Miracle-dz/UniFAR-FTUs huggingface dataset:
Cunetsim: A GPU based simulation testbed for large scale mobile networks

Most of the existing packet-level simulation tools are designed to perform experiments modeling small to medium scale networks. The main reason of this limitation is the amount of available computation power and memory in CPU-based simulation environments. To enable efficient packet-level simulation for large scale scenarios, we introduce a CPU-GPU co-simulation framework where synchronization and experiment design are performed in CPU and node's logical processes are executed in parallel in GPU according to the master/worker model. The framework is developed using the Compute-Unified Device Architecture (CUDA) API and denoted as Cunetsim, CUDA network simulator. In this work, we study the node mobility and connectivity as they are among the most time consuming task when large scale networks are simulated. Simulation results show that Cunetsim runtime remains stable and that it achieves significantly lower runtime than existing approaches when computing mobility and connectivity with no degradation in the accuracy of the results. Further, the connectivity is achieved up to 870 times faster than Sinalgo, which presents the best performances know until now.
Quarterly Economic Commentary, Spring 2010

For 2010, we expect GNP to be essentially unchanged from its 2009 volume; the corresponding figure for GDP is -½ per cent. Underlying these annual figures is a quarterly profile in which positive growth emerges during the year but not at a pace to return the annual figure to positive territory. For 2011, we expect GNP to grow by 2¾ per cent and GDP to grow by 2½ per cent. While this return to growth is to be welcomed, it should be seen as a modest pace of growth.
Labeling-based knowledge construction for real-world event understanding

A sensor networked environment is capable of observing real-world phenomena as sensor readings, however, there are difficulties in understanding real-world ‘events’ such as activities of daily life occurring in the environment. We propose an incremental model for constructing real-world knowledge to allow us to understand real-world events. The central plank of the proposed model is the labeling practice. In the model, both the ontology of real-world events and the implementation of a sensor system are simultaneously improved based on a manually labeled event corpus. A labeling tool is developed in accordance with the model and event vocabularies are evaluated in a practical labeling experiment.
ENTREPRENEUR INTENTION AMONG COLLEGE STUDENT IN RIAU PROVINCE

This study aim to examine which factors can influence entrepreneurship intention among college student in Riau Province from several factors by previous researches scholars: personality characteristic factors, entrepreneurial competencies factors, and environmental factor. This study applies correlation and regression analysis to test on the sample of 105 college student by using electronic questionnaire. This research shows that the correlation coefficient all independent variable to the dependent variable is significant. Moreover, this study indicate that determinants of entrepreneurial intention (personality characteristic, entrepreneurial competencies, and environmental) were have significant impact on the entrepreneurial intention among college student in Riau Province Indonesia.
Speech Compression Using the Matrix Pencil Technique

Matrix pencils (MP) facilitate the study of differential equations resulting from oscillating systems. Certain problems in linear ordinary differential equations, such as speech processing, can be represented as the problem of finding a canonical pencil strictly equivalent to a given pencil. The MP is a direct data domain approach to estimate the signal's poles. The MP depends on only the data and is not a stochastic estimator. This approach has many benefits over a statistical approach. One benefit is that a smaller amount of data could be used to estimate the poles. The second benefit is that it results in a lower variance associated with the estimates of the parameters, which comes close to the Cramer-Rao bound
A Case for Virtualizing the Electric Utility in Cloud Data Centers

Since energy-related costs make up an increasingly significant component of overall costs for data centers run by cloud providers, it is important that these costs be propagated to their tenants in ways that are fair and promote workload modulation that is aligned with overall cost-efficacy. We argue that there exists a big gap in how electric utilities charge data centers for their energy consumption (on the one hand) and the pricing interface exposed by cloud providers to their tenants (on the other). Whereas electric utilities employ complex features such as peak-based, time-varying, or tiered (load-dependent) pricing schemes, cloud providers charge tenants based on IT abstractions. This gap can create shortcomings such as unfairness in how tenants are charged and may also hinder overall cost-effective resource allocation. To overcome these shortcomings, we propose a novel idea of a virtual electric utility (VEU) that cloud providers should expose to individual tenants (in addition to their existing IT-based offerings). We discuss initial ideas underlying VEUs and challenges that must be addressed to turn them into a practical idea whose merits can be systematically explored.
Tracking Multiple Video Objects in Complex Scenes

Tracking multiple objects is an essential task for many video applications. One of the key technical issues for effectively tracking the objects is to deal with the shadows and occlusions in video scenes. In this paper, an adaptive shadow suppression method, which combines chrominance and texture features, is proposed. Moreover, in order to handle the occlusions effectively, the relationship between the bounding boxes of object at previous and present time has been taken into account, so that the color distributions of objects are recorded when they merge and the identity of each object is certified by the Bhattacharyya distance when they separate. Experimental results on tracking objects in various video sequences demonstrate the robustness and efficiency of the proposed algorithm.
The impact of synchronization and granularity on parallel systems

A study is made of the impact of synchronization and granularity on the performance of parallel systems using an execution-driven simulation technique. It is found that, even though there can be a lot of parallelism at the fine-grain level, synchronization and scheduling strategies determine the ultimate performance of the system. Loop-iteration-level parallelism seems to be a more appropriate level when those factors are considered. Barrier synchronization and data synchronization at the loop-iteration level are also studied. It is found that both schemes are needed for a better performance. <<ETX>>
An analytical framework for performance comparison of bandwidth reservation schemes in WDM ring

A number of bandwidth reservation schemes have been proposed for multi-channel rings, generally classified as centralized and distributed. Besides simulation results, the existing analytical models address only the blocking probability and achievable throughput of such schemes. However, in determining the properties and advantages of each reservation scheme (especially the LightRing, a scheme previously proposed by the authors) the above performance figures are not sufficient, as network latency plays a determinant role when fast bandwidth provisioning is of the essence. This paper presents an analytical framework that allows one to derive the response time and throughput of such schemes under the assumption that a single request for bandwidth can be stored and processed by the source at a time. Numerical results obtained using the proposed model reveal a number of interesting properties of the existing bandwidth reservation schemes.
Using a Cognitive Model to Represent Information in a Social Simulation

The future of national security will require winning not only the heart and minds of political leaders but also of the global population. The increased importance of the thoughts and opinions of the global population require a greater understanding of how information is disseminated across a society. The Seldon toolkit and the Cognitive Framework are two tools which address this need. They provide analysts and policy makers insight into how social dynamics and cognitive reasoning determine the result of actions taken. This concept paper outlines an integrated tool whose foundations are the Seldon toolkit and the Cognitive Framework which codifies psychologically plausible mechanisms for the reception, processing, and sharing of information through interactions.
A Novel Postsynaptic Mechanism for Heterosynaptic Sharing of Short-Term Plasticity

Postsynaptic release of Ca2+ from intracellular stores is an important means of cellular signaling that mediates numerous forms of synaptic plasticity. Previous studies have identified a postsynaptic intracellular Ca2+ requirement for a form of short-term plasticity, post-tetanic potentiation (PTP) at sensory neuron (SN)–motor neuron synapses in Aplysia. Here, we show that postsynaptic IP3-mediated Ca2+ release in response to a presynaptic tetanus in an SN that induces PTP can confer transient plasticity onto a neighboring SN synapse receiving subthreshold activation. This heterosynaptic sharing of plasticity represents a dynamic, short-term synaptic enhancement of synaptic inputs onto a common postsynaptic target. Heterosynaptic sharing is blocked by postsynaptic disruption of Ca2+- and IP3-mediated signaling, and, conversely, it is mimicked by postsynaptic injection of nonhydrolyzable IP3, and by photolysis of caged IP3 in the MN. The molecular mechanism for heterosynaptic sharing involves metabotropic glutamate receptors and Homer-dependent interactions, indicating that Homer can facilitate the integration of Ca2+-dependent plasticity at neighboring postsynaptic sites and provides a postsynaptic mechanism for the spread of plasticity induced by presynaptic activation. Our results support a model in which postsynaptic summation of IP3 signals from suprathreshold and subthreshold inputs results in molecular coincidence detection that gives rise to a novel form of heterosynaptic plasticity.
Bluetooth Low Energy (BLE) based blood pressure monitoring system

In this paper, we successfully developed a Bluetooth Low Energy (BLE) based blood pressure monitoring system, which integrated a homemade blood pressure measuring device and a smartphone. The device uses single BLE System-on-Chip to process the algorithm of blood pressure measurement and data transmission. Through the newest Bluetooth Low Energy technology, device can send measured results to the smartphone. Therefore, users can get the information of systolic blood pressure, diastolic blood pressure and pulse rate on the smartphone. Besides, the format of data transmission packet is based on the standard Blood Pressure Profile specification from Bluetooth SIG. The homemade blood pressure monitor has high compatibility to communication with other devices using the same Bluetooth profile. The accuracy of pulse rate and blood pressures are verified through the CuffLink simulator. The accuracy of pulse rate is -1.13 ± 0.52 beats, the accuracy of systolic blood pressure is 0.69 ± 1.63 mmHg, and the accuracy of diastolic blood pressure is 0.20 ± 1.02 mmHg. In clinical trials, the systolic blood pressure average difference between our method and auscultatory method is 2.66 ± 2.71 mmHg. The diastolic blood pressure average difference between our method and auscultatory method is 3.42 ± 4.42 mmHg. As a result, this device has high accuracy for measuring blood pressure and pulse rate.
Chordal Distance-Based User Selection Algorithm for the Multiuser MIMO Downlink with Perfect or Partial CSIT

In this paper, we consider user selection algorithms for Multi-user MIMO systems with perfect or partial channel state information at the transmitter (CSIT). A novel user selection algorithm based on chordal distance is proposed. The basic principle is to serve the user subset in which one is approximately orthogonal to the others. Since the chordal distance relies only on the channel direction information, the proposed algorithm has a low computational complexity, and can be extended straightly to the limited feedback system. Analysis and simulations verify the effectiveness of the proposed method.
A Method of Improving Qualities of True Random Sequences Based-On Wavelet Analysis

With the higher demands for qualities of random sequences, true random sequences are paid more attention because of their higher security features. Although true random sequences have the character of unprediction, they still have problems on big deviation and correlation. The problem on how to get rid of these factors affecting security and obtain good randomicity is becoming the research focus. In this paper, the theory of wavelet analysis is applied to improve the qualities of true random sequences. The emulation results prove that the method used is effective in obtaining unpredictable and unrepeated random sequences.
Infant brain structures, executive function, and attention deficit/hyperactivity problems at preschool age. A prospective study.

BACKGROUND Neuroimaging findings have provided evidence for a relation between variations in brain structures and attention deficit/hyperactivity disorder (ADHD). However, longitudinal neuroimaging studies are typically confined to children who have already been diagnosed with ADHD. In a population-based study, we aimed to characterize the prospective association between brain structures measured during infancy and executive function and attention deficit/hyperactivity problems assessed at preschool age. METHODS In the Generation R Study, the corpus callosum length, the gangliothalamic ovoid diameter (encompassing the basal ganglia and thalamus), and the ventricular volume were measured in 784 6-week-old children using cranial postnatal ultrasounds. Parents rated executive functioning at 4 years using the behavior rating inventory of executive function-preschool version in five dimensions: inhibition, shifting, emotional control, working memory, and planning/organizing. Attention deficit/hyperactivity problems were assessed at ages 3 and 5 years using the child behavior checklist. RESULTS A smaller corpus callosum length during infancy was associated with greater deficits in executive functioning at 4 years. This was accounted for by higher problem scores on inhibition and emotional control. The corpus callosum length during infancy did not predict attention deficit/hyperactivity problem at 3 and 5 years, when controlling for the confounders. We did not find any relation between gangliothalamic ovoid diameter and executive function or Attention deficit/hyperactivity problem. CONCLUSIONS Variations in brain structures detectible in infants predicted subtle impairments in inhibition and emotional control. However, in this population-based study, we could not demonstrate that early structural brain variations precede symptoms of ADHD.
Research Narrative

The first challenge, power dissipation, became evident at the beginning of this decade, and the importance has only grown in magnitude in the last several years. Power dissipation manifests as a problem in three fundamental ways: 1) high power dissipation is the primary performance limiter for mainstream highperformance microprocessors — it is simply not cost-effective to cool and deliver power to microprocessors with high power dissipation; 2) power dissipation limits the capabilities of battery-powered mobile devices and “off-grid” computers such as wireless sensor nodes and computing devices in the developing world; and 3) energy costs dominate the cost of modern internet datacenters; 80% of the costs of Microsoft’s recent 200MW datacenter in Chicago are energy related. The environmental impact of increased energy dissipation in information technology devices must also be considered.
Templates-instruments for standardizing ERP systems

Today's large companies face significant challenges in the integration of differently configured ERP systems which have evolved within the last decade. These systems impede the flow of information along the value chain which is vital for supply chain management and holistic controlling processes. They also create implementation inefficiencies since learning and scale effects are not taken advantage of. Therefore, establishing standards for the harmonization of independent and distributed systems would have a profound positive competitive impact. This article describes the Template Handbook, a standardization approach which as developed and implemented in a project with a multinational company, the Robert Bosch Group. ERP templates establish interoperability by identically configuring individual ERP systems within a company. They are enablers for the automatic exchange of information between ERP systems and the multiplication of know-how obtained from multiple ERP implementations. A vital component for the development and the roll-out of the templates was the method which was elaborated in the project.
Trumping Racism: The Interactions of Stereotype Incongruent Clothing, Political Racial Rhetoric, and Prejudice Toward African Americans

Clothing type and exposure to racial rhetoric may influence prejudice toward African Americans. We used a between-group design with clothing type (stereotype congruent or incongruent) and exposure to racial rhetoric (strong/weak/none) as independent variables. We found a main effect for clothing type (p < .001, ηp = .71) and racial rhetoric exposure (p < .001, ηp = .65), but no interaction. Participants' Symbolic Racism scores were significant covariates, positively related to prejudice. Participants rated African American models in stereotype incongruent clothing more positively. Viewing President Trump speak negatively about African Americans significantly decreased participants' prejudice of African American models. The findings of this study show how the clothing one wears, the racial oratory one views, and symbolic racism can drastically impact one’s perceptions. Research should seek to reduce automatic judgments and continue to pursue how other clothing styles affect perceptions, as well as how major political figures can play a role in those judgments.
Feature Extraction of EEG-P 300 Signals Using Nonlinear Independent Component Analysis

— Electroencephalogram (EEG) recordings provide an important means of brain-computer communication, but their classification accuracy and transfer rate are limited by unexpected signal variations due to artifacts and noises. In this paper, a nonlinear independent component analysis (NICA) extraction method for brain signal based EEG-P300 are proposed. The performance of the proposed method is investigated through a comparison of well known extraction methods (i.e., AAR, JAD E, and SOBI algorithms). Finally, the promising results reported here reflect the considerable potential of EEG for the continuous classification of mental states. I. INTRODUCTION The human brain consists of appro ximately 10 10 to 10 11 neurons [1]. Signals between neurons are transmitted by means of action potentials, which are very short bursts of electrical activity. The total electric current produced in such a cluster is large enough to be detected by measuring the potential distribution on the scalp, which is the method used in electroencephalographic (EEG). EEG is used extensively for monitoring the electrical activ ity within the human brain, both for research and clin ical purposes. EEG is used both for the measurement of spontaneous activity and for the study of evoked potentials. In particular the P300 evoked potential [2] is a positive peak that is evoked 300 ms stimu lus onset. The presence, magnitude, topography, and time of the response signal are often used as met rics of cognitive function in decision making processes. In general, the detection of a P300 is made difficu lt by its low signal-to-noise (SNR) ratio compared to the ongoing background EEG. Hu man scalp EEG recording has the advantage of being noninvasive, inexpensive, and portable, wh ich make it a very popular technique among the Brain computer interface (BCI) community [3-6]. Most EEG research seeks to understand the brain's dynamic processes that are the basis of physical and mental act ivities. In addition to this, EEG signals are being investigated as a new mode o f hu man-co mputer co mmun ication. If the informat ion in a mental task is accurately obtained fro m EEG signals, a user can compose the sequence of the task to indicate commands that can operate a co mputer display or other devices. Successful
Face recognition using eigenfaces

An approach to the detection and identification of human faces is presented, and a working, near-real-time face recognition system which tracks a subject's head and then recognizes the person by comparing characteristics of the face to those of known individuals is described. This approach treats face recognition as a two-dimensional recognition problem, taking advantage of the fact that faces are normally upright and thus may be described by a small set of 2-D characteristic views. Face images are projected onto a feature space ('face space') that best encodes the variation among known face images. The face space is defined by the 'eigenfaces', which are the eigenvectors of the set of faces; they do not necessarily correspond to isolated features such as eyes, ears, and noses. The framework provides the ability to learn to recognize new faces in an unsupervised manner. <<ETX>>
The Role of Christianity and Islam in Explaining Prejudice against Asylum Seekers: Evidence from Malaysia

ABSTRACT Prejudicial attitudes toward asylum seekers are prevalent, and an emerging body of literature has revealed that this is partly driven by religious affiliation. The population of Malaysia is multireligious, making it a fruitful location for testing religion-based prejudice hypotheses. Thus, across 2 studies we tested the roles of Christianity and Islam in explicit and implicit prejudices against asylum seekers in the Malaysian context. In Study 1 (n = 97), we present evidence that there are religion-based differences in prejudice against asylum seekers; specifically, Muslims reported higher levels of (classical) explicit prejudice toward asylum seekers than Christians (there were no differences in conditional or implicit prejudices). In Study 2 (n = 117), we tested the hypothesis that these religion-based differences are qualified by the religion of the asylum seeker. In this study, we used a framing paradigm to experimentally manipulate the religion of the asylum-seeking targets. The results revealed an out-group exacerbation effect; that is, participants reported higher levels of prejudice toward asylum seekers who had a different religion from their own. For classical explicit prejudice, the effect was strongest from Muslims toward Christian asylum seekers. Conversely, for implicit prejudice, the reverse was true: The effect was strongest from Christians toward Muslim asylum seekers. These findings are discussed in terms of the political and social circumstances in Malaysia, but we interpret these findings as evidence that explicit and implicit attitudes toward asylum seekers are driven by a complex pattern of religion-based intergroup biases.