Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a communication-efficient mapping of AUTOSAR runnables on multi-cores

Multi-core technology is recognized as a key component to develop new cost-efficient products. It can lead to reduction of the overall hardware cost through hardware consolidation. However, it also results in tremendous challenges related to the combination of predictability and performance. The AUTOSAR consortium has developed as the worldwide standard for automotive embedded software systems. One of the prominent aspects of this consortium is to support multi-core systems. In this paper, the ongoing work on addressing the challenge of achieving a resource efficient and predictable mapping of AUTOSAR runnables onto a multi-core system is discussed. The goal is to minimize the runnables' communication cost besides meeting timing and precedence constraints of the runnables. The basic notion utilized in this research is to consider runnable granularity, which leads to an increased flexibility in allocating runnables to various cores, compared of task granularity in which all of the runnables hosted on a task should be allocated on the same core. This increased flexibility can potentially enhance communication cost. In addition, a heuristic algorithm is introduced to create a task set according to the mapping of runnables on the cores. In our current work, we are formulating the problem as an Integer Linear Programming (ILP). Therefore, conventional ILP solvers can be easily applied to derive a solution.
A Survey of Peer-to-Peer Systems

Peer-to-Peer systems have become, in a short period of time, one of the fastest growing and most popular applications. The decentralized and distributed nature of p2p systems leads to living aside the client-server model. In p2p model each node takes both the roles of client and server. As a client, it can query and download its wanted data files from other nodes and as a server, it can provide data files to other nodes. Two main objectives in p2p systems are data location and search for interesting data. In order to present these topics, we survey various structured and unstructured p2p systems. We also study content-based p2p systems that are systems with clusters of nodes, according to the content of their data files. We point replication strategies and techniques and we show how range queries are performed.
A function space approach to sampled data control systems and tracking problems

This paper presents a new framework for hybrid sampled data control systems. Instead of considering the state only at sampling instants, this paper introduces a function piece during the sampling period as the state and gives an infinite-dimensional model with such a state space. This gives the advantage that sampled data systems with built-in intersample behavior can be regarded as linear, time-invariant, discrete-time systems. As a result, the approach makes it possible to introduce such time-invariant concepts as transfer functions, poles, and zeros to the sampled data systems even with the presence of the intersample behavior. In particular, tracking problems can be studied in this setting in a simple and unified way, and ripples are completely characterized as a mismatch between the intersample reference signal and transmission zero directions. This leads to the internal model principle for sampled data systems. >
Space Profile-Based Reverse Geocoding Service Using Cloud Platform

Reverse geocoding has raised potential privacy concerns, especially regarding the ability to reverse engineer geographical location to obtain the street address of an individual. In most cases, direct reference to the geography of the area mapped that elucidates sensitive information isn't of much interest than having the knowledge of what we can do or find there. Rather than raising a flag, this paper presents a design framework of the space profile-based reverse geocoding service that creates an abstract space which explains area characteristic and can be used to infer probable activities that individuals can be engaged in the area.
Individual and Social Influences on Students’ Attitudes to Debt: a Cross‐National Path Analysis Using Data from England and New Zealand

© 2016 John Wiley & Sons Ltd. This study examines the construction of debt attitudes among 439 first-year undergraduates in England and New Zealand. It works from a conceptual model that predicts that attitudes will be partly determined by a range of social factors, mediated through personality and ‘financial literacy’. Path analysis is used to explore this model. The proposed model was found to be basically sound, with some notable negative findings. Socio-economic status was found to have a negligible role in determining debt attitudes, while the role of financial literacy was limited to reducing the likelihood of seeing debt as useful for lifestyle expenditure. Debt anxiety was found to be higher among students with a general predisposition to anxiety and inversely related to viewing student debt as a form of educational investment. It is concluded that student debt attitudes are multidimensional and individualised, challenging simplistic ideas of debt aversion in earlier literature.
A Trio-RhoA-Shroom3 pathway is required for apical constriction and epithelial invagination

Epithelial invagination is a common feature of embryogenesis. An example of invagination morphogenesis occurs during development of the early eye when the lens placode forms the lens pit. This morphogenesis is accompanied by a columnar-to-conical cell shape change (apical constriction or AC) and is known to be dependent on the cytoskeletal protein Shroom3. Because Shroom3-induced AC can be Rock1/2 dependent, we hypothesized that during lens invagination, RhoA, Rock and a RhoA guanine nucleotide exchange factor (RhoA-GEF) would also be required. In this study, we show that Rock activity is required for lens pit invagination and that RhoA activity is required for Shroom3-induced AC. We demonstrate that RhoA, when activated and targeted apically, is sufficient to induce AC and that RhoA plays a key role in Shroom3 apical localization. Furthermore, we identify Trio as a RhoA-GEF required for Shroom3-dependent AC in MDCK cells and in the lens pit. Collectively, these data indicate that a Trio-RhoA-Shroom3 pathway is required for AC during lens pit invagination.
Combined Efficient Precoding Technique for Multi-User MIMO

Recently, a multiuser MIMO system has attracted much attention because of an important area of focus for next generation wireless system because of their potential for higher capacity, increased diversity and interference suppression with leading higher data rate support. In Multiuser MIMO (MU-MIMO) systems, precoding is essential to eliminate or minimize the multiuser interference (MUI) as in the downlink of the multiuser MIMO system where the base station simultaneously transmits signals to terminals. However, the design of a suitable precoding algorithm with good performance and low computational complexity at the same time is quite challenging, especially with the increase of system dimensions which increases with number of antennas. In this thesis, we mainly focus on MU-MIMO broadcast channel, consider the case where the multiple transmit antennas are used to deliver independent data streams to multiple users and compare the performance for linear and non linear precoding techniques in terms of BER, SNR and complexity point with increase in the number of users and the number of transmit antennas. We propose a new practical scheme leads with low computation complexity and better BER performance with better system utilization.
The Native Coordinate System of Spatial Attention Is Retinotopic

Visual processing can be facilitated by covert attention at behaviorally relevant locations. If the eyes move while a location in the visual field is facilitated, what happens to the internal representation of the attended location? With each eye movement, the retinotopic (eye-centered) coordinates of the attended location change while the spatiotopic (world-centered) coordinates remain stable. To investigate whether the neural substrates of spatial attention reside in retinotopically and/or spatiotopically organized maps, we used a novel gaze-contingent behavioral paradigm that probed spatial attention at various times after eye movements. When task demands required maintaining a spatiotopic representation after the eye movement, we found facilitation at the retinotopic location of the spatial cue for 100–200 ms after the saccade, although this location had no behavioral significance. This task-irrelevant retinotopic representation dominated immediately after the saccade, whereas at later delays, the task-relevant spatiotopic representation prevailed. However, when task demands required maintaining the cue in retinotopic coordinates, a strong retinotopic benefit persisted long after the saccade, and there was no evidence of spatiotopic facilitation. These data suggest that the cortical and subcortical substrates of spatial attention primarily reside in retinotopically organized maps that must be dynamically updated to compensate for eye movements when behavioral demands require a spatiotopic representation of attention. Our conclusion is that the visual system's native or low-level representation of endogenously maintained spatial attention is retinotopic, and remapping of attention to spatiotopic coordinates occurs slowly and only when behaviorally necessary.
Nonuniform recovery of excitability in the left ventricle.

The purpose of this study was to determine left ventricular activation, dispersion of refractoriness, and total recovery time in patients with coronary artery disease and ventricular tachycardia and in patients with the long QT syndrome and to compare these patients with a group of normal patients. Left ventricular endocardial catheter mapping and left ventricular refractory period determination were performed in 18 patients. Group 1 consisted of seven patients with no heart disease and no arrhythmia; group 2 consisted of six patients with previous infarction and sustained ventricular tachycardia; and group 3 consisted of five patients with prolonged QT interval and previous cardiac arrest. Total left ventricular endocardial activation was significantly longer in group 2 (75 +/- 23 msec, mean +/- SD) compared with group 1 (34 +/- 9 msec, p less than 0.01) and group 3 (42 +/- 5 msec, p less than 0.05). Dispersion of refractoriness was significantly greater in group 3 (87 +/- 27 msec) than in group 1 (40 +/- 14 msec, p less than 0.01) and group 2 (53 +/- 14 msec, p less than 0.05). Dispersion of total recovery time was significantly greater in group 2 (90 +/- 30 msec) than in group 1 (52 +/- 14 msec, p less than 0.05) as well as group 3 (114 +/- 43 msec) compared with group 1 (p less than 0.01). (ABSTRACT TRUNCATED AT 250 WORDS)
Software requirements for a (more) manageable multi-touch ecosystem

Having designed, implemented and evaluated multi-touch techniques, applications and systems, members of our research team have had a number of needs that were not necessarily met by current tools. These tools notably lack proper support for standard but extensible device and event descriptions, test-driven development and flexible networking configurations, for example. In this paper, we detail and explain these different needs, discuss potential solutions and present the first steps we have taken towards a new multitouch toolkit to address them.
Multi-Object Classification and Unsupervised Scene Understanding Using Deep Learning Features and Latent Tree Probabilistic Models

Author(s): Nimmagadda, Tejaswi; Anandkumar, Anima | Abstract: Deep learning has shown state-of-art classification performance on datasets such as ImageNet, which contain a single object in each image. However, multi-object classification is far more challenging. We present a unified framework which leverages the strengths of multiple machine learning methods, viz deep learning, probabilistic models and kernel methods to obtain state-of-art performance on Microsoft COCO, consisting of non-iconic images. We incorporate contextual information in natural images through a conditional latent tree probabilistic model (CLTM), where the object co-occurrences are conditioned on the extracted fc7 features from pre-trained Imagenet CNN as input. We learn the CLTM tree structure using conditional pairwise probabilities for object co-occurrences, estimated through kernel methods, and we learn its node and edge potentials by training a new 3-layer neural network, which takes fc7 features as input. Object classification is carried out via inference on the learnt conditional tree model, and we obtain significant gain in precision-recall and F-measures on MS-COCO, especially for difficult object categories. Moreover, the latent variables in the CLTM capture scene information: the images with top activations for a latent node have common themes such as being a grasslands or a food scene, and on on. In addition, we show that a simple k-means clustering of the inferred latent nodes alone significantly improves scene classification performance on the MIT-Indoor dataset, without the need for any retraining, and without using scene labels during training. Thus, we present a unified framework for multi-object classification and unsupervised scene understanding.
Will you have a good sleep tonight?: sleep quality prediction with mobile phone

Understanding the relationship between sleep and daily life can provide insights into a healthy life style since the sleep quality is one of the most important indicators of people's health status. This paper studies the extent to which a person's sleep quality can be predicted by his/her daily context information. A combination of the machine learning technology and medical knowledge is used to study the relation between context and sleep quality, so that sleep quality can be predicted in real time according to the relation. We propose a novel sleep quality predicting framework from user context data, without requiring users to wear special devices. We develop a data collecting and analyzing prototype system called SleepMiner, which uses on-phone data such as mobile sensor data and communication data to extract human contexts. Then the relationship between context data and sleep quality is analyzed and a learning model based on factor graph model is proposed to predict sleep quality. From experimental results we demonstrate that it is possible to accurately infer sleep quality (around 78%) from user context information. A set of solutions are proposed to address the practical problems of Android phone in data collection, making SleepMiner work with minimal impact on the phone's resources. We finally carry out experiments to evaluate our design in effectiveness and efficiency.
Architectural Views of a Reactive System: a Case Study

The signiicance of software architecture views as a means for separating the designer's concerns have been addressed in the literature and a number of papers have attempted to illustrate this concept through examples 19, 8, 16, 12]. Nevertheless, as far as we are aware, none has shown a complete and concrete example of the usefulness of views. In this paper, we attempt to address this issue. We introduce the software system of a fast-food restaurant that we designed with a CASE tool called Statemate, and then illustrate and discuss diierent architectural representations of this restaurant system. We use Zach-man's framework 19] consisting of diierent views and perspectives as the basis for composing these representations.
The Fundamental Gap

The second main problem to be focused on at the workshop is what we’ll refer to as the Fundamental Gap Problem, which is the problem of finding a sharp lower bound to the gap between the first two eigenvalues of a Schrodinger operator on a bounded convex domain with convex potential in terms of the diameter of the domain. We call the lowest eigenvalue gap, i.e., the gap between the first two eigenvalues, the fundamental gap. We shall describe two versions of this problem, one for the Laplacian alone and the other for Schrodinger operators. The second problem contains the first as a special case, but the first is of course of substantial interest in its own right, and may possibly be more tractable than the general problem. In the first problem one just considers the Laplacian −∆ on a bounded convex domain Ω with Dirichlet boundary conditions. This problem has a purely discrete spectrum, {λi(Ω)}i=1, with ∞ as its only point of accumulation. Listed in increasing order, with multiplicities, we have 0 < λ1(Ω) < λ2(Ω) ≤ λ3(Ω) ≤ · · · → ∞. (1)
Heart versus mind: How affective and cognitive message frames change attitudes.

Abstract. Several researchers have pursued the question of whether affective or cognitive persuasion appeals are more successful in changing attitudes. The vast majority of studies in this field have found that the persuasiveness of affective and cognitive appeals depends on the extent to which recipients’ existing attitudes are based on affect or cognition: Affective messages are more successful in changing affect-based attitudes; cognitive messages are more successful in changing cognition-based attitudes. However, research to date has not uncovered the processes leading to these effects. In the present article it is argued that there are two plausible explanations. First, matching messages to informational attitude bases might heighten message scrutiny. This would mean that a central process underlies the effects. Second, a peripheral process might account for the effects. Specifically, processing fluency might act as a peripheral cue. The results of an experimental study clearly suggest that that proc.
GPU-accelerated MoM based scattering/radiation analysis using NVIDIA CUDA

This paper investigates utilization of graphics processing units (GPUs) for accelerating run-time critical phase of a well-known matrix-based technique in the field of computational electromagnetics viz. method of moments (MoM) using NVIDIA CUDA. More specifically, taking care of numerical accuracy without sacrificing the generality, parallelization and resulting speedup using CUDA-capable GPU, is investigated for the runtime critical phase of the MoM. Speedup of 30× and 4× are obtained for MoM-matrix setup and overall solution, respectively.
VARIATION IN ANTIOXIDANTS AMONG THREE WHEAT CULTIVARS VARYING IN TOLERANCE TO NaCl

Salinity is one of the major environmental factors affecting plant growth and productiv ity (Ashraf and Harris, 2004; Mandhania et al., 2006; Azevedo Neto et al., 2006; Aghaleh and Niknam, 2009). The effects of salinity arise from osmotic and ionic toxicity. Plant metabolism should be flexible to allow plants to cope with environmental stresses. Salt stress can VARIATION IN ANTIOXIDANTS AMONG THREE WHEAT CULTIVARS VARYING IN TOLERANCE TO NaCl
Effects of chemotherapeutic agents on normal mouse bone marrow grown in vitro.

The effects of several antineoplastic chemotherapeutic drugs on normal mouse bone marrow were studied with the use of an enriched methylcellulose culture system in which marrow forms discrete colonies of myeloid and mononuclear cells. Twenty-four hr after incremental doses, cyclophosphamide, nitrogen mustard, and 1,3-bis(2-chloroethyl)-1-nitrosourea resulted in exponential decreases in the fraction of surviving in vitro colony-forming cells per femur, while vinblastine sulfate, methotrexate, and polyinosinic-polycytidylic acid resulted in dose-response curves which showed that despite increasing doses a maximal kill of colony-forming cells was approached. The repopulation of bone marrow colony-forming cells following a single large dose of cyclophosphamide was also studied. The in vitro culture technique provides another system of assessing bone marrow effects following tumor therapy and may be adaptable to investigation of human bone marrow.
Inflammation induced by increased frequency of intermittent hypoxia is attenuated by tempol administration

The levels of serum inflammatory cytokines and the activation of nuclear factor kappa B (NF-κB) and hypoxia inducible factor-1α (HIF-1α) in heart tissues in response to different frequencies of intermittent hypoxia (IH) and the antioxidant tempol were evaluated. Wistar rats (64 males, 200-220 g) were randomly divided into 6 experimental groups and 2 control groups. Four groups were exposed to IH 10, 20, 30, or 40 times/h. The other 2 experimental groups were challenged with IH (30 times/h) plus tempol, either beginning on day 0 (IH30T0) or on day 29 (IH30T29). After 6 weeks of challenge, serum levels of tumor necrosis factor (TNF)-α, intracellular adhesion molecule (ICAM)-1, and interleukin-10 were measured, and western blot analysis was used to detect NF-κB p65 and HIF-1α in myocardial tissues. Serum levels of TNF-α and ICAM-1 and myocardial expression of NF-κB p65 and HIF-1α were all significantly higher in IH rats than in controls (P<0.001). Increased IH frequency resulted in more significant changes. Administration of tempol in IH rats significantly reduced levels of TNF-α, ICAM-1, NF-κB and HIF-1α compared with the non-tempol-treated group (F=16.936, P<0.001). IH induced an inflammatory response in a frequency-dependent manner. Additionally, HIF-1α and NF-κB were increased following IH administration. Importantly, tempol treatment attenuated this effect.
Quantum dot semiconductor lasers with optical feedback

We analyse the sensitivity of quantum dot semiconductor lasers to optical feedback. While bulk and quantum well semiconductor lasers are usually extremely unstable when submitted to back reflection, quantum dot semiconductor lasers exhibit a reduced sensitivity. Using a rate equation approach, we show that this behaviour is the result of a relatively low but nonzero line-width enhancement factor and strongly damped relaxation oscillations.
CORP: Cooperative Opportunistic Resource Provisioning for Short-Lived Jobs in Cloud Systems

In cloud systems, achieving high resource utilization and low Service Level Objective (SLO) violation rate are important to the cloud provider for high profit. For this purpose, recently, some methods have been proposed to predict allocated but unused resources and reallocate them to long-running service jobs. However, the accuracy of their prediction method relies on the existence of patterns in jobs' resource utilization. Therefore, these methods cannot be used for short-lived jobs, which usually do not have certain patterns but exhibit frequent fluctuations in resource requirements. Also, these methods may result in resource fragmentation and lead to low resource utilization because they neglect job resource intensity in multi-resource allocation and may allocate much more resources to jobs. To handle this problem, we propose a Cooperative Opportunistic Resource Provisioning scheme (CORP) for short-lived jobs. CORP uses the deep learning method to predict the amount of temporarily-unused resource of each short-lived job. It also predicts the fluctuations of the amount of unused resource using Hidden Markov Model, and adjusts the predicted amount for the peak and valley of unused resource, and dynamically allocates the corrected amount of resource to jobs. Further, CORP uses a job packing strategy by leveraging complementary jobs' requirements on different resource types and allocates such jobs to the same VM to fully utilize unused resources, which increases resource utilization. Extensive experimental results based on a real cluster and Amazon EC2 show that CORP achieves high resource utilization and low SLO violation rate compared to previous resource provisioning schemes.