Miracle-dz/UniFAR-FTUs huggingface dataset:
Closer destination selection scheme for mobile sink and charger enabled WRSNs

In WRSNs (Wireless Rechargeable Sensor Networks), the wireless energy transfer technology enables charging sensor batteries and maintaining perpetual operation of the network. The MC (mobile charger) is able to provide stable and reliable energy supply for sensor nodes. Although many researchers study the efficient scheduling of the MC, none of them considers the situation where both the static sink and the MC can collect packets. In this case, each sensor node should choose the appropriate destination, i.e., the static sink or the MC. In this paper, we propose closer destination selection scheme for mobile sink and charger enabled WRSNs where a static sink and an MC coexist. In order for each sensor node to send packets to the closer destination, i.e., the static sink or the MC, when an MC tours to charge sensor nodes, it constructs another temporal tree-based topology network by sending a route construction packet to sensor nodes within the limited area. Whenever the MC stays at a sensor node, it calculates the maximum number of hops that sensor nodes should switch to a temporal network. This temporal network that the MC creates does not disturb the original network. By constructing a temporal network, an MC relaxes the load of sensor nodes around the static sink without unnecessary path extension. We evaluate the performance of our scheme through the computer simulation. Results indicate that our scheme improves the packet arrival rate and energy efficiency compared to the conventional scheme.
Preventing Human Error : Developing a Consensus Led Safety Culture based on Best Practice

The first section of the paper discusses the relationship between ‘Best Practice’ and formal procedures in high-risk systems such as chemical processing, aerospace and transportation. The results of a survey, which addressed the factors influencing the use of procedures in a high-risk industry, are described. This and other evidence shows that there is often a wide disparity between the formal written procedures in an organisation and the ways in which the work is actually carried out. This has major implications for the control of risks and the maintenance of quality. The paper describes how a culture can be created in which operations staff actively participates in assessing the risks in the system and developing best practices to control these risks. The buy–in provided by this process creates a culture where best practices become the preferred practices. A comprehensive description of this process, called CARMAN (Consensus based Approach to Risk Management) is provided, together with a set of case studies illustrating its application.
Threshold based algorithms for UXO detection using magnetometry

Iron buried objects induce anomalies in the earth's magnetic field that appear on the surface below items and that can be measured by a magnetometer. In this work, two approaches already used in radar detection are introduced and modified to improve the UXO detection. The measurement noises, the weak value of the earth's magnetic field and the variations due to the soil heterogeneity increase the false alarm probability. In order to reduce this last, we introduce a cell-averaging-based threshold algorithm used in radar detection. It consists of doing a comparison between each measure and a weighted average of the neighbor measures. The proposed algorithm is validated using simulation data and promising results have been obtained.
Sentiment Classification with Graph Co-Regularization

Sentiment classification aims to automatically predict sentiment polarity (e.g., positive or negative) of user-generated sentiment data (e.g., reviews, blogs). To obtain sentiment classification with high accuracy, supervised techniques require a large amount of manually labeled data. The labeling work can be time-consuming and expensive, which makes unsupervised (or semisupervised) sentiment analysis essential for this application. In this paper, we propose a novel algorithm, called graph co-regularized non-negative matrix tri-factorization (GNMTF), from the geometric perspective. GNMTF assumes that if two words (or documents) are sufficiently close to each other, they tend to share the same sentiment polarity. To achieve this, we encode the geometric information by constructing the nearest neighbor graphs, in conjunction with a nonnegative matrix tri-factorization framework. We derive an efficient algorithm for learning the factorization, analyze its complexity, and provide proof of convergence. Our empirical study on two open data sets validates that GNMTF can consistently improve the sentiment classification accuracy in comparison to the state-of-the-art methods.
Place and Psychoanalysis

In this article, we highlight the importance of psychoanalysis and the Heideggerian concept of ‘place’ for each respective domain of inquiry. In particular, the writings of Jung and Lacan can unconceal and reveal new dimensions of Jeff Malpas’s work on place. Alternatively, Malpas can extend the work of these psychoanalysts by showing new dimensions of their ideas through an analysis of ‘place’. Ultimately, this article sets up a number of possibilities for future research through this novel interaction and engagement between the philosophy of place and psychoanalysis. One of these possibilities is in genomics and genetic determinism, which we briefly acknowledge throughout.
In vitro toxicity of melamine against Tetrahymena pyriformis cells

This study assessed the toxicity of melamine against the unicellular eukaryotic system of Tetrahymena (T.) pyriformis exposed to 0, 0.05, 0.25, 0.5, 2.5, and 5 mg/mL of melamine. Cell growth curves of different cultures, the half maximum inhibition concentration (IC50) value of melamine, and morphological changes in cells were obtained via optical and transmission electron microscopic observation. The effects of eleven melamine concentrations, 0.25, 0.5, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5 and 5 mg/mL, on protein expression levels of T. pyriformis were examined using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). The results showed an obvious inhibitory effect of melamine on the growth of eukaryotic cells. Cell growth dynamics indicated that the IC50 value of melamine on T. pyriformis was 0.82 mg/mL. The cellular morphology was also affected in a concentration-dependent manner, with characteristics of atrophy or cell damage developing in the presence of melamine. The relative contents of the top four main proteins corresponding to peak mass-to-charge ratios (m/z) of 4466, m/z 6455, m/z 6514, and m/z 7772 in the MALDI-TOF-MS spectra were all found to be closely correlated with the melamine concentrations. In conclusion, exposure of eukaryotic cells to melamine could inhibit cell growth, cause changes in cytomorphology and even disturb the expression of proteins in a concentration-dependent manner. The described method of examining four sensitive proteins affected by melamine was also proposed to be used in a preliminary study to identify protein biomarkers in T. pyriformis.
Unsupervised Local Spatial Mixture Segmentation of Underwater Objects in Sonar Images

In this paper, we focus on the segmentation of sonar images to achieve underwater object detection and classification. Our goal is to achieve accurate segmentation of the object's highlight and shadow regions. We target a robust solution that can manage different seabed backgrounds. Segmentation of sonar images is a challenging task. Speckle noise and intensity inhomogeneity may cause false detections and complex seabed textures, such as sand ripples and seagrass, often leading to false segmentation. In this paper, we propose our local spatial mixture (LSM) method for image segmentation of sidescan deployed sonar systems of any type. This new method estimates pixel labels in sonar images by incorporating the possible spatial correlation between neighboring pixels for improved segmentation. LSM modifies the expectation–maximization algorithm by adding an intermediate step (I-step) between the expectation (E-step) and maximization (M-step) steps. To combat intensity inhomogeneity, we employ a new initialization algorithm, one whose thresholds are set automatically to achieve and maintain robustness in various underwater environments. Using multiple evaluation indexes that measure the geometrical features of the segmented objects, we tested LSM using synthetic and real sonar images, one of which is obtained from our own sea experiment. Our results show that LSM achieves improved segmentation performance over the state-of-the-art methods of four different approaches; LSM is also robust to different seabed textures and intensity inhomogeneity. We share the sonar images from our sea experiments.
Mining Sequential Patterns and Tree Patterns to Detect Erroneous Sentences

An important application area of detecting erroneous sentences is to provide feedback for writers of English as a Second Language. This problem is difficult since both erroneous and correct sentences are diversified. In this paper, we propose a novel approach to identifying erroneous sentences. We first mine labeled tree patterns and sequential patterns to characterize both erroneous and correct sentences. Then the discovered patterns are utilized in two ways to distinguish correct sentences from erroneous sentences: (1) the patterns are transformed into sentence features for existing classification models, e.g, SVM; (2) the patterns are used to build a rule-based classification model. Experimental results show that both techniques are promising while the second technique outperforms the first approach. Moreover, the classification model in the second proposal is easy to understand, and we can provide intuitive explanation for classification results.
Fuzzy Propositional Formulas under the Stable Model Semantics.

We define a stable model semantics for fuzzy propositional formulas, which generalizes both fuzzy propositional logic and the stable model semantics of classical propositional formulas. The syntax of the language is the same as the syntax of fuzzy propositional logic, but its semantics distinguishes stable models from non-stable models. The generality of the language allows for highly configurable nonmonotonic reasoning for dynamic domains involving graded truth degrees. We show that several properties of Boolean stable models are naturally extended to this many-valued setting, and discuss how it is related to other approaches to combining fuzzy logic and the stable model semantics.
User perceptions of evaluation criteria for three system types

Information systems are often evaluated by different groups of users. Differences in users could create difficulties in assigning weights to evaluation criteria using methods such as multiattribute utility theory. Of additional concern is the type of system under evaluation. This study finds that user differences in the perceived importance of various evaluation criteria do not exist as anticipated in the literature, but that differences do exist for system types.
Sensor Modeling for Aerial Triangulation with Three-Line-Scanner (TLS) Imagery

This article describes the sensor modeling and the photogrammetric triangulation procedure for the TLS (Three-Line-Scanner) system. This system is a new airborne digital sensor, developed by STARLABO Corporation, Tokyo jointly with the Institute of Industrial Science, University of Tokyo. It utilizes the Three-Line-Scanner principle to capture digital image triplets in along-strip mode. The imaging system contains three times three (RGB) one-dimensional CCD arrays, with 10 200 pixels of 7μm each, mounted parallel to each other in the focal plane. They produce seamless high-resolution images (5-10 cm footprint on the ground) with three viewing directions (forward, nadir and backward). In order to get precise attitude data and high quality image data from an aerial platform, a high quality stabilizer stabilizes the camera and outputs attitude data at 500 Hz. A Trimble MS750 serves as Rover GPS and collects L1/L2 kinematic data at 5 Hz and another Trimble MS750 serves as Base GPS on the ground. The position and attitude elements measured by the on-board GPS/INS do not refer to the perspective center of the imaging camera. Additionally, there is a boresight misalignment between the axes of the INS and the camera. These translational and rotational offsets have been taken into account in our sensor model and triangulation procedures. In our experiments, the following 3 trajectory model are evaluated: (a) Direct georeferencing with stochastic exterior orientations (DGR), (b) Piecewise Polynomials with kinematic model up to second order and stochastic first and second order constraints (PPM) and (c) Lagrange Polynomials with variable orientation fixes (LIM). With different numbers and distributions of control points and tie points, 4.9-6.3 cm and 8.6-9.4 cm absolute accuracy in planimetry and height is achieved using the DGR model under the condition that the GPS/camera displacement corrections have been applied. Moreover, with different numbers of spline sections or orientation fixes, 2.6-6.0 cm and 4.9-11.7 cm absolute accuracy in planimetry and height is attained using the PPM and LIM models. These results show that a ground point determination of 0.5-1.2 pixel accuracy in planimetry and 0.7-2.1 pixel accuracy in height has been achieved. The orientation parameter determination using the DGR model has the advantage of stability and needs less control points, but the obtained accuracy is better with the PPM and LIM models. This however is penalized by the need to have more well-distributed control and tie points.
Measuring individual legitimacy perceptions: Scale development and validation

To fully understand legitimacy as a complex construct, it is necessary to capture both collective perceptions and individual judgments. Much of the empirical research on legitimacy has focused on measuring the collective perceptions of groups of evaluators or critical institutions. This research develops and validates a psychometric measure of individual perceptions of pragmatic, moral, and cognitive legitimacy. Across seven studies, we demonstrate consistent reliability and scale structure, as well as convergent, discriminant, nomological, and predictive validity. We further show the generalizability and robustness of the measure across a variety of organizations and industries. This measure will advance empirical research on legitimacy by enabling researchers to capture the perceptions of individual evaluators directly and permit the comparison of results across studies.
A Lightweight Formalization of the Metatheory of Bisimulation-Up-To

Bisimilarity of two processes is formally established by producing a bisimulation relation that contains those two processes and obeys certain closure properties. In many situations, particularly when the underlying labeled transition system is unbounded, these bisimulation relations can be large and even infinite. The bisimulation-up-to technique has been developed to reduce the size of the relations being computed while retaining soundness, that is, the guarantee of the existence of a bisimulation. Such techniques are increasingly becoming a critical ingredient in the automated checking of bisimilarity. This paper is devoted to the formalization of the meta theory of several major bisimulation-up-to techniques for the process calculi CCS and the π-calculus (with replication). Our formalization is based on recent work on the proof theory of least and greatest fixpoints, particularly the use of relations defined (co-)inductively, and of co-inductive proofs about such relations, as implemented in the Abella theorem prover. An important feature of our formalization is that our definitions of the bisimulation-up-to relations are, in most cases, straightforward translations of published informal definitions, and our proofs clarify several technical details of the informal descriptions. Since the logic behind Abella also supports λ-tree syntax and generic reasoning using the ∇-quantifier, our treatment of the λ-calculus is both direct and natural.
An Effective Resource Allocation Scheme in Relay Enhanced LTE -

Long Term Evolution-Advanced (LTE-A) is a mobile communication standard of high-speed data for mobile phones and data terminals. LTE-A inherits all basic technologies of LTE such as Orthogonal Frequency Division multiplexing access, Multiple Input Multiple Output, Flexible bandwidth and Provides new features to improve the capacity and Performance. Some of the new features supports by LTE-A are: wider Bandwidth, Advanced Multiple Input Output Technique, Co-operative Multiple Transmission and Reception, Relaying. LTE-Advanced will have to co-exist with 2G and 3G cellular systems for some time, so interworking necessities, resource management, potential interference etc. remain an important issues. The role of Radio Resource Management (RRM) is to ensure that the radio resources are efficiently used, taking advantage of the available adaptation techniques, and to serve the users according to their configured Quality of Service (QoS) parameters. To facilitate the resource assignment, Relay techniques provided a high degree of flexibility in terms of the types of RNs, type of deployment, functions performed by Relay Node (RN), and protocol definitions. Determining the best relay is a challenging task and requires a best selection algorithm because the relays are geographically separated and only have local channel knowledge. Selecting the bets relay is equivalent to the relay with the largest metric, where each relay computes its metric using local channel knowledge, in order to meet the performance targets such as cell edge throughput, user fairness, minimizing power consumption.
Distance Transformation for Effective Dimension Reduction of High-Dimensional Data

In this paper we address the problem of high-dimensionality for data that lies on complex manifolds. In high-dimensional spaces, distances between the nearest and farthest neighbour tend to become equal. This behaviour hardens data analysis, such as clustering. We show that distance transformation can be used in an effective way to obtain an embedding space of lower-dimensionality than the original space and that increases the quality of data analysis. The new method, called High-Dimensional Multimodal Embedding (HDME) is compared with known state-of-the-art methods operating in high-dimensional spaces and shown to be effective both in terms of retrieval and clustering on real world data.
Discourse Contribution of Enumerative Structures involving "pour deux raisons"

In this article, we propose to study the discourse contribution of enumerative structures involving the prepositional phrase pour deux raisons. We would like to highlight the contribution of the textual information conveyed by enumerative structures and the prepositional phrase both to the discourse structure and the discourse content within the SDRT model. We will show that prepositional phrase like pour deux raisons must introduce a discourse constituent in the structure attached by the Commentary relation to the left context and the Enumeration relation to the right context. Finally we propose to treat pour deux raisons as a new kind of discourse marker: we will show that its discursive role within enumerative structures is to signal the content-level relation Explanation.
Predicting irrigation return flows to river systems: Conceptualisation and model development of an irrigation area return flow model

Irrigated agricultural uses 72% of total water diversions in Australia and its potential to generate returns flows to river systems in terms of both quantity and quality is significant. Increased hydraulic loading under irrigation and changes in land use has lead to high water tables and land salinisation and sodification. Drainage schemes have been implemented to reduce the consequences of land salinisation. These drainage schemes contribute large amounts of salt, nutrients and sediments into natural water courses and have lead to a decline in water quality in rivers and reduced health in riverine ecosystems.
Infidelity Goes Online: Communicating About Sexual Health in Personal Ads When Seeking Extra-Dyadic Relationships on Craigslist

Abstract Objectives: The present study explored married and partnered individuals’ ads on Craigslist seeking extra-dyadic sexual relationships. An analysis of the ads containing words related to health and safety was conducted to better understand the ways that individuals communicate about safe sex when seeking extra-dyadic relationships online. Methods: A total of 819 ads containing 6,279 words were analyzed. Thematic analysis revealed that the words used in the ads fell into 8 unique categories, with one category comprising words related to health and safety. Results: The results revealed that men seeking men used more words related to health and safety than men seeking women, women seeking men, and women seeking women, though ads within all 4 groups noted health and safety concerns. For men seeking women, broader issues of safety (often pertaining to meeting up) were also expressed, and for women seeking men, issues of discretion arose. Lastly, women seeking women were the only group to mention polyamorous or nonmonogamous relationships, in addition to expressing concerns about sexual safety. Conclusions: The findings revealed that partnered or married men seeking sexual activity with other men posted the most ads and had the largest percentages for several key words related to safe sex, though such concerns were also prevalent in the ads of men seeking women, women seeking women, and to a limited degree (given the small sub-sample), women seeking men. These results suggest that interventions should aim at encouraging individuals who seek relationships online to not only state safe sex preferences and concerns, but also to continue such conversations and implement safe sex behaviors in offline contexts.
Finding minimum representative pattern sets

Frequent pattern mining often produces an enormous number of frequent patterns, which imposes a great challenge on understanding and further analysis of the generated patterns. This calls for finding a small number of representative patterns to best approximate all other patterns. An ideal approach should 1) produce a minimum number of representative patterns; 2) restore the support of all patterns with error guarantee; and 3) have good efficiency. Few existing approaches can satisfy all the three requirements. In this paper, we develop two algorithms, MinRPset and FlexRPset, for finding minimum representative pattern sets. Both algorithms provide error guarantee. MinRPset produces the smallest solution that we can possibly have in practice under the given problem setting, and it takes a reasonable amount of time to finish. FlexRPset is developed based on MinRPset. It provides one extra parameter K to allow users to make a trade-off between result size and efficiency. Our experiment results show that MinRPset and FlexRPset produce fewer representative patterns than RPlocal---an efficient algorithm that is developed for solving the same problem. FlexRPset can be slightly faster than RPlocal when K is small.