Miracle-dz/UniFAR-FTUs huggingface dataset:
Offline Smooth path planning for a mobile robot in dynamic environment using evolutionary multi-objective optimization

—This paper studies the path planning problem for mobile robots to move smoothly and safely along a shorter curvature-constrained path in completely known dynamic environments. The cost of travel is defined by an obstacle-avoidance cost, which is designed as a weighted penetration depth to vertices of obstacles, and a length cost. The path is composed of a pre-specified number of cubic spiral segments. The intermediate configurations are generated by evolutionary multi-objective optimization aiming for smooth and shorter collision-free paths. Comparison of path planning performance of two different intrinsic cost definitions based on island-based parallel genetic algorithm (IPGA) with migration are conducted in terms of success rate in separate runs and path length whenever a collision-free path can be found. Results are presented for simulated environments containing three distinct types of obstacles: polygons, walls and their combinations.
Lipid Bilayer Composition Affects Transmembrane Protein Orientation and Function

Sperm membranes change in structure and composition upon ejaculation to undergo capacitation, a molecular transformation which enables spermatozoa to undergo the acrosome reaction and be capable of fertilization. Changes to the membrane environment including lipid composition, specifically lipid microdomains, may be responsible for enabling capacitation. To study the effect of lipid environment on proteins, liposomes were created using lipids extracted from bull sperm membranes, with or without a protein (Na+ K+-ATPase or α-amylase). Protein incorporation, function, and orientation were determined. Fluorescence resonance energy transfer (FRET) confirmed protein inclusion in the lipid bilayer, and protein function was confirmed using a colourometric assay of phosphate production from ATP cleavage. In the native lipid liposomes, ATPase was oriented with the β subunit facing the outer leaflet, while changing the lipid composition to 50% native lipids and 50% exogenous lipids significantly altered this orientation of Na+ K+-ATPase within the membranes.
Transferring corporate knowledge via succession planning: analysis and solutions – Part 2

Purpose – The focus of the paper is a large, national, publicly traded company. As a large number of its workforce consists of “baby boomers”, 50 percent of its employees will be of retirement age within the next five years. Having acknowledged the company's concerns about efficiency of new employees and the loss of morale in senior employees, this two‐part article sets out to provide motivational tools for management and to suggest solutions to restructure and reorganize in a way to prevent the inevitable – i.e. the loss of corporate knowledge – via succession planning.Design/methodology/approach – A survey and individual interviews were conducted within the company to measure current job satisfaction and company culture as well as how the different generations of employees view each other and themselves. Employees were also questioned about their legacy in the organization and their thoughts about transferring corporate knowledge from one generation to another. This is a two‐part article. Part 1 covers .
Controlling overlap in content-oriented XML retrieval

The direct application of standard ranking techniques to retrieve individual elements from a collection of XML documents often produces a result set in which the top ranks are dominated by a large number of elements taken from a small number of highly relevant documents. This paper presents and evaluates an algorithm that re-ranks this result set, with the aim of minimizing redundant content while preserving the benefits of element retrieval, including the benefit of identifying topic-focused components contained within relevant documents. The test collection developed by the INitiative for the Evaluation of XML Retrieval (INEX) forms the basis for the evaluation.
Palm vein recognition system based on corner point detection

Nowadays, the biometric palm vein is leading trait for person recognition. The biometric is formed on the basis of physiological and behavioral characteristic of human being. The blood vascular structure of each and every individual is unique and distinct. The blood vessel carries oxygenated or deoxygenated blood and found under the skin. The near infrared light illumination visualizes a palm vein pattern. The blood vessel is a superior trait, as it lies beneath a skin that makes it very hard to duplicate, forge or fake. This paper discuss about development of the new recognition technique. The paper also discusses a use of Gabor and canny edge detector to form a basis of vascular structure and thereafter using corner point detection algorithm for efficient extraction of features. The work was focused on the palm vein analysis, its feature extraction and finally identification.
De novo Assembly of Leaf Transcriptome in the Medicinal Plant Andrographis paniculata

Andrographis paniculata is an important medicinal plant containing various bioactive terpenoids and flavonoids. Despite its importance in herbal medicine, no ready-to-use transcript sequence information of this plant is made available in the public data base, this study mainly deals with the sequencing of RNA from A. paniculata leaf using Illumina HiSeq™ 2000 platform followed by the de novo transcriptome assembly. A total of 189.22 million high quality paired reads were generated and 1,70,724 transcripts were predicted in the primary assembly. Secondary assembly generated a transcriptome size of ~88 Mb with 83,800 clustered transcripts. Based on the similarity searches against plant non-redundant protein database, gene ontology, and eukaryotic orthologous groups, 49,363 transcripts were annotated constituting upto 58.91% of the identified unigenes. Annotation of transcripts—using kyoto encyclopedia of genes and genomes database—revealed 5606 transcripts plausibly involved in 140 pathways including biosynthesis of terpenoids and other secondary metabolites. Transcription factor analysis showed 6767 unique transcripts belonging to 97 different transcription factor families. A total number of 124 CYP450 transcripts belonging to seven divergent clans have been identified. Transcriptome revealed 146 different transcripts coding for enzymes involved in the biosynthesis of terpenoids of which 35 contained terpene synthase motifs. This study also revealed 32,341 simple sequence repeats (SSRs) in 23,168 transcripts. Assembled sequences of transcriptome of A. paniculata generated in this study are made available, for the first time, in the TSA database, which provides useful information for functional and comparative genomic analysis besides identification of key enzymes involved in the various pathways of secondary metabolism.
ADHM is tachyon condensation

We completely realize the ADHM construction of instantons in D-brane language of tachyon condensations. Every step of the construction is given a physi- cal interpretation in string theory, in a boundary state formalism valid all order in � ' . Accordingly, equivalence between Yang-Mills configurations on D4-branes and D0-branes inside the D4-branes is proven, which shows that small instanton config- urations of the Yang-Mills fields are protected against stringy � ' corrections. We provide also D-brane realizations of the inverse ADHM construction, the complete- ness, and the noncommutative ADHM construction.
Efficient Graph Algorithms for Network Analysis

The GC problem is to identify a pre-determined number of center vertices such that the distances or costs from (or to) the centers to (or from) other vertices is minimized. The bottleneck of a path is the minimum capacity of edges on the path. The Bottleneck Paths (BP) problem is to compute the paths that give us the maximum bottleneck values between pairs of vertices. The Graph Bottleneck (GB) problem is to find the minimum bottleneck value out of bottleneck paths for all possible pairs of vertices. We give two similar algorithms that are based on binary search to solve the 1-center GC problem and the GB problem on directed graphs with unit edge costs. We achieve $\tilde{O}(n^{2.373})$ worst case time complexity for both the 1-center GC problem and the GB problem, where $n$ is the number of vertices in the graph. This is better than the straightforward methods of solving the two problems in $O(n^{2.575})$ and $O(n^{2.688})$ time bounds, respectively. We then combine the Bottleneck Paths (BP) problem with the well known Shortest Paths (SP) problem to compute the shortest paths for all possible flow values. We call this problem the Shortest Paths for All Flows (SP-AF) problem. We show that if the flow demand is uncertain, but between two consecutive capacity values, the unique shortest path can be computed to push that flow. If the uncertainty stretches over two intervals, we need to prepare two shortest paths to accommodate the uncertainty, etc. In introducing this new problem, we define a new semi-ring called the distance/flow semi-ring, and show that the well known algorithm by Floyd can be used over the distance/flow semi-ring to solve the All Pairs Shortest Paths for All Flows (APSP-AF) problem.
Operating point dependent anisotropies and assessment for position-sensorless control

Position-sensorless speed and position control of surface mounted permanent magnet synchronous machines (SMPMSMs) is of special interest in industrial automation due to their high efficiency and simple design. In the low speed range and at standstill high frequency injection based control schemes are employed in order to maintain field oriented control. These methods exploit rotor-position dependent anisotropies of the stator inductances which are measured as a response signal to the injected high frequency excitation. The rotor-position dependency of the stator inductances is either caused by a geometrical saliency of the rotor structure of by local magnetic saturation caused by the permanent magnet field. However, a SMPMSM typically has no geometrical saliency and the anisotropy is therefore solely caused by magnetic saturation and is therefore very small. Moreover the inductive anisotropy is also influenced by the presence of the torque producing fundamental wave stator current components. This typically results in nonlinear functions for the differential inductive parameters. The operating point dependent behavior of the anisotropy must be described and analyzed in order to be able to deduce the correct rotor position from the measured high frequency response. This paper introduces an operating point dependent description of the anisotropy parameters in a general applicable form. A procedure to measure these dependencies is shown and criteria are derived to assess the observability of the rotor position from the measured anisotropy data. This can be used to compensate for load torque dependent position errors and also rotor-position dependent harmonic distortions. Finally a new criterion is introduced that allows to assess the stability of a closed loop position observer which uses the high frequency response as a feedback signal.
1 Error Detection in Service-Oriented Distributed Systems

Consumer Electronics systems are composed of components developed by different vendors. These components rely on open hardand software standards for their cooperation. With the increased digitization of content and use of digital networks, Service Oriented Architectures (SOA) represent a natural approach to this openness. In a SOA, functionality, resources and content are encapsulated as services; applications are composed by connecting these services. In this paper we describe this approach in the context of an advanced consumer electronics setup, viz. a prototype for the distributed processing of multimedia content to derive meta-information from the content. The system architecture is fully based on the concept of SOA by using the new CE standard UPnP. Particular contribution of the paper is an analysis and a solution for error detection in this context. We derive requirements for error detection from the architecture, which dictates that this aspect should follow the same approach of loose coupling and late binding as the functional elements of the SOA. We define a fault model and a corresponding architecture for the solution. We introduce quantifiable parameters to evaluate quality of this solution. The solution was built into a prototype of which we present and analyze experimental results.
Understanding Chinese Users' Adoption Decision of Wireless Internet Services via Mobile Technology: An Integrative Model

Technology acceptance research has tended to focus on extrinsic motivation based on sole theoretical paradigm. Building upon and integrating the key findings of four closely related theoretical paradigms (the technology acceptance model, the theory of planned behavior, innovation diffusion theory, and the flow theory), we developed and test a more comprehensive and unified model in the context of Chinese users’ adoption decision of wireless Internet services via mobile technology. Structural equation analysis demonstrate that perceived usefulness and perceived enjoyment significantly influence the attitude towards using WIMT, which in turn impacts their behavioral intention, reveals that both extrinsic and intrinsic motivations are important determinants of adopt intention. Further more, social influences and personal traits such as individual innovativeness are important determinants of adoption as well. The paper concludes with some important implications.
Situational Awareness from Environmental Sounds

Environmental sounds provide many contextual cues that ena ble us to recognize important aspects of our surroundings. The goal of this project is to consider tech niques to allow machines to extract and classify features from pre-defined classes of sounds in the enviro nment. We will present the different phases of the project: capture of environmental audio, pre-processing of audio data, feature extraction using power spectral density and filter-banks, training and testing vi a a simple nearest-neighbor algorithm. We will discuss some preliminary results and future work on incorpor ating such techniques on a wearable computer to provide a form of "situational awareness" to the system.
A Second Look at Microfinance The Sequence of Growth and Credit in Economic History

such as small loans to the world’s poor—has grown in the past decade, extending billions of dollars in credit to tens of millions of people. A major aim of the microfinance movement is to provide funds for investment in microbusinesses, thus lifting people out of poverty and promoting economic growth. Recent experience and the economic history of rich countries, however, suggest that those expectations are unrealistic. Most people, poor or otherwise, are not entrepreneurs, so there is little reason to think that mass credit would in general lead to viable business start-ups. Today as in the past, business start-ups in the advanced countries depend predominantly on savings and informal sources of credit; past forms of microcredit never played a role in small business development, and much microcredit is actually used for consumption rather than investment. In the history of today’s rich countries, moreover, economic growth occurred first, then came credit for the masses. That credit was and is predominantly for consumption rather than investment. There is no reason to believe that the nature and sequence of growth and mass credit are fundamentally different for poor countries today than they were in the past. We should not expect microfinance to noticeably affect growth or successful business development.
A research on AIS-based embedded system for ship collision avoidance

This paper uses the data provided by AIS as the sources of information and combines the actual needs for ship collision avoidance perception. Considering the major factor for ship collision impact, a mathematical model of risk evaluation is established for embedded system, and a new design of AIS-based embedded system for ship collision avoidance is proposed. By utilizing an ARM platform, the system has realized many decision support functions, such as intelligent analysis, forewarning prompt, operation suggestion, and data backtracking, displaying and human-computer interaction. The results shows that the system can satisfy the demand of auxiliary decision support for ship collision avoidance operation.
TLSH -- A Locality Sensitive Hash

Cryptographic hashes such as MD5 and SHA-1 are used for many data mining and security applications -- they are used as an identifier for files and documents. However, if a single byte of a file is changed, then cryptographic hashes result in a completely different hash value. It would be very useful to work with hashes which identify that files were similar based on their hash values. The security field has proposed similarity digests, and the data mining community has proposed locality sensitive hashes. Some proposals include the Nilsimsa hash (a locality sensitive hash), Ssdeep and Sdhash (both Ssdeep and Sdhash are similarity digests). Here, we describe a new locality sensitive hashing scheme the TLSH. We provide algorithms for evaluating and comparing hash values and provide a reference to its open source code. We do an empirical evaluation of publically available similarity digest schemes. The empirical evaluation highlights significant problems with previously proposed schemes; the TLSH scheme does not suffer from the flaws identified.
2012 International Conference on Information Management, Innovation Management and Industrial Engineering the Layout Characteristics of China's Nonferrous Metals Industry and Implication of Industry Structural Adjustment Innovation Policy

This paper analyzed the changing pattern of the concentration level of the spatial layout of China's nonferrous metals industry from 2002 to 2010, conducted analysis on the supply and demand balance of regional layouts in 2010, and developed an econometrics model to make empirical analysis on the influences of mineral resource endowment, market demand and geographical location on industry layouts of 4 concluded that the features of China's current nonferrous metals industry layout is mainly "relying on market" type, and there exist a serious imbalance between supply and demand of regional layouts. Based on those empirical results, the paper proposed some suggestions on innovative policies to adjust and optimize the industry layout.
Penalized and weighted K-means for clustering with scattered objects and prior information in high-throughput biological data

MOTIVATION Cluster analysis is one of the most important data mining tools for investigating high-throughput biological data. The existence of many scattered objects that should not be clustered has been found to hinder performance of most traditional clustering algorithms in such a high-dimensional complex situation. Very often, additional prior knowledge from databases or previous experiments is also available in the analysis. Excluding scattered objects and incorporating existing prior information are desirable to enhance the clustering performance. RESULTS In this article, a class of loss functions is proposed for cluster analysis and applied in high-throughput genomic and proteomic data. Two major extensions from K-means are involved: penalization and weighting. The additive penalty term is used to allow a set of scattered objects without being clustered. Weights are introduced to account for prior information of preferred or prohibited cluster patterns to be identified. Their relationship with the classification likelihood of Gaussian mixture models is explored. Incorporation of good prior information is also shown to improve the global optimization issue in clustering. Applications of the proposed method on simulated data as well as high-throughput data sets from tandem mass spectrometry (MS/MS) and microarray experiments are presented. Our results demonstrate its superior performance over most existing methods and its computational simplicity and extensibility in the application of large complex biological data sets. AVAILABILITY http://www.pitt. edu/~ctseng/research/software.html. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
High-Performance Biomedical Association Mining with MapReduce

MapReduce has been applied to data-intensive applications in different domains because of its simplicity, scalability and fault-tolerance. However, its uses in biomedical association mining are still very limited. In this paper, we investigate using MapReduce to efficiently mine the associations between biomedical terms extracted from a set of biomedical articles. First, biomedical terms were obtained by matching text to Unified Medical Language System (UMLS) Metathesaurus, a biomedical vocabulary and standard database. Then we developed a MapReduce algorithm that could be used to calculate a category of interestingness measures defined on the basis of a 2×2 contingency table. This algorithm consists of two MapReduce jobs and takes a stripes approach to reduce the number of intermediate results. Experiments were conducted using Amazon Elastic MapReduce (EMR) with an input of 3610 articles retrieved from two biomedical journals. Test results indicate that our algorithm has linear scalability.
COMMON COMPUTATIONAL STRATEGIES IN MACHINE AND BIOLOGICAL VISION

Humans effortlessly perform visual tasks, like face detection and recognition, that have turned out to be extremely difficult for artificial vision systems. Research into the principles underlying biological object recognition therefore is of great potential interest to the machine vision community. Recent experiments — both psychophysical and physiological — have provided evidence that instead of using 3D models as in many “classical” computer vision systems, a biological strategy for object recognition is view-based, in the sense that objects are represented by a set of 2D views. Several models have presented plausible mechanisms explaining how this “snapshot”-based representation can develop and how it can be used to perform object recognition. Extending the view-based paradigm to artificial systems has proved to be an extremely successful approach to developing robust and flexible computer vision systems that are able to perform reliably in real-world situations. Among others, we present applications to object detection, face recognition, and pose estimation and synthesis.
Short and Long Run Parametric Dynamics in the Balkans Stock Markets

This paper examines dynamics between the behaviour of the emerging Balkans stock markets, namely Romania, Bulgaria, Serbia, FYROM, Turkey, Croatia, and Albania and mature stock markets, particularly US, UK, Germany, and Greece. We use linear (error correction vector autoregressive model) and non – linear (switching regime error correction models) estimation methods to test for possible linkages between the Balkans and developed markets. Our findings show that (i) the Balkans markets display equilibrium relations with their mature counterparts, supporting the hypothesis that there are interdependencies between emerging and developed stock markets, which limit the potential for portfolio diversification by investing in different Balkans market; (ii) an active strategy provides more potential to create exceptional returns than a passive strategy.