Miracle-dz/UniFAR-FTUs huggingface dataset:
Exact Analysis of Energy-Aware Multiserver Queueing Systems with Setup Times

Energy consumption of today's datacenters is a constant concern from the standpoints of monetary and environmental costs. We model a datacenter as a queueing system, where each server can be switched on or off, with the time to switch a server on being nonnegligible. Previously derived structural properties of the optimal policy allow us to intelligently select policies to analyse further. Using the recursive renewal reward technique, we offer an exact analysis of these policies alongside offering insights, observations, and implications for how these systems behave. In particular, we provide insight into the question of the number of servers that should remain on at all times under a general cost function.
A Review of Self-Exciting Spatio-Temporal Point Processes and Their Applications

Self-exciting spatio-temporal point process models predict the rate of events as a function of space, time, and the previous history of events. These models naturally capture triggering and clustering behavior, and have been widely used in fields where spatio-temporal clustering of events is observed, such as earthquake modeling, infectious disease, and crime. In the past several decades, advances have been made in estimation, inference, simulation, and diagnostic tools for self-exciting point process models. In this review, I describe the basic theory, survey related estimation and inference techniques from each field, highlight several key applications, and suggest directions for future research.
Efficient Global Threshold Vector Outlyingness Ratio Filter for the Removal of Random Valued Impulse Noise

This research paper proposes a filter to remove Random Valued Impulse Noise (RVIN) based on Global Threshold Vector Outlyingness Ratio (GTVOR) that is applicable for real time image processing. This filter works with the algorithm that breaks the images into various decomposition levels using Discrete Wavelet Transform (DWT) and searches for the noisy pixels using the outlyingness of the pixel. This algorithm has the capability of differentiating high frequency pixels and the “noisy pixel” using the threshold as well as window adjustments. The damage and the loss of information are prevented by means of interior mining. This global threshold based algorithm uses different thresholds for different quadrants of DWT and thus helps in recovery of noisy image even if it is 90% affected. Experimental results exhibit that this method outperforms other existing methods for accurate noise detection and removal, at the same time chain of connectivity is not lost.
A survey on approaches to the protection of personal data gathered by IoT devices

Security is always at the forefront of developing technologies. One can seldom go a week without hearing of a new data breach or hacking attempt from various groups around the world, often taking advantage of a simple flaw in a system’s architecture. The Internet of Things (IoT) is one of these developing technologies which may be at risk of such attacks. IoT devices are becoming more and more prevalent in everyday life. From keeping track of an individual’s health, to suggesting meals from items available in an individual’s fridge, these technologies are taking a much larger role in the personal lives of their users. With this in mind, how is security being considered in the development of these technologies? Are these devices that monitor individual’s personal lives just additional vectors for potential data theft? Throughout this survey, various approaches to the development of security systems concerning IoT devices in the home will be discussed, compared, and contrasted in the hope of providing an ideal solution to the problems this technology may produce.
Validity of brief alcohol screening tests among adolescents: a comparison of the AUDIT, POSIT, CAGE, and CRAFFT.

BACKGROUND Adolescents should be screened for alcohol misuse as part of routine care. The objective of this study was to compare the criterion validity of the Alcohol Use Disorders Identification Test (AUDIT), the Problem Oriented Screening Instrument for Teenagers substance use/abuse scale (POSIT), and the CAGE and CRAFFT questions among adolescents. METHODS Fourteen- to 18-year-old patients arriving for routine healthcare at a large, hospital-based adolescent clinic completed the four screens and the criterion standard Adolescent Diagnostic Interview, which yields DSM-IV diagnoses of alcohol abuse and dependence. Receiver operating characteristic (ROC) curves were plotted to determine optimal cut-points. Areas under the ROC curves of the four screens were compared, and sensitivities and specificities were calculated. RESULTS Participants' past 12-month alcohol diagnostic classifications were as follows: no use (58.6%), nonproblem use (13.0%), problem use (20.8%), abuse (5.4%), and dependence (2.2%). Optimal cut-points associated with problem use or higher were 2 for AUDIT, 1 for POSIT, 1 for CAGE, and 1 for CRAFFT. ROC curve area of the CAGE was significantly lower compared with areas of all other screens. Sensitivities (95% confidence intervals) were AUDIT 0.88 (0.83-0.93), POSIT 0.84 (0.79-0.90), CAGE 0.37 (0.29-0.44), and CRAFFT 0.92 (0.88-0.96); specificities were AUDIT 0.81 (0.77-0.85), POSIT 0.89 (0.86-0.92), CAGE 0.96 (0.94-0.98), and CRAFFT 0.64 (0.59-0.69). CONCLUSIONS The AUDIT, POSIT, and CRAFFT have acceptable sensitivity for identifying alcohol problems or disorders in this age group. The CAGE is not recommended for use among adolescents.
Toward Personalized Public Transportation Recommendation System with Adaptive User Interface

Public transportation guidance services, such as Yahoo, Jorudan and NAVITIME, are widely used nowadays and support our daily lives. Although they provide useful services, they have not fully been personalized yet. This paper presents a personalized transportation system called PATRASH: Personalized Autonomous TRAnsportation recommendation System considering user context and History. In particular, we discuss an Adaptive User Interface (AUI) of Patrash. Before designing a personalized route recommendation function for Patrash's AUI, we investigated possibilities and effectiveness of the function. First, we collected and analyzed 10 subjects' usage histories of public transportation. Through this investigation, we confirmed the possibilities and effectiveness of the personalized route recommendation function. Second, we investigated the effectiveness of the basic functions of Patrash's AUI by comparing with two major transportation guidance systems in Japan. We evaluated those systems from the points of views of usabilities: click costs and time costs. The experimental results illustrate the effectiveness of AUI of Patrash.
Antioxidant Activity of Leek towards Free Radical Resulting from Consumption of Carbonated Meat in Rats

Forty -two albino male rats were randomly classified into six groups (7 rats each). The first group kept as control negative fed basal diet only. The other five groups fed on basal diet with 10% extreme grilled meat and classified into non treated group and treated groups with water leek extract, methanol leek extract, 2.5 % leek powder and 5% leek powder. Consumption of carbonyl meat only in non treated group decreased final weight, weight gain, food intake ,feed efficiency ratio(FER) , hemoglobin , packed cell volume ,blood glutathione peroxidase (GPX) , blood super oxide dismutase (SOD) , liver super oxide dismutase (SOD), liver glutathione peroxidase (GPX) and liver glutathione transferase (GST) but significant increase in AST enzyme, creatinine ,urea nitrogen blood free radical and serum lipid peroxide (LPX) and liver malondialdehyde (MDA) compared to normal control group. The treated groups with water ,methanol extracts, 2.5 % and 5% leak showed that the values of final weight, weight gain, food intake ,FER, hemoglobin, serum alanine amino transferase (ALT) enzyme, creatinine, urea nitrogen , blood GPX , blood SOD and blood GST around the values of normal control group. The treated groups with water ,methanol extracts, 2.5 % and 5% leak showed significant decrease in packed cell volume , liver SOD and GPX but significant increase in AST, blood free radical , LPX ,liver MDA compared to normal control group. The values of final weight, weight gain, food intake , FER hemoglobin , packed cell volume ,blood GPX , blood SOD, liver SOD, liver GPX and liver GST were increased but the values of AST enzyme, creatinine ,urea nitrogen, blood free radical, serum lipid peroxide and liver MDA were decreased in all treated groups compared to non treated group. [Wafeka Abdulah Al Hamedan and Manal Lalualit Khalid Anfenan. Antioxidant Activity of Leek towards Free Radical Resulting from Consumption of Carbonated Meat in Rats. Life Science Journal. 2011;8(1):169-176] (ISSN:1097–8135). http://www.lifesciencesite. com. Key wards: leek, free radical, antioxidant, carbonated meat& rats
Joint Channel and Network Decoding for XOR-Based Relay in Multi-Access Channel

In this paper network coding based relay for multi-access channel is studied. In the system, two nodes send messages to a common access point (AP). A relay assists the two nodes by forwarding a network coded version of the messages. The AP performs joint channel and network decoding to recover the two original messages from three received signals. Two schemes, soft network coding (SoftNC) and turbo network coding (TurboNC), both focusing on bitwise exclusive or (XOR) based network coding, are proposed to salvage messages from erroneous signals. SoftNC is simple and backward compatible with existing protocol stack of wireless networks, and reduces packet errors by maximal ratio combining (MRC). TurboNC improves channel efficiency by letting the relay node transmit only parity check bits of the interleaved XORed message, where reliability is retained by iterative decoding. Simulation results show that compared with the network-layer path diversity scheme [8], both SoftNC and TurboNC greatly improve the reliability, and TurboNC also achieves a much higher throughput. The proposed schemes are suitable for improving the performance of wireless local area networks (WLAN).
A New Method to Generate Artificial Frames Using the Empirical Mode Decomposition for an EEG-Based Motor Imagery BCI

EEG-based Brain-Computer Interfaces (BCIs) are becoming a new tool for neurorehabilitation. BCIs are used to help stroke patients to improve the functional capability of the impaired limbs, and to communicate and assess the level of consciousness in Disorder of Consciousness (DoC) patients. BCIs based on a motor imagery paradigm typically require a training period to adapt the system to each user's brain, and the BCI then creates and uses a classifier created with the acquired EEG. The quality of this classifier relies on amount of data used for training. More data can improve the classifier, but also increases the training time, which can be especially problematic for some patients. Training time might be reduced by creating new artificial frames by applying Empirical Mode Decomposition (EMD) on the EEG frames and mixing their Intrinsic Mode Function (IMFs). The purpose of this study is to explore the use of artificial EEG frames as replacements for some real ones by comparing classifiers trained with some artificial frames to classifiers trained with only real data. Results showed that, in some subjects, it is possible to replace up to 50% of frames with artificial data, which reduces training time from 720 to 360 s. In the remaining subjects, at least 12.5% of the real EEG frames could be replaced, reducing the training time by 90 s. Moreover, the method can be used to replace EEG frames that contain artifact, which reduces the impact of rejecting data with artifact. The method was also tested on an out of sample scenario with the best subjects from a public database, who yielded very good results using a frame collection with 87.5% artificial frames. These initial results with healthy users need to be further explored with patients' data, along with research into alternative IMF mixing strategies and using other BCI paradigms.
Low-Cost Wake-Up Receiver for RF Energy Harvesting Wireless Sensor Networks

The existing passive wake-up receivers (WuRxs) are radio frequency identification (RFID) tag based, which incur high cost and complexity. In this paper, we study cost-effective and long-range WuRx solutions for range-based wake-up (RW) as well as directed wake-up (DW). In particular, we consider the case of an RF energy harvesting wireless sensor node and investigate how a low-cost WuRx can be built using an RF energy harvester available at the node. Experimental results show that our developed prototype can achieve a wake-up range of 1.16 m with +13 dBm transmit power. Furthermore, our empirical study shows that at +30 dBm transmit power the wake-up distance of our developed RW module is >9 m. High accuracy of DW is demonstrated by sending a 5-bit ID from a transmitter at a bit rate up to 33.33 kbps. Finally, we present optimized WuRx designs for RW and DW using Agilent advanced design system, which offer up to 5.69 times higher wake-up range for RW and energy savings per bit of about 0.41 mJ and 21.40 nJ, respectively, at the transmitter and the sensor node in DW.
A Scale Adaptive Tracker Using Hybrid Color Histogram Matching Scheme

In this paper we propose a computationally efficient scale adaptive tracking method using a hybrid color histogram matching scheme. Firstly, we report an important property of the Chi-squared measure- It outperforms Bhattacharyya measure in the task of histogram matching from a few significantly similar multimodal histograms. Also, Bhattacharyya measure performs better while selecting matches from a varied dataset. We employ these results to develop a hybrid histogram matching procedure using the two measures. This method is used for a patch matching algorithm in real time tracking. We first calculate a color histogram of the target which is then compared with histograms of patches in the neighborhood in subsequent frames using this hybrid procedure to obtain the best match. We devise a systematic scale adaptive tracking method which is robust to rapid changes in the target size. It is also robust to partial occlusion of the target. Extensive experimental proof based on real life and test datasets is presented which demonstrates the excellent tracking accuracy achieved by our algorithm at real time.
Envisioning future cognitive telerehabilitation technologies: a co-design process with clinicians

Abstract Purpose Cognitive telerehabilitation is the concept of delivering cognitive assessment, feedback, or therapeutic intervention at a distance through technology. With the increase of mobile devices, wearable sensors, and novel human–computer interfaces, new possibilities are emerging to expand the cognitive telerehabilitation paradigm. This research aims to: (1) explore design opportunities and considerations when applying emergent pervasive computing technologies to cognitive telerehabilitation and (2) develop a generative co-design process for use with rehabilitation clinicians. Methods We conducted a custom co-design process that used design cards, probes, and design sessions with traumatic brain injury (TBI) clinicians. All field notes and transcripts were analyzed qualitatively. Results Potential opportunities for TBI cognitive telerehabilitation exist in the areas of communication competency, executive functioning, emotional regulation, energy management, assessment, and skill training. Designers of TBI cognitive telerehabilitation technologies should consider how technologies are adapted to a patient’s physical/cognitive/emotional state, their changing rehabilitation trajectory, and their surrounding life context (e.g. social considerations). Clinicians were receptive to our co-design approach. Conclusion Pervasive computing offers new opportunities for life-situated cognitive telerehabilitation. Convivial design methods, such as this co-design process, are a helpful way to explore new design opportunities and an important space for further methodological development. Implications for Rehabilitation Designers of rehabilitation technologies should consider how to extend current design methods in order to facilitate the creative contribution of rehabilitation stakeholders. This co-design approach enables a fuller participation from rehabilitation clinicians at the front-end of design. Pervasive computing has the potential to: extend the duration and intensity of cognitive telerehabilitation training (including the delivery of ‘booster’ sessions or maintenance therapies); provide assessment and treatment in the context of a traumatic brain injury (TBI) patient’s everyday life (thereby enhancing generalization); and permit time-sensitive interventions. Long-term use of pervasive computing for TBI cognitive telerehabilitation should take into account a patient’s changing recovery trajectory, their meaningful goals, and their journey from loss to redefinition.
Identical anthropometric characteristics of impaired fasting glucose combined with impaired glucose tolerance and newly diagnosed type 2 diabetes: anthropometric indicators to predict hyperglycaemia in a community-based prospective cohort study in southwest China

Objectives To assess the anthropometric characteristics of normoglycaemic individuals who subsequently developed hyperglycaemia, and to evaluate the validity of these measures to predict prediabetes and diabetes. Design A community-based prospective cohort study. Participants In total, 1885 residents with euglycaemia at baseline from six communities were enrolled. Setting Sichuan, southwest China. Primary outcome measures The incidences of prediabetes and diabetes were the primary outcomes. Methods The waist-to-height ratio (WHtR), body mass index (BMI), waist circumference (WC) and waist-to-hip ratio (WHR) of all participants were measured at baseline and during follow-up. A 75 g glucose oral glucose tolerance test was conducted at each survey. Results During a median of 3.00 (IQR: 2.92–4.17) years follow-up, the cumulative incidence of isolated impaired fasting glucose (IFG), isolated impaired glucose tolerance (IGT), IFG combined with IGT (IFG+IGT), and newly diagnosed diabetes mellitus (NDDM) were 8.44%, 18.14%, 8.06% and 13.79%, respectively. WHtR, BMI, WC and WHR were significantly different among subjects who subsequently progressed to isolated IFG or IGT, IFG+IGT or NDDM (p<0.05). The anthropometric characteristics of IFG+IGT subjects were similar to those of the NDDM population (p>0.005). All the baseline anthropometric measurements were useful for the prediction of future prediabetes and NDDM (p<0.05). The optimal thresholds for the four measurements were calculated for the prediction of hyperglycaemia, with a WHtR value of 0.52 performing best to identify isolated IFG or IGT, IFG+IGT and NDDM. Conclusions Anthropometric measures, especially WHtR, could be used to predict hyperglycaemia 3 years in advance. Distinct from isolated IFG and IGT, the individuals who developed combined IFG+IGT had identical anthropometric profiles to those who progressed to NDDM.
Sex differences in kin bias at maturation: Male rhesus macaques prefer paternal kin prior to natal dispersal

Dispersal and mating patterns are known to affect the availability of both maternal and paternal kin within social groups, with important effects on the evolution of sociality. It is generally assumed that the philopatric sex forms stronger social bonds than the dispersing sex, possibly as a result of reduced kin availability for the dispersing sex after departure. However, few primate studies have directly compared whether sex differences in association patterns, particular with kin, are already present prior to dispersal when kin availability should be the same for both sexes. Here, we compared affiliative and aggressive interactions in a female philopatric species, the rhesus macaque (Macaca mulatta), to test whether sex differences in kin bias already occur around the age of maturation, when both sexes still live together with kin in their natal group. Our data confirmed that kin availability was the same for both sexes prior to male dispersal. Similar kin availability was partially reflected by comparable association patterns, as both females and males preferentially interacted with maternal kin. However, females had stronger affiliative bonds with maternal kin than males of the same age, indicating that kin associations not only depended upon kin availability, but were also sex‐specific. Similarly, males were significantly more likely to affiliate with paternal kin than non‐kin, as compared to females, suggesting that males discriminated paternal kin from non‐kin earlier in life than females. Males might have a stronger need than females to affiliate with paternal kin due to a reduced integration in the matrilineal family prior to dispersal and the high availability of paternally related age‐peers, with whom males could potentially migrate. Females, in contrast, form stronger affiliations with maternal kin, which may enhance their offspring's survival. More comparative studies are needed to understand the impact of different dispersal regimes on patterns of kin associations. Am. J. Primatol. 78:78–91, 2016. © 2016 Wiley Periodicals, Inc.
Quantification of the cerebrospinal fluid from a new whole body MRI sequence

Our work aims to develop a biomechanical model of hydrocephalus both intended to perform clinical research and to assist the neurosurgeon in diagnosis decisions. Recently, we have defined a new MR imaging sequence based on SPACE (Sampling Perfection with Application optimized Contrast using different flip-angle Evolution). On these images, the cerebrospinal fluid (CSF) appears as a homogeneous hypersignal. Therefore such images are suitable for segmentation and for volume assessment of the CSF. In this paper we present a fully automatic 3D segmentation of such SPACE MRI sequences. We choose a topological approach considering that CSF can be modeled as a simply connected object (i.e. a filled sphere). First an initial object which must be strictly included in the CSF and homotopic to a filled sphere, is determined by using a moment-preserving thresholding. Then a priority function based on an Euclidean distance map is computed in order to control the thickening process that adds "simple points" to the initial thresholded object. A point is called simple if its addition or its suppression does not result in change of topology neither for the object, nor for the background. The method is validated by measuring fluid volume of brain phantoms and by comparing our volume assessments on clinical data to those derived from a segmentation controlled by expert physicians. Then we show that a distinction between pathological cases and healthy adult people can be achieved by a linear discriminant analysis on volumes of the ventricular and intracranial subarachnoid spaces.
Phylogenetic Relationships Within the Drosophila haleakalae Species Group Inferred by Molecular and Morphological Characters ( Diptera : Drosophilidae )

The Drosophila haleakalae species group, the most basal lineage within the Hawaiian Drosophila lineage, consists of 54 described species placed in 5 subgroups. Previous taxonomic studies, initiated by Elmo Hardy, have provided an excellent groundwork on which to base further evolutionary studies. We present a phylogenetic hypothesis of the Drosophila haleakalae species group using a suite of morphological, behavioral, and molecular characters (including 5 newly developed nuclear gene regions) that is more resolved and better supported than any previous phylogeny of this group. We use our phylogeny to refine and revise the taxonomic relationships of species in the haleakalae species group.