Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing image and camera trajectories in robot vision control using on-line boosting

In this paper, we present a novel boosted robot vision control algorithm. The method utilizes on-line boosting to produce a strong vision-based robot control starting from two weak algorithms. The notion of weak and strong algorithms has been presented in the context of robot vision control, in presence of uncertainty in the measurement process. Appropriate probabilistic error functions are defined for the weak algorithm to evaluate their suitability in the task. An on-line boosting algorithm is employed to derive a final strong algorithm starting from two weak algorithms. This strong one has superior performance both in image and Cartesian spaces. Experiments justify this claim.
Lossy Lzw Algorithm with Adaptive Threshold for Palettized Image Compression

Color palettized image file formats especially the GIF format are widely used in the World Wide Web of the intemet. In these file formats. only lossless compression techniques are used for the encoding of palettized image. thus the compression ratio is only 1.2 to 2.5. To achieve higher compression ratio. lossy compression techniques have to be use. However. significant visual artifact due to lossy encoding of the palettized image may occur in the reconstructed images. and the compressed file format is not compatible to the conventional formats. To avoid these two problems. a Lossy LZW algorithm is proposed for palettized images compression. In the proposed algorithm, adaptive thresholds according to the human visual characteristics are used to consnain the color pixel’s error of the reconstructed image. In addition, the algorithm can be embedded in the GIF encoder so that the original GIF decoder can be used to decode the image compressed by the new algorithm.
Research of multicast routing protocol in wireless sensor networks based on network coding

Aiming ate the disadvantage of network resource and load balance, this paper analyses the traditional multicast routing protocol base on tree, and then puts forward an improved multicast routing protocol based on network coding and existing distributed shared tree. It adopts minimal link to select the node and puts forward the algorithm of node selecting and shared tree constructing based on network coding.
Kinematic analysis of a novel 3-CRU translational parallel mechanism

Abstract. In this paper, a modified 3-DOF (degrees of freedom) translational parallel mechanism (TPM) three-CRU (C, R, and U represent the cylindrical, revolute, and universal joints, respectively) structure is proposed. The architecture of the TPM is comprised of a moving platform attached to a base through three CRU jointed serial linkages. The prismatic motions of the cylindrical joints are considered to be actively actuated. Kinematics and performance of the TPM are studied systematically. Firstly, the structural characteristics of the mechanism are described, and then some comparisons are made with the existing 3-CRU parallel mechanisms. Although these two 3-CRU parallel mechanisms are both composed of the same CRU limbs, the types of freedoms are completely different due to the different arrangements of limbs. The DOFs of this TPM are analyzed by means of screw theory. Secondly, both the inverse and forward displacements are derived in closed form, and then these two problems are calculated directly in explicit form. Thereafter, the Jacobian matrix of the mechanism is derived, the performances of the mechanism are evaluated based on the conditioning index, and the performance of a 3-CRU TPM changing with the actuator layout angle is investigated. Thirdly, the workspace of the mechanism is obtained based on the forward position analysis, and the reachable workspace volume is derived when the actuator layout angle is changed. Finally, some conclusions are given and the potential applications of the mechanism are pointed out.
MEDACO : Solving Multiobjective Combinatorial Optimization with Evolution , Decomposition and Ant Colonies

We propose a novel multiobjective evolutionary algorithm, MEDACO, a shorter acronym for MOEA/D-ACO, combining ant colony optimization (ACO) and multiobjective evolutionary algorithm based on decomposition (MOEA/D). The motivation is to use the online-learning capabilities of ACO, according to the Reactive Search Optimization (RSO) paradigm of ”learning while optimizing”, to further improve the effectiveness of the original MOEA/D algorithms. Following other MOEA/D-like algorithms, MEDACO decomposes a multiobjective optimization problem into a number of single-objective optimization tasks solved by different iterated greedy construction processes (a.k.a. ants). Each ant has an individual heuristic information matrix and several neighboring ants, characterized by a similar combination of the individual objectives. All ants are divided into groups, with each group maintaining a different pheromone matrix. During the search, each ant records the best solution found so far for its subproblem. To construct a new solution, an ant combines information from its group’s pheromone matrix, its own heuristic information matrix and its current solution. Extensive experimental comparisons are executed. On the multiobjective 0-1 knapsack problem, MEDACO outperforms MOEA/D-GA on all the nine test instances. Furthermore, we demonstrate that the heuristic information matrices in MEDACO are crucial to significantly improve the performance. On the biobjective traveling salesman problem, MEDACO performs much better than the previously proposed BicriterionAnt algorithm on the 12 test instances. We also critically evaluate the effects of the group, the neighborhood and the location information of current solutions on the performance of MEDACO.
A Multiresolution Study of Eective Properties of Complex Electromagnetic Systems 3

A systematic study of the across scale coupling phenomenology in EM scattering problems is addressed using the theory of multiresolution decomposition and orthogonal wavelets. By projecting an integral equation formulation of the scattering problem onto a set of subspaces that constitutes a multiresolution decomposition of L 2 (R), one can derive two coupled formulations. The rst governs the macroscale response, and the second governs the microscale response. By substituting the formal solution of the latter in the former, a new self consistent formulation that governs the macroscale response component is obtained. This formulation is written on a macroscale grid, where the e ects of the microscale heterogeneity is expressed via an across scale coupling operator. This operator can also be interpreted as representing the e ective properties of the microstructure. We study the properties of this operator versus the characteristics of the Green function and the microstructure for various electromagnetic problems, using general asymptotic considerations. A speci c numerical example of TM scattering from a laminated complex structure is provided. Acknowledgment This research was supported in part by THE ISRAEL SCIENCE FOUNDATION administered by THE ISRAEL ACADEMY OF SCIENCE AND HUMANITIES
Equilibrium in erasure coding for ALOHA MAC protocols

In this paper we use game theory to analyze Slotted ALOHA when integrating erasure coding, from the perspective of a selfish user. We construct a ALOHA game model and examine the optimal behavior of individual users. We confirm the existence of Nash equilibrium, and then we compare our results with those found in conventional model. By the use of game theory assumption, we have been able to improve the performances of ALOHA protocols.
Teaching racial microaggressions: implications of critical race hypos for social work praxis

ABSTRACT This article provides a conceptual understanding of racial microaggressions from a critical race theoretical (CRT) perspective, as relevant to the field of Social Work. To do this, we utilize Critical Race Hypos, hypothetical pedagogical tools developed from existing literature on racial microaggressions, and meant to engage critical dialogue on everyday racism in the lives of People of Color. We explain the pedagogical utility of Critical Race Hypos for engaging discussions about racial microaggressions in social work training. This article provides three Critical Race Hypos that focus on common questions about racial microaggressions set within the context of a social work graduate program classroom. The article concludes with implications of these hypos for social work theory and practice.
Return to Sepharad: Is it possible to heal an ancient wound? A reflection on the construction of large-group identity

Abstract Spanish parliament recently issued a new law offering Spanish nationality to Sephardic Jews who so desired and could demonstrate a basic knowledge of the Spanish language and culture. This law attempted to redress a five-centuries-old injustice and was expected to unleash both criticism and praise. Surprisingly, reactions in the public or the press were minimal or absent. Reasons for this are explored through a qualitative study with focus groups, which showed ideas that can be grouped into four main categories: ignorance, justice, distrust, and fear. It is hypothesized that the predominantly silent response to the new law might be due to the fact that it touches on an extremely sensible issue: the historically fragmented Spanish identity. A position of negation is constructed, to avoid deep anxieties related to the fragile core of a collective identity built from many “others” forced to the refuge of an introspection that protects them from the conviction of not fulfiling the ideal identity status, known by all but reached by none. All those “others” have mixed their bloods with the Old Christians along the centuries, possibly transmitting a profound insecurity about their personal and collective identity that might contribute to understanding current social reactions.
A tail bound for read‐k families of functions

We prove a Chernoff‐like large deviation bound on the sum of non‐independent random variables that have the following dependence structure. The variables Y1,…,Yr are arbitrary [0,1]‐valued functions of independent random variables X1,…,Xm , modulo a restriction that every Xi influences at most k of the variables Y1,…,Yr . © 2014 Wiley Periodicals, Inc. Random Struct. Alg. , 47, 99–108, 2015
The Query Complexity of Scoring Rules

Proper scoring rules are crucial tools to elicit truthful information from experts. A scoring rule maps X, an expert-provided distribution over the set of all possible states of the world, and ω, a realized state of the world, to a real number representing the expert’s reward for his provided information. To compute this reward, a scoring rule queries the distribution X at various states. The number of these queries is thus a natural measure of the complexity of the scoring rule. We prove that any bounded and strictly proper scoring rule that is deterministic must make a number of queries to its input distribution that is a quarter of the number of states of the world. When the state space is very large, this makes the computation of such scoring rules impractical. We also show a new stochastic scoring rule that is bounded, strictly proper, and which makes only two queries to its input distribution. Thus, using randomness allows us to have significant savings when computing scoring rules.
Regular and non regular snore features as markers of SAHS

Sleep Apnea-Hypopnea Syndrome (SAHS) diagnosis is still done with an overnight multi-channel polysomnography. Several efforts are being made to study profoundly the snore mechanism and discover how it can provide an opportunity to diagnose the disease. This work introduces the concept of regular snores, defined as the ones produced in consecutive respiratory cycles, since they are produced in a regular way, without interruptions. We applied 2 thresholds (THadaptive and THmedian) to the time interval between successive snores of 34 subjects in order to select regular snores from the whole all-night snore sequence. Afterwards, we studied the effectiveness that parameters, such as time interval between successive snores and the mean intensity of snores, have on distinguishing between different levels of SAHS severity (AHI (Apnea-Hypopnea Index)<5h−1, AHI<10 h−1, AHI<15h−1, AHI<30h−1). Results showed that THadaptive outperformed THmedian on selecting regular snores. Moreover, the outcome achieved with non-regular snores intensity features suggests that these carry key information on SAHS severity.
Semi-supervised dimensionality reduction using orthogonal projection divergence-based clustering for hyperspectral imagery

Abstract. Band clustering and selection are applied to dimensionality reduction of hyperspectral imagery. The proposed method is based on a hierarchical clustering structure, which aims to group bands using an information or similarity measure. Specifically, the distance based on orthogonal projection divergence is used as a criterion for clustering. After clustering, a band selection step is applied to select representative band to be used in the following data analysis. Different from unsupervised clustering using all the pixels or supervised clustering requiring labeled pixels, the proposed semi-supervised band clustering and selection needs class spectral signatures only. The experimental results show that the proposed algorithm can significantly outperform other existing methods with regard to pixel-based classification task.
Overview of Taiwan information security center and its research on privacy

The Taiwan Information Security Center (TWISC) was initiated as a research program in April 2005 and funded by the Ministry of Science and Technology for the past few years. TWISC pulls together experts in information security from various universities and research institutes in Taiwan with an aim to boost research and development activities in information security, promote public awareness, and foster partnership among government, academia, and the private sector. Its research topics cover data/software/hardware/network security and security management. TWISC has become the hub of security research in Taiwan and have been making significant impact through publishing and creating of toolkits. Recently privacy also becomes one of the main focuses of TWISC. The research team at CITI, Academia has been working on a toolkit to enable privacy-preserved release of open data. Preliminary research result will be presented in this paper.
Intergenerational Transfers and Household Structure. Why Do Most Italian Youths Live With Their Parents

85 percent of Italian men aged 18-33 live with their parents. We argue that Italian parents like to live with their children and a rise in their income makes it possible for them to offer their children higher consumption in exchange for their presence at home. Children prefer to live on their own but are willing to exchange some independence for extra consumption. We formalize this intuition with a bargaining model between parents and children. We test the predictions of the model by estimating the effect of parental income on the probability that children live with their parents. The key econometric issue is the endogeneity of parental income. In order to identify the causal effect of parental income on children's living arrangements we use changes in parents' retirement age induced by the 1992 reform of the Italian social security as an instrument for parental income. By raising retirement age, this reform forced some fathers to remain in the labor market longer than the cohort immediately preceding them, therefore raising their income. Our instrumental variable estimates indicate that a rise in parents' income significantly raises the children's propensity to live at home: a $500 increase in annual parental income results in a 3 to 3.5 percentage point rise in the proportion of children living with their parents.
Bounded-Degree Graphs have Arbitrarily Large Geometric Thickness

The geometric thickness of a graph G is the minimum integer k such that there is a straight line drawing of G with its edge set partitioned into k plane subgraphs. Eppstein [Separating thickness from geometric thickness. In: Towards a Theory of Geometric Graphs, vol. 342 of Contemp. Math., AMS, 2004] asked whether every graph of bounded maximum degree has bounded geometric thickness. We answer this question in the negative, by proving that there exists Delta-regular graphs with arbitrarily large geometric thickness. In particular, for all Delta >= 9 and for all large n, there exists a Delta-regular graph with geometric thickness at least c Delta^{1/2} n^{1/2 - 4/Delta - epsilon}. Analogous results concerning graph drawings with few edge slopes are also presented, thus solving open problems by Dujmovic' et al. [Really straight graph drawings. In: Proc. 12th International Symp. on Graph Drawing (GD '04), vol. 3383 of Lecture Notes in Comput. Sci., Springer, 2004] and Ambrus et al. [The slope parameter of graphs. Tech. Rep. MAT-2005-07, Department of Mathematics, Technical University of Denmark, 2005].
The Impact of E-Commerce Strategies on Firm Value: Lessons from Amazon.com and its Early Competitors

Which strategies generate value in e-commerce environments? In a step towards answering this question, this paper estimates the impacts of several competitive strategies on the values of the well-known Internet retailer Amazon.com and three of its early competitors, BarnesandNoble.com, CDNOW, and N2K, from their IPO dates until exit or the end of 2001. The strategies analyzed include alliance formation, offline expansion, pricing, product line expansion, and service improvement. The results provide insight into the usefulness of various ways of competing online and could be applied in other settings where firms enter new environments about which they have little information.
Lightweight, High-Resolution Monitoring for Troubleshooting Production Systems

Production systems are commonly plagued by intermittent problems that are difficult to diagnose. This paper describes a new diagnostic tool, called Chopstix, that continuously collects profiles of low-level OS events (e.g., scheduling, L2 cache misses, CPU utilization, I/O operations, page allocation, locking) at the granularity of executables, procedures and instructions. Chopstix then reconstructs these events offline for analysis. We have used Chopstix to diagnose several elusive problems in a largescale production system, thereby reducing these intermittent problems to reproducible bugs that can be debugged using standard techniques. The key to Chopstix is an approximate data collection strategy that incurs very low overhead. An evaluation shows Chopstix requires under 1% of the CPU, under 256KB of RAM, and under 16MB of disk space per day to collect a rich set of system-wide data.
Intrusion detection using clustering

In increasing trends of network environment every one gets connected to the system. So there is need of securing information, because there are lots of security threats are present in network environment. A number of techniques are available for intrusion detection. Data mining is the one of the efficient techniques available for intrusion detection. Data mining techniques may be supervised or unsuprevised.Various Author have applied various clustering algorithm for intrusion detection, but all of these are suffers form class dominance, force assignment and No Class problem. This paper proposes a hybrid model to overcome these problems. The performance of proposed model is evaluated over KDD Cup 1999 data set.
A User-Study on Context-aware Group Recommendation for Concerts

In this paper, we present a prototype of a group recommendation system for concerts. The prototype is context sensitive taking the user’s location and time into account when giving recommendations. The prototype implements three algorithms to recommend concerts by taking advantage of what users have listened to before: a collaborative filtering algorithm (K-Nearest Neighbor), a Matrix Factorization algorithm, and a Hybrid approach combining these two. The usability of the prototype was evaluated using the System Usability Scale and a user centered evaluation was performed to evaluate the quality of recommendations. The results from the usability evaluation shows that users generally were satisfied with the usability of the prototype. The results from the Quality Evaluation shows that the KNearest Neighbor and Hybrid approach produces satisfactory results whereas the Matrix Factorization implementation was experienced to be a bit poorer. The users testing the prototype were generally satisfied with the quality of recommendations.
Secure Secret Recovery by using Weighted Personal Entropy

Authentication plays a vital role in many secure systems. Most of these systems require user to log in with his or her secret password or pass phrase before entering it. This is to ensure all the valuables information is kept confidential guaranteeing also its integrity and availability. However, to achieve this goal, users are required to memorize high entropy passwords or pass phrases. Unfortunately, this sometimes causes difficulty for user to remember meaningless strings of data. This paper presents a new scheme which assigns a weight to each personal question given to the user in revealing the encrypted secrets or password. Concentration of this scheme is to offer fault tolerance to users by allowing them to forget the specific password to a subset of questions and still recover the secret and achieve successful authentication. Comparison on level of security for weight-based and weightless secret recovery scheme is also discussed. The paper concludes with the few areas that requires more investigation in this research.
Mixed analog-digital pulse-width modulator for massive-MIMO transmitters

This paper presents a mixed-signal outphasing RF-PWM modulator with improved time resolution and high dynamic range realized in 40nm CMOS. Phase shifting is implemented using synchronously tapped analog delay lines comprising integrated L and C devices and achieving a fine-step delay of 2 ps while occupying acceptable silicon area and consuming zero power. The analog outputs of the delay lines are converted to CMOS-compatible square pulses that drive an AND gate which generates RF-PWM pulses with minimum pulse width of 10ps on a 50-Ohm load. According to system-integrated modulator co-simulation results, an ACLR of -45dBc is achieved from a 40 MHz baseband signal on a 2.65 GHz carrier.
The Tomato Prf Complex Is a Molecular Trap for Bacterial Effectors Based on Pto Transphosphorylation

The major virulence strategy of phytopathogenic bacteria is to secrete effector proteins into the host cell to target the immune machinery. AvrPto and AvrPtoB are two such effectors from Pseudomonas syringae, which disable an overlapping range of kinases in Arabidopsis and Tomato. Both effectors target surface-localized receptor-kinases to avoid bacterial recognition. In turn, tomato has evolved an intracellular effector-recognition complex composed of the NB-LRR protein Prf and the Pto kinase. Structural analyses have shown that the most important interaction surface for AvrPto and AvrPtoB is the Pto P+1 loop. AvrPto is an inhibitor of Pto kinase activity, but paradoxically, this kinase activity is a prerequisite for defense activation by AvrPto. Here using biochemical approaches we show that disruption of Pto P+1 loop stimulates phosphorylation in trans, which is possible because the Pto/Prf complex is oligomeric. Both P+1 loop disruption and transphosphorylation are necessary for signalling. Thus, effector perturbation of one kinase molecule in the complex activates another. Hence, the Pto/Prf complex is a sophisticated molecular trap for effectors that target protein kinases, an essential aspect of the pathogen's virulence strategy. The data presented here give a clear view of why bacterial virulence and host recognition mechanisms are so often related and how the slowly evolving host is able to keep pace with the faster-evolving pathogen.