Miracle-dz/UniFAR-FTUs huggingface dataset:
Microlens OGLE-2005-BLG-169 Implies That Cool Neptune-like Planets Are Common

We detect a Neptune mass ratio (q ≃ 8 × 10-5) planetary companion to the lens star in the extremely high magnification (A ~ 800) microlensing event OGLE-2005-BLG-169. If the parent is a main-sequence star, it has mass M ~ 0.5 M☉, implying a planet mass of ~13 M⊕ and projected separation of ~2.7 AU. When intensely monitored over their peak, high-magnification events similar to OGLE-2005-BLG-169 have nearly complete sensitivity to Neptune mass ratio planets with projected separations of 0.6-1.6 Einstein radii, corresponding to 1.6-4.3 AU in the present case. Only two other such events were monitored well enough to detect Neptunes, and so this detection by itself suggests that Neptune mass ratio planets are common. Moreover, another Neptune was recently discovered at a similar distance from its parent star in a low-magnification event, which are more common but are individually much less sensitive to planets. Combining the two detections yields 90% upper and lower frequency limits f = 0.38 over just 0.4 decades of planet-star separation. In particular, f > 16% at 90% confidence. The parent star hosts no Jupiter-mass companions with projected separations within a factor 5 of that of the detected planet. The lens-source relative proper motion is μ ~ 7-10 mas yr-1, implying that if the lens is sufficiently bright, I ≲ 23.8, it will be detectable by the Hubble Space Telescope by 3 years after peak. This would permit a more precise estimate of the lens mass and distance and, so, the mass and projected separation of the planet. Analogs of OGLE-2005-BLG-169Lb orbiting nearby stars would be difficult to detect by other methods of planet detection, including radial velocities, transits, and astrometry.
[18] Masahiro Yasugi and Akinori Yonezawa. an Object-oriented Parallel Algorithm for the Newtonian N-body Problem. Yonezawa: Abcl/onem-4: a New Software/hardware Architecture for Object-oriented Concurrent Computing on an Extended Data

Novel software technologies for implementing concurrent object-oriented languages on di erent types of multicomputers (including stock multicomputers) are presented. Performance numbers suggest that concurrent object-oriented programming on currently available multicomputers is highly viable and promising in performance, thus allowing us exploit the computing power and modeling power provided in the concurrent object-oriented paradigm.
A CMOS nonlinear-map circuit array for threshold-coupled chaotic maps using pulse-modulation approach

As one of adaptive lattice dynamics, a nonlinear dynamical model with threshold activated coupling has been proposed by S. Sinha since 1994. In this model, each lattice site performs an arbitrary nonlinear transformation and thresholding. The excess of an output over the threshold is transported to the neighboring lattice site(s). This dynamics generates various spatiotemporal patterns. S. Sinha, et al. have also proposed the applications of this model to computing using nonlinear dynamics. In this paper, we propose a CMOS LSI chip designed using a pulse modulation approach for this model. The chip includes 30×30 nonlinear-map element circuits, each of which corresponds to a lattice site. The measurement results using the fabricated LSI chip demonstrate that the designed circuit successfully performs arbitrary nonlinear transformation and thresholding
The A(ffective) B(ehavioral) C(ognitive) of Taboo Words in Natural Language: The Relationship Between Taboo Words’ Intensity and Frequency

We investigated the relationship between the affective component (A: the level of offensiveness/intensity) and the behavioral component (B: the frequency of usage) of taboo words that are part of an individual’s natural language (C: the cognitive component). In Study 1, 900 U.S. residents generated the 10 most common taboo words they use in their daily lives (C). In Study 2, 1,000 U.S. residents were presented with the 30 most common taboo words (C) from Study 1 and asked to rate how offensive they perceived the words (A) and how often they used these words (B). This relationship was controlled for self-reported trait affectivity. We found a slight change in which taboo words people use in everyday life. The results suggest that the level of offensiveness of taboo words (A) predicts the usage of the words (B) that are part of a person’s natural language (C): the ABC-hypothesis of taboo words.
Determinants of Secondary Traumatic Stress among Korean Social Workers for Suicide Prevention Programs

In the present study, the actual state of secondary traumatic stress among Korean social workers for suicide prevention programs was figured out and factors that affect the secondary traumatic stress were examined. According to the results of a survey conducted with 56 current Korean social workers for suicide prevention programs, the average score of their secondary traumatic stress was 37.71 points and 53.6% of the respondents showed secondary traumatic stress. According to the results of multiple regression analysis, the degree of exhaustion, personal empowerment, relational empowerment, weekly working hours, and monthly incomes were significantly related with secondary traumatic stress.
Novel Metrics of Speech Rhythm for the Assessment of Emotion

Whereas rhythmic speech analysis is known to bear great potential for the recognition of emotion, it is often omitted or reduced to the speaking rate or segmental durations. An obvious explanation is that the characterisation of speech rhythm is not an easy task itself and there exist many types of rhythmic information. In this paper, we study advanced methods to define novel metrics of speech rhythm. Their ability to characterise spontaneous emotions is demonstrated on the recent Audio/Visual Emotion Challenge Task on 3.6 hours of natural human affective conversational speech. Emotion is assessed for the four dimensions Activation, Expectation, Power and Valence as binary classification tasks on the word level. We compare our new rhythmic feature types to the official 2 k bruteforce acoustic baseline feature set on the Audio Sub-Challenge. In the results, the rhythmic features achieve a promising relative improvement of 16% for Valence, whereas the performance is more contrasted for the three others dimensions.
Cognitive Control and Expectation: an EEG Study

People regulate their behavior in a flexible way, according to internal goals. This is called cognitive control. Research has shown that the behavioral adjustments arise from both reactive and proactive control. In two experiments we investigated the influence of both types of cognitive control on the congruency sequence effect. This effect is characterized by a modulation of current trial conflict in function of the degree of previous trial conflict. Participants were subjected to a vocal Stroop task (Experiment 1) and a vocal Stroop task where participants had to predict the congruency (alternation/repetition) of the next trial (proactive; Experiment 2), while the underlying neural signals were measured by means of EEG. We focused on two components involved in conflict: a) N450: supposedly involved in conflict detection and b) conflict sustained potential (CSP): putatively involved in conflict resolution. Their relation to the congruency sequence effect was further explored. Experiment 1 showed a stronger N450 for incongruent trials, irrespective of previous trial congruency. Secondly, a congruency sequence effect for the SP was observed, with higher amplitudes for cI trials as compared to iI trials. Experiment 2 started with investigating the influence of predictions on the slow contingent negative variation (CNV), a slow component associated with advance preparation and expectation. Results revealed that the CNV was more pronounced when participants expected an alternation of congruency. Moreover, this was dependent on the tendency to expect congruency repetitions to occur (i.e. repetition bias). Secondly, the N450 showed a congruency sequence effect, but only for the repetition condition, with a stronger N450 for the iC trials (compared to the cC). The results for the conflict SP were in both prediction conditions the same as Experiment 1. The current results suggested that the notion of the N450 being involved in conflict detection might not be entirely correct. Theoretical implications for cognitive control theories and consequences are discussed. Cognitive Control and Expectation: An EEG study 2 Cognitive Control and Expectation: An EEG Study
Reading Barcodes from Digital Imagery

This document was prepared for Dr. John Loomis as part of the written PhD. candidacy exam by Timothy R. Tuinstra. This report provides a look at the automatic detection and decoding of barcodes found within imagery. Such techniques could conceivably be used in the retail, manufacturing, inventory and travel industries as well as others. A general description of barcodes is included as well as a review of some of the techniques used to automatically locate barcodes within larger images containing additional objects. The author will also present some results from implementing a variant of these techniques.
Fielded Autonomous Posture Classification Systems: Design and Realistic Evaluation

Few Body Sensor Network (BSN) based posture classification systems have been fielded to date, despite laboratory based research work confirming their theoretical suitability for a range of applications. This paper reports and reflects on two algorithms which i) improve the accuracy of real-time, multi-accelerometer based posture classifiers when dealing with natural movement and transitions and ii) maximize a wearable system's battery life through distributed computation at nodes. The EWV transition filters proposed here increase the classification accuracy by 1% over unfiltered results in realistic scenarios and significantly reduces spurious classifier output in real-time visualizations. A 200 fold transmission reduction from the on-body system to an outside system was achieved in practice by combining the transition filters with an event-based design. Furthermore, a method of reducing transmissions between on-body data gathering nodes based on distributed processing of the classifier rules (but maintaining a one-way flow of communications during system use) is also described. This provides a 3.3 fold reduction in packets and a 13.5 fold reduction in data transmitted from one node to the other in a two-node wearable system.
Opinion-Polarity Identification in Bengali

In this paper, opinion polarity classification on news texts has been carried out for a less privileged language Bengali using Support Vector Machine (SVM) 1 . The present system identifies semantic orientation of an opinionated phrase as either positive or negative. The classification of text as either subjective or objective is clearly a precursor to determine the opinion orientation of evaluative text since objective text is not evaluative by definition. A subjectivity classifier has been used to perform sentence level subjectivity classification. The present system is a hybrid approach to the overall opinion polarity identification problem and works with lexicon entities and linguistic syntactic features. The baselines system works only with SentiWordNet (Bengali) 2 . The use of lexical features like negative words, stemming cluster, functional word and parts of speech improved the performance of the present system over baseline. Inclusion of the chunk feature has improved the precision of the system by 19.2%. A further improvement of 3.6% in precision of the system has been obtained with the use of dependency relations information. Evaluation results of the final system have demonstrated a precision of 70.04% and a recall of 63.02%. KeywordsOpinion Mining, Polarity Identification, Bengali and Phrase Level Polarity Identification.
D2MA: Accelerating coarse-grained data transfer for GPUs

To achieve high performance on many-core architectures like GPUs, it is crucial to efficiently utilize the available memory bandwidth. Currently, it is common to use fast, on-chip scratchpad memories, like the shared memory available on GPUs' shader cores, to buffer data for computation. This buffering, however, has some sources of inefficiency that hinder it from most efficiently utilizing the available memory resources. These issues stem from shader resources being used for repeated, regular address calculations, a need to shuffle data multiple times between a physically unified on-chip memory, and forcing all threads to synchronize to ensure RAW consistency based on the speed of the slowest threads. To address these inefficiencies, we propose DataParallel DMA, or D2MA. D2MA is a reimagination of traditional DMA that addresses the challenges of extending DMA to thousands of concurrently executing threads. D2MA decouples address generation from the shader's computational resources, provides a more direct and efficient path for data in global memory to travel into the shared memory, and introduces a novel dynamic synchronization scheme that is transparent to the programmer. These advancements allow D2MA to achieve speedups as high as 2.29×, and reduces the average time to buffer data by 81% on average.
Two-tier Cellular Networks with Frequency Selective Surface

A key challenge is how to improve the wireless capacity of cellular networks for both outdoor and indoor users. Whilst deploying low power femtocells can significantly improve the indoor capacity, its interference can erode the outdoor capacity. In order to maximise the performance of the co-frequency two-tier network, the research challenge is how to minimise their mutual interference through coordination and other methods. This paper proposes a controllable interface that acts as a dynamic barrier between the outdoor and indoor networks. The interfaces comprises of a frequency-selective-surface (FSS) which is a band-stop filter. The paper also demonstrates that without any FSS interfaces, the mutual interference between indoor and outdoor networks erodes the capacity of each other significantly. The benefit of the FSS interface is that it is able to mitigate the mutual interference to the extent that their capacities are maximised. The results show that by deploying FSS interfaces, an improvement of up to 1.3 fold in mean throughput, 4.6 fold in throughput fairness for outdoor users and 1.2 fold in mean throughput, 2 fold in throughput fairness for indoor users can be achieved. The analysis is conducted using both a theoretical stochastic geometry analysis and multi-cell simulation results.
Achievable Secrecy Rates of an Energy Harvesting Device

The secrecy rate represents the amount of information per unit time that can be securely sent on a communication link. In this work, we investigate the achievable secrecy rates in an energy harvesting communication system composed of a transmitter, a receiver and a malicious eavesdropper. In particular, because of the energy constraints and the channel conditions, it is important to understand when a device should transmit and to optimize how much power should be used to improve security. Both full knowledge and partial knowledge of the channel are considered under a Nakagami fading scenario. We show that high secrecy rates can be obtained only with power and coding rate adaptation. Moreover, we highlight the importance of optimally dividing the transmission power in the frequency domain, and note that the optimal scheme provides high gains in secrecy rate over the uniform power splitting case. Analytically, we explain how to find the optimal policy and prove some of its properties. In our numerical evaluation, we discuss how the maximum achievable secrecy rate changes according to the various system parameters. Furthermore, we discuss the effects of a finite battery on the system performance and note that, in order to achieve high secrecy rates, it is not necessary to use very large batteries.
Timbral, Perceptual, And Statistical Attributes for Synthesized Sound

A set of 40 timbral, perceptual, and statistical sound attributes is described and studied, with reference to machine learning applications and statistical experiments using a software synthesizer. The attributes include trajectory, vibrato, and statistical subsets, and subsets defined in the time, Fouriertransform, and partial domains. High correlations between some attributes are confirmed: this has application to future choice of attributes for machine learning applications. The synthesizer’s achievable attribute ranges give an indication of its relative flexibility and strengths, and the method described has application to synthesizer design.
Whither the liquidity effect: the impact of Federal Reserve Open Market Operations in recent years

Previous research indicated that the daily liquidity effect, or the change in the federal funds rate associated with an exogenous change in Fed balances, varies with several factors including the day of the maintenance period. In this paper, we examine the data over the recent period of increased Federal Reserve transparency and find that the liquidity effect stabilized across days of the maintenance period. Rather, the liquidity effect may be a function of the uncertainty about banks' end-of-day balances. Moreover, we find that increased transparency led to a larger liquidity effect on the days prior to an FOMC meeting.
Reputation-Based Dynamic Trust Evaluation Model for Multi-Agent Systems Based on Service Satisfaction

— Trust and security issues have become critically important with the fast expansion of multi-agent system. Many computer applications such as the E-business systems, Agent-to-Agent, Grid and Semantic Web can be viewed as multi-agent systems which are open, anonymous and dynamic in nature. By its nature of multi-agent systems, malicious agents are always seeking to spread malicious content in the multi-agent network. To address threats of untrustworthy agents and their malicious behavior in the multi-agent system, many trust/reputation-based models have given solutions, but they fail to properly evaluate trust when malicious agents start to behave in an unpredictable way. Another aspect of trust evaluation models is becoming critical for sustaining good quality of service, because different trust evaluation models use different standards in its opinion. In this study, we propose a reputation-based dynamic trust evaluation model to help evaluating the trustworthiness and predicting the feature behavior of agents. There are two main features of our model. First, we use trust parameter amount of satisfaction as reputation value to represent the quality of service offered by an agent. The amount of satisfaction; a service requester agent has about a service provider agent. The amount of satisfaction is a major parameter to measure the trustworthiness of service provider. Second, we suggest suitable trust mechanisms that use personal experience or the experiences of others, possibly combined to help agent in evaluating the trustworthiness of another agent by considering major trust parameters such as the amount of satisfaction of transaction, the size of transaction, trust Decays with time of transaction, context of transaction, successful rate of transactions, and the feedback provided by the other entities in the past. Simulation results show that the model can evaluate accurately the agents’ trust degree and effectively control of malicious agents attack. When the malicious agents have a higher proportion in the system, it can effectively detect sudden strategic alteration in malicious behavior, and still keep high success rates. The experimental results illustrate the effectiveness of the proposed approach.
Gravity Anomaly Separation based on Bidimensional Empirical Mode Decomposition

Empirical Mode Decomposition is a time-frequency analysis method which can adaptive decomposition of complex signals. This article proposed the bidimensional empirical mode decomposition based on the calculation principle of empirical mode decomposition and the structural characteristics of the regional gravity anomaly. This method can be applied to the separation of gravity anomalies. The intrinsic mode functions of different scales contain various bands of compositions, then obtained the depth of field source by Power spectrum of radial average logarithmic. Compared with the conventional methods, such as the upward continuation method in the potential field separation method, we don't need to set any parameters beforehand. The application shows that in DaolangheDuge area: the multi-scale component based on bidimensional empirical mode decomposition could reflect the anomaly source form from shallow to deep. The field source of local gravity high value in the depth of less than 200 m, The field source of area gravity anomaly in the depth of 500 m, the base form is slope towards the North East which northwest high to southeast low.
Automatic recognition of affective cues in the speech of car drivers to allow appropriate responses

Speech interaction with in-car systems is becoming more commonplace as systems improve. New cars are often equipped with speech recognition systems to dial phone numbers and or control the in-car environment, and with speech output to provide verbal directions from navigation systems. The paper explores the possibilities of richer speech interaction between driver and car with automatic recognition of the emotional state of the driver with appropriate responses from the car. Driver's emotions often influence driving performance that could be improved if the car actively responds to the emotional state of the driver. This paper focuses on an in-car emotion recognition system to recognise driver emotional state.
The Theory of Planned Behavior, Past Behavior, Situational Factors, and Self-Identity Factors Drive Indonesian Enterpreneurs to Be Indebtedness

This study investigates the factors affecting borrowing intention among young entrepreneur of Indonesia TDA community based on the Theory of Planned Behavior (TPB). About 100 questionnaires were accepted and analyzed using structural equation modeling (SEM) in determining the relationships. The results show that borrowing intention amongst young entrepreneur of Indonesia TDA community is influenced by attitude, subjective norms, perceived behavior control, self identity, situational temptation, and past behavior. The young entrepreneur of Indonesia TDA community believe that they have complete control of their behavior in borrowing as they perceived to be equipped with the knowledge about the personal financing. In addition, because of their experience in students’ loans since undergraduates’ level, the result explains why situational temptation were found to be a significant predictor. The findings offer implications for researchers and government.
The Motion Analysis and Control of a Three-Degree-of-Freedom Parallel Mechanism

The purpose of this research is to study the motion analysis and control of a 3 degree of freedom parallel mechanism by confining the motion of a 6 degree of freedom platform. The pitch, roll and length of the upper moving platform are assumed be movable. The relationships between the limb length and moving platform are first derived and verified by numerical simulation, and then by using the Lagrange equation, the roll and pitch equations of motion are derived. Based on the advantages of linear and nonlinear control, P.I. D. (proportional integral derivative) and sliding mode control is added to control the mechanism. The limb lengths are varied to control the pitch and roll posture of moving platform and showed satisfactory results