OpenRaiser/Intern-Atlas huggingface dataset:
Comparing Dataset Characteristics that Favor the Apriori, Eclat or FP-Growth Frequent Itemset Mining Algorithms
Venue: arXiv cs.DB 2017
Year: 2017

Frequent itemset mining is a popular data mining technique. Apriori, Eclat, and FP-Growth are among the most common algorithms for frequent itemset mining. Considerable research has been performed to compare the relative performance between these three algorithms, by evaluating the scalability of each algorithm as the dataset size increases. While scalability as data size increases is important, previous papers have not examined the performance impact of similarly sized datasets that contain different itemset characteristics. This paper explores the effects that two dataset characteristics can have on the performance of these three frequent itemset algorithms. To perform this empirical analysis, a dataset generator is created to measure the effects of frequent item density and the maximum transaction size on performance. The generated datasets contain the same number of rows. This provides some insight into dataset characteristics that are conducive to each algorithm. The results of this paper's research demonstrate Eclat and FP-Growth both handle increases in maximum transaction size and frequent itemset density considerably better than the Apriori algorithm. This paper explores the effects that two dataset characteristics can have on the performance of these three frequent itemset algorithms. To perform this empirical analysis, a dataset generator is created to measure the effects of frequent item density and the maximum transaction size on performance. The generated datasets contain the same number of rows. This provides some insight into dataset characteristics that are conducive to each algorithm. The results of this paper's research demonstrate Eclat and FP-Growth both handle increases in maximum transaction size and frequent itemset density considerably better than the Apriori algorithm.
Software Engineering Practice using Multi-Criteria Decision in Health Care Organizations
Venue: arXiv cs.SE 2017
Year: 2017

A sound performance of health care organizations depends on vigorous financing system, skilled and well paying personnel, trustworthy information, well sustained health services and reliable technologies they used. The management and organization of health care systems and other health care settings can deeply have an effect on health result, excellence of care, and patient pleasure. Environmental assessment of an organization must considered political, technical and environmental aspects. This research is paying attention on dangerous and unresolved issues resulting from waste. The insufficient managing of hospital waste be capable of creating a danger to people, in the spreading of infectious diseases, and also for the environment. Issues are classified in different groups like dangerous chemical waste, cytotoxic with carcinogenic, mutagenic and teratogenic risk and radioactive. This study focuses on the analysis of above mentioned risks and decision will be made through Multi-Criteria Decision Analysis (MCDA). MCDA techniques give considerable enhancement in decision making. Survey is used for collecting information and results are evaluated by applying some statistical tool.
Untangling Planar Curves
Venue: arXiv cs.CG 2017
Year: 2017

Any generic closed curve in the plane can be transformed into a simple closed curve by a finite sequence of local transformations called homotopy moves. We prove that simplifying a planar closed curve with $n$ self-crossings requires $Θ(n^{3/2})$ homotopy moves in the worst case. Our algorithm improves the best previous upper bound $O(n^2)$, which is already implicit in the classical work of Steinitz; the matching lower bound follows from the construction of closed curves with large defect, a topological invariant of generic closed curves introduced by Aicardi and Arnold. Our lower bound also implies that $Ω(n^{3/2})$ facial electrical transformations are required to reduce any plane graph with treewidth $Ω(\sqrt{n})$ to a single vertex, matching known upper bounds for rectangular and cylindrical grid graphs. More generally, we prove that transforming one immersion of $k$ circles with at most $n$ self-crossings into another requires $Θ(n^{3/2} + nk + k^2)$ homotopy moves in the worst case. Finally, we prove that transforming one noncontractible closed curve to another on any orientable surface requires $Ω(n^2)$ homotopy moves in the worst case; this lower bound is tight if the curve is homotopic to a simple closed curve.
Asymptotically Efficient Identification of Known-Sensor Hidden Markov Models
Venue: arXiv cs.SY 2017
Year: 2017

We consider estimating the transition probability matrix of a finite-state finite-observation alphabet hidden Markov model with known observation probabilities. The main contribution is a two-step algorithm; a method of moments estimator (formulated as a convex optimization problem) followed by a single iteration of a Newton-Raphson maximum likelihood estimator. The two-fold contribution of this letter is, firstly, to theoretically show that the proposed estimator is consistent and asymptotically efficient, and secondly, to numerically show that the method is computationally less demanding than conventional methods - in particular for large data sets.
SMPOST: Parts of Speech Tagger for Code-Mixed Indic Social Media Text
Venue: arXiv cs.CL 2017
Year: 2017

Use of social media has grown dramatically during the last few years. Users follow informal languages in communicating through social media. The language of communication is often mixed in nature, where people transcribe their regional language with English and this technique is found to be extremely popular. Natural language processing (NLP) aims to infer the information from these text where Part-of-Speech (PoS) tagging plays an important role in getting the prosody of the written text. For the task of PoS tagging on Code-Mixed Indian Social Media Text, we develop a supervised system based on Conditional Random Field classifier. In order to tackle the problem effectively, we have focused on extracting rich linguistic features. We participate in three different language pairs, ie. English-Hindi, English-Bengali and English-Telugu on three different social media platforms, Twitter, Facebook & WhatsApp. The proposed system is able to successfully assign coarse as well as fine-grained PoS tag labels for a given a code-mixed sentence. Experiments show that our system is quite generic that shows encouraging performance levels on all the three language pairs in all the domains.
A level training set with both a computer-based control and a compact controller
Venue: arXiv cs.SY 2017
Year: 2017

In engineering education, the combination with theoretical education and practical education is an essential problem.
The non-cooperative tile assembly model is not intrinsically universal or capable of bounded Turing machine simulation
Venue: arXiv cs.CC 2017
Year: 2017

The field of algorithmic self-assembly is concerned with the computational and expressive power of nanoscale self-assembling molecular systems. In the well-studied cooperative, or temperature 2, abstract tile assembly model it is known that there is a tile set to simulate any Turing machine and an intrinsically universal tile set that simulates the shapes and dynamics of any instance of the model, up to spatial rescaling. It has been an open question as to whether the seemingly simpler noncooperative, or temperature 1, model is capable of such behaviour. Here we show that this is not the case, by showing that there is no tile set in the noncooperative model that is intrinsically universal, nor one capable of time-bounded Turing machine simulation within a bounded region of the plane. Although the noncooperative model intuitively seems to lack the complexity and power of the cooperative model it was not obvious how to prove this. One reason is that there have been few tools to analyse the structure of complicated paths in the plane. This paper provides a number of such tools. A second reason is that almost every obvious and small generalisation to the model (e.g. allowing error, 3D, non-square tiles, signals/wires on tiles, tiles that repel each other, parallel synchronous growth) endows it with great computational, and sometimes simulation, power. Our main results show that all of these generalisations provably increase computational and/or simulation power. Our results hold for both deterministic and nondeterministic noncooperative systems. Our first main result stands in stark contrast with the fact that for both the cooperative tile assembly model, and for 3D noncooperative tile assembly, there are respective intrinsically universal tilesets. Our second main result gives a new technique (reduction to simulation) for proving negative results about computation in tile assembly.
Agreement Functions for Distributed Computing Models
Venue: arXiv cs.DC 2017
Year: 2017

The paper proposes a surprisingly simple characterization of a large class of models of distributed computing, via an agreement function: for each set of processes, the function determines the best level of set consensus these processes can reach. We show that the task computability of a large class of fair adversaries that includes, in particular superset-closed and symmetric one, is precisely captured by agreement functions.
Segmentation of optic disc, fovea and retinal vasculature using a single convolutional neural network
Venue: arXiv cs.CV 2017
Year: 2017

We have developed and trained a convolutional neural network to automatically and simultaneously segment optic disc, fovea and blood vessels. Fundus images were normalised before segmentation was performed to enforce consistency in background lighting and contrast. For every effective point in the fundus image, our algorithm extracted three channels of input from the neighbourhood of the point and forward the response across the 7 layer network. In average, our segmentation achieved an accuracy of 92.68 percent on the testing set from Drive database.
Complexity results for $k$-domination and $α$-domination problems and their variants
Venue: arXiv cs.CC 2017
Year: 2017

Let $G=(V, E)$ be a simple and undirected graph. For some integer $k\geq 1$, a set $D\subseteq V$ is said to be a k-dominating set in $G$ if every vertex $v$ of $G$ outside $D$ has at least $k$ neighbors in $D$. Furthermore, for some real number $α$ with $0<α\leq1$, a set $D\subseteq V$ is called an $α$-dominating set in $G$ if every vertex $v$ of $G$ outside $D$ has at least $α\times d_v$ neighbors in $D$, where $d_v$ is the degree of $v$ in $G$. The cardinality of a minimum $k$-dominating set and a minimum $α$-dominating set in $G$ is said to be the $k$-domination number and the $α$-domination number of $G$, respectively. In this paper, we present some approximability and inapproximability results on the problem of finding $k$-domination number and $α$-domination number of some classes of graphs. Moreover, we introduce a generalization of $α$-dominating set which we call an $f$-dominating set. Given a function $f:\mathbb{N}\rightarrow \mathbb{R}$, where $\mathbb{N}=\{1, 2, 3, \ldots\}$, a set $D\subseteq V$ is said to be an $f$-dominating set in $G$ if every vertex $v$ of $G$ outside $D$ has at least $f(d_v)$ neighbors in $D$. We prove NP-hardness of the problem of finding a minimum $f$-dominating set in $G$, for a large family of functions $f$.
CrowdFusion: A Crowdsourced Approach on Data Fusion Refinement
Venue: arXiv cs.DB 2017
Year: 2017

Data fusion has played an important role in data mining because high-quality data is required in a lot of applications. As on-line data may be out-of-date and errors in the data may propagate with copying and referring between sources, it is hard to achieve satisfying results with merely applying existing data fusion methods to fuse Web data. In this paper, we make use of the crowd to achieve high-quality data fusion result. We design a framework selecting a set of tasks to ask crowds in order to improve the confidence of data. Since data are correlated and crowds may provide incorrect answers, how to select a proper set of tasks to ask the crowd is a very challenging problem. In this paper, we design an approximation solution to address this challenge since we prove that the problem is at NP-hard. To further improve the efficiency, we design a pruning strategy and a preprocessing method, which effectively improve the performance of the proposed approximation solution. Furthermore, we find that under certain scenarios, we are not interested in all the facts, but only a specific set of facts. Thus, for these specific scenarios, we also develop another approximation solution which is much faster than the general approximation solution. We verify the solutions with extensive experiments on a real crowdsourcing platform.
Quantitative Characterization of Components of Computer Assisted Interventions
Venue: arXiv cs.OH 2017
Year: 2017

Purpose: We propose a mathematical framework for quantitative analysis weighting the impact of heterogeneous components of a surgery. While multi-level approaches, surgical process modeling and other workflow analysis methods exist, this is to our knowledge the first quantitative approach. Methods: Inspired by the group decision making problem from the field of operational research, we define event impact factors, which combine independent and very diverse low-level functions. This allows us to rate surgical events by their importance. Results: We conducted surveys with 4 surgeons to determine the importance of roles, phases and their combinations within a laparoscopic cholecystectomy. Applying this data on a recorded surgery, we showed that it is possible to define a quantitative measure for deciding on acception or rejection of calls to different roles and at different phases of surgery. Conclusions: This methodology allows us to use components such as expertise and role of the surgical staff and other aspects of a given surgery in order to quantitatively analyze and evaluate events, actions, user interfaces or procedures.
Joint Offloading and Computing Optimization in Wireless Powered Mobile-Edge Computing Systems
Venue: arXiv cs.IT 2017
Year: 2017

Mobile-edge computing (MEC) and wireless power transfer (WPT) have been recognized as promising techniques in the Internet of Things (IoT) era to provide massive low-power wireless devices with enhanced computation capability and sustainable energy supply. In this paper, we propose a unified MEC-WPT design by considering a wireless powered multiuser MEC system, where a multi-antenna access point (AP) (integrated with an MEC server) broadcasts wireless power to charge multiple users and each user node relies on the harvested energy to execute computation tasks. With MEC, these users can execute their respective tasks locally by themselves or offload all or part of them to the AP based on a time division multiple access (TDMA) protocol. Building on the proposed model, we develop an innovative framework to improve the MEC performance, by jointly optimizing the energy transmit beamformer at the AP, the central processing unit (CPU) frequencies and the numbers of offloaded bits at the users, as well as the time allocation among users. Under this framework, we address a practical scenario where latency-limited computation is required. In this case, we develop an optimal resource allocation scheme that minimizes the AP's total energy consumption subject to the users' individual computation latency constraints. Leveraging the state-of-the-art optimization techniques, we derive the optimal solution in a semi-closed form. Numerical results demonstrate the merits of the proposed design over alternative benchmark schemes.
Adaptive Multiscale Homogenization of the Lattice Discrete Particle Model for the Analysis of Damage and Fracture in Concrete
Venue: arXiv cs.CE 2017
Year: 2017

This paper presents a new adaptive multiscale homogenization scheme for the simulation of damage and fracture in concrete structures. A two-scale homogenization method, coupling meso-scale discrete particle models to macro- scale finite element models, is formulated into an adaptive framework. A continuum multiaxial failure criterion for concrete is calibrated on the basis of fine-scale simulations, and it serves as the adaptive criterion in the multiscale framework. Thus, in this approach, simulations start without assigning any material Representative Volume Element (RVE) to the macro-scale finite elements. The finite elements that meet the adaptive criterion and must be entered into the multiscale homogenization framework are detected on the fly. This leads to a substantial reduction of the computational cost especially for loading conditions leading to damage localization in which only a small portion of the FE mesh is enriched with the homogenized RVE. Several numerical simulations are carried out to investigate the capability of the developed adaptive homogenization method. In addition, a detailed study on the computational cost is performed.
Multilingual and Cross-lingual Timeline Extraction
Venue: arXiv cs.CL 2017
Year: 2017

In this paper we present an approach to extract ordered timelines of events, their participants, locations and times from a set of multilingual and cross-lingual data sources. Based on the assumption that event-related information can be recovered from different documents written in different languages, we extend the Cross-document Event Ordering task presented at SemEval 2015 by specifying two new tasks for, respectively, Multilingual and Cross-lingual Timeline Extraction. We then develop three deterministic algorithms for timeline extraction based on two main ideas. First, we address implicit temporal relations at document level since explicit time-anchors are too scarce to build a wide coverage timeline extraction system. Second, we leverage several multilingual resources to obtain a single, inter-operable, semantic representation of events across documents and across languages. The result is a highly competitive system that strongly outperforms the current state-of-the-art. Nonetheless, further analysis of the results reveals that linking the event mentions with their target entities and time-anchors remains a difficult challenge. The systems, resources and scorers are freely available to facilitate its use and guarantee the reproducibility of results.
Intel MPX Explained: An Empirical Study of Intel MPX and Software-based Bounds Checking Approaches
Venue: arXiv cs.CR 2017
Year: 2017

Memory-safety violations are a prevalent cause of both reliability and security vulnerabilities in systems software written in unsafe languages like C/C++. Unfortunately, all the existing software-based solutions to this problem exhibit high performance overheads preventing them from wide adoption in production runs. To address this issue, Intel recently released a new ISA extension - Memory Protection Extensions (Intel MPX), a hardware-assisted full-stack solution to protect against memory safety violations. In this work, we perform an exhaustive study of the Intel MPX architecture to understand its advantages and caveats. We base our study along three dimensions: (a) performance overheads, (b) security guarantees, and (c) usability issues. To put our results in perspective, we compare Intel MPX with three prominent software-based approaches: (1) trip-wire - AddressSanitizer, (2) object-based - SAFECode, and (3) pointer-based - SoftBound. Our main conclusion is that Intel MPX is a promising technique that is not yet practical for widespread adoption. Intel MPX's performance overheads are still high (roughly 50% on average), and the supporting infrastructure has bugs which may cause compilation or runtime errors. Moreover, we showcase the design limitations of Intel MPX: it cannot detect temporal errors, may have false positives and false negatives in multithreaded code, and its restrictions on memory layout require substantial code changes for some programs.
Topic Modeling the Hàn diăn Ancient Classics
Venue: arXiv cs.CL 2017
Year: 2017

Ancient Chinese texts present an area of enormous challenge and opportunity for humanities scholars interested in exploiting computational methods to assist in the development of new insights and interpretations of culturally significant materials. In this paper we describe a collaborative effort between Indiana University and Xi'an Jiaotong University to support exploration and interpretation of a digital corpus of over 18,000 ancient Chinese documents, which we refer to as the "Handian" ancient classics corpus (Hàn diăn gŭ jí, i.e, the "Han canon" or "Chinese classics"). It contains classics of ancient Chinese philosophy, documents of historical and biographical significance, and literary works. We begin by describing the Digital Humanities context of this joint project, and the advances in humanities computing that made this project feasible. We describe the corpus and introduce our application of probabilistic topic modeling to this corpus, with attention to the particular challenges posed by modeling ancient Chinese documents. We give a specific example of how the software we have developed can be used to aid discovery and interpretation of themes in the corpus. We outline more advanced forms of computer-aided interpretation that are also made possible by the programming interface provided by our system, and the general implications of these methods for understanding the nature of meaning in these texts.
String stability and a delay-based spacing policy for vehicle platoons subject to disturbances
Venue: arXiv cs.SY 2017
Year: 2017

A novel delay-based spacing policy for the control of vehicle platoons is introduced together with a notion of disturbance string stability. The delay-based spacing policy specifies the desired inter-vehicular distance between vehicles and guarantees that all vehicles track the same spatially varying reference velocity profile, as is for example required for heavy-duty vehicles driving over hilly terrain. Disturbance string stability is a notion of string stability of vehicle platoons subject to external disturbances on all vehicles that guarantees that perturbations do not grow unbounded as they propagate through the platoon. Specifically, a control design approach in the spatial domain is presented that achieves tracking of the desired spacing policy and guarantees disturbance string stability with respect to a spatially varying reference velocity. The results are illustrated by means of simulations.
On repetition thresholds of caterpillars and trees of bounded degree
Venue: arXiv cs.DM 2017
Year: 2017

The repetition threshold is the smallest real number $α$ such that there exists an infinite word over a $k$-letter alphabet that avoids repetition of exponent strictly greater than $α$. This notion can be generalized to graph classes. In this paper, we completely determine the repetition thresholds for caterpillars and caterpillars of maximum degree $3$. Additionally, we present bounds for the repetition thresholds of trees with bounded maximum degrees.
Sense Amplifier Comparator with Offset Correction for Decision Feedback Equalization based Receivers
Venue: arXiv cs.AR 2017
Year: 2017

A decision feedback circuit with integrated offset compensation is presented in this paper. The circuit is built around the sense amplifier comparator. The feedback loop is closed around the first stage of the comparator resulting in minimum loop latency. The feedback loop is implemented using a switched capacitor network that picks from one of pre-computed voltages to be fed back. The comparator's offset that is to be compensated for, is added in the same path. Hence, an extra offset correction input is not required. The circuit is used as a receiver for a 10 mm low swing interconnect implemented in UMC 130 nm CMOS technology. The circuit is tested at a frequency of 1 GHz and it consumes 145 $μ$A from a 1.2V supply at this frequency.