Miracle-dz/UniFAR-FTUs huggingface dataset:
Coordinated hybrid force/position control for robot with three branches

This paper presents a coordinated hybrid force/position control method for robot with three branches (two arms and a coupled torso). To design the control system, the dynamic model of the robot is established. Then based on the dynamic model, a control algorithm which considers both the motion and the internal force of the manipulated object is proposed. The algorithm views the object as part of the end link of the arms, and adopts master-slave control method to transfer the control of the object to the synchronous control of the arms and torso. Finally, a simulation of a robot with a 2-DOF coupled torso and two 7-DOF arms verifies the proposed method.
IRONMAN: Using Social Networks to Add Incentives and Reputation to Opportunistic Networks

Opportunistic networks enable users to communicate in the absence of network infrastructure. But forwarding messages in such a network incurs costs for nodes in terms of energy and storage. This may lead to nodes being selfish and not forwarding messages for other nodes, resulting in degraded network performance. This paper presents a novel incentive mechanism for opportunistic networks that uses pre-existing social-network information to detect and punish selfish nodes, incentivising them to participate in the network. Trace-driven simulations demonstrate that our mechanism performs better than existing mechanisms, and that social-network information can also be used to improve existing incentive mechanisms.
Facial expression recognition using Hough forest

This paper introduces a new facial expression recognition system. Facial expressions analysis encounters two major problems: non-rigid morphing (human facial expression are non-rigid and shape deformation) and person-specific appearance (the facial action features are people-dependent). Our facial expression system analyzes the non-rigid morphing facial expressions and eliminates the person-specific effects through patch features extracted from facial motion due to different facial expressions. Finally, classification and localization of the center of the facial expression in the video sequences are performed by using a Hough forest.
2 NATURE AND DETERMINANTS OF PRODUCTIVITY GROWTH OF FOREIGN SUBSIDIARIES IN CENTRAL AND EAST EUROPEAN COUNTRIES

The paper examines the determinants of productivity growth in foreign manufacturing subsidiaries in five Central and East European (CEE) countries by analysing patterns of control, nature of firms’ capabilities and firms’ market orientation. Building on the so called ‘developmental subsidiaries’ perspective we show that productivity growth is determined jointly by corporate governance, production capability and market orientation variables. CEE subsidiaries have relatively strong autonomy over control of their business functions, but within a dominantly production oriented mandate. Majority foreign equity share has a significant and positive impact on subsidiaries’ productivity growth. These results present very strong regional characteristic.
Invention Under Uncertainty and the Threat of Ex Post Entry

This article proposes a theoretical framework for studying the invention of new products when demand is uncertain. In this framework, under general conditions, the threat of ex post entry by a competitor can deter invention ex ante. Asymmetric market power in the ex post market exacerbates the problem. The implications of these general results are examined in a series of examples that represent important markets in the computer industry. The first is a model that shows how an operating system monopolist, by its mere presence, can deter the invention of complements, to its own detriment as well as that of society. The implications of policies such as patent protection, price regulation, and mandatory divestiture are considered. Three additional examples consider the ability of a monopolist in one market to commit to bundling an unrelated product, a pair of horizontally differentiated firms that can add a new feature to their products, and a platform leader that can be challenged in its base market by the supplier of a complementary product.
Resource Certification - A Public Key Infrastructure for IP Addresses and AS's

We examine a form of an X.509 Public Key certificate that is used to bind IP address and AS number resources to a public/private key pair. These certificates are used to attest to resource allocation actions, so that digitally signed attestations relating to a party's right-of-use of IP addresses and AS numbers can be validated by relying parties, using a related Resource Certificate Public Key Infrastructure. This has particular application in the area of demonstrable attestations related to the right-of-use of IP addresses, and in the area of inter-domain routing security. The issues related to the application of this PKI to inter-domain routing security are considered, and the design, management and use of resource certificates, and the structure of the related Public Key Infrastructure are described in detail.
A Survey on Key Management for Body Sensor Network

Nowadays Body Sensor Networks (BSN) is considered to be the most potential technology in wireless sensor network. In the area of body sensor network, the main work is to monitor the physical data of users and transmit it through the whole network. Due to the sensitivity of data in the era of network development, privacy protection has become the hot topic in BSN authentication area. In this paper, we give a comparative survey on key management in BSN, and compare them in terms of different factors. Finally, the comparison results are presented.
Mining Wooden Pillar Features from Point Cloud

For huge quantity of point cloud data gotten from ancient buildings, the common algorithms (e.g. the Hough Transform) can do extract relative features but their efficiency and time expense are not acceptable. In order to improve the data process efficiency and reconstruct their 3D models quickly, more effective and more practicable algorithms should be developed. Here introduce a new algorithm for rapid extracting the wooden pillar features of Chinese ancient buildings from their point cloud data, the algorithm has the least human interaction in the procedure of data processing and is more efficient to extract pillars from point cloud data than existing feature extracting algorithms. With this algorithm we mine wooden pillar features by dividing the point cloud into slices firstly, and then get their projective parameters of relative pillar objects from selected slices, next to compare the local projective parameters in adjacent slices, next to combine them to get the global parameters of wooden pillars and at last reconstruct the 3D wooden pillar models based on acquired global parameters.
Eager Synching

Flash storage has been a standard component in Android devices. Recent research has reported that application data management in Android involves frequent fsync() operations. The current fsync() implementations, including those of ext4 and F2FS, have several common drawbacks. Specifically, ext4 commits a transaction every time to sync a file, whereas F2FS commits a checkpoint to sync a directory. Committing a transaction or checkpoint flushes all dirty data from the page cache to the flash storage via many small, random block write requests. The resultant high I/O frequency and excessive write traffic cause a high fsync() latency. This study presents an efficient fsync() method, called eager synching, which is based on a simple idea: write less, and write sequentially. To sync a file, eager synching writes only a subset of all dirty data in the page cache to a sequential log space using a few sequential block write requests. It does not involve transaction or checkpoint committing. We successfully implemented eager synching in ext4 and F2FS, and our experimental results show that, compared with the original fsync() methods of ext4 and F2FS, eager synching reduced the average and maximum fsync() latencies by up to 72% and 91%, respectively, block-level write traffic by up to 35%, and I/O frequency by up to 66%. Through enhanced crash recovery procedures, eager synching can successfully recover all previously synched files while still guaranteeing the file system integrity. We also conducted live application replays using the proposed eager synching approach and observed that this approach significantly improved the application frame updating rate and application execution time.
USING CTO-HARDWARE ACCELERATION IN FPGAS FOR WAVEFORM BASEBAND PROCESSING

Software-defined radio (SDR) architectures typically include general-purpose CPUs (GPPs), digital signal processing (DSP) ASSPs and FPGAs that process different waveforms, functions, and algorithms. GPPs typically handle network protocol processing and management functions. Historically, DSPs handled transceiver baseband processing and encoding, while FPGAs provided highperformance IF up/down conversion and preconditioning functions. Now FPGAs, when used with embedded softcore processors, have absorbed the DSP baseband processing and some GPP functionality as well, providing a smaller, lower power solution. However, meeting the baseband performance requirements requires aggressive use of hardware acceleration. In this paper, we discuss an efficient methodology for hardware acceleration of SDR waveforms, the creation and use of hardware acceleration units, and a tool that automates the flow. The Altera Nios II C-to-Hardware (C2H) Acceleration Compiler is a coprocessor generation tool that converts performancecritical ANSI C functions into hardware accelerator modules with direct memory access. Results are presented showing performance gains of 13–73X over software only, offering a promising solution for rapid development of high-performance SDR systems.
Sparse Representations for Efficient Shape Matching

Graph matching is a fundamental problem with many applications in computer vision. Patterns are represented by graphs and pattern recognition corresponds to finding a correspondence between vertices from different graphs. In many cases, the problem can be formulated as a quadratic assignment problem, where the cost function consists of two components: a linear term representing the vertex compatibility and a quadratic term encoding the edge compatibility. The quadratic assignment problem is NP-hard and the present paper extends the approximation technique based on graph matching and efficient belief propagation, described in a previous work, by using sparse representations for efficient shape matching. Successful results of recognition of 3D objects and handwritten digits are illustrated, using COIL and MNIST datasets, respectively.
ERBB-2 Intratumor Heterogeneity in Human Breast Cancer'

Amplification of the ERBB-2 (HER-2/neu) gene Is accompanied by overexpression of Its ceH surface receptor product, pl85â€(cid:157)@2. Heteroge neity has been observed for both the gene copy number and the level of overexpresslon ofits proteIn product. To better understand their relation ship, correlation between the level of cellular expression of pf85@@an2and ERBB-2 gene amplification was studied in four human breast cancer cell lines (BT-474, SK-BR-3, MDA-453, and MCF-7) and in a primary human breast tumor sample. The relative expression of pl85@'t2 was measured by hnmunofiuorescence by using flow and/or image cytometry while correlated DNA analysis was performed on the same cells by fluorescence in situ hybridization to determine ERBB-2 gene and chromosome 17 copy numbers. Marked heterogeneity was observed in both protein expression and ERBB-2 copy number. Despite this heterogeneity, and in accordance with previous studies, the average levels of p1ss@R2 expression corre. lated well with average ERBB-2 gene copy numbers in the four lines examined (r = 0.99). When the relationship between copy number and proteIn expression was studied on a cell-by-cell basis, p185â€(cid:157)@2 expres sion correlated with both the absolute number ofERBB-2 gene copies/cell (r 0.59â€”0.63)and chromosome 17copy number (r 0.45â€”0.61). It Isof Interest that there was weak or no correlation between p185â€(cid:157)@2protein expression and the ERBB-2 copy number:chroinosome 17 copy number ratio (r = 0.0-0.25). In more than one-half of cells expressing a high level of p185@@E@@2,thechromosome 17 copy number was @ (two or three times the average copy number), whereas <2% of an unselected popula tion had a high chromosome 17 copy number. Bromodeoxyuridineincor poration indicated that the S-phase-labeling index was homogeneous across various p185'@2-expressing subpopulations In the SK-BR-3 cell line. Analysis of the primary breast tumor sample showed results similar to the cell lines, supporting the strong possibility of a mechanistic link among p185@2 overexpresslon, ERBB-2 amplification, and high chro mosome 17 copy number. antibody of We also compared immunofluorescence caused a loss fluorescence intensity compared 25 Because this loss was not significant, and the two other cell lines could not be harvested with 25 mM EDTA, we used trypsin to harvest cells for flow cytometric analysis. Results from monoclonal antibody (mAbi) raised against extracellular domain @l85H@. 2 protein unnecessary,
Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic–there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.
Constructional paradigms affect visual lexical decision latencies in English

Previous research on morphological processing suggests that the probability distribution of a word across its inflected variants influences the recognition of that word. Recently, similar effects have been reported for relations between prepositions and definite-noun-phrase heads in English trigrams (e.g., in the bucket). In the present study, we test whether both effects could be accounted for in terms of string proximity and/or semantic similarity alone, or whether the findings for English trigrams should be attributed to syntactic paradigm effects. We ‘fake’ a case system for English using syntactic positions and prepositions as proxies for the relational meanings expressed inflectionally in other languages. Based on these syntactic factors, we define a syntactic inflectional entropy to parallel the morphological entropy measures used in prior studies. We found that this new measure correlates negatively with visual lexical decision RTs. However, unlike prior studies, we did not find a semantic priming effect between nouns with similar distributions in our paradigmatic vectors. This finding suggests that abstract constructional distributions facilitate lexical access while obscuring semantic relations between similarly distributed words.
Applying ontological modeling on quranic "nature" domain

The holy Quran is the holy book of the Muslims. It contains information about many domains. Often people search for particular concepts of holy Quran based on the relations among concepts. An ontological modeling of holy Quran can be useful in such a scenario. In this paper, we have modeled nature related concepts of holy Quran using OWL (Web Ontology Language) / RDF (Resource Description Framework). Our methodology involves identifying nature related concepts mentioned in holy Quran and identifying relations among those concepts. These concepts and relations are represented as classes/instances and properties of an OWL ontology. Later, in the result section it is shown that, using the Ontological model, SPARQL queries can retrieve verses and concepts of interest. Thus, this modeling helps semantic search and query on the holy Quran. In this work, we have used English translation of the holy Quran by Sahih International, Protege OWL Editor and for querying we have used SPARQL.
Improved Linear Parallel Interference Cancellers

In this paper, taking the view that a linear parallel interference canceller (LPIC) can be seen as a linear matrix filter, we propose new linear matrix filters that can result in improved bit error performance compared to other LPICs in the literature. The motivation for the proposed filters arises from the possibility of avoiding the generation of certain interference and noise terms in a given stage that would have been present in a conventional LPIC (CLPIC). In the proposed filters, we achieve such avoidance of the generation of interference and noise terms in a given stage by simply making the diagonal elements of a certain matrix in that stage equal to zero. Hence, the proposed filters do not require additional complexity compared to the CLPIC, and they can allow achieving a certain error performance using fewer LPIC stages. We also extend the proposed matrix filter solutions to a multicarrier DS-CDMA system, where we consider two types of receivers. In one receiver (referred to as Type-I receiver), LPIC is performed on each subcarrier first, followed by multicarrier combining (MCC). In the other receiver (called Type-II receiver), MCC is performed first, followed by LPIC. We show that in both Type-I and Type-II receivers, the proposed matrix filters outperform other matrix filters. Also, Type-II receiver performs better than Type-I receiver because of enhanced accuracy of the interference estimates achieved due to frequency diversity offered by MCC.
Automatic Method for Author Name Disambiguation Using Social Networks

A name is a key feature for distinguishing people, but we often fail to distinguish people because an author may have multiple names or multiple authors may share the same name. Such name ambiguity problems affect the performance of the document retrieval, web search and database integration. Especially, in bibliographic information, a number of errors may be included since there are different authors with the same name or an author name may be misspelled or represented with an abbreviation. For solving these problems, it is necessary to disambiguate the names inputted into the database. In this paper, we propose a method to solve the name ambiguity by using social networks constructed based on the relations among authors. We evaluated the effectiveness of the proposed system based on the DBLP data that offer computer science bibliographic information.
Analyse du Cycle de Vie (ACV)

L’ACV consiste a evaluer les impacts environnementaux potentiels d’un systeme, un produit voire un procede ou un service, assurant une (ou plusieurs) fonction(s), tout le long de son cycle de vie. Cette approche se deroule en quatre etapes : objectifs, bilan matiere energie, analyse des impacts et interpretation. Cet article introduit l’outil Analyse du Cycle de vie, de sa genese a ses points forts, en passant par ses applications et sa methodologie.
AN INVESTIGATION OF THE EFFECT OF FAMILY BACKGROUND VARIABLES ON INNOVATION PERCEPTIONS OF ENGINEER AND TEACHER CANDIDATES

The aim of this study is to investigate the innovation perceptions of teacher candidates in the areas of mathematics, science and social sciences. The data collection tools are the Turkish versions of the Individual Innovativeness Scale (IIS) and Big5 Scale for personality characteristics. Multivariate linear regression is the main data analysis technique. Results indicate that 47% of the variation in the IIS is explained by the independent variables.
Turkey’s governance of irregular migration at European Union borders: Emerging geographies of care and control

Combining insights from critical studies on humanitarianism and scholarly work emphasising everyday practices, this study examines Turkish policing of human mobility at European Union borders in two border cities: Edirne and İzmir. Through a focus on the central understandings, justifications and operational responses by Turkish border officials, the article highlights the intertwinement of care and control as inherent to humanitarianism in the daily governance of mobile populations at Turkey’s western borders. In so doing, the findings draw attention to discursive articulations and practices, while pointing to their moral, emotional and cultural elements. The article advances the literature by underlining the centrality of geography in impacting on the logics and practices of governing mobility within the territory of the nation state. The findings also underscore variations in border practices and the embodiment of humanitarianism between the two border cities under investigation as well as across the country. In addition, the article adds to debates on the emerging spaces of humanitarianism by bringing into focus the operation of humanitarian border policing in Turkey before departure and/or after the unsuccessful attempt of border crossing.
Towards Addressing Challenges in Green Security Games in the Wild

Based on the successful deployment of gametheoretic decision support systems in protecting critical infrastructure such as ports, air ports and trains, recent research have started focusing on Green Security Games, where the law enforcement agencies aim to protect forest, wildlife and fishery with limited patrol resources. This paper (i) lays out the challenges in Green Security Games in the wild, including the challenges in planning patrol strategies, in learning from data and in real-world deployment; (ii) outlines the lessons learned from an initial test in an protected area in Southeast Asia during which patrol routes are generated based on game-theoretic models; (iii) outlines our on-going research of address some of the challenges.
Mechanical design of a simple bipedal robot

The thesis objective was to design a walking robot appropriate for testing a machine learning control system. As a robot that would learn how to walk, it was pre-maturely named Toddler. The passive dynamic walker, a class of simple robots driven by gravity and inertia, was selected as the model for the Toddler robot. Two preliminary passive walkers were explored: a three-dimensional, toy-like biped with one degree of freedom at the hip; and a two-dimensional, four-legged kneed walker with degrees of freedom at the hip and knees. Bench level and computer modeled analyses were conducted during the design and construction of these robots. The simpler, toy-like walker was selected as the unactuated model for actuated Toddler. Two degrees of freedom, controlling step size and frequency, were introduced at the ankle. Toddler was able to walk with a dynamically-stable gait either passively down a ramp, or actively on a flat or slightly uphill surface. With its simple design and robust performance, Toddler provides an excellent platform for testing machine learning control in walking robotics. Thesis Supervisor: H. Sebastian Seung Title: Professor, Department of Brain and Cognitive Sciences and Department of Physics