Miracle-dz/UniFAR-FTUs huggingface dataset:
Broadcast Approaches to the Diamond Channel

The problem of dual-hop transmission from a source to a destination via two parallel full-duplex relays in block Rayleigh fading environment is investigated. All nodes in the network are assumed to be oblivious to their forward channel gains; however, they have perfect information about their backward channel gains. We also assume a stringent decoding delay constraint of one fading block that makes the definition of ergodic (Shannon) capacity meaningless. The focus of this paper is on simple, efficient, and practical relaying schemes to increase the expected-rate at the destination. For this purpose, various combinations of relaying protocols and the broadcast approach (multi-layer coding) are proposed. For the decode-forward (DF) relaying, the maximum finite-layer expected-rate as well as two upper-bounds on the continuous-layer expected-rate are obtained. The main feature of the proposed DF scheme is that the layers being decoded at both relays are added coherently at the destination although each relay has no information about the number of layers being successfully decoded by the other relay. It is proved that the optimal coding scheme is transmitting uncorrelated signals via the relays. Next, the maximum expected-rate of ON/OFF based amplify-forward (AF) relaying is analytically derived. For further performance improvement, a hybrid decode-amplify-forward (DAF) relaying strategy, adopting the broadcast approach at the source and relays, is proposed and its maximum throughput and maximum finite-layer expected-rate are presented. Moreover, the maximum throughput and maximum expected-rate in the compress-forward (CF) relaying adopting the broadcast approach, using optimal quantizers and Wyner-Ziv compression at the relays, are fully derived. All theoretical results are illustrated by numerical simulations. As it turns out from the results, when the ratio of the relay power to the source power is high, the CF relaying outperforms DAF (and hence outperforms both DF and AF relaying); otherwise, DAF scheme is superior.
Automated resource release in device drivers

Device drivers require system resources to control hardware and provide fundamental services for applications. The acquired resources must be explicitly released by drivers. Otherwise, these resources will never be reclaimed by the operating system, and they are not available for other programs any more, causing hard-to-find system problems. We study on Linux driver mailing lists, and find many applied patches handle improper resource-release operations, especially in error handling paths. In order to improve current resource management and avoid resource-release omissions in device drivers, we propose a novel approach named AutoRR, which can automatically and safely release resources based on specification-mining techniques. During execution, we maintain a resource-state table by recording the runtime information of function calls. If the driver fails to release acquired resources during execution, AutoRR will report violations and call corresponding releasing functions with the recorded runtime information to release acquired resources. To fully and safely release acquired resources, a dynamic analysis of resource dependency and allocation hierarchy is also performed, which can avoid dead resources and double frees. AutoRR works in both normal execution and error handling paths for reliable resource management. We implement AutoRR with LLVM, and evaluate it on 8 Ethernet drivers in Linux 3.17. 2. The evaluation shows that the overhead of AutoRR is very low, and it has successfully fixed 18 detected resource-release omission violations without side effects. Our work shows a feasible way of using specification-mining results to avoid related violations.
Transfer Learning for Survival Analysis via Efficient L2,1-Norm Regularized Cox Regression

In survival analysis, the primary goal is to monitor several entities and model the occurrence of a particular event of interest. In such applications, it is quite often the case that the event of interest may not always be observed during the study period and this gives rise to the problem of censoring which cannot be easily handled in the standard regression approaches. In addition, obtaining sufficient labeled training instances for learning a robust prediction model is a very time consuming process and can be extremely difficult in practice. In this paper, we propose a transfer learning based Cox method, called Transfer-Cox, which uses auxiliary data to augment learning when there are insufficient amount of training examples. The proposed method aims to extract "useful" knowledge from the source domain and transfer it to the target domain, thus potentially improving the prediction performance in such time-to-event data. The proposed method uses the l_2,1-norm penalty to encourage multiple predictors to share similar sparsity patterns, thus learns a shared representation across source and target domains, potentially improving the model performance on the target task. To speedup the computation, we apply the screening approach and extend the strong rule to sparse survival analysis models in multiple high-dimensional censored datasets. We demonstrate the performance of the proposed transfer learning method using several synthetic and high-dimensional microarray gene expression benchmark datasets and compare with other related competing state-of-the-art methods. Our results show that the proposed screening approach significantly improves the computational efficiency of the proposed algorithm without compromising the prediction performance. We also demonstrate the scalability of the proposed approach and show that the time taken to obtain the results is linear with respect to both the number of instances and features.
Home-centric visualization of network traffic for security administration

Today's system administrators, burdened by rapidly increasing network activity, must quickly perceive the security state of their networks, but they often have only text-based tools to work with. These tools often provide no overview to help users grasp the big-picture. Our interviews with administrators have revealed that they need visualization tools; thus, we present VISUAL (Visual Information Security Utility for Administration Live), a network security visualization tool that allows users to see communication patterns between their home (or internal) networks and external hosts. VISUAL is part of our Network Eye security visualization architecture, also described in this paper. We have designed and tested a new computer security visualization that gives a quick overview of current and recent communication patterns in the monitored network to the users. Many tools can detect and show fan-out and fan-in, but VISUAL shows network events graphically, in context. Visualization helps users comprehend the intensity of network events more intuitively than text-based tools can. VISUAL provides insight for networks with up to 2,500 home hosts and 10,000 external hosts, shows the relative activity of hosts, displays them in a constant relative position, and reveals the ports and protocols used.
Denotational semantics for program analysis

Syntax P : = K Program K : := begin D; S end Block D : := D 1 ; D 2 I var I I const I= N [ proc I (I 1 , . ., Iq) = S Declaration S : := S i ; S 2 I read I I write E I I := E Statemen t I call I (E 1 , . ., E n ) I if 13 then S 1 else S 2 I while B do S I K E ::=E 1 + E2 1E 1 E2 1E 1 E 2 1E 1 /E1 II I N B : :=E1=E2IE1 E21E1 <E2 (E 1 > E2 [E 1 <E1 I E 1 > E 1 Semantic Domains 3: T = {true, false, co } 3 : N = {0, 1, 2, . ., w } a : L = {1, 2, 3, . ., w } = N File a :E=LAN Store E= E X X 1 Configuratio n rr :II=E E Procedur e d : A = L + N + I7 Denotable-valu e 3: T = I © Environment Semantic Equations P : Program -4 File r File P [[ K][ X0 (K [ K] (XI .w) <X a . w, 0, nil > )13 K: Block — Environment --. Configuration --b Configuratio n K [ begin D ; S end] ° Xv . XE . let <v', a ' >= D ED] u (e11) in S [[ S] v' <a', e12, e13 > D: Declaration . Environment -+ Store ---► Environment X Stor e D [ D 1 ; D 2] = Xv . Xa . let <v', a'> d D [ D1] v a in D [[ D 2] v' a ' D [ const I= N]] . Xv . Xa . <(I~--ink N]v, a > D [[ var I] = Xv.Xa .let a=new-loco in <[I.--ini a]v, [a<--1 a > D [[ pros I (I,, . ., I n)= S] Xv . Xa . <[I+-inA X(a,, . ., an) . ( S ([ S][I14-a1, . ., In4-an]v))]v, a > S : Statement -_4 Environment -4 Configuration -4 Configuration S [ S 1 ; S2 ]] Xv . (S [[ S2]] v ) o (S [[ S i] v) S [ I:= E]] Xv.X4 . <[(v [[ I] I L)4---E [[ E]] v (ell)](e11), e1 2 , G3 > S [ read I]] = Xv . X4 . <[(v [[ I] I L)+-hd(e12)](e j1), tl(e12), E13 > S [write E]] Xv . Xe. <ell, ell, append(e13, E[E] v (ci)) > S [[ if B then S i else S2]] Xv . X4 . (B [ B]] v (ell) C-+ S [ S 1 ]] v g, S [ S 2] v e ) S [[ while B do S] _ Xv . Xe' . (B [[ B]] v (411) (S [ while B do S]] v) o (S [ S]] v), e ) S [ call I (E 1 , . ., E n)] Xv . XC . let a 1 = new-Ioc(), . , a n= new-loco in ((v [ I]] I Il)(a l , . ., a n ) ) <(a 1 + E [[ E1] v (~11), . , an -E F En ][ v (el l )]( I ), 01 2 , G13 > S [[ K]] Xv.XC. K[[ K]] u 4 E: Expression -+ Environment -4 Store —# Natural number E [[E 1 opE2]]Xv.Xa . E [E1]]vaopE [[E2]]v a E [[ I]I Xv . Xa.a (v [ I]]I L) E [ N]] Xv.Xa . N B : Boolean-expression Environment -# Store Truth B [ E 1 rel-op E2] _ Xv . Xa. (E [ E 1 ]] v a ee1-op E [ E2 ]] v a -d true, false ) Figure 2 . 1 Denotational Semantics of a Simple Algol-like Languag e Expressio n Boolean-expression Identifier Truth valu e Natural number Location
MPI-Based Heterogeneous Cluster Construction Technology

Nowadays, the applications of MPI-based clusters are used widely, such as the damage prediction of nuclear explosion and gene decryption. However, the usages of MPIbased heterogeneous cluster are nearly reported in contrast to the MPI-based homogeneous clusters due to the immature technology. This paper focuses on building a MPI based heterogeneous cluster with the MPICH2, which is released last year and has not supported the heterogeneous cluster yet. Beside, we give the reasons and test results in the paper to illustrate the benefits of using the MPI-based heterogeneous cluster without virtualization.
Exemplar-Based Human Action Pose Correction

The launch of Xbox Kinect has built a very successful computer vision product and made a big impact on the gaming industry. This sheds lights onto a wide variety of potential applications related to action recognition. The accurate estimation of human poses from the depth image is universally a critical step. However, existing pose estimation systems exhibit failures when facing severe occlusion. In this paper, we propose an exemplar-based method to learn to correct the initially estimated poses. We learn an inhomogeneous systematic bias by leveraging the exemplar information within a specific human action domain. Furthermore, as an extension, we learn a conditional model by incorporation of pose tags to further increase the accuracy of pose correction. In the experiments, significant improvements on both joint-based skeleton correction and tag prediction are observed over the contemporary approaches, including what is delivered by the current Kinect system. Our experiments for the facial landmark correction also illustrate that our algorithm can improve the accuracy of other detection/estimation systems.
Discourse Relation Sense Classification Systems for CoNLL-2016 Shared Task

This paper reports the submitted discourse relation classification systems of the language information processing group of Beijing Institute of Technology (BIT) to the CoNLL-2016 shared task. In this work, discriminative methods were employed according to the different characteristics of English and Chinese discourse structures. Additionally, distributed representations were introduced to catch the deep semantic relations. Experiments shows their effectiveness on both English and Chinese tasks.
The Relationship Between Specific Pavlovian Instrumental Transfer and Instrumental Reward Probability

Goal-directed behavior is influenced by environmental cues: in particular, cues associated with a reward can bias action choice toward actions directed to that same reward. This effect is studied experimentally as specific Pavlovian-instrumental transfer (specific PIT). We have investigated the hypothesis that cues associated to an outcome elicit specific PIT by rising the estimates of reward probability of actions associated to that same outcome. In other words, cues reduce the uncertainty on the efficacy of instrumental actions. We used a human PIT experimental paradigm to test the effects of two different instrumental contingencies: one group of participants had a 33% chance of being rewarded for each button press, while another had a 100% chance. The group trained with 33% reward probability showed a stronger PIT effect than the 100% group, in line with the hypothesis that Pavlovian cues linked to an outcome work by reducing the uncertainty of receiving it. The 100% group also showed a significant specific PIT effect, highlighting additional factors that could contribute to specific PIT beyond the instrumental training contingency. We hypothesize that the uncertainty about reward delivery due to testing in extinction might be one of these factors. These results add knowledge on how goal-directed behavior is influenced by the presence of environmental cues associated with a reward: such influence depends on the probability that we have to reach a reward, namely when there is less chance of getting a reward we are more influenced by cues associated with it, and vice versa.
Sensing urban mobility with taxi flow

The analysis of taxi flow can help better understand the urban mobility. In this work, we analyze 177, 169 taxi trips collected in Lisbon, Portugal, to explore the relationships between pick-up and drop-off locations; the behavior between the previous drop-off to the following pick-up; and the impact of area type in taxi services. We also carry out the analysis of predictability of taxi trips given history of taxi flow in time and space.
A New Method for Lower Bounds on the Running Time of Evolutionary Algorithms

In this paper a new method for proving lower bounds on the expected running time of evolutionary algorithms (EAs) is presented. It is based on fitness-level partitions and an additional condition on transition probabilities between fitness levels. The method is versatile, intuitive, elegant, and very powerful. It yields exact or near-exact lower bounds for LO, OneMax, long k-paths, and all functions with a unique optimum. Most lower bounds are very general; they hold for all EAs that only use bit-flip mutation as variation operator, i.e., for all selection operators and population models. The lower bounds are stated with their dependence on the mutation rate. These results have very strong implications. They allow us to determine the optimal mutation-based algorithm for LO and OneMax, i.e., the algorithm that minimizes the expected number of fitness evaluations. This includes the choice of the optimal mutation rate.
Relationship between Sarcopenic Obesity and Cardiovascular Disease Risk as Estimated by the Framingham Risk Score

This study was conducted to assess the association between sarcopenic obesity and cardiovascular disease (CVD) risk in Korean adults (n=3,320; ≥40 yr) who participated in the 5th Korean National Health and Nutrition Examination Survey in 2010. The appendicular skeletal muscle mass divided by body weight was calculated for each participant; participants with values <1 standard deviation below the mean reference value (i.e., aged 20-39 yr) were considered sarcopenic. Subjects were further classified into 4 groups according to their obesity (i.e., body mass index ≥25 kg/m2) and sarcopenic status. Individuals' 10-yr CVD risk was determined using the Framingham risk model. The sarcopenic obese group had more participants (43.8% men, 14.6% women) with a high risk of CVD (≥20%). The sarcopenic obese group was associated with an increased 10-yr CVD risk than the non-sarcopenic, non-obese group (odds ratio [OR], 2.49; 95% confidence interval [CI], 1.53-4.06, P<0.001 in men; OR, 1.87; 95% CI, 1.02-3.41, P=0.041 in women). Sarcopenic non-obese and non-sarcopenic obese subjects were not associated with an increased 10-yr CVD risk. Sarcopenic obesity, but not non-sarcopenic obesity, was closely associated with an increased CVD risk in Korean adults. Graphical Abstract
Load balancing strategies in software defined networks

In the past few years, network requirements have been changing frequently as the amount of data traffic increasing exponentially so it is difficult to utilize the full capacity of network resources. Software Defined Networking (SDN) is emerging as a new networking technology which decouples the control plane from the data plane in the network devices. Separation of control and data plane allows a network administrator a better control over network management and also enables new development through network programmability. Presently Open-Flow is the most popular SDN protocol which provides communication between network devices and controller. In this paper, the Round Robin algorithm is compared with the Dynamic load balancing algorithm using the OpenFlow protocol in SDN under varying load conditions of TCP and UDP traffic. Experimental analysis shows that the dynamic load balancing strategy works better than the Round Robin load balancing.
Design and Performance Evaluation of BICM-ID in Slow Fading Channels

The demands for high data rates and spectrally efficient modulation techniques are increasing due to the evolution of multimedia service in wireless communication systems. Bit-interleaved coded modulation with iterative decoding (BICM-ID) is a bandwidth efficient transmission scheme and is well suitable for the next-generation mobile communications. But the performance of BICM-ID is poor in slow fading channels. As we know that diversity is an effective method to cope with fading and channel interleaving with error correction coding brings time diversity, an effective scheme is proposed in the paper in which a block interleaver is introduced to the BICM-ID encoder at the transmitter. This block interleaver serves as a channel interleaver which makes the burst errors induced by slow fading to be changed into random errors. Simulation results show that channel interleaving greatly improves the performance of BICM-ID in slow fading channels.
Progressive Depletion of Rough Endoplasmic Reticulum in Epithelial Cells of the Small Intestine in Monosodium Glutamate Mice Model of Obesity

Chronic obesity is a known risk factor for metabolic syndrome. However, little is known about pathological changes in the small intestine associated with chronic obesity. This study investigated cellular and subcellular level changes in the small intestine of obese mice. In this study, a mouse model of obesity was established by early postnatal administration of monosodium glutamate. Changes in body weight were monitored, and pathological changes in the small intestine were evaluated using hematoxylin-eosin and Nissl staining and light and electron microscopy. Consequently, obese mice were significantly heavier compared with controls from 9 weeks of age. Villi in the small intestine of obese mice were elongated and thinned. There was reduced hematoxylin staining in the epithelium of the small intestine of obese mice. Electron microscopy revealed a significant decrease in and shortening of rough endoplasmic reticulum in epithelial cells of the small intestine of obese mice compared with normal mice. The decrease in rough endoplasmic reticulum in the small intestine epithelial cells of obese mice indicates that obesity starting in childhood influences various functions of the small intestine, such as protein synthesis, and could impair both the defense mechanism against invasion of pathogenic microbes and nutritional absorption.
Development of numerical cognition in children and artificial systems: a review of the current knowledge and proposals for multi-disciplinary research

Numerical cognition is a distinctive component of human intelligence such that the observation of its practice provides a window in high-level brain function. The modelling of numerical abilities in artificial cognitive systems can help to confirm existing child development hypotheses and define new ones by means of computational simulations. Meanwhile, new research will help to discover innovative principles for the design of artificial agents with advanced reasoning capabilities and clarify the underlying algorithms (e.g. deep learning) that can be highly effective but difficult to understand for humans. This study promotes new investigation by providing a common resource for researchers with different backgrounds, including computer science, robotics, neuroscience, psychology, and education, who are interested in pursuing scientific collaboration on mutually stimulating research on this topic. The study emphasises the fundamental role of embodiment in the initial development of numerical cognition in children. This strong relationship with the body motivates the cognitive developmental robotics (CDR) approach for new research that can (among others) help standardise data collection and provide open databases for benchmarking computational models. Furthermore, the authors discuss the potential application of robots in classrooms and argue that the CDR approach can be extended to assist educators and favour mathematical education.
Peg-in-Hole assembly under uncertain pose estimation

A large part of industrial assembly tasks can be broken down to permutations of Peg-in-Hole actions. In this paper we compare the success rate of such actions using traditional robot control to an adaptive control strategy based on Dynamic Motor Primitives. Both methods use vision-based pose estimation to locate the peg and the hole in the workspace of an industrial robot, and a dexterous gripper to grasp the peg. The experiments show that the traditional robot control performs the PiH action with a low success rate, while the DMP based PiH can achieve a high success rate.
Polymorphisms of HPC2/ELAC2 and SRD5A2 (5α-Reductase Type II) Genes in Prostate Cancer

Polymorphisms of HPC2/ELAC2 and SRD5A2 (5α-Reductase Type II) Genes in Prostate Cancer Prostate cancer is the proliferation of malignant cells in the prostate gland. The HPC2/ELAC2 gene on chromosome 17p11.2 and SRD5A2 gene on chromosome 2p22-23 are predisposing genetic factors. We examined the relationship between Ser217Leu and Ala541Thr polymorphisms of the former gene, and Ala49Thr and Val89Leu polymorphisms of the latter gene to prostate cancer in Turkish men, using the polymerase chain reaction (PCR) method and appropriate restriction enzymes. The HPC2/ ELAC2 gene Ser217-Leu and SRD5A2 gene Ala49Thr polymorphisms were associated with an increased risk of prostate cancer in Turkish men [for the HPC2/ELAC2 gene Ser217Leu polymorphism: odds ratio (OR) 2.7; confidence interval 95% (CI 95%) 1.6-4.8; p 0.000<0.05, and for the SRD5A2 gene Ala49Thr polymorphism: OR 2.4; CI 95% 1.2-4.9; p 0.004<0.05].