Miracle-dz/UniFAR-FTUs huggingface dataset:
Cones of Matrices and Successive Convex Relaxations of Nonconvex Sets

Let F be a compact subset of the n-dimensional Euclidean space Rn represented by (finitely or infinitely many) quadratic inequalities. We propose two methods, one based on successive semidefinite programming (SDP) relaxations and the other on successive linear programming (LP) relaxations. Each of our methods generates a sequence of compact convex subsets Ck (k = 1, 2, . . .) of Rn such that (a) the convex hull of $F \subseteq C_{k+1} \subseteq C_k$ (monotonicity), (b) $\cap_{k=1}^{\infty} C_k = \text{the convex hull of F (asymptotic convergence). Our methods are extensions of the corresponding Lovasz--Schrijver lift-and-project procedures with the use of SDP or LP relaxation applied to general quadratic optimization problems (QOPs) with infinitely many quadratic inequality constraints. Utilizing descriptions of sets based on cones of matrices and their duals, we establish the exact equivalence of the SDP relaxation and the semi-infinite convex QOP relaxation proposed originally by Fujie and Kojima. Using this equivalence, we investigate some fundamental features of the two methods including (a) and (b) above.
Study on assessment method for computer network security based on rough set

As the traditional network security assessment methods have subjective factors when the wights a assessment indexes are identified, it is difficult to make accurate and objective assessment. However, the Rough set theory has the advantages of not needing apriori knowledge when dealing with uncertain problems. Therefore, the application of the Rough set theory in network security assessment is quite necessary. This paper is identifies the principle of assessment indexes system of network security and establishes the indexes system of network security assessment, establishes security assessment model and common steps of network security assessment which are both based on the Rough set theory, and finally analyzes and validates this model by an example. The network security assessment based on the Rough set theory effectively overcomes the subjectivity of determining the weights of indexes by traditional methods, gives more objective results, and enhances the veracity and validity of network security assessment.
Delirium during Weaning from Mechanical Ventilation

Background. We compare the incidence of delirium before and after extubation and identify the risk factors and possible predictors for the occurrence of delirium in this group of patients. Methods. Patients weaned from mechanical ventilation (MV) and extubated were included. The assessment of delirium was conducted using the confusion assessment method for the ICU and completed twice per day until discharge from the intensive care unit. Results. Sixty-four patients were included in the study, 53.1% of whom presented with delirium. The risk factors of delirium were age (P = 0.01), SOFA score (P = 0.03), APACHE score (P = 0.01), and a neurological cause of admission (P = 0.01). The majority of the patients began with delirium before or on the day of extubation. Hypoactive delirium was the most common form. Conclusion. Acute (traumatic or medical) neurological injuries were important risk factors in the development of delirium. During the weaning process, delirium developed predominantly before or on the same day of extubation and was generally hypoactive (more difficult to detect). Therefore, while planning early prevention strategies, attention must be focused on neurological patients who are receiving MV and possibly even on patients who are still under sedation.
Estimating Fish Populations by Removal Methods with Minnow Traps in Southeast Alaska Streams

Abstract Passive capture methods, such as minnow traps, are commonly used to capture fish for mark–recapture population estimates; however, they have not been used for removal methods. Minnow traps set for 90-min periods during three or four sequential capture occasions during the summer of 1996 were used to capture coho salmon Oncorhynchus kisutch fry and parr, Dolly Varden Salvelinus malma, cutthroat trout O. clarki, and juvenile steelhead O. mykiss to estimate population size with the Zippin or generalized removal method. More than 45% of the total catch was obtained during the first capture occasion, and in most cases, the catch during the fourth occasion was less than 15% of the total catch. In most pools, the probability of capture was greater than 0.4 but was lower for coho salmon fry than for coho salmon parr and other species. Mean population estimates for coho salmon parr made with concurrent mark–recapture and removal methods differed significantly in small streams. Estimates from mark–recaptur.
Multi-user Searching of Top-k Objects with Data on Remote Servers

This paper focuses on searching the best k objects with more attributes according to user preferences in the Web environment. Attributes of an object type are distributed on servers in a disjunctive way, i.e. values of one attribute are stored in only one remote server on the Internet. In our work, every user can express his/her preferences for each attribute by a fuzzy function and mutual relations between the attributes by an aggregation function. We use client/server architecture and communication via Web Services. We deal with the usage of Fagin’s NRA algorithm, which can find the best k objects without accessing all the objects. Because of support of sorting objects according to a fuzzy function, an indexing method based on B+-tree is used in each remote server. Moreover, each server is stateless, i.e. independent from any previous request. Our solution is based on cache memory, which loads objects from remote servers in batches and thus reduces the amount of network communication. In this paper we present a system TOPKNET, which can efficiently find the best k objects for various users with data on remote servers.
Ieee 6th Workshop on Signal Processing Advances in Wireless Communications Optimal Waveform Design for M M O Relaying

Non-regenerative MIMO relaying between a source and a destination is studied in this paper. Optimal weighting matrix operating on baseband signals (waveforms) at the relay is found that maximizes the capacity between the source and the destination. Relay channels with or without direct link between the source and the destination are considered. The optimal refay exploits the knowledge of the channel matrix between the source and the relay and the channel matrix between the relay and the destination. T h e optimal weighting matrix can be considered as a matched filter along the singular vectors of the channel matrices. Such a non-regenerative relay can be deployed in mobile ad hoc networks as well as in cellularnetworks. MlMO relaying is useful for a variety of applications. In a cellular environment, a MIMO relay can be depIoyed in areas where there are strong shadowing effects, such as inside buildings and tunnels. For mobile ad hoc networks, MIMO relaying is essential not only to overcome shadowing due to obstacles but also to reduce transmission power and RF interference. Capacity analysis of a generic MIMO relay is recently reported in [I, 21. In this paper, we study non-regenerative MIMO relaying where the information data are not regenerated at the relay except that the baseband synibols are reproduced, weighted and then retrans-mitted. As for any relay, two orthogonal channels are required: one for the received signal and the other €or the retransmitted signal. The two channels required can be implemented through either time-division or frequency-division. But the latter seems much easier to do in practice as no additional synchronization requirement between the source and the destination is necessaq A non-regenerative relay may be easier to install (especiaffy for two-hop relaying) than a regenerative relay as the former needs no high level codes. We note here however that for many-hops relaying, non-regenerative relays may not be as networking-friendly as re-generative relays. The previously reported schemes of non-regenerative MIMO relays such as in E 9 are not optimal, and in fact they are ad hoc.
Voronoi diagrams of lines in 3-space under polyhedral convex distance functions

The combinatorial complexity of the Voronoi diagram ofnlines in three dimensions under a convex distance function induced by a polytope with a constant number of edges is shown to beO(n2? (n)logn), where ? (n) is a slowly growing inverse of the Ackermann function. There are arrangements ofnlines where this complexity can be as large as ? (n2? (n)).
Improving Security and Integrity of Data Storage in Cloud Computing By Using Homomorphic Authentication technique

-as we seen that, today’s generation of IT has widely use the cloud computing services, that means in future cloud computing will important part of IT enterprise. In which the application software and databases are stored at centralized large data storage. Now in cloud data center, management of data & services may not be fully trustworthy. This new phenomenon brings many security challenges. This paper focus on the integrity and security of data storage in cloud computing. The data integrity verification is done by introducing third party auditor (TPA) who has privileges to check the integrity of dynamic data in cloud on behalf of cloud client. Which is significant in economies achievement for cloud computing because TPA can eliminate the direct involvement of cloud client for auditing the data to be stored? Cloud client can get notification from TPA when the data integrity is lost. These systems also support data dynamics via the data operation such as modification, insertion, deletion. There is many work has been done but there is lacks the support of either public auditability or dynamic data operations. This paper achieves both public auditability and data dynamics. This work shows that proposed systems are highly efficient and secure.
Evolutionary product line modelling

A traditional product line approach struggles with complexity and weak evolution support. We propose an evolutionary software product line modelling approach based on controllable inheritance of product line members specifications. Instead of a predefined product line architecture we use hierarchies of implemented product specifications accompanied by correctness control of product model transformations. An industrial case study from the embedded systems domain demonstrating a modelling technique is provided. The approach is supported by an appropriate tool prototype.
IITP: Supervised Machine Learning for Aspect based Sentiment Analysis

The shared task on Aspect based Sentiment Analysis primarily focuses on mining relevant information from the thousands of online reviews available for a popular product or service. In this paper we report our works on aspect term extraction and sentiment classification with respect to our participation in the SemEval-2014 shared task. The aspect term extraction method is based on supervised learning algorithm, where we use different classifiers, and finally combine their outputs using a majority voting technique. For sentiment classification we use Random Forest classifier. Our system for aspect term extraction shows the F-scores of 72.13% and 62.84% for the restaurants and laptops reviews, respectively. Due to some technical problems our submission on sentiment classification was not evaluated. However we evaluate the submitted system with the same evaluation metrics, and it shows the accuracies of 67.37% and 67.07% for the restaurants and laptops reviews, respectively.
Tuple MapReduce: Beyond Classic MapReduce

This paper proposes Tuple Map Reduce, a new foundational model extending Map Reduce with the notion of tuples. Tuple Map Reduce allows to bridge the gap between the low-level constructs provided by Map Reduce and higher-level needs required by programmers, such as compound records, sorting or joins. This paper presents as well Pangool, an open-source framework implementing Tuple Map Reduce. Pangool eases the design and implementation of applications based on Map Reduce and increases their flexibility, still maintaining Hadoop's performance.
An Improved Helferich Method for the α/β-Stereoselective Synthesis of 4-Methylumbelliferyl Glycosides for the Detection of Microorganisms

An improved Helferich method is presented. It involves the glycosylation of 4-methyl-umbelliferone with glycosyl acetates in the presence of boron trifluoride etherate combined with triethylamine, pyridine, or 4-dimethylaminopyridine under mild conditions, followed by deprotection to give fluorogenic 4-methylumbelliferyl glycoside substrates. Due to the use of base, the glycosylation reaction proceeds more easily, is uncommonly α- or β-stereoselective, and affords the corresponding products in moderate to excellent yields (51%–94%) under appropriate conditions.
Graded and Hessenberg Form together for Symmetric Matrices in QR Algorithm

The significance of the present research can be attributed to the systematic study of QR algorithm to solve eigenvalues. The main objective is to study how to develop a new method or strategy to find eigenvalues which improve the convergence of QR algorithm. It is observed that in general the QR algorithm succeeds when the matrix is graded downward with hessenberg form. Our future goal is to analyze theoretical proof for the same and find the well balanced input matrix for QR algorithm. This paper will helpful to all new students who want to work on Matrix decomposition problem.
Computational approach to solvability of refinement equations

The solvability and Fredholm properties of refinement equations in spaces of square-integrable functions are studied. Necessary and jointly necessary and sufficient conditions for the solvability of homogeneous and non-homogeneous refinement equations are established. It is shown that in the space L 2 (R) the kernel space of any homogeneous equation with a non-trivial solution is infinite dimensional. Moreover, the solvability problem is reduced to the study of singular values of certain matrix sequences. These sequences arise from Galerkin approximations of auxiliary linear operators. The corresponding constructions use only the coefficients of refinement equations that generate multiresolution analysis, and the coefficients of the refinement equation studied. For the equations with polynomial symbols the most complete results are obtained if the corresponding operator is considered on an appropriate subspace of the space L 2 (ℝ).
Identifying Structures with Informative Dimensions in Streams

Discovering structures in streaming data is an important data mining task and has motivated design of several well known algorithms. However, in some applications, a higher level of analysis is desirable to reveal the set of dimensions which contribute heavily to the structures. In this paper, we propose an algorithm ISID (Identifying Structures with Informative Dimensions), which operates in the streaming environment and delivers clusteres along with dimensions that contribute significantly to these clusters. The algorithm uses a three stage approach and utilizes entropy in an innovative way to achieve the goal in four different ways, depending on the desired guarantees on structural richness or minimal dimension set for a cluster.The experimental results on synthetic and real data sets demonstrate the efficiency and effectiveness of the proposed algorithm.
Identifying UMLS concepts from ECG Impressions using Knowledge Map

Electrocardiogram (ECG) impressions represent a wealth of medical information for potential decision support and drug-effect discovery. Much of this information is inaccessible to automated methods in the free-text portion of the ECG report. We studied the application of the KnowledgeMap concept identifier (KMCI) to map Unified Medical Language System (UMLS) concepts from ECG impressions. ECGs were processed by KMCI and the results scored for accuracy by multiple raters. Reviewers also recorded unidentified concepts through the scoring interface. Overall, KMCI correctly identified 1059 out of 1171 concepts for a recall of 0.90. Precision, indicating the proportion of ECG concepts correctly identified, was 0.94. KMCI was particularly effective at identifying ECG rhythms (330/333), perfusion changes (65/66), and noncardiac medical concepts (11/11). In conclusion, KMCI is an effective method for mapping ECG impressions to UMLS concepts.
A MODIFIED DIRECT-SEQUENCE SPREAD SPECTRUM MODULATION SCHEME FOR BURST TRANSMISSIONS

The Direct-Sequence Spread Spectrum modulation (DSSS) is a very attractive modulation technique for military communication systems, mainly due to its resistance to interference and low probability of detection. However, the synchronisation to the spreading code phase in the receiver takes time, which makes this technique less interesting for sending very short messages. In this paper a novel direct-sequence modulation scheme for spread spectrum communication systems is presented, defined as the Delay-and-AddDirect-Sequence (DADS) modulation. The DADS spread spectrum modulation is easy to implement and there is no more need for code alignment at the receiver side, which makes it very suitable for short burst transmissions. The performance of the DADS technique is studied in Additive White Gaussian Noise (AWGN) and flat Rayleigh channels, as well as the influence of some important parameters in the modulation scheme.
Learning in a Misspecied Multivariate Self-Referential Linear Stochastic Model

This paper introduces a general method to study stability (under learning) of equilibria resulting from agents with misspeci ed perceptions of the law of motion of the economy. This is done by transforming the actual and perceived laws of motion into the form of seemingly unrelated regressions and then linearly projecting the actual law of motion into the same class as the perceived law of motion. I study the New Keynesian IS-LM model with inertia under all possible classes of restricted perceptions. It turns out that the results found in Bullard and Mitra (2002, 2003) are robust under misspeci ed expectations. Key Words: Adaptive Learning; Expectational Stability; Monetary Policy Rules; Restricted Perceptions Equilibria; Seemingly Unrelated Regression JEL Classi cation: E4; E5 Address correspondence to: Faculty of Economics, University of Cambridge, Cambridge CB3 9DD, UK. Phone: +44 1223 335473. E-mail: eg295@econ.cam. ac.uk. I would like to thank George Evans, Seppo Honkapohja, Ben McCallum, and participants of the Bank of Finland Research Department seminars for useful comments and suggestions. All errors are mine.
Professionalism Mini-Evaluation Exercise in Finland: A preliminary investigation introducing the Finnish version of the P-MEX instrument

Introduction Teaching medical professionalism is increasingly acknowledged as an important aspect of medical education. The Professionalism Mini-Evaluation Exercise (P-MEX) is an assessment tool for evaluating medical professionalism, but no studies using it as a self-assessment instrument have been reported. This paper reports on a preliminary investigation of the Finnish version of the P-MEX instrument as an assessment and self-assessment measure. Methods The sample in the present cross-sectional study comprised all 23 medical students and recent graduates (15 females and 8 males) participating in a summer school of psychiatry program in 2014. The two-month program combines clinical work with multifaceted teaching and intensive tutoring. At the end of the program, the participants’ medical professionalism was assessed by the tutors and other members of the work community as well as the students themselves using the Finnish version of the P-MEX instrument. The P-MEX scores were compared, using the Friedman test. Results The mean values and SD for the P-MEX assessments were as follows: tutor assessment 3.26±0.21, work community assessment 3.32±0.26 and self-assessment 3.01±0.07. No significant gender differences were observed. The tutor and work community assessments were significantly correlated (r=0.573, p=0.040), but the self-assessment scores did not correlate with either of the other assessments. Overall, the students evaluated their skills significantly poorer in comparison to the other assessments. Conclusion Although the small sample size limits the generalization of these preliminary results, the Finnish version of the P-MEX instrument appears to be a feasible measure of medical professionalism. The instrument can also be used as a self-assessment instrument, but subjective evaluations should be complemented with external assessments or feedback in order to take individual and cultural aspects into account.
Influence of personality on satisfaction with mobile phone services

We propose a conceptual model that explains the relationship between the users' personality profile and their satisfaction with basic mobile phone services (calls, messages, and simple GPRS/3G services). The model captures direct and indirect effects on satisfaction by means of two variables: actual mobile phone usage and perceived usability of the related services. We empirically validate the model with data gathered from 603 customers of a telecommunication operator, and find that: (1) extroversion, conscientiousness, and intellect have a significant impact on customer satisfaction—positively for the first two traits and negatively for the latter; (2) extroversion positively influences mobile phone usage; and (3) extroversion and conscientiousness positively influence the users' perceived usability of mobile services. Interestingly, usability has the strongest positive impact on satisfaction, whereas mobile phone usage has a negative impact on satisfaction. We discuss key findings of this model and propose several implications for the design of mobile phone services.
Fun and games with mobile phones : SMS messaging in microeconomics experiments

This paper details the application of SMS messaging to facilitate ‘classroom experiments’ in microeconomics classes. Laboratory style experiments and simulations have long been used for teaching and learning in many disciplines, however classroom experiments in economics have a feature that distinguishes them from their counterparts in many other disciplines. This is that students participate in dual roles as both experimental subjects and as researchers in analysing the outcomes of an experiment. Good experimental designs should thus support student learning with feedback at both levels. In the past, this was done most effectively by conducting experiments in fully networked laboratories. However in view of the cost of developing fully computerised experiments, paper based designs have remained prevalent, even though these are cumbersome and time consuming to conduct. By using SMS as a response medium, the limitations of paper based experiments are overcome without incurring the costs of full computerisation. Individual feedback is delivered by return messaging, while aggregate results are summarised in automated charts and tables. This makes it possible to conduct classroom experiments in large classes in lecture halls.
Calibration Error Bound Estimation in Performance Modeling

Performance modeling of embedded systems is used to explore the system-level design-space and compare a wide range of possible solutions with respect to their performance gain. Calibration and validation of the developed performance models help ensure that the performance predictions of these models are accurate. This paper presents formal definitions of the errors associated with the calibration and prediction process. In addition to a quantitative description of these errors, this paper also provides formal means to estimate their upper bounds, based on known or measured quantities.