Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploiting Java instruction/thread level parallelism with horizontal multithreading

Java bytecodes can be executed with the following three methods: a Java interpreter running on a particular machine interprets bytecodes; a Just-in-Time (JIT) compiler translates bytecodes to the native primitives of the particular machine and the machine executes the translated codes; and a Java processor executes bytecodes directly. The first two methods require no special hardware support for the execution of Java bytecodes and are widely used currently. The last method requires an embedded Java processor, picoJavaI or picoJavaII for instance. The picoJavaI and picoJavaII are simple pipelined processors with no ILP (instruction level parallelism) and TLP (thread level parallelism) supports. A so-called MAJC (microprocessor architecture for Java computing) design can exploit ILP and TLP by using a modified VLIW (very long instruction word) architecture and vertical multithreading technique, but it has its own instruction set and cannot execute Java bytecodes directly. In this paper, we investigate a processor architecture which can directly execute Java bytecodes meanwhile can exploit Java ILP and TLP simultaneously. The proposed processor consists of multiple slots implementing horizontal multithreading and multiple functional units shared by all threads executed in parallel. Our architectural simulation results show that the Java processor could achieve an average 20 IPC (instructions per cycle), or 7.33 EIPC (effective IPC), with 8 slots and a 4-instruction scheduling window for each slot. We also check other configurations and give the utilization of functional units as well as the performance improvement with various kinds of working loads.
A Better Dipole

We present a dipole BSSRDF with modified diffusion asymptotics, improved exitance calculations and consistent boundary conditions. This BSSRDF improves significantly upon the classical dipole model, requires negligible extra evaluation cost and is very easy to adapt in new and existing subsurface scattering algorithms. While not as accurate as a diffusion model using an extended source, such as the recent quantized diffusion method, this dipole model is far easier to implement and is of potential interest in some rendering and measurement applications. We include a comprehensive quantitative comparison between the classical dipole and the “better" dipole as well as quantized diffusion and benchmark Monte Carlo results for reference.
Deep Learning and Quantum Entanglement: Fundamental Connections with Implications to Network Design

Deep convolutional networks have witnessed unprecedented success in various machine learning applications. Formal understanding on what makes these networks so successful is gradually unfolding, but for the most part there are still significant mysteries to unravel. The inductive bias, which reflects prior knowledge embedded in the network architecture, is one of them. In this work, we establish a fundamental connection between the fields of quantum physics and deep learning. We use this connection for asserting novel theoretical observations regarding the role that the number of channels in each layer of the convolutional network fulfills in the overall inductive bias. Specifically, we show an equivalence between the function realized by a deep convolutional arithmetic circuit (ConvAC) and a quantum many-body wave function, which relies on their common underlying tensorial structure. This facilitates the use of quantum entanglement measures as well-defined quantifiers of a deep network's expressive ability to model intricate correlation structures of its inputs. Most importantly, the construction of a deep ConvAC in terms of a Tensor Network is made available. This description enables us to carry a graph-theoretic analysis of a convolutional network, with which we demonstrate a direct control over the inductive bias of the deep network via its channel numbers, that are related to the min-cut in the underlying graph. This result is relevant to any practitioner designing a network for a specific task. We theoretically analyze ConvACs, and empirically validate our findings on more common ConvNets which involve ReLU activations and max pooling. Beyond the results described above, the description of a deep convolutional network in well-defined graph-theoretic tools and the formal connection to quantum entanglement, are two interdisciplinary bridges that are brought forth by this work.
Antagonismo, modernismo e inercia: la política regulatoria brasileña en tres actos

Regulatory policy in Brazil has evolved as a result of the political-ideological interchanges between political coalitions that have governed the country over the last two decades. However, this has not been the only element outlining the policy. Since the State reform in the 1990s, regulation has been conceptually attached to a liberalizing rationale of economic policy and it is, from the theoretical viewpoint, highly dependent on modernizing currents in the field of international public management. The main consequence of this consists in poorly structured and, to some extent, incoherent movements regarding this public policy. At different moments, the assimilation of modernizing global trends has lost ground to ideological antagonisms or periods of significant stagnation. Thus, this article aims to prospect the main stages of the recent history of the Brazilian regulatory policy by means of a detailed evaluation of the most relevant aspects behind this public policy. The three acts demarcating distinct phases and the specific problems that have changed the core of the policy for regulatory management will be introduced. The relation between State, market, and society is crucial to understand the creation of this public policy, as well as the assimilation and resilience degrees of regulatory tools adopted by the country. In the end, it is possible to notice that the regulatory policy still remains partial and deficient at the federal level, although clear tendencies are already perceptible, particularly the permeability to resocialization and decentralization elements.
A hybrid image registration technique for multi-spectral images application

A hybrid scheme which uses both feature-based and intensity-based methods is proposed. In particular, an edge-based image registration approach is developed to guide the intensity-based registration which uses optical flow estimation. The idea of coarse-to-fine multi-scale iterative refinement is also utilized. The combination of these different methods tends to compensate for any deficiencies in the individual methods. Experiments show that our approach provides accurate registrations for the multispectral images application.
Networks on Chip: The New Trend of On-Chip Interconnection

With continuous shrinking in the size of deep sub-micron in this million transistor era, the interconnection of these hundreds and thousands of cores on a single chip is still constraint. Providing an efficient communication among these cores is a major challenge in the on-chip domain. Although hierarchical architecture has addressed most of the issues of the traditional approaches like point-to-point and bus architecture, scalability still remains to be a limitation. Network on chip architecture provides a viable solution to all these issues. A network is established on the chip among the cores and communication occurs through this network, making it highly efficient and mostly scalable. In this paper we present a brief introduction to network-on-chip along with some of its popular topologies and routing techniques. Also, some of the major challenges of network-on-chip have been stated.
Joint Calibration of a Range and Visual Sensor for the Acquisition of RGBZ Concentric Mosaics

In this paper we present an algorithm for joint extrinsic calibration of a moving sensor device consisting of a low cost industrial 2D laser range finder and a single high quality consumer DV video camera mounted on a camera crane. The calibration is based on the minimization of the Euclidean projection error of scene points in many frames captured at different viewpoints. The calibration procedure is designed to support any arbitrary motion trajectory of the acquisition device. In this work the capture geometry for concentric mosaics, a well known image-based rendering technique, is used to evaluate the performance of the proposed algorithm. The projection error after calibration is less than one pixel on average.
Hantaviruses: genome structure, expression and evolution.

Introduction. The isolation by Ho Wang Lee and collaborators of the virus causing Korean haemorrhagic fever, now called Hantaan virus (HTN), from the lungs of striped field mice (Apodemus agrarius) in 1976 (Lee & Lee, 1976) launched a new era in the study of haemorrhagic fever with renal syndrome (HFRS) throughout the world. This was soon followed by the discovery of the causative agent of the European form of HFRS, nephropathia epidemica, now known as Puumala virus (PUU) (Brummer-Korvenkontio et al., 1980), and of the urban rat virus, Seoul virus (SEO) (Lee et al., 1980). The identification in 1993 of Sin Nombre virus (SN) as the causative agent of hantavirus-associated pulmonary syndrome (HPS) (Nichol et al., 1993a) led to intensive search for further hantaviruses and as a result today a total of as many as 16 well-established sero/genotypes may be listed.
The effects of identifier retention and stop word removal on a latent Dirichlet allocation based feature location technique

Feature location, an important task in program comprehension, occurs when the developer identifies the source code entity or entities responsible for implementing a functionality. Researchers have applied static analysis techniques to multiple software maintenance tasks, including feature localization. Static analysis techniques operate on a document corpus. Configuration and preprocessing decisions are required to build a suitable source code corpus for a static analysis technique. Currently, there is little guidance in the software engineering literature for making such configuration decisions. This paper focuses on two preprocessing methods for source code corpora, identifier splitting and stop word lists. We experiment on three open source Java test suites, i.e. Mylyn 1.0. 1, Rhino 1.5R5, and Rhino 1.6R5. Our results indicate that identifier splitting and stop word list decisions do not significantly affect the performance of the LDA based feature location technique.
Improving Efficiency of Apriori Algorithm Using Transaction Reduction

Association rules are the main technique to determine the frequent itemset in data mining. Apriori algorithm is a classical algorithm of association rule mining. This classical algorithm is inefficient due to so many scans of database. And if the database is large, it takes too much time to scan the database. In this paper, we proposed an Improved Apriori algorithm which reduces the scanning time by cutting down unnecessary transaction records as well as reduce the redundant generation of sub-items during pruning the candidate itemsets, which can form directly the set of frequent itemsets and eliminate candidate having a subset that is not frequent.
High expression of the mismatch repair protein MSH6 is associated with poor patient survival in melanoma.

OBJECTIVES The outcome of patients with primary melanoma (PM) cannot be completely explained based on currently adopted clinical-histopathologic criteria. In this study, we evaluated the potential prognostic value of mismatch repair protein expression in PMs. METHODS We examined the immunohistochemical staining of mismatch repair proteins in 18 benign nevi and 101 stage I to III PMs and investigated their association with tumor clinicopathologic variables and melanoma mortality. RESULTS Expression of MSH2, MLH1, and PMS2 was high in benign nevi and reduced in a subset of PMs. Conversely, MSH6 expression was absent or extremely low in benign nevi and increased in a subset of PMs. In the multivariate analysis, including sex, age, Breslow thickness, and ulceration, high MSH6 expression in PMs (ie, immunostaining in >20% of tumor cells) was significantly associated with an increased risk of melanoma mortality (relative risk, 3.76; 95% confidence interval, 1.12-12.70). CONCLUSIONS MSH6 protein expression can be a valuable marker to improve prognosis assessment in PMs.
Chinese Character Expansion for Retrieving Japanese Paraphrases

This paper proposes two methods of query expansion for retrieving paraphrase candidates indexed by Kanzi (Chinese) characters. The idea is to calculate similarity between Kanzi characters based on an ordinary thesaurus defining relations between words. The local analysis method calculates similarity of Kanzi characters based on a semantic class to which words in a query belong, in contrast, the global analysis method calculates similarity based on whole semantic classes in the thesaurus. The methods were evaluated by using the EDR concept dictionary which defines about 410,000 concepts. In the experiments, both headwords and concept descriptions of dictionary entries were indexed by Kanzi characters, and concept descriptions were retrieved by giving a headword as a query. The experiments showed that Kanzi character expansion is significantly effective, and the global analysis method is better than the local analysis method in recall.
Clinical Efficacy of Two Different Methods to Initiate Sensor-Augmented Insulin Pumps: A Randomized Controlled Trial

Aim. To analyze clinical effect of a novel approach to initiate sensor-augmented insulin pumps in type 1 diabetes mellitus (T1DM) patients through early real-time continuous glucose monitoring (RT-CGM) initiation. Methods. A 26-week pilot study with T1DM subjects randomized (1 : 1) to start RT-CGM three weeks before continuous subcutaneous insulin infusion (CGM pre-CSII) or adding RT-CGM three weeks after continuous subcutaneous insulin infusion (CGM post-CSII). Results. Twenty-two patients were enrolled with a mean age of 36.6 yr. (range 19–59 yr.) and T1DM duration of 16.8 ± 10.6 yr. Higher adherence in CGM pre-CSII patients was confirmed at study end (84.6 ± 11.1% versus 64.0 ± 25.4%; P = 0.01). The two intervention groups had similar HbA1c reduction at study end of −0.6% (P = 0.9). Hypoglycemic event frequency reduction was observed from baseline to study end only in CGM pre-CSII group (mean difference in change, −6.3%; 95% confidence interval, −12.0 to −0.5; P = 0.04). Moreover, no severe hypoglycemia was detected among CGM pre-CSII subjects during the study follow-up (0.0 ± 0.0 events versus 0.63 ± 1.0 events; P = 0.03). CGM pre-CSII patients showed better satisfaction than CGM post-CSII patients at the end of the study (27.3 ± 9.3 versus 32.9 ± 7.2; P = 0.04). Conclusions. CGM pre-CSII is a novel approach to improve glycemic control and satisfaction in type 1 diabetes sensor-augmented pump treated patients.
Red, green, and blue LEDs for white light illumination

The rapid improvement of the white light efficacy achievable with light-emitting diodes (LEDs) opens up new opportunities in the general illumination market. An LED light source made of red, green, and blue LEDs (RGB-LEDs) can provide the unique feature of color variability, allowing the user to select the desired color point of the lamp. The white light color accuracy required in the general illumination market is a challenge for LEDs. The variation in lumen output and wavelength for nominally identical LEDs and the change in these parameters with temperature and time result in an unacceptably high variability in the color point of white light from RGB-LEDs. In this paper, we show that these problems can be overcome with suitable feedback control schemes that can be implemented in a practical LED lamp. We present results of experiment and theoretical modeling that shows the performance that can be achieved with a number of different control schemes.
A HIERARCHICAL VIEW OF SEX-RATIO PATTERNS

Most organisms have two sexes ; thus it is reasonable to ask what is the ratio of the sexes, and does this ratio fluctuate in a predictable manner. Basic researchers have long recognized that the sex ratio is a phenotypic trait of an organism, and therefore may be subject to natural selection. In addition, it has been widely noted that (i) the relative fitness of a male versus a female ranges widely according to a variety of ecological factors (e.g., size of individual, local sex ratio, inbreeding) , implying that the selection of sex-ratio traits should be strong; and (ii) relative to other traits studied by behavioral ecologists, sex ratios can often be measured with a high degree of precision. Hence, the subject of sex ratios is ideal for testing the efficacy of natural selection, and for testing our understanding of the selective process. Applied researchers also have a long history of interest in sex ratios. Efficiency of live-stock breeding would be greatly enhanced by control over the sex ratio ; mass-rearing of parasites as biological control agents is often improved by a female-biased sex ratio ; and causing a male-biased sex ratio in a population of pests would aid ind reducing the amount of damage. This paper is an introduction to a way of viewing sex-ratio puzzles that has had some success—both theoretically and empirically—and points out some of the difficulties of sex-ratio problems. After a methodology has been developed, the following questions will be addressed : What sex-ratio patterns are observed in nature? What are the causes and what are the ecological correlates of the patterns? What sort of logic is required to explain each pattern? What general themes underlie the patterns? Some assumptions and extensions of the theory are discussed in the appendix. ,
Optimal Design of Power Transformer Using Genetic Algorithm

The paper presents power transformer design, using genetic algorithm (GA) and simulated annealing (SA) by minimizing total active cost, keeping in view the constraints imposed by international standards and power transformer specifications. The design results using conventional method (CM) have been compared with those obtained by applying GA and SA techniques and it is quite evident that the dimensions as well as active cost have been reduced in comparison to CM using same set of constraints. The results of GA and SA have been obtained using optimization tool box MATLAB Release 9.1 which have not been applied for power transformer design so far. Present paper firstly provides efficient and reliable solution for the design optimization problem with several variables and secondly, it guarantee that the obtained solution is a global optimum. Hence, this paper demonstrates a better and efficient solution for power transformer design using the said optimization techniques.
Putting routing tables in silicon

Moving routing tables from RAM to custom or semicustom VLSI can lower cost and boost performance. The routing table problem is presented by discussing the available architectures and how they are related. It is shown that simple table lookup is just a special case of the standard trie structure and that the use of partitioning combined with the trie structure provides a continuum that can lead to a CAM implementation at one extreme. The high-level tradeoffs in the choice of various parameters for the trie are estimated. A careful choice of word size can balance the requirements for speed with the costs of area. Also considered are the costs and benefits of splitting the table into a number of tries, which are searched simultaneously. VLSI implementations are outlined, and the costs are compared. General CAM structures are not needed for the routing table application, and custom CAMs can be very efficient. Tries, however, can be competitive in many cases, due to the resources available for building conventional memories. <<ETX>>
Evaluation Methodologies for Spoken and Multi Modal Dialogue Systems-a COST 278 WG 2 and WG 3 Report

Note: Parts of this draft is based on unpublished work and articles. Please do not cite or in other ways use material from the report before the final version is released. Summary This report is a part of the collaborative results of the COST278 project on Spoken Language in Telecommunication, Working Group 2 and 3. The report addresses usability evaluation of Spoken and Multi Modal Dialogue Systems. It introduces usability evaluation in general and for speech driven systems in particular. The theoretic background for the elicitation of user attitudes through the use of questionnaires is briefly reviewed. This is a field with a number of pitfalls, both regarding the psychological aspects as well as the statistical methods applied in the analysis of the results. It is unfortunately a field that have received little or no attention from the speech community till date. The PARADISE scheme for the evaluation of Spoken Dialogue Systems is described. PARADISE is unique in the sense that it attempts to estimate a performance function through Multivariate Linerar Regression (MLR). Thus " User Satisfaction " is directly expressed as a function of various metrics for " Dialogue Costs " and " Dialogue Quality ". The scheme has quickly gained support and have been applied to a number of domains, especially in the U.S. However, the approach also has weaknesses. An important part of the report is an extensive literature list reflecting a broad overview of the current state-of-the-art of the field.
Description of the POMELO System for the Task 2 of QALD-2014

In this paper, we present the POMELO system developed for participating in the task 2 of the QALD-4 challenge. For translating natural language questions in SPARQL queries we exploit Natural Language Processing methods, semantic resources and RDF triples description. We designed a four-step method which pre-processes the question, performs an abstraction of the question, then builds a representation of the SPARQL query and finally generates the query. The system was ranked second out of three participating systems. It achieves good performance with 0.85 F-measure on the set of 25 test questions.
An Automatic Calorie Estimation System of Food Images on a Smartphone

In recent years, due to a rise in healthy thinking on eating, many people take care of their eating habits, and some people record daily diet regularly. To assist them, many mobile applications for recording everyday meals have been released so far. Some of them employ food image recognition which can estimate not only food names but also food calorie. However, most of such applications have some problems especially on their usability. Then, in this paper, we propose a novel single-image-based food calorie estimation system which runs on a smartphone as a standalone application without external recognition servers. The proposed system carries out food region segmentation, food region categorization, and calorie estimation automatically. By the experiments and the user study on the proposed system, the effectiveness of the proposed system was confirmed.