearly 22% of all crashes [1]. Vehicle-to Infrastructure (V2I) communications is a powerful technology that can address some of these crash scenarios. In order for tV2I based vehicle safety systems to be tested for correct functionality, and Field Operational Test FOT) readiness, Objective Test Procedures (OTP) have to be adopted. The Vehicle Safety Communications 2 (VSC- Consortium developed a Cooperative Intersection Collision Avoidance System - Violations (CICAS-V) and, in cooperation with the Research and Innovative Technology Administration's Intelligent Transportation Systems Joint Program Office and Of the National Highway Traffic Safety Administration (NHTSA) the United States Department of Transportation (USDOT). Using cooperatively developed OTP the performance of the CICAS-V was tested to determine if the system could be driven by naïve drivers on open roads. The CICAS-V was tested against all the OTP and successfully passed every test.
Fuzzy portfolio optimization using Chen and Huang model: Evidence from Iranian mutual funds

In this study, we examine the performance of mutual funds in Iran in order to determine the best allocation of money to equity mutual funds base on the Chen and Huang (2009) model. First, funds are categorized based on the four criteria through cluster analysis: return rates, standard deviation, Sortino ratio, and turnover rate. In the Chen and Huang (2009) model, the Treynor ratio has been used while we use Sortino ratio. The clustering process shows that mutual funds can be categorized into three groups which we called, inferior performance funds, aggressive funds, and good performance funds. Chen categorized the funds in Taiwan into four groups. Future return rates and future risk are presented as triangular fuzzy numbers and then portfolio optimization problem is developed in two ways: maximizing the future expected return subject to the given greatest future risk, and minimizing the future risk subject to a required lowest future expected return. We suggest that risk-averse investors consider the minimization of the risk as objective and take returns as constraint. Risk-seeking investors can maximize the returns at a given level of risk. Key words: Portfolio optimization, equity mutual funds, performance indices, cluster analysis, fuzzy set.
Designing on-chip networks for throughput accelerators

As the number of cores and threads in throughput accelerators such as Graphics Processing Units (GPU) increases, so does the importance of on-chip interconnection network design. This article explores throughput-effective Network-on-Chips (NoC) for future compute accelerators that employ Bulk-Synchronous Parallel (BSP) programming models such as CUDA and OpenCL. A hardware optimization is “throughput effective” if it improves parallel application-level performance per unit chip area. We evaluate performance of future looking workloads using detailed closed-loop simulations modeling compute nodes, NoC, and the DRAM memory system. We start from a mesh design with bisection bandwidth balanced to off-chip demand. Accelerator workloads tend to demand high off-chip memory bandwidth which results in a many-to-few traffic pattern when coupled with expected technology constraints of slow growth in pins-per-chip. Leveraging these observations we reduce NoC area by proposing a “checkerboard” NoC which alternates between conventional full routers and half routers with limited connectivity. Next, we show that increasing network terminal bandwidth at the nodes connected to DRAM controllers alleviates a significant fraction of the remaining imbalance resulting from the many-to-few traffic pattern. Furthermore, we propose a “double checkerboard inverted” NoC organization which takes advantage of channel slicing to reduce area while maintaining the performance improvements of the aforementioned techniques. This organization also has a simpler routing mechanism and improves average application throughput per unit area by 24.3%.
What Drives Media Use in Authoritarian Regimes? Extending Selective Exposure Theory to Iran

Most work on selective exposure comes from the United States or other western democracies and typically examines partisan attitudes as the cognitive or motivational drivers of selectivity. This study extends the boundary conditions of existing literature by studying the factors affecting media choice in the Islamic Republic of Iran, a drastically understudied context. Within the overarching framework of motivated reasoning, we propose two theoretically relevant factors that should drive selective exposure into regime media or non-regime alternatives in authoritarian contexts: (1) system-justifying attitudes and (2) regime-sanctioned identities, here religiosity. Relying on two different surveys conducted within Iran in 2012 and 2016, we find that religiosity strongly predicts the reliance on non-regime media in both studies, whereas system-justifying attitudes predict selectivity in Study 2. Theoretical implications for the selectivity literature are discussed.
Can we identify genes for alcohol consumption in samples ascertained for heterogeneous purposes?

BACKGROUND Previous studies have identified evidence of genetic influence on alcohol use in samples selected to be informative for alcoholism research. However, there are a growing number of genome-wide association studies (GWAS) using samples unselected for alcohol consumption (i.e., selected on other traits and forms of psychopathology), which nevertheless assess consumption as a risk factor. Is it reasonable to expect that genes contributing to variation in alcohol consumption can be identified in such samples? METHODS An exploratory approach was taken to determine whether linkage analyses for heaviness of alcohol consumption, using a sample collected for heterogeneous purposes, could replicate previous findings. Quantity and frequency measures of consumption were collected in telephone interviews from community samples. These measures, and genotyping, were available for 5,441 individuals (5,067 quasi-independent sibling pairs). For 1,533 of these individuals, data were collected on 2 occasions, about 8.2 years apart, providing 2 datasets that maximize data collected at either a younger or an older age. Analyses were conducted to address the question of whether age and heavier levels of alcohol consumption effects outcome. Linkage results were compared in the younger and older full samples, and with samples in which approximately 10, 20, and 40 of drinkers from the lower end of the distribution of alcohol consumption were dropped. RESULTS Linkage peaks varied for the age differentiated samples and for percentage of light drinkers retained. Larger peaks (LOD scores >2.0) were typically found in regions previously identified in linkage studies and/or containing proposed candidate genes for alcoholism including AGT, CARTPT, OPRD1, PIK3R1, and PDYN. CONCLUSIONS The results suggest that GWAS assessing alcohol consumption as a covariate for other conditions will have some success in identifying genes contributing to consumption-related variation. However, sample characteristics, such as participant age, and trait distribution, may have substantial effects on the strength of the genetic signal. These results can inform forthcoming GWAS where the same restrictions apply.
Power Optimization With Power Islands Synthesis

With the migration to deep sub-micron process technologies, the power consumption of a circuit has come to the forefront of concerns, and as a result, the power has become a critical design parameter. This paper presents a novel high-level synthesis methodology, called Power Islands Synthesis, that eliminates the spurious switching activity and the leakage in a great portion of the resulting circuit by partitioning it into islands. Each island is a cluster of logic whose power can be controlled independently from the rest of the circuit and hence can be completely powered down when all of the logic it contains is idling. The partitioning is done in such a way that the components with maximally overlapping lifetimes are placed on the same island. By powering down an island during its idle cycles, the following occur: 1) The spurious switching that results from the broadcast to idle components is silenced and 2) the power consumption due to leakage in inactive components is eliminated. Experiments conducted on several synthesis benchmarks implemented at the layout level with a 65-nm process technology and simulated using a transistor-level simulator showed power savings ranging from 5% to 20% due to our methodology. The reported savings were entirely from the power down of combinational elements (functional resources) of the data path.
A review on level of detail

Advances in modern 3D scanning technology and the increasingly size of computer simulations have led to a rapid increase in the availability and size of geometry data sets. Gigantic polygonal data sets, consisting of hundreds of millions of faces, are becoming quite common. While the performance of graphics hardware also seen a drastic rise in these years, however, ability to produce enormous data sets overload the capabilities of the state-of-the-art graphics chip. Therefore, automatic model simplification and run-time level of detail (LOD) management techniques are introduced. We present a review on level of detail techniques in an organized structure. Level of detail framework, level of detail management, level of detail simplification models and metrics for simplification and error evaluation are discussed in sequence. Finally, some current issues and conclusion are given.
Gestión del conocimiento y desafíos en PyMEs proveedoras de la cadena de hidrocarburos en la Cuenca Neuquina. Avance de investigación y reflexión para el diseño de políticas

El documento aborda un conjunto de aspectos que destacan en el desenvolvimiento de las PyMEs de hidrocarburos de la Cuenca Neuquina, en la Norpatagonia argentina. La indagacion esta motivada, por un lado, en los cambios recientes del sector energetico en general, e hidrocarburifero en particular, la caida de los precios del petroleo y una tendencia hacia energias mas limpias. Y por otro, a nivel estructural, por la dinamica de innovacion que se ha abierto con el desarrollo de los reservorios no convencionales para las firmas del segmento PYME, que integran las cadenas globales de valor del gas y el petroleo. La nueva fase de desarrollo de los hidrocarburos exige nuevos sistemas tecnicos en la perforacion y terminacion de pozos y nuevos procedimientos en la extraccion, asi como cambios en los insumos, componentes y equipos. Ellos movilizan una nueva organizacion del trabajo, la introduccion creciente de las TICs, la toma de informacion ad hoc, capacitacion especifica, y una rigurosa coordinacion de procesos que se traduce en una nueva division del trabajo aguas arriba. En este marco, desde un enfoque evolucionista de la economia, se analizan un conjunto de problematicas que enfrentan grupos de PyMEs regionales proveedoras de bienes y servicios del rubro electronica y metalmecanica. Se indago acerca de las rutinas de las firmas en la construccion de capacidades tecnologicas, el desarrollo de nuevos procesos y productos, los vinculos externos y las mejoras de gestion internas, los cambios en la productividad, y la competencia comercial en el nuevo escenario de volatilidad de los precios del petroleo.
Cervical Spondylotic Myelopathy: Pathophysiology, Diagnosis, and Surgical Techniques

Cervical spondylotic myelopathy is a degenerative spinal disease which may lead to significant clinical morbidity. The onset of symptoms is usually insidious, with long periods of fixed disability and episodic worsening events. Regarding the pathophysiology of CSM, the repeated injuries to the spinal cord are caused by both static and dynamic mechanical factors. The combination of these factors affects the spinal cord basically through both direct trauma and ischemia. Regarding the diagnosis, both static and dynamics X-rays, as well as magnetic resonance imaging are important for preoperative evaluation as well as individualizing surgical planning. The choice of the most appropriate technique is affected by patient's clinical condition radiologic findings, as well as surgeon's experience. In opposition to the old belief that patients presenting mild myelopathy should be treated conservatively, there has progressively been amount of evidence indicating that the clinical course of this disease is progressive deterioration and that early surgical intervention improves long-term functional recovery and neurological prognosis.
Doing Argumentation Theory in Modal Logic

The present paper applies well-investigated modal logics to provide formal foundations to specific fragments of argumentation theory. This logic-driven analysis of argumentation allows: first, to systematize several results of argumentation theory reformulating them within suitable formal languages; second, to import several techniques (calculi, model-checking games, bisimulation games); third, to import results (completeness of axiomatizations, complexity of model-checking, adequacy of games) from modal logic to argumentation theory.
Binomial Checkpointing for Arbitrary Programs with No User Annotation

Heretofore, automatic checkpointing at procedure-call boundaries, to reduce the space complexity of reverse mode, has been provided by systems like Tapenade. However, binomial checkpointing, or treeverse, has only been provided in Automatic Differentiation (AD) systems in special cases, e.g., through user-provided pragmas on DO loops in Tapenade, or as the nested taping mechanism in adol-c for time integration processes, which requires that user code be refactored. We present a framework for applying binomial checkpointing to arbitrary code with no special annotation or refactoring required. This is accomplished by applying binomial checkpointing directly to a program trace. This trace is produced by a general-purpose checkpointing mechanism that is orthogonal to AD.
Understanding Network Forensics Analysis in an Operational Environment

The manual forensics investigation of security incidents is an opaque process that involves the collection and correlation of diverse evidence. In this work we conduct a complex experiment to expand our understanding of forensics analysis processes. During a period of four weeks we systematically investigated 200 detected security incidents about compromised hosts within a large operational network. We used data from four commonly-used security sources, namely Snort alerts, reconnaissance and vulnerability scanners, blacklists, and a search engine, to manually investigate these incidents. Based on our experiment, we first evaluate the (complementary) utility of the four security data sources and surprisingly find that the search engine provided useful evidence for diagnosing many more incidents than more traditional security sources, i.e., blacklists, reconnaissance and vulnerability reports. Based on our validation, we then identify and make available a list of 138 good Snort signatures, i.e., signatures that were effective in identifying validated malware without producing false positives. In addition, we compare the characteristics of good and regular signatures and highlight a number of differences. For example, we observe that good signatures check on average 2.14 times more bytes and 2.3 times more fields than regular signatures. Our analysis of Snort signatures is essential not only for configuring Snort, but also for establishing best practices and for teaching how to write new IDS signatures.
Effect of maternal weight, adipokines, glucose intolerance and lipids on infant birth weight among women without gestational diabetes mellitus

Background: The delivery of excess maternal nutrients to the fetus is known to increase the risk of macrosomia, even among infants of women without gestational diabetes mellitus. With the current obesity epidemic, maternal adiposity and its associated effects on circulating adipokines and inflammatory proteins may now have a greater impact on fetal growth. We sought to evaluate the independent effects of maternal glycemia, lipids, obesity, adipokines and inflammation on infant birth weight. Methods: We included 472 women who underwent an oral glucose tolerance test in late pregnancy and were found not to have gestational diabetes; 104 (22.0%) had gestational impaired glucose tolerance. We also measured fasting levels of insulin, low-and high-density lipoprotein cholesterol, triglycerides, leptin, adiponectin and C-reactive protein. Obstetric outcomes were assessed at delivery. Results: The mean birth weight was 3481 g (standard deviation 493 g); 68 of the infants were large for gestational age. On multiple linear regression analysis, positive determinants of birth weight were length of gestation, male infant, weight gain during pregnancy up to the time of the oral glucose tolerance test, body mass index (BMI) before pregnancy and impaired glucose tolerance in pregnancy. Leptin, adiponectin and C-reactive protein levels were each negatively associated with birth weight. On logistic regression analysis, the significant metabolic predictors of having a large-for-gestational-age infant were BMI before pregnancy (odds ratio [OR] 1.16, 95% confidence interval [CI] 1.05–1.27, per 1 kg/m2 increase), weight gain during pregnancy up to the time of the oral glucose tolerance test (OR 1.12, 95% CI 1.05–1.19, per 1 kg increase) and leptin level (OR 0.50, 95% CI 0.30–0.82, per 1 standard deviation change). Interpretation: Among women without gestational diabetes, maternal adiposity and leptin levels were the strongest metabolic determinants of having a large-for-gestational-age infant rather than glucose intolerance and lipid levels.
Performance Modeling and Evaluation of Network Processors

In recent years there has been an exponential growth in Internet traffic resulting in increased network bandwidth requirements which, in turn, has led to stringent processing requirements on network layer devices like routers. Present backbone routers on OC 48 links (2.5Gbps) have to process four million minimum-sized packets per second. Further, the functionality supported in the network devices is also on the increase leading to programmable processors, such as Intel’s IXP, Motorola’s C5 and IBM’s NP. These processors support multiple processors and multiple threads to exploit packet-level-parallelism inherent in network workloads. This thesis studies the performance of network processors. We develop a Petri Net model for a commercial network processors (Intel IXP 2400,2850) for three different applications viz., IPv4 forwarding, Network Address Translation and IP security protocols. A salient feature of the Petri net model is its ability to model the application, architecture and their interaction in great detail. The model is validated using the Intel proprietary tool (SDK 3.51 for IXP architecture) over a range of configurations. Our Performance evaluation results indicate that 1. The IXP processor is able to support a throughput of 2.5 Gbps for all modeled applications. 2. Packet buffer memory (DRAM) is the bottleneck resource in a network processor and even multithreading is ineffective beyond a total of 16 threads in case of header processing applications and beyond 32 threads for payload processing applications.
Maximally Confined Silicon Microring and Microdisk Modulators and Switches

Silicon resonant microdisk and microring modulators and switches based on free-carrier depletion and injection were designed and fabricated with the aim of minimizing device radius to theoretical bend-radiation imposed limits. Minimizing device area serves to simultaneously maximize resonator free-spectral-range, minimize switching energy, and maximize component density, all critical parameters for wideband chip-to-chip and intrachip communication applications. Confinement of the bend-mode in the modulators is minimized by contacting the modulator from within the interior of the resonator to ensure a hard outer wall of the cavity. Both numerical and experimental results will be presented.