Miracle-dz/UniFAR-FTUs huggingface dataset:
Planning Smooth and Obstacle-Avoiding B-Spline Paths for Autonomous Mining Vehicles

We study the problem of automatic generation of smooth and obstacle-avoiding planar paths for efficient guidance of autonomous mining vehicles. Fast traversal of a path is of special interest. We consider fourwheel four-gear articulated vehicles and assume that we have an a priori knowledge of the mine wall environment in the form of polygonal chains. Computing quartic uniform B-spline curves, minimizing curvature variation, staying at least at a proposed safety margin distance from the mine walls, we plan high speed paths. We present a study where our implementations are successfully applied on eight path-planning cases arising from real-world mining data provided by the Swedish mining company Luossavaara-Kiirunavaara AB (LKAB). The results from the study indicate that our proposed methods for computing obstacle-avoiding minimum curvature variation B-splines yield paths that are substantially better than the ones used by LKAB today. Our simulations show that, with an average 32.13%, the new paths are faster to travel along than the paths currently in use. Preliminary results from the production at LKAB show an overall 5%-10% decrease in the total time for an entire mining cycle. Such a cycle includes both traveling, ore loading, and unloading.
Caring for the community : An exploratory comparison of waste reduction behaviour by British and Brazilian consumers

Purpose – The symbolic and social roles of waste are explored through a small sample of UK and Brazilian consumers from urban and rural communities. These findings are relevant in highlighting the importance of considering socio‐cultural differences in waste policies.Design/methodology/approach – Following an ontologically realist and epistemologically interpretive perspective on waste a series of semi‐structured interviews was conducted in English and Portuguese.Findings – While Brazilian interviewees view waste as opportunity, their discourses reproduce the inequalities among and between their communities. UK participants view waste as burdensome, but demonstrate more awareness of their rights as citizens within their communities.Research limitations/implications – The study is exploratory and future work should address a broader range of respondents within communities across different cultures, demographic and socio‐economic circumstances.Practical implications – Ideas generated from the study have bot.
Neurologic Outcomes of Preoperative Acute Silent Cerebral Infarction in Patients with Cardiac Surgery

Background Acute cerebral infarction is a major risk factor for postoperative neurologic complications in cardiac surgery. However, the outcomes associated with acute silent cerebral infarction (ASCI) have not been not well established. Few studies have reported the postoperative outcomes of these patients in light of preoperative Diffusion-weighted magnetic resonance imaging (DWI). We studied the postoperative neurologic outcomes of patients with preoperative ASCI detected by DWI. Methods We retrospectively studied 32 patients with preoperative ASCI detected by DWI. None of the patients had preoperative neurologic symptoms. The mean age at operation was 68.8±9.5 years. Five patients had previous histories of stroke. Four patients had been diagnosed with infective endocarditis. Single cerebral infarct lesions were detected in 16 patients, double lesions in 13, and multiple lesions (>5) in three. The median size of the infarct lesions was 4 mm (range, 2 to 25 mm). The operations of three of the 32 patients were delayed pending follow-up DWI studies. Results There were two in-hospital mortalities. Neurologic complications also occurred in two patients. One patient developed extensive cerebral infarction unrelated to preoperative infarct lesions. One patient showed sustained delirium over one week but recovered completely without any neurologic deficits. In two patients, postoperative DWI confirmed that no significant changes had occurred in the lesions. Conclusion Patients with preoperative ASCI showed excellent postoperative neurologic outcomes. Preoperative ASCI was not a risk factor for postoperative neurologic deterioration.
Two Chikungunya Isolates from the Outbreak of La Reunion (Indian Ocean) Exhibit Different Patterns of Infection in the Mosquito, Aedes albopictus

Background A Chikungunya (CHIK) outbreak hit La Réunion Island in 2005–2006. The implicated vector was Aedes albopictus. Here, we present the first study on the susceptibility of Ae. albopictus populations to sympatric CHIKV isolates from La Réunion Island and compare it to other virus/vector combinations. Methodology and Findings We orally infected 8 Ae. albopictus collections from La Réunion and 3 from Mayotte collected in March 2006 with two Chikungunya virus (CHIKV) from La Réunion: (i) strain 05.115 collected in June 2005 with an Alanine at the position 226 of the glycoprotein E1 and (ii) strain 06.21 collected in November 2005 with a substitution A226V. Two other CHIKV isolates and four additional mosquito strains/species were also tested. The viral titer of the infectious blood-meal was 107 plaque forming units (pfu)/mL. Dissemination rates were assessed by immunofluorescent staining on head squashes of surviving females 14 days after infection. Rates were at least two times higher with CHIKV 06.21 compared to CHIKV 05.115. In addition, 10 individuals were analyzed every day by quantitative RT-PCR. Viral RNA was quantified on (i) whole females and (ii) midguts and salivary glands of infected females. When comparing profiles, CHIKV 06.21 produced nearly 2 log more viral RNA copies than CHIKV 05.115. Furthermore, females infected with CHIKV 05.115 could be divided in two categories: weakly susceptible or strongly susceptible, comparable to those infected by CHIKV 06.21. Histological analysis detected the presence of CHIKV in salivary glands two days after infection. In addition, Ae. albopictus from La Réunion was as efficient vector as Ae. aegypti and Ae. albopictus from Vietnam when infected with the CHIKV 06.21. Conclusions Our findings support the hypothesis that the CHIK outbreak in La Réunion Island was due to a highly competent vector Ae. albopictus which allowed an efficient replication and dissemination of CHIKV 06.21.
Disguised Chromium Browser: Robust Browser, Flash and Canvas Fingerprinting Protection

Browser fingerprinting is a widely used technique to uniquely identify web users and to track their online behavior. Until now, different tools have been proposed to protect the user against browser fingerprinting. However, these tools have usability restrictions as they deactivate browser features and plug-ins (like Flash) or the HTML5 canvas element. In addition, all of them only provide limited protection, as they randomize browser settings with unrealistic parameters or have methodical flaws, making them detectable for trackers. In this work we demonstrate the first anti-fingerprinting strategy, which protects against Flash fingerprinting without deactivating it, provides robust and undetectable anti-canvas fingerprinting, and uses a large set of real word data to hide the actual system and browser properties without losing usability. We discuss the methods and weaknesses of existing anti-fingerprinting tools in detail and compare them to our enhanced strategies. Our evaluation against real world fingerprinting tools shows a successful fingerprinting protection in over 99% of 70.000 browser sessions.
The Effects of Types of Decision-Making and Collaborative Information Processing on Collaboration Performance, and Social Support and Collaboration Load among Collaborators in CSCL

This study investigate the process of thinking required by individual learners in collaborative learning and the process of collaborative learning from the perspective of information processing and suggest a specific process of collaborative information processing with information externalization to make effective collaboration performance. In particular, the body of research mainly focused on the optimal process of information processing on the basis of individual learners’ types of decision-making.
Double scaling limit in the random matrix model: The Riemann‐Hilbert approach

We prove the existence of the double scaling limit in the unitary matrix model with quartic interaction, and we show that the correlation functions in the double scaling limit are expressed in terms of the integrable kernel determined by the ψ function for the Hastings‐McLeod solution to the Painlevé II equation. The proof is based on the Riemann‐Hilbert approach, and the central point of the proof is an analysis of analytic semiclassical asymptotics for the ψ function at the critical point in the presence of four coalescing turning points. © 2003 Wiley Periodicals, Inc.
Combining Associative and Navigational Access in Persistent Object Stores

We introduce an approach allowing to support queries involving both navigation along references (i.e. navigational access) and imposition of conditions on object data (i.e. associative access) in Persistent Object Stores. Our approach does not directly rely on the knowledge of the database schema and of the queries to be supported, and thus can be used to support ad-hoc querying of semistructured data. The basic access structures it uses (i.e. selector meta-objects representing sets of values connected via references to database objects and references) are stable with respect to changes in database data in a sense that changes in the value of one object do not necessitate changes of the elements of the support structure facilitating access to other objects. In addition, we propose an extension of the matrix index approach to support navigational access such that main memory space usage is decreased. Also, we demonstrate how matrix index coding can be enhanced further to support the combined navigational and associative access by providing guarantees for encoded object sequences by referencing selector meta-objects.
Detecting movement patterns using Brownian bridges

In trajectory data a low sampling rate leads to high uncertainty in between sampling points, which needs to be taken into account in the analysis of such data. However, current algorithms for movement analysis ignore this uncertainty and assume linear movement between sample points. In this paper we develop a framework for movement analysis using the Brownian bridge movement model (BBMM), that is, a model that assumes random movement between sample points. Many movement patterns are composed from basic building blocks, like distance, speed or direction. We efficiently compute their distribution over space and time in the BBMM using parallel graphics hardware. We demonstrate our framework by computing patterns like encounter, avoidance/attraction, regular visits, and following. Our motivation to study the BBMM stems from the rapidly expanding research paradigm of movement ecology. To this end, we provide an interface to our framework in R, an environment widely used within the natural sciences for statistical computing and modeling, and present a study on the simultaneous movement of groups of wild and free-ranging primates.
Enhancing Text Clustering Using Concept-based Mining Model

1 PG Scholar,Department of CSE, Adhiyamaan College of Engineering, Hosur, TamilNadu, India. liptha24@yahoo.com Professor, Department of CSE,Adhiyamaan College of Engineering, Hosur, TamilNadu, India. ckrajacse@gmail.com 2 Principal, Jayam college of Engineering and Techno logy, Dharmapuri, TamilNadu, India. AbstractText Mining techniques are mostly based on statistical analysis of a word or phrase. The statistical analysis of a term frequency captures the importance of the term without a document only. But two terms can have the same frequency in the same document. But the meaning that one term contributes might be more appropriate than the meaning contributed by the other term. Hence, the terms that capture the semantics of the text should be given more importance. Here, a new concept-based mining is introduced. It analyses the terms based on the sentence, document and corpus level. The model consists of sentence-based concept analysis which calculates the conceptual term frequency (ctf), document-based concept analysis which finds the term frequency (tf), corpus-based concept analysis which determines the document frequency (df) and concept-based similarity measure. The process of calculating ctf, tf, df, measures in a corpus is attained by the proposed algorithm which is called Concept-Based Analysis Algorithm. By doing so we cluster the web documents in an efficient way and the quality of the clusters achieved by this model significantly surpasses the traditional single-term-base approaches.
Highly Scalable X10-Based Agent Simulation Platform and Its Application to Large-Scale Traffic Simulation

This paper describes highly scalable X10-based agent simulation platform called XAXIS. XAXIS is designed to handle millions or billions of agents on recent highly distributed and parallel computing environments with more than hundreds of CPU cores. To make the runtime scalable on such environments, we need to redesign and implement the simulation middleware. In this paper, we propose the software design, implementation on X10, one of the state-of-the-art PGAS language, and then application to large-scale traffic simulation. By using 192 CPU cores in distributed memory computing environment, the performance scalability is achieved with a traffic simulation.
Software optimization for embedded communication system

This paper presents general software optimization techniques to improve software performance and energy consumption in embedded systems. Software optimization can be categorized into three levels: algorithmic, source code-level. Then these techniques are applied to optimize our tactical message processing software, which is a message encoder-decoder for tactical communication equipped on weapon systems. The optimized software achieved performance increase of about 12%, memory access decrease of 72% and memory usage decrease of 35% over the original software.
Particle Acceleration by Fast Modes in Solar Flares

We address the problem of particle acceleration in solar flares by fast modes which may be excited during the reconnection and undergo cascade and are subjected to damping. We extend the calculations beyond the quasi-linear approximation and compare the acceleration and scattering by transit time damping and gyroresonance interactions. We find that the acceleration is dominated by the so-called transit time damping mechanism. We estimate the total energy transferred into particles and show that our approach provides sufficiently accurate results. We compare this rate with the energy-loss rate. Scattering by fast modes appears to be sufficient to prevent the protons from escaping the system during the acceleration. Confinement of electrons, on the other hand, requires the existence of plasma waves. Electrons can be accelerated to GeV energies through the process described here for solar flare conditions.
Electrical phenomena in amorphous oxide films

Thin layers of insulators, from 100 A to 20 000 A thick, have a number of interesting electrical properties. These properties include forming, which is a profound and essentially permanent change produced by an electrical field, and, after forming, differential negative resistance together with switching and memory phenomena. Electroluminescence and electron emission also occur. These features are shown by most amorphous or microcrystalline insulators of the appropriate thickness, and are particularly clearly shown by the oxides, such as Al2O3, Ta2O5 and SiO. In our review we survey the observed properties of metal-insulator-metal devices involving such insulating layers, and discuss the mechanisms which have been proposed for their operation. Further, since the unusual properties may be technologically important, we outline some of the possible uses of these devices and the relevance of the phenomena to the mechanism of corrosion of certain metals.
A Novel Method for Respiration-Like Clutter Cancellation in Life Detection by Dual-Frequency IR-UWB Radar

Detection of trapped survivors under collapsed buildings using impulse-radio ultra-wideband (IR-UWB) radar has become an important research topic. However, due to the jitter or drift of the radar, clutter reflected from walls or rubble is similar to the human respiratory response in some scenarios. Thus, it becomes difficult to determine the presence or absence of the survivor under ruins. In this paper, a novel dual-frequency IR-UWB radar with low center frequencies is developed and a method based on adaptive clutter cancellation is proposed to eliminate the respiration-like clutter. Experiments are carried out in both through-wall and simulated rubble cases, and the results shows that the proposed method outperforms the common method, which is based on linear-trend subtraction with single-frequency IR-UWB radar in removing the respiration-like clutter and improves the radar performance in life detection.
Calculation of Surface Electromygram Discharge Rate

The discharge rate of motor unit action potential sequences has been related to fatigue and neuromuscular diseases, but typically simple methods are used to do so. We adapted more advanced methods used to calculate heart rate to fit in the context of surface electromyogram discharge rate calculation. Simulation results with a deterministic discharge rate modulation model suggest that parameter fine-tuning is necessary to accurately and robustly estimate discharge rate.
Degrees of Freedom of the MIMO X Channel

We provide achievability as well as converse results for the degrees of freedom region of a MIMO X channel, i.e., a system with two transmitters, two receivers, each equipped with multiple antennas, where independent messages need to be conveyed over fixed channels from each transmitter to each receiver. The inner and outerbounds on the degrees of freedom region are tight whenever integer degrees of freedom are optimal for each message. If all nodes have equal number of antennas M > 1 and channel matrices are non-degenerate then the degrees of freedom etaX* = 4/3 M. If the channels vary with time/frequency then the X channel with single antennas (M = 1) at all nodes has 4/3 degrees of freedom. Thus, the MIMO X channel has non-integer degrees of freedom when M is not a multiple of 3. Simple zero forcing without dirty paper encoding or successive decoding, suffices to achieve the 4/3 M degrees of freedom in all cases. The key idea for the achievability of the degrees of freedom is interference alignment - i.e., signal spaces are aligned at receivers where they constitute interference while they are separable at receivers where they are desired. With equal number of antennas at all nodes, we also explore the increase in degrees of freedom when some of the messages are made available to a transmitter or receiver in the manner of cognitive radio.
Survey of Computational Algorithms for MicroRNA Target Prediction

MicroRNAs (miRNAs) are 19 to 25 nucleotides non-coding RNAs known to possess important post-transcriptional regulatory functions. Identifying targeting genes that miRNAs regulate are important for understanding their specific biological functions. Usually, miRNAs down-regulate target genes through binding to the complementary sites in the 3' untranslated region (UTR) of the targets. In part, due to the large number of miRNAs and potential targets, an experimental based prediction design would be extremely laborious and economically unfavorable. However, since the bindings of the animal miRNAs are not a perfect one-to-one match with the complementary sites of their targets, it is difficult to predict targets of animal miRNAs by accessing their alignment to the 3' UTRs of potential targets. Consequently, sophisticated computational approaches for miRNA target prediction are being considered as essential methods in miRNA research. We surveyed most of the current computational miRNA target prediction algorithms in this paper. Particularly, we provided a mathematical definition and formulated the problem of target prediction under the framework of statistical classification. Moreover, we summarized the features of miRNA-target pairs in target prediction approaches and discussed these approaches according to two categories, which are the rule-based and the data-driven approaches. The rule-based approach derives the classifier mainly on biological prior knowledge and important observations from biological experiments, whereas the data driven approach builds statistic models using the training data and makes predictions based on the models. Finally, we tested a few different algorithms on a set of experimentally validated true miRNA-target pairs [1] and a set of false miRNA-target pairs, derived from miRNA overexpression experiment [2]. Receiver Operating Characteristic (ROC) curves were drawn to show the performances of these algorithms.
Accurate UWB Radar Three-Dimensional Imaging Algorithm for a Complex Boundary Without Range Point Connections

Ultrawide-band pulse radars have immeasurable potential for a high-range-resolution imaging in the near field and can be used for noncontact measurement of industrial products with specular or precision surfaces, such as reflector antenna or aircraft fuselage, or identifying and locating the human body in security systems. In our previous work, we developed a stable and high-speed 3-D imaging algorithm, Envelope, which is based on the principle that a target boundary can be expressed as inner or outer envelopes of spheres, which are determined using antenna location and observed ranges. Although Envelope produces a high-resolution image for a simple shape target that may include edges, it requires an exact connection for observed ranges to maintain the imaging quality. For complex shapes or multiple targets, this connection becomes a difficult task because each antenna receives multiple echoes from many scattering points on the target surface. This paper proposes a novel imaging algorithm without range point connection to accomplish high-quality and flexible 3-D imaging for various target shapes. The algorithm uses an accurate estimation for the direction of arrival using signal amplitudes and realizes direct mapping from observed ranges to target points. Several comparative studies of conventional algorithms clarify that our proposed method accomplishes accurate and reliable 3-D imaging even for complex or multiple boundaries.
PT: A Lightweight Job Scheduler with Remote Interface for Multiprocessors

PT is a lightweight job scheduler based on client-server architecture with remote interfaces. PTServer, the server-side of PT, is designed as an open service running on the multiprocessor system to collaborate with any PTClient, the client-side of PT, on top of PTComer protocol. In PT, we call once execute of program as a task and several tasks formed into a job. The two functionality PT need to implement is scheduling policy and resource allocation. Scheduling polices exist in two levels, job scheduling and task scheduling. Job scheduling can be realized in PTServer, PTClient or directly by the user. Task scheduling can be constructed in centralized or distributed way in PTServer. Distributed task scheduling is more efficient with little complexity increase. The allocable resource we care about is the cpu-cores that target system could provide. Resource allocation can be cpu-core based or computation based. Computation based allocation can extract better utilization of cpu for the target system.