Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Sensor Network Lifetime Through Hierarchical Multihop Clustering

In this project, we developed an adaptive multihop clustering algorithm MaxLife for sensor networks. MaxLife significantly improves sensor network lifetime by balancing energy dissipation and minimizing energy consumption at the same time. The algorithm is compared to Random and MinEnergy algorithms and shows great performance gain. Random is extended from its original design of single hop clustering in [1] to multihop clustering, which elects cluster heads with absolute fairness. However, the idea of rotating the role of cluster heads does not work well in a multihop environment, because relay nodes can also drain out energy quickly. MinEnergy chooses cluster heads to minimize total energy consumption, which leads to large energy disparity and hurts long-term performance. MaxLife on the other hand, uses global optimization techniques and directly maximizes network lifetime. Simulation results verified that MaxLife achieves the best tradeoff between fairness and energy efficiency, and the clustering topology computed from it has significantly longer lifetime than those from the other two algorithms.
THE EXTRACTION OF FIELD BOUNDARIES AND WIND EROSION OBSTACLES FROM AERIAL IMAGERY

In this paper work on image analysis methods extracting field boundaries and wind erosion obstacles from aerial imagery is presented. Describing the objects of interest and additional GIS-data together in an integrated semantic model is essential to get an overview of the numerous relations between the different objects and how to exploit the prior knowledge. The strategy is derived from the modelled characteristics taking into account an automatic processing flow. The field boundaries and wind erosion obstacles are first extracted separately: A segmentation within selected regions of interest in the imagery leads to field areas, which are split, if necessary, to preliminary fields. Furthermore, a snake algorithm is initialized to correct the geometric inaccuracies in some parts yielding final field boundaries. Wind erosion obstacles are derived using DSM-data in addition to the imagery to verify search areas from the prior GIS knowledge, for example parallel and nearby roads, or to extract wind erosion obstacles without prior information about their location. Finally, a combined evaluation of the different objects is accomplished to exploit the modelled geometrical similarities resulting in a refined and integrated solution. Results of the different steps prove the potential of the proposed solution.
Defining the Term "Argument"

Informal logic has expanded the concept of an 'argument' beyond that presented traditionally by formal logicians-to include arguments as encountered in 'real-life'. Existent definitions of argument structure are argued to be inadequate by failing to fully recognise that, ultimately, arguments have a human source. Accordingly, a new definition is proposed which appeals to relevant cognitive and behavioural factors. The definition retains some traditional concepts, but introduces the term 'supportive' as a modification to 'premiss'. The concept of a 'persuader' is also developed. The definition is argued to capture more fully the intricacies, subtleties and rich diversity of informal arguments.
Ipos, Over-valued Equity & Sentiment Investors Predictions of the Under-valued Equity Approach Firm Level Strategies in the Pre-ipo Period

Market discipline isn’t what it used to be. In the past, investors could count on efficient markets to resolve the problem of under-valued equity through hostile takeovers, leveraged buyouts and management buyouts (Jensen (2005: 14). In fact, the market for corporate control could solve much of the managerial agency problem. Moreover, substitutes for market discipline such as ownership structure, incentive compensation, and board of directors oversight could be counted on to constrain self-serving managers. Despite their theoretical appeal, empirical evidence does not offer unequivocal support for the efficacy of these mechanisms. Most if not all of these mechanisms were crashing failures. Corporate governance apparently deteriorated as new problems surfaced which seem to have over-shadowed what seems in today’s light quite tractable problems. Incentives which were supposed to align managerial-shareholder interests wound up producing entrenched mangers, conflicts surfaced between majority and minority owners (principal-principal agency costs) and most recently, Jensen (2005) presents the case for the agency costs associated with over-valued equity.
O R I G I N a L a R T I C L E Open Access

Distraction in diagnostic radiology: How is search through volumetric medical images affected by interruptions? Abstract Observational studies have shown that interruptions are a frequent occurrence in diagnostic radiology. The present study used an experimental design in order to quantify the cost of these interruptions during search through volumetric medical images. Participants searched through chest CT scans for nodules that are indicative of lung cancer. In half of the cases, search was interrupted by a series of true or false math equations. The primary cost of these interruptions was an increase in search time with no corresponding increase in accuracy or lung coverage. This time cost was not modulated by the difficulty of the interruption task or an individual's working memory capacity. Eye-tracking suggests that this time cost was driven by impaired memory for which regions of the lung were searched prior to the interruption. Potential interventions will be discussed in the context of these results. Significance Radiologists are frequently interrupted during the interpretation of medical images. The current research provides the first attempt to quantify the effect of these interruptions using an experimental design. In our study, we found that interruptions lead to a significant increase in task completion time. Through the use of eye-tracking, we were able to determine that this inefficiency is driven by impaired memory for previously searched areas of the image. In natural settings, these results translate to longer patient turnaround times and increase the cost of providing and receiving healthcare. By establishing a causal link between interruptions and productivity loss, we aim to encourage healthcare providers to reduce unnecessary interruptions in radiology reading rooms. In addition, our eye-tracking results hint at potential interventions, such as eye-tracking feedback, that may help lower the cost of unavoidable interruptions.
The selection of the Dissertation Problem for Ph.D. theses in Psychology and Social Anthropology/Etnology from the Graduate Students’ Perspective

In this study doctoral students in psychology and social anthropology/ethnology were interviewed as to their selection of research problem for their Ph.D. thesis. From the perspective of activity theory it is suggested that the research problem can profitably be seen as the object of activity in research. Graduate students’ selection of a research problem was analyzed as a process occurring over time, and the results showed that that the selection process was characterized by a mutual adaptation of interests between the Ph.D. student and the research community. Different factors appeared to have influenced the selection process at different points in the process, ‘external factors’ having had a greater influence on the choice process in its early stages, especially for the social anthropologists. In the present study, compared with the anthropologists, the psychologists’ selection processes were more clearly directed by the discipline, for example through the availability of research funds. The results suggest that the Ph.D. student often arrived at a research problem by acting opportunistically in an activity system that was partly unknown to them. (Less)
Data-Driven Generation of Decision Trees for Motif-Based Assignment of Protein Sequences to Functional Families

This paper describes an approach to data-driven discovery of sequence motif-based models in the form of decision trees for assigning protein sequences to functional families. Unlike approaches that try to classify protein sequences based on presence of a single motif, this method is able to capture regularities that can be described in terms of presence or absence of arbitrary combinations of motifs. A training set of sequences with known functions is used to automatically construct decision trees that capture regularities that are sufficient to assign the sequences to their respective functional families. The accuracy of the resulting decision tree classifiers are then evaluated on an independent test set. Experiments using several protein data sets indicate that proposed approach matches or beats the technique of assigning protein sequences to functional families based on the presence of a single characteristic motif in terms of the accuracy of resulting classification.
Automatic Synthesis of Linear Process Models from Temporal Constraints: An Incremental Approach

We present PM-MetaFrame, a tool for automatic synthesis (i.e. prior to any enaction) of linear process models from speci cations written as global constraints in linear time temporal logic. Key to the automatic synthesis is its level of abstraction: process model components are described logically by a taxonomic classi cation, expressing semantic properties, and the ow of data is only considered on the level of types, which is su cient to guarantee executability of synthesized process models. Thus our approach can be regarded as a high-level extension of existing process model approaches, where, if at all, global constraints are described on the data level. The result of the synthesis is the set of all executable linear process models satisfying the, typically very loose, temporal constraints. Incremental re nement of global constraints by strengthening/loosening via conjunction/disjunction helps minimizing the search space.
Maximum Efficiency Current Waveforms for a PMSM Including Iron Losses and Armature Reaction

Permanent magnet synchronous machines (PMSMs) are popular due to their high efficiency and favorable dynamic properties. In practice, these machines often have a back-electromotive force (EMF) waveform, which deviates from a theoretically ideal sinusoid or trapezoid. In the past, current waveform shaping techniques were developed for these machines to calculate nonconventional current waveforms to reduce the torque ripple. However, in the light of global warming, energy efficiency has become more important than torque ripple in many applications. Therefore, current waveform shaping techniques can be used to focus on maximum efficiency. In this paper, a technique is presented that maximizes the efficiency of both the PMSM and the drive simultaneously. A time domain approach is used instead of the classical frequency domain approach, which allows us to include many machine aspects that had to be neglected previously, i.e., armature reaction, reluctance, zero-sequence components, and iron losses.
Moving Horizon State Estimation for Networked Control Systems With Multiple Packet Dropouts

This technical note studies some of the challenging issues on moving horizon state estimation for networked control systems in the presence of multiple packet dropouts in both sensor-to-controller and controller-to-actuator channels, which both situations are modeled by two mutually independent stochastic variables satisfying the Bernoulli binary distribution. Compared with standard Kalman filter, this study proposes a novel moving horizon estimator to deal with the uncertainties induced from the multiple packet dropouts, which has a larger degree of freedom to obtain better behavior by tuning the weight parameters. A sufficient condition for the convergence of the norm of the average estimation error is also presented to guarantee the performance of the estimator. Finally, a real-time simulation experiment is presented to demonstrate the feasibility and efficiency of the proposed method.
The Great PV Cephei Outflow: A Case Study in Outflow-Cloud Interaction

We present a set of detailed molecular-line maps of the region associated with the giant Herbig-Haro flow HH 315 from the young star PV Cephei, aimed at studying the outflow-cloud interaction. Our study clearly shows that the HH 315 flow is affecting the kinematics of its surrounding medium and has been able to redistribute considerable amounts of the surrounding medium-density (~103 cm-3) gas in its star-forming core as well at parsec-scale distances from the source. The single-dish observations include a map of the outflow in the 12CO (2-1) line, with a beam size of 27'', and more extended maps of the outflow region in the 12CO (1-0) and 13CO (1-0) lines, with 45'' and 47'' beam sizes, respectively. A companion paper published in this issue presents higher resolution (IRAM 30 m) observations and discusses their implications. The giant molecular outflow HH 315 is a highly asymmetric bipolar flow with a projected linear extent of about 2 pc. Our results indicate that the two outflow lobes are each interacting with the ambient medium in different ways. The southern (redshifted) lobe, with a mass of 1.8 M☉, interacts with a dense ambient medium, very close to the young stellar outflow source, and its kinetic energy is comparable to both the turbulent and gravitational binding energy of its host cloud (of order 1044 ergs). In addition, we find evidence that the southern lobe is responsible for the creation of a cavity in the 13CO emission. In contrast, the northern (mainly blueshifted) outflow lobe, with a total mass of 4.8 M☉, extends farther from PV Cep and interacts with ambient gas much less dense than the southern lobe. There is very little 13CO emission north of the outflow source, and the only prominent 13CO emission is a shell-like structure coincident with the outer edge of the northern lobe, about 1.2 pc northwest of PV Cep. It appears that the northern lobe of the HH 315 outflow has been able to "push" aside a substantial fraction of the gas in the area, piling it in a dense shell-like structure at its edges. In addition, we find that about 50% of the gas in the region of the northern lobe has been put into motion by the outflow and that the northern outflow lobe is responsible for a velocity gradient in the ambient gas.
How Violent Video Games Communicate Violence: A Literature Review and Content Analysis of Moral Disengagement Factors

Mechanisms of moral disengagement in violent video game play have recently received considerable attention among communication scholars. To date, however, no study has analyzed the prevalence of moral disengagement factors in violent video games. To fill this research gap, the present approach includes both a systematic literature review and a content analysis of moral disengagement cues embedded in the narratives and actual game play of 17 top-ranked first-person shooters (PC). Findings suggest that moral disengagement factors are frequently embedded in first-person shooters, but their prevalence varies considerably. Most violent video games include justifications of the portrayed violence, a distorted portrayal of consequences, and dehumanization of opponents. Implications of the findings for research on violent games are discussed.
Crafting a Class: The Trade-Off between Merit Scholarships and Enrolling Lower-Income Students

This paper uses panel data for the 100 colleges and universities at which the largest number of National Merit Scholarship (NMS) winners enrolled in 2003 to test whether an expansion in the number of institutionally funded NMS winners at an institution is associated with a decline in the number of Pell Grant recipients at the institution. Our findings suggest a trade-off between enrolling institutionally sponsored NMS winners and enrolling Pell grant recipients and thus that institutions should focus on both student selectivity and socioeconomic diversity in crafting their classes.
Selecting fuzzy if-then rules for classification problems using genetic algorithms

This paper proposes a genetic-algorithm-based method for selecting a small number of significant fuzzy if-then rules to construct a compact fuzzy classification system with high classification power. The rule selection problem is formulated as a combinatorial optimization problem with two objectives: to maximize the number of correctly classified patterns and to minimize the number of fuzzy if-then rules. Genetic algorithms are applied to this problem. A set of fuzzy if-then rules is coded into a string and treated as an individual in genetic algorithms. The fitness of each individual is specified by the two objectives in the combinatorial optimization problem. The performance of the proposed method for training data and test data is examined by computer simulations on the iris data of Fisher. >
Short-term changes in neck pain, widespread pressure pain sensitivity, and cervical range of motion after the application of trigger point dry needling in patients with acute mechanical neck pain: a randomized clinical trial.

STUDY DESIGN Randomized clinical trial. OBJECTIVES To determine the effects of trigger point dry needling (TrPDN) on neck pain, widespread pressure pain sensitivity, and cervical range of motion in patients with acute mechanical neck pain and active trigger points in the upper trapezius muscle. BACKGROUND TrPDN seems to be effective for decreasing pain in individuals with upper-quadrant pain syndromes. Potential effects of TrPDN for decreasing pain and sensitization in individuals with acute mechanical neck pain are needed. Methods Seventeen patients (53% female) were randomly assigned to 1 of 2 groups: a single session of TrPDN or no intervention (waiting list). Pressure pain thresholds over the C5-6 zygapophyseal joint, second metacarpal, and tibialis anterior muscle; neck pain intensity; and cervical spine range-of-motion data were collected at baseline (pretreatment) and 10 minutes and 1 week after the intervention by an assessor blinded to the treatment allocation of the patient. Mixed-model analyses of variance were used to examine the effects of treatment on each outcome variable. RESULTS Patients treated with 1 session of TrPDN experienced greater decreases in neck pain, greater increases in pressure pain threshold, and higher increases in cervical range of motion than those who did not receive an intervention at both 10 minutes and 1 week after the intervention (P<.01 for all comparisons). Between-group effect sizes were medium to large immediately after the TrPDN session (standardized mean score differences greater than 0.56) and large at the 1-week follow-up (standardized mean score differences greater than 1.34). CONCLUSION The results of the current randomized clinical trial suggest that a single session of TrPDN may decrease neck pain intensity and widespread pressure pain sensitivity, and also increase active cervical range of motion, in patients with acute mechanical neck pain. Changes in pain, pressure pain threshold, and cervical range of motion surpassed their respective minimal detectable change values, supporting clinically relevant treatment effects. Level of Evidence Therapy, level 1b-.
Stock Selection with a Novel Sigmoid-Based Mixed Discrete-Continuous Differential Evolution Algorithm

A stock selection model with both discrete and continuous decision variables is proposed, in which a novel sigmoid-based mixed discrete-continuous differential evolution algorithm is especially developed for model optimization. In particular, a stock scoring mechanism is first designed to evaluate candidate stocks based on their fundamental and technical features, and the top-ranked stocks are selected to formulate an equal-weighted portfolio. Generally, the proposed model makes literature contributions from two main perspectives. First, to determine the optimal solution in terms of feature selections (discrete variables) and the corresponding weights (continuous variables), the original differential evolution algorithm focusing only on continuous problems is extended to a novel mixed discrete-continuous variant based on sigmoid-based conversion for the discrete part. Second, the stock selection model also resolves the gap of the application of differential evolution algorithm to stock selection. Using the Shanghai A share market of China as the study sample, the empirical results show that the novel stock selection model can make a profitable portfolio and significantly outperform its benchmarks (with other model designs and optimization algorithms used in the existing studies) in terms of both investment return and model robustness.
Influence of the human activity on wide-band characteristics of the 60 GHz indoor radio channel

This paper presents propagation measurements in the presence of human activity for a 60 GHz channel. Series of 40-min-long measurements of the channel impulse response have been recorded with a sampling period of 1.6 ms, for a total duration of about 20 h. During measurements, the human activity (between zero and 15 persons) was observed with a video camera. The obstruction phenomenon due to the human bodies is characterized in duration and amplitude from the propagation characteristics (attenuation, coherence bandwidth) by means of an appropriate method. The results highlight and quantify the problems due to the human activity for high data rate communication systems. When the direct path is shadowed by a person, the attenuation generally increases by more than 20 dB, for a median duration of about 100 ms for an activity of one to five persons and 300 ms for 11-15 persons. Globally, the channel is "unavailable" for about 1% or 2% of the time in the presence of one to five persons. This channel characterization makes it possible to modelize the temporal variations of the 60 GHz channels. The results also give orientations for the design of high data rate communications systems and networks architectures at 60 GHz.
A Novel Web-Oriented Writing Environment Using Objects' Facts Acquired from the Web

This paper presents a novel web-oriented writing environment that helps users describe their opinions on topics/events through weblogs, by showing facts related to the objects. Our writing environment automatically recognizes information needs for facts on aspects (e.g., "opening hours") of the objects (e.g., "J's cafe") by applying lexico- syntactic patterns to the snapshots of users' writings. It then attempts to extract facts that satisfy the information needs from the Web, and shows the extracted facts (e.g., "opening hours"-"10am-8:30pm") to the users. The users can thus refer to necessary facts without searching the web by themselves. We realized this environment for Japanese on a browser with AJAX, and evaluated how much useful information could be provided by our environment.