Miracle-dz/UniFAR-FTUs huggingface dataset:
Event-to-sink reliable transport in wireless sensor networks

Wireless sensor networks (WSNs) are event-based systems that rely on the collective effort of several microsensor nodes. Reliable event detection at the sink is based on collective information provided by source nodes and not on any individual report. However, conventional end-to-end reliability definitions and solutions are inapplicable in the WSN regime and would only lead to a waste of scarce sensor resources. Hence, the WSN paradigm necessitates a collective event-to-sink reliability notion rather than the traditional end-to-end notion. To the best of our knowledge, reliable transport in WSN has not been studied from this perspective before. In order to address this need, a new reliable transport scheme for WSN, the event-to-sink reliable transport (ESRT) protocol, is presented in this paper. ESRT is a novel transport solution developed to achieve reliable event detection in WSN with minimum energy expenditure. It includes a congestion control component that serves the dual purpose of achieving reliability and conserving energy. Importantly, the algorithms of ESRT mainly run on the sink, with minimal functionality required at resource constrained sensor nodes. ESRT protocol operation is determined by the current network state based on the reliability achieved and congestion condition in the network. This self-configuring nature of ESRT makes it robust to random, dynamic topology in WSN. Furthermore, ESRT can also accommodate multiple concurrent event occurrences in a wireless sensor field. Analytical performance evaluation and simulation results show that ESRT converges to the desired reliability with minimum energy expenditure, starting from any initial network state.
Visual attention: low-level and high-level viewpoints

This paper provides a brief outline of the approaches to modeling human visual attention. Bottom-up and top-down mechanisms are described together with some of the problems that they face. It has been suggested in brain science that memory functions by trading measurement precision for associative power; sensory inputs from the environment are never identical on separate occasions, but the associations with memory compensate for the differences. A graphical representation for image similarity is described that relies on the size of maximally associative structures (cliques) that are found to reflect between pairs of images. This is applied to the recognition of movie posters, the location and recognition of characters, and the recognition of faces. The similarity mechanism is shown to model popout effects when constraints are placed on the physical separation of pixels that correspond to nodes in the maximal cliques. The effect extends to modeling human visual behaviour on the Poggendorff illusion.
Comments on IEEE 802.11 saturation throughput analysis with freezing of backoff counters

This letter presents an accurate model for the performance analysis of the IEEE 802.11 saturation throughput with freezing of the backoff counter. The model corrects the existing model presented by Ziouva and Antonakopoulos which assumes that the channel access probability and station collision probability are independent of channel status. Simulation results show the accuracy of the new model.
Sensors and Asymptotic w-observer for Distributed Diffusion Systems

The aim of this paper is to study the regional observer concept through the consideration of sensors. For a class of distributed diffusion systems, we propose an approach derived from the Luenberger observer type as introduced by Gressang and Lamont [1]. Furthermore, we show that the structures of sensors allow the existence of regional observer and we give a sufficient condition for each regional observer. We also show that, there exists a dynamical system for diffusion systems is not observer in the usual sense, but it may be regional observer.
Unemployment duration and sport participation: evidence from Germany

In this study I use the German Socio-Economic Panel to evaluate the impact of leisure sport participation on the unemployment duration. The empirical literature on sport participation has focused on labour market outcomes and job quality while the impact of this activity on job search has not been studied. However, sports participation fosters socialization which, through the networking effect, accelerates the exit from unemployment. Furthermore, there may be a selection effect of individuals with higher non-cognitive skills (which may optimize their job search). These hypotheses are tested using a duration model, taking into account unobservable heterogeneity. Because the timing of participation in sports activities is relevant, various measure of sport participation are tested as well as other activities
Vascular Complications After Balloon and New Device Angioplasty

BackgroundDespite their potential advantages, new coronary angioplasty devices may be associated with more frequent vascular complications than noted after standard balloon angioplasty, theoretically due to the larger sheaths and prolonged periods of anticoagulation required by some of these devices. This study sought to identify the incidence, predictors, and clinical outcome of vascular complications after new device angioplasty. Methods and ResultsThe clinical course of 1413 patients was reviewed after balloon or new device angioplasty. Vascular complications were defined as formation of a pseudoaneurysm, arteriovenous fistula, retroperitoneal hematoma, or groin hematoma associated with a >15-point hematocrit drop or the need for surgical repair. Stepwise logistic regression was used to identify independent predictors for vascular complications. Vascular complications developed after 84 (5.9%o) procedures; they occurred more frequently after intracoronary stenting (14.0%o) and extraction atherectomy (12.5%) than after balloon angioplasty (3.2%) (odds ratios, 4.86; P<.001, and 4.26, p<.05, respectively). Independent predictors of vascular complications included the use of intraprocedural thrombolytic agents (P<.01), intracoronary stenting (P<.005), or extraction atherectomy (P<.05); high maximum creatinine level (P<.005); low nadir platelet count (P<.001); longer periods of excess anticoagulation (P<.05); and the need for repeat coronary angioplasty (P<.005). Vascular complications were not related to the size of the arterial sheath used. ConclusionsVascular complications developed more frequently after new device angioplasty than after balloon angioplasty, with the risk for vascular complications directly related to the degree of periprocedural anticoagulation.
Language, Power, and Race: A Comparative Approach to the Sociopolitics of English

This thesis highlights the sociopolitics of English as a dominant/colonial language by focusing on the linkage between language, power, and race. Grounded in critical language theory, comparative education theory, and anti-racism research methodology, this research examines the inextricable relationship between language, power, and race. With this in mind, this thesis argues that language, specifically English, is not a neutral tool of communication but a highly contentious issue that is deeply embedded in sociopolitical ideologies and practices. The contexts of Japan and Trinidad and Tobago are used to illustrate how colonialism continues to impact English language policy, practice, and perceptions. In sum, this research aims to bridge the gap between critical language theory, comparative education theory, and anti-racism studies in a way that (1) highlights the complexity of language politics, (2) explores ideological assumptions inherent in the discourse of the “native” language, and (3) underscores the overlooked ubiquity of race.
Playing Pinball with non-invasive BCI

Compared to invasive Brain-Computer Interfaces (BCI), non-invasive BCI systems based on Electroencephalogram (EEG) signals have not been applied successfully for precisely timed control tasks. In the present study, however, we demonstrate and report on the interaction of subjects with a real device: a pinball machine. Results of this study clearly show that fast and well-timed control well beyond chance level is possible, even though the environment is extremely rich and requires precisely timed and complex predictive behavior. Using machine learning methods for mental state decoding, BCI-based pinball control is possible within the first session without the necessity to employ lengthy subject training. The current study shows clearly that very compelling control with excellent timing and dynamics is possible for a non-invasive BCI.
Kinesin is bound with high affinity to squid axon organelles that move to the plus-end of microtubules

This paper addresses the question of whether microtubule-directed transport of vesicular organelles depends on the presence of a pool of cytosolic factors, including soluble motor proteins and accessory factors. Earlier studies with squid axon organelles (Schroer et al., 1988) suggested that the presence of cytosol induces a > 20-fold increase in the number of organelles moving per unit time on microtubules in vitro. These earlier studies, however, did not consider that cytosol might nonspecifically increase the numbers of moving organelles, i.e., by blocking adsorption of organelles to the coverglass. Here we report that treatment of the coverglass with casein, in the absence of cytosol, blocks adsorption of organelles to the coverglass and results in vigorous movement of vesicular organelles in the complete absence of soluble proteins. This technical improvement makes it possible, for the first time, to perform quantitative studies of organelle movement in the absence of cytosol. These new studies show that organelle movement activity (numbers of moving organelles/min/micron microtubule) of unextracted organelles is not increased by cytosol. Unextracted organelles move in single directions, approximately two thirds toward the plus-end and one third toward the minus-end of microtubules. Extraction of organelles with 600 mM KI completely inhibits minus-end, but not plus-end directed organelle movement. Upon addition of cytosol, minus-end directed movement of KI organelles is restored, while plus--end directed movement is unaffected. Biochemical studies indicate that KI-extracted organelles attach to microtubules in the presence of AMP-PNP and copurify with tightly bound kinesin. The bound kinesin is not extracted from organelles by 1 M KI, 1 M NaCl or carbonate (pH 11.3). These results suggest that kinesin is irreversibly bound to organelles that move to the plus-end of microtubules and that the presence of soluble kinesin and accessory factors is not required for movement of plus-end organelles in squid axons.
A novel similar background components connection algorithm for colorful text detection in natural images

In this paper, a novel similar background components connection algorithm is presented to detect colorful texts. Before, the components were extracted accurately according to a color-based stroke width extraction rule proposed in the paper. In the stage of filtering non-text components, a specially designed metric is presented to adjust the parameter values of the filter, so that the filter is more robust under various conditions. Experiments on the ICDAR 2003 test set demonstrate that the proposed algorithm outperforms the state-of-the-art methods when detecting texts in same color. Furthermore, it achieves significantly performance on detecting colorful texts in natural images.
Open-loop and closed-loop recursive identification of an electro-hydraulic actuator system

This paper presents experimental work on recursive identification of an electro-hydraulic system that represented by a discrete-time model in open-loop and closed-loop configurations. A recursive least square (RLS) method is used to estimate the unknown parameters of the system based on auto regression with exogenous input (ARX) model. Residual analysis is utilized for a model validation. Results are presented which show variations in parameters of the electro-hydraulic system. From the results obtained, position tracking for electro-hydraulic system can be implemented by using conventional proportional-integral-derivative (PID) controller with the aim of the modeling validation.
Face recognition using multiple recognizers

In this paper we have presented a fusion of three face recognizers, LFA, LBA and KDDA, which combines the three confidence measure factors (CMFs) using a RBF neural network. This strategy is used to increase the accuracy of the face recognition system. The recognizer is tested on AT&T-ORL, AR and IITK face database and the results are found to be more than 95%.
Dynamic Harmony Search with Polynomial Mutation Algorithm for Valve-Point Economic Load Dispatch

Economic load dispatch (ELD) problem is an important issue in the operation and control of modern control system. The ELD problem is complex and nonlinear with equality and inequality constraints which makes it hard to be efficiently solved. This paper presents a new modification of harmony search (HS) algorithm named as dynamic harmony search with polynomial mutation (DHSPM) algorithm to solve ORPD problem. In DHSPM algorithm the key parameters of HS algorithm like harmony memory considering rate (HMCR) and pitch adjusting rate (PAR) are changed dynamically and there is no need to predefine these parameters. Additionally polynomial mutation is inserted in the updating step of HS algorithm to favor exploration and exploitation of the search space. The DHSPM algorithm is tested with three power system cases consisting of 3, 13, and 40 thermal units. The computational results show that the DHSPM algorithm is more effective in finding better solutions than other computational intelligence based methods.
HEALTH, FOOD SAFETY AND MEAT DEMAND

For nearly two decades, the U.S. beef industry has faced a long term structural change, which has resulted in consumers shifting from beef to chicken. This shift has occurred due to consumer concerns on cholesterol consumption. More recently, this industry has confronted new challenges on the safety of beef, due to the potential presence of biological contaminants. This study incorporates a measure on food safety with a measure on health information in a meat demand system. Beef safety information is found to have a modest impact on beef demand, but is dominated by health information.
BIST to Diagnosis Delay Fault in the LUT of Cluster Based FPGA

This work reports a novel scheme for testing and diagnosis of a delay fault in LUT of a cluster based FPGA. The solution is based on implementing a BISTer structure to diagnosis the delay fault of the LUT. The BUT is implemented by chaining k-number of Look-Up Tables (LUT) in specific way. The ORA used a polling scheme to determine the most suitable result and an ATPG will generate the optimum test pattern that will have full test coverage. The entire scheme was implemented and simulated for Virtex-II FPGA . Here the intention was to overcome the drawbacks of previously used method. A design example using the proposed method shows better result. The entire testing scheme can also be applied in On-Line testing environment by using Xilinx Jbits 3.0 API (Application Program Interface) for Xilinx Virtex-II FPGAs. Index Terms—Delay fault, FPGA, JBits, Look-up table (LUT), Testing.
Integration of Maximum Information Using Outerjoins, Predicates and Foreign Functions

The goal of this paper is to present algorithms for creating an optimized query plan for retrieving maximum information from multiple relations, using outerjoins. Especially we focus on conjunctive queries in the presence of predicates and foreign functions. We show first with examples that retrieving maximum information by integrating multiple relations requires outerjoin operators. The outerjoin is essential to prevent information loss that would be caused by the inner join. We also show that predicates and foreign functions are useful to mediate the discrepancy among the relations and to create arbitrary views. Outerjoins and foreign functions, together with predicates, make it difficult to create query processing plans since they impose restrictions on the order of query processing. The rest of this paper describes algorithms for creating such query processing plans for conjunctive queries expressed in extended Datalog. First, we show simple algorithms for creating query plans with outerjoins, but without predicates and foreign functions. We use the hypergraph representation of the relations to explain an optimized algorithm. Then, we show a more complex algorithm that works for query plans with predicates and foreign functions. In our algorithm, we create an initial expression graph whose nodes represent query processing units, including outerjoin, predicate and foreign function operators. Then, we convert the initial expression graph into an executable, optimized expression tree. This algorithm is implemented and deployed in a mediation system that integrates heterogeneous information sources. key words: database, query processing, outerjoin, integration
Associative Memory-Based Reasoning

Through analogy, novel situations and problems can be understood in terms of familiar ones. There is converging evidence that analogy-making lies at the very core of human cognition. Conversely, successful analogy-making requires the resources of an entire cognitive architecture. This book describes a computational model of analogy-making called AMBR (Associative Memory-Based Reasoning). AMBR is based on a hybrid symbolic-connectionist multi-agent cognitive architecture called DUAL. Macroscopic behavior in DUAL emerges from the interactions of simple processing agents in dynamic coalitions. Unlike the mainstream models of analogy-making, AMBR uses a decentralized representational scheme for problems and situations. The dynamic emergent processing of these decentralized representations is consistent with the context-sensitive and constructive nature of human memory. Both DUAL and AMBR were developed by Boicho N. Kokinov and his graduate students at New Bulgarian University. This book is a revised and expanded version of the author's Ph.D. thesis written under Prof. Kokinov's supervision at NBU. It will be of interest to cognitive modelers and cognitive scientists more generally.
A Family of Activity-Dependent Neuronal Cell-Surface Chondroitin Sulfate Proteoglycans in Cat Visual Cortex

Monoclonal antibody Cat-301 recognizes a chondroitin sulfate proteoglycan (CSPG) expressed on the extracellular surface of cell bodies and proximal dendrites of specific subsets of neurons in many areas of the mammalian CNS, including the cat visual cortex. The Cat-301 CSPG is first detected at the close of the critical period in development, a period during which the pattern of neuronal activity determines the mature synaptic circuitry and neuronal phenotype. In the cat visual cortex, dark-rearing from birth prolongs the duration of the critical period and attenuates the expression of the Cat-301 antigen, implicating the Cat-301 CSPG in the cellular mechanisms that terminate the period of synaptic plasticity. Because the Cat-301 antigen is expressed on only a limited subset of neurons, we have further examined the molecular heterogeneity among neuronal cell-surface CSPGs and have asked (1) whether other neuronal subsets carry distinct CSPGs and (2) whether the activity-dependent expression of the Cat-301 CSPG is a property generalizable to related cell-surface CSPGs. Here, we report two new monoclonal antibodies, Cat-315 and Cat-316, which together with Cat-301 define a family of at least seven related yet distinct CSPGs. These three antibodies define nonidentical subsets of neurons in the cat visual cortex. The expression of normal levels of these CSPGs is reduced by dark-rearing. Together, these data show that the family of cell-surface CSPGs is molecularly diverse, that different sets of neurons express distinct complements of cell-surface antigens, and that the regulation of CSPG expression by activity may be a general feature of neuronal cell-surface CSPGs.
Improving Pedestrian Detection Using Support Vector Regression

Pedestrian detection has been always a challenging problem in computer vision. Numerous approaches based on features extraction and classification have been proposed over the years. In this paper, we present a novel pedestrian detection approach based on supervised classification. We propose here the use of basic statistical operators to adapt support vector regression (SVR) to binary classification. The classification chain adopted in this work is presented as follows: First, we use Haar wavelet decomposition and Histograms of Oriented Gradients (HOG) for features extraction. For the classification task, we use our proposed method and compare it with KNN and SVM classifiers. Experiments have been done on a public pedestrian data set. The obtained results prove the high performance of our proposed classification approach.
Understanding successful principal leadership: progress on a broken front

Purpose – To synthesize the results of the seven country reports covered in the special issue of JEA on successful school principalship.Design/methodology/approach – Presents the main themes of the articles with their main implications and benefits. Examines the different models.Findings – The country reports provide encouraging signs of progress in addressing this limitation. Such progress seems primarily due to the development of multiple cases, over time, within each country. This allows for ongoing refinement of ideas and data collection techniques, eventually resulting in the cross‐case reports appearing in this issue. These reports provide some indication, as well, that researchers are beginning to learn from their colleagues in other countries.Originality/value – Summarizes multiple case studies of successful principal leadership in seven countries.
Obfuscation of sensitive data in network flows

In the last decade, the release of network flows has gained significant popularity among researchers and networking communities. Indeed, network flows are a fundamental tool for modeling the network behavior, identifying security attacks, and validating research results. Unfortunately, due to the sensitive nature of network flows, security and privacy concerns discourage the publication of such datasets. On the one hand, existing techniques proposed to sanitize network flows do not provide any formal guarantees. On the other hand, microdata anonymization techniques are not directly applicable to network flows. In this paper, we propose a novel obfuscation technique for network flows that provides formal guarantees under realistic assumptions about the adversary's knowledge. Our work is supported by extensive experiments with a large set of real network flows collected at an important Italian Tier II Autonomous System, hosting sensitive government and corporate sites. Experimental results show that our obfuscation technique preserves the utility of network flows for network traffic analysis.
Finding with the Crowd Anish

We consider the problem of using humans to nd a bounded number of items satisfying certain properties, from a data set. For instance, we may want humans to identify a select number of travel photos from a data set of photos to display on a travel website, or a candidate set of resumes that meet certain requirements from a large pool of applicants. Since data sets can be enormous, and since monetary cost and latency of data processing with humans can be large, optimizing the use of humans for nding items is an important challenge. We formally dene the problem using the metrics of cost and time, and design optimal algorithms that span the skyline of cost and time, i.e., we provide designers the ability to control the cost vs. time trade-o. We study the deterministic as well as error-prone human answer settings, along with multiplicative and additive approximations. Lastly, we study how we may design algorithms with specic expected cost and time measures.