Miracle-dz/UniFAR-FTUs huggingface dataset:
A Scalability Analysis of Many Cores and On-Chip Mesh Networks on the TILE-Gx Platform

TILE-Gx processors that have emerged in recent years can be considered as the representative of prevailing many-core processors. The available TILE-Gx processors are featured with directory-based cache coherence protocol, two-dimensional mesh networks and up to 72 on-chip cores. In this paper, we study and analyze problems of performance scalability and network collision of many-core processors using the TILE-Gx36 processor. We find that most multi-threaded programs from the PARSEC benchmark suite, which aim at shared-memory on-chip processors, cannot scale well on Linux as the number of cores increases. Meanwhile, applications compiled with Pthreads get affected by the approach of task-to-core assignment. The results also show that current multi-threaded applications do not entirely utilize the hardware resources on TILE-Gx36 processor. Moreover, OS designers might need to pay attention to the memory allocation if memory stripping is not supported. Because huge memory accesses to only one memory controller can burden the two-dimensional mesh network. This observation appears if cores access the further memory controllers intensively as well.
Clinical and Prognostic Significance of Positive Hepatojugular Reflux on Discharge in Acute Heart Failure: Insights from the ESCAPE Trial

Background. There has been a decline in emphasis of the value of physical examination in heart failure (HF) with increased reliance on cardiac imaging. We aim to study the clinical and prognostic significance of positive hepatojugular reflux (HJR) on discharge in patients hospitalized with HF. Methods. Using the ESCAPE trial data, patients were compared according to the presence or absence of a positive HJR on discharge. The primary study endpoints were all-cause mortality and a composite endpoint of death, rehospitalization, and cardiac transplant during the first 6 months after discharge. Results. Among 392 patients (age: 56 years, 74% men), the HJR correlated well with clinical and objective hemodynamic markers of volume overload including right atrial pressure (RAP, P = 0.002), pulmonary capillary wedge pressure (PCWP, P = 0.006), and inferior vena cava size during inspiration (P = 0.005) and expiration (P = 0.003). The RAP had the highest AUC for predicting a positive HJR on admission (AUC: 0.655, P = 0.004) and discharge (AUC: 0.672, P = 0.001). Cox's proportional hazards analysis revealed that a positive HJR on discharge is an independent predictor of 6-month mortality (estimated hazard ratio: 1.689; 95% CI: 1.032–2.764; P = 0.037) after adjusting for age, baseline creatinine, baseline hematocrit, baseline NYHA class, chronic obstructive pulmonary disease, and the presence of tricuspid regurgitation. Conclusion. The HJR should be routinely checked in patients admitted with acute HF throughout hospitalization and especially on discharge as it serves as an important prognostic marker for postdischarge outcomes.
Unsupervised feature selection for text classification via word embedding

The key of big text documents data analysis is to classify those text documents. To classify those text documents, it is necessary to represent those text documents as vectors which is vector space model (VSM). A powerful vector space model should remain the classification information with dimensions as little as possible. To achieve that, it is important to select most effective features for text classification. Unlike the supervised selection method which utilizes the category information in the training data, we propose an unsupervised feature selection method. Our method requires no category information which makes our method has more application scenarios as the labeled data is expensive and inaccurate. Unlike other unsupervised methods, our method utilizes word embedding to find the words with similar semantic meaning. The word embedding maps the words into vectors and remains the semantic relationships between words. We select the most representative word on behalf of the words with similar semantic meaning because it is redundant to include all those words as features. We demonstrate on Reuters-21578 dataset, that our method outperforms other methods. Especially, our method has great advantage when select limited features.
Making Data Talk: Communicating Public Health Data to the Public, Policy Makers, and the Press

1. Introduction 2. Communication Fundamentals 3. Overcoming General Audience Tendencies and Biases to Enhance Lay Understanding of Data 4. Presenting Data 5. Putting it all Together: Communicating Data for Public Health Impact 6. Communicating Data in Acute Public Health Situations 7. Communicating Data for Policy or Program Advocacy 8. Conclusions and New Challenges
A demo of a PaaS for IoT applications provisioning in hybrid cloud/fog environment

This demo will show the key features of a Platform as-a-Service (PaaS) we have proposed in a research paper accepted for presentation at IEEE LANMAN 2016 conference. The proposed PaaS enables IoT applications provisioning in hybrid cloud/fog environments. Two goals are assigned to the demo. On the one hand, we will highlight how IoT applications can be provisioned in such environments. On the other hand, we will show concretely the advantages these hybrid environments have over traditional cloud environments. The provisioning in these hybrid environments enables latency reduction and processing performance enhancement. Indeed, in order to reduce latency, the applications can have some of its components running in a distant cloud and interacting with the other components running in the fog, closer to IoT devices.
Low-serum GTA-446 anti-inflammatory fatty acid levels as a new risk factor for colon cancer

Gastrointestinal tract acid‐446 (GTA‐446) is a long‐chain polyunsaturated fatty acid present in the serum. A reduction of GTA‐446 levels in colorectal cancer (CRC) patients has been reported previously. Our study compared GTA‐446 levels in subjects diagnosed with CRC at the time of colonoscopy to the general population. Serum samples and pathology data were collected from 4,923 representative subjects undergoing colonoscopy and from 964 subjects from the general population. Serum GTA‐446 levels were determined using a triple‐quadrupole tandem mass spectrometry method. A low‐serum GTA‐446 level was based on the bottom tenth percentile of subjects with low risk based on age (40–49 years old) in the general population. Eighty‐six percent of newly diagnosed CRC subjects (87% for stages 0–II and 85% for stages III–IV) showed low‐serum GTA‐446 levels. A significant increase in the CRC incidence rate with age was observed in subjects with low GTA‐446 levels (p = 0.019), but not in subjects with normal levels (p = 0.86). The relative risk of CRC given a low GTA‐446 level was the highest for subjects under age 50 (10.1, 95% confidence interval [C.I.] = 6.4–16.4 in the reference population, and 7.7, 95% C.I. = 4.4–14.1 in the colonoscopy population, both p < 0.0001), and declined with age thereafter. The CRC incidence rate in subjects undergoing colonoscopy with low GTA‐446 levels was over six times higher than for subjects with normal GTA‐446 levels and twice that of subjects with gastrointestinal symptoms. The results show that a low‐serum GTA‐446 level is a significant risk factor for CRC, and a sensitive predictor of early‐stage disease.
REDUCING DEPRECIATION ALLOWANCES TO FINANCE A LOWER CORPORATE TAX RATE

This paper considers the tradeoffs in using revenues from slowing depreciation deductions to lower the corporate tax rate. It estimates how much the rate could be lowered and the resulting effective tax rates on different types of assets. Two issues arise: the overall effect on marginal tax burdens and the challenges of using a provision that largely reflects timing effects to finance a steady state rate reduction.
Simulation and Digital Prototyping of Tangible User Interfaces

Prototyping is an important part in research and development of tangible user interfaces (TUIs). On the way from the idea to a working prototype, new hardware prototypes usually have to be crafted repeatedly in numerous iterations. This brings us to think about virtual prototypes that exhibit the same functionality as a real TUI, but reduce the amount of time and resources that have to be spent. Building upon existing open-source software – the middleware Robot Operating System (ROS) and the 3D simulator Gazebo – we have created a toolkit that can be used for developing and testing fully functional implementations of a tangible user interface as a virtual device. The entire interaction between the TUI and other hardware and software components is controlled by the middleware, while the human interaction with the TUI can be explored using the 3D simulator and 3D input/output technologies. We argue that by simulating parts of the hardware-software co-design process, the overall development effort can be reduced.
Gestural Origo and Loci-Transitions in Natural Discourse Segmentation

Human multimodal communicative behaviors form a tightly integrated whole. By matching up gestural features with a carefully time-tagged transcription of the speech, we can observe how gesture features and discourse unit transitions cohere. Pointing is a key gestural component. Although pointing appears to be simply a matter of aiming the hand at some target, it is in fact a complex process of several components including an origo (zero point of reference) and a deictic field. In our experiments where subjects make action plans around a terrain map, such origos become key organizational loci around which the discourse may be built. Our vision-based approach extracts ‘origo histograms’ from stereo video describing the locus of motion of a speaker’s dominant hand. A N N ‘fuzzy correlation’ of these histograms yields a correlation space in which similar origos are clustered. By locating the cluster transitions we can locate topical shifts in the discourse. We show results by comparing the transitions extracted from a sentential coding with a psycholinguistic semantic coding. We do the same with a uniform distributed time units and demonstrate the ability to recover discourse transitions.
Humanistic computing: "WearComp" as a new framework and application for intelligent signal processing

Humanistic computing is proposed as a new signal processing framework in which the processing apparatus is inextricably intertwined with the natural capabilities of our human body and mind. The emphasis of this paper is on personal imaging applications of humanistic computing, to take a first step toward an intelligent wearable camera system that can allow one to effortlessly capture our day-to-day experiences, help us remember and see better, provide us with personal safety through crime reduction, and facilitate new forms of communication through collective connected humanistic computing. The author's wearable signal processing hardware currently provides the computational power of a UNIX workstation concealed within ordinary-looking eyeglasses and clothing. Thus it may be worn continuously during all facets of ordinary day-to-day living, so that, through long-term adaptation, it begins to function as a true extension of the mind and body.
Computer vision-based clear path guidance for blind wheelchair users

We describe a system for guiding blind and visually impaired wheelchair users along a clear path that uses computer vision to sense the presence of obstacles or other terrain features and warn the user accordingly. Since multiple terrain features can be distributed anywhere on the ground, and their locations relative to a moving wheelchair are continually changing, it is challenging to communicate this wealth of spatial information in a way that is rapidly comprehensible to the user. The main contribution of our system is the development of a novel user interface that allows the user to interrogate the environment by sweeping a standard (unmodified) white cane back and forth: the system continuously tracks the cane location and sounds an alert if a terrain feature is detected in the direction the cane is pointing. Experiments are described demonstrating the feasibility of the approach.
Minimum Cost Matching in a Random Graph with Random Costs

Let $G_{n,p}$ be the standard Erdős-Renyi-Gilbert random graph and let $G_{n,n,p}$ be the random bipartite graph on $n+n$ vertices, where each $e\in [n]^2$ appears as an edge independently with probability $p$. For a graph $G=(V,E)$, suppose that each edge $e\in E$ is given an independent uniform exponential rate one cost. Let $C(G)$ denote the random variable equal to the length of the minimum cost perfect matching, assuming that $G$ contains at least one. We show that w.h. p. if $d=np\gg(\log n)^2$ then w.h. p. ${\bf E}[C(G_{n,n,p})] =(1+o(1))\frac{\p^2}{6p}$. This generalises the well-known result for the case $G=K_{n,n}$. We also show that w.h. p. ${\bf E}[C(G_{n,p})] =(1+o(1))\frac{\p^2}{12p}$ along with concentration results for both types of random graph.
GeneralizationGeneralizationGeneralizationGeneralization oooof Functional Dependencies in Total f Functional Dependencies in Total f Functional Dependencies in Total f Functional Dependencies in Total Neutrosophic Relation Neutrosophic Relation Neutrosophic Relation Neutrosophic Relation

Essentially the data and documents on the Web are heterogeneous; inconsistency is unavoidable in Web mining. Using the presentation and reasoning method of our method, it is easier to capture imperfect information on the Web which will provide more potentially valued-added information. We introduce the concept of total neutrosophic relation with a new type of Functional dependency for the searching techniques using the neutrosophic theory to meet the predicates posed in natural language in order to answer imprecise queries of the lay users. For this neutrosophic set needs to be specified from a technical point of view. To this effect we define the set theoretic operators on an instance of neutrosophic set. It may be claimed that the method could be well incorporated in the existing commercial query languages so that the users of any level of knowledge can get some results to his queries.
Maximization of negative correlations in time-course gene expression data for enhancing understanding of molecular pathways

Positive correlation can be diversely instantiated as shifting, scaling or geometric pattern, and it has been extensively explored for time-course gene expression data and pathway analysis. Recently, biological studies emerge a trend focusing on the notion of negative correlations such as opposite expression patterns, complementary patterns and self-negative regulation of transcription factors (TFs). These biological ideas and primitive observations motivate us to formulate and investigate the problem of maximizing negative correlations. The objective is to discover all maximal negative correlations of statistical and biological significance from time-course gene expression data for enhancing our understanding of molecular pathways. Given a gene expression matrix, a maximal negative correlation is defined as an activation–inhibition two-way expression pattern (AIE pattern). We propose a parameter-free algorithm to enumerate the complete set of AIE patterns from a data set. This algorithm can identify significant negative correlations that cannot be identified by the traditional clustering/biclustering methods. To demonstrate the biological usefulness of AIE patterns in the analysis of molecular pathways, we conducted deep case studies for AIE patterns identified from Yeast cell cycle data sets. In particular, in the analysis of the Lysine biosynthesis pathway, new regulation modules and pathway components were inferred according to a significant negative correlation which is likely caused by a co-regulation of the TFs at the higher layer of the biological network. We conjecture that maximal negative correlations between genes are actually a common characteristic in molecular pathways, which can provide insights into the cell stress response study, drug response evaluation, etc.
A Modified Speaker Clustering Method for Efficient Speaker Identification

In speaker identification system, along with the growth of the population size, scoring process can be extremely time consuming. In such a case, speaker clustering is generally used to alleviate the situation. K-means is the widely used clustering algorithms, however, its performance suffers from the so-called local optimum problem. To deal with the problem, a novel initialization approach was introduced in this paper, which performs the initialization to the intrinsic spreading patterns of speaker models. In essence, the proposal is of the same spirit to the well-known Canopy mechanism. However, it differs from the Canopy in the aspects of candidate selection and thresholds setting. It is showed, to the application purpose, the proposed approach could work effectively and generates more rational and stable clustering outcome.
ROUTING PROBLEM FOR PARALLEL ROUTE BASED MAX- MIN ANT SYSTEM

The proposed work presented a modified MAX-MIN Ant System (MMAS) algorithm to solve the routing problem, in which known demand are supplied from a store house with parallel routes for new local search. Routing Problem is an optimization problem and solved to nearly optimum by heuristics. The objective of routing issues is to use a fleet of vehicles with specified capacity to serve a number of users with dissimilar demands at minimum cost, without violating the capacity and route length constraints. Many meta-heuristic approaches like Simulated Annealing (SA), Tabu Search (TS) and An Improved Ant Colony System (IACS) algorithm are compared for the performance result analysis. The real life problems deal with imperfectly specified knowledge and some degree of imprecision, uncertainty or inconsistency is embedded in the problem specification. The well-founded theory of fuzzy sets is a special way to model the uncertainty. The rules in a fuzzy model contain a set of propositions, each of which restricts a fuzzy variable to a single fuzzy value by means of the predicate equivalency. That way, each rule covers a single fuzzy region of the fuzzy grid. The proposed system of this thesis extends this structure to provide more general fuzzy rules, covering the input space as much as possible. In order to do this, new predicates are considered and a Max-Min Ant System is proposed to learn such fuzzy rules. 1. Introduction The system has shown that Ant Colony System (ACS) is competitive with other nature-inspired algorithms on some relatively simple problems. Heuristic approaches to the routing can be classified as path constructive heuristics and path improvement heuristics. The most used and well-known path improvement heuristics are 2-optimization and 3-optimization, and Lin-Kernighan [3] in which respectively two, three, and a variable number of edges are exchanged. It has been experimentally shown that, in general, path improvement heuristics produce better quality results than path constructive heuristics. A general approach is to use path constructive heuristics to generate a solution and then to apply a path improvement heuristic to locally optimize it. It has been shown recently that it is more effective to alternate an improvement heuristic with updation of the last (or of the best) solution produced, rather than iteratively executing a path improvement heuristic starting from solutions generated randomly or by a constructive heuristic. An example of successful application of the above alternate strategy is the work by Freisleben and Merz …
A Modified Peer-to-peer Lookup Service for Internet Applications with an ‘ Extended Chord ’ Implementation

Implementation of this function may rely on distributed hash tables or multicast trees. However, there are concerns about the performance and dependability of these overlays in realistic environments [1]. Several studies have shown that current peer-to-peer environments have high churn rates: nodes join and leave the overlay continuously. Most of implementations relying on multicast trees generate more network traffic for each lookup in comparison to ones that use distributed hash tables (DHT).
Enhancing SOAP Performance by achieving Service Differentiation and Predictability

Simple Object Access Protocol (SOAP) based web services have become a widely used middleware for heterogeneous distributed systems over the years. Although the driving factor of its popularity has been the simple text based nature of eXtensible Markup Languge (XML) SOAP, the same reason has resulted web services being overlooked for certain classes of applications. To this date, binary based middleware such as Common Request Broker Architecture (CORBA) is still preferred for applications that require predictability in remote invocations. This document presents an approach for achieving predictability in SOAP based web services by means of service differentiation. This research proposes a model and an a priority based Real-time scheduling algorithm based on Real-time scheduling principles. The proposed algorithm schedules requests based on a deadline which would be associated with each request received by the server. Every request is subjected to an acceptance test which checks for schedulability of the request. The request is only accepted for execution if the associated deadline requirement could be met and only if the request does not compromise the deadlines of the tasks already accepted and active in the system. Upon not being able to satisfy these conditions, the request will be rejected. The accepted requests are prioritized based on their deadline requirements, giving priority to the earliest deadline. The proposed model and algorithm is empirically evaluated by implementing it on the widely used SOAP engine Apache Axis2. To ensure predictability a Real-time Operating System in the form of Sun Solaris and a development platform supporting Real-time development in the form of Sun Real-time Java is used in the implementation. The implementation is benchmarked against the unmodified version of Axis2 for various types of workloads and arrival rates, given different deadlines. The workloads are characterized by probability distributions and the number of tasks accepted, the number of deadlines achieved and their execution times are considered as metrics of performance. This document provides a brief overiew of principles behind real-time scheduling, and a detailed discussion on the proposed model and algorithm followed by the implementation details on Axis2. Finally challenges faced in implementation and testing it presented followed by the results of the performance comparison. The results confirm that the proposed technique can be used to benefit applications requiring predictability in execution.