Miracle-dz/UniFAR-FTUs huggingface dataset:
Section R: Research Plan 1. Specific Aims

This proposal is aimed at solving a communications challenge that has been dubbed the " last meter " problem – specifically the challenge of sending Gb/sec lightly compressed HD video streams over a short-range wireless indoor link. The application of this technology is the transmission from a DVD or DVR player to a high definition display. This transmission has to be done in a low-cost consumer application type of environment. Clearly, the need for a product like this is real, since expensive and bulky cables are one of the well-known bete noire's of the video industry. In order to accomplish this, research is required on several fronts, since scaled application of existing wireless communications approaches will not achieve the necessary bandwidth and data rate. The problem is unique in some ways, because the HDTV stream should be lightly coded to make copying and piracy very difficult. At the same time, some coding is required for error-control and channel mitigation reasons. The result of these considerations will be a wide-bandwidth waveform (from 1 to 4 GB/sec). This will require mmW transmission, since there is insufficient spectrum available at lower frequencies to transmit data at this rate in a wireless environment at low cost. As a result, we have structured this program to develop the key enablers for these low-cost wireless video links, which will operate at 60 GHz. These key enablers actually cut across several electrical engineering disciplines, including communications theory, solid-state circuit design and coding theory. As a result, we have structured this program as an interdisciplinary effort that addresses the key challenges of Gb/sec short-range wireless transmission. The relevance of this project to the State of California is enormous. We are entering an era of wireless communications devices that are increasingly viewed as " commodities. " This commodi-fication of the wireless telecommunications industry is especially detrimental to " high-wage " environments like California, especially when they have to compete against low wage Asian competitors. One solution to this dilemma is to develop new and innovative products and services, instead of simply trying to reduce the cost of existing products and services. The outcome of this project will be a new type of wireless device, that provides a unique new capability in the communications arena, enabling Californians to provide innovative new services in the future. The FCC has allocated a large bandwidth, spanning several gigahertz, for unlicensed use around 60 …
Parametric Bayesian Rejuvenation in Ambient Assisted Living through Software-based Thematic 5G Management

Ameliorating elderly engagement is vital in rejuvenating independent living. However, recommended practices lack realization of personal traits despite socio -economic promise. The recent proliferation of IoT with the advent of smart-objects/things and personalized services pave the way for context-aware service management. Eventually, the major goal of this paper is to develop a context-aware model in predicting engagement of elderly care. Hence, key requirements are identified for elderly engagement, namely (a) discovery of contexts, which are relevant (b) scaling up (over time) of engagement. However, paramount challenges are imposed on this stipulation, such as, un-observability, independence and composite relationship of contexts. Therefore, a Topic-model based model is proposed to address scalability of contexts and its conjugal relationship with engagement. Eventually, systematic framework is demonstrated, which pinpoints key goals of context-aware services by participants' opinions, usage and feed-back.
Detecting air travel to survey passengers on a worldwide scale

Market research in the transportation sector is often based on traditional surveys, such as travel diaries, which have well-documented shortcomings and biases. The advent of mobile and wireless technologies enables new methods of investigation of passengers’ behaviour that can eventually provide original insights into mobility studies. Because these technologies can capture travellers’ experience in context and real time, they pave the road for new survey methods. In this article, we demonstrate that mobile phones can recognise air travel with a light algorithm that scans their connectivity to cellular networks. The originality of our method is that it does not rely on any Global Positioning System-like location information and runs on a large variety of mobile phones. It detects flights on a worldwide scale and asks travellers to report on their travel experiences as they occur, eliminating the recall bias of traditional solutions. Once the system detects a journey, it triggers a flight satisfaction questionnaire that sends answers to a centralised server. This approach respects the traveller's privacy and proved a 97% success rate in detecting flights in a 12-months study involving six travellers who boarded on 76 planes.
Discovering Evolutionary Theme Patterns from Text ∗ CS 598 CXZ Project Report , Professor ChengXiang Zhai Qiaozhu

Temporal Text Mining (TTM) is concerned with discovering temporal patterns in text information collected over time. Since most text information bears some time stamps, TTM has many applications in multiple domains, such as summarizing events in news articles and revealing research trends in scientific literature. In this paper, we study a particular TTM task – discovering and summarizing the evolutionary patterns of themes in a text stream. The evolutionary patterns of a theme are divided into content evolution and strength evolution. We define the problem of discovering evolutionary theme patterns on both aspects and present general probabilistic methods for (1) discovering latent themes from text; (2) constructing an evolution graph of themes; and (3) analyzing life cycles of themes. Evaluation of the proposed methods on three different data collections (i.e., one news articles collection and two literature collections) shows that the proposed methods can discover interesting evolutionary theme patterns effectively.
The Influence of Neighborhood Quality on Adolescents’ Educational Values and School Effort

Interview data from a sample of 262 poor African American single mothers and their 7th- and 8th-grade children were used to investigate the relations between neighborhood conditions and adolescents’educational values and school effort. The model tested incorporates both subjective and objective assessments of neighborhood quality and controls for several family- and school-related constructs. United States Census data on household incomes served as an objective measure of neighborhood quality. In the full sample, the findings revealed that the percentage of middle-class neighbors and self-perceived academic abilities were significantly linked to adolescents’educational values, which were, in turn, related to school effort. Several theories identifying the processes by which neighborhood characteristics influence adolescents’ educational values are discussed. Gender differences emerged when the model was tested separately for females and males. For African American females, but not for adolescent males, neighborhood conditions were associated with educational values.
Secretoneurin Gene Therapy Improves Blood Flow in an Ischemia Model in Type 1 Diabetic Mice by Enhancing Therapeutic Neovascularization

Deficient angiogenesis after ischemia may contribute to worse outcome of peripheral arterial disease in patients with diabetes mellitus. Based on our previous work where we demonstrated that Secretoneurin (SN) is up-regulated under hypoxic conditions and enhances angiogenesis, we analyzed the therapeutic potential of SN gene therapy using a model of severe hind limb ischemia in streptozotocin-induced diabetic mice (STZ-DM). After induction of hind limb ischemia, blood flow was assessed by means of laser Doppler perfusion imaging (LDPI) and increased blood perfusion in the SN-treated animal group was observed. These results were complemented by the clinical observation of reduced necrosis and by an increased number of capillaries and arterioles in the SN-treated animal group. In vitro, we found that SN is capable of promoting proliferation and chemotaxis and reduces apoptosis in HUVECs cultured under hyperglycemic conditions. Additionally, SN activated ERK, eNOS and especially AKT as well as EGF-receptor in hyperglycemic HUVECs. In conclusion, we show that SN gene therapy improves post-ischemic neovascularization in diabetic mice through stimulation of angiogenesis and arteriogenesis indicating a possible therapeutic role of this factor in ischemia-related diseases in diabetic patients.
A GPU task generator for rendering

We present an original GPU task generator that can be attached to the rasterization based rendering process, in order to provide a dynamic parallelism. Compared to other existing GPU task generators or schedulers our method creates new tasks using the GPU graphics pipeline task scheduler. These are generated in the geometry shader, by means of rasterizing new geometry that produces additional fragments. The parallel processing of these fragments represents the new threads, which are used as general purpose threads. Thus, our solution is extremely lightweight and it can run in parallel with the rasterization based rendering process. By using our generator, work-heavy rendering threads can distribute their load to a sufficiently large group of workers without any CPU interference. By doing this we are effectively reducing the complexity on a per-rendering thread basis and therefore we are able to obtain a performance increase of 1 or even 2 orders of magnitude in critical cases. Tasks such as tracing rays, dynamic geometry generation, expensive BSSRDFs evaluation or ray marching are handled in a unified manner, making it easy to integrate our generator into game engines. In contrast with other GPU task generators and schedulers our method does not occupy all hardware threads nor does it need specialized hardware, only requiring Shader Model 5. Since rarely are dynamic rendering tasks complicated enough to generate dynamic child tasks on their own, our generator can be configured to run as just a simple non recursive task dispatcher.
A review on mobile threats and machine learning based detection approaches

The research of mobile threats detection using machine learning algorithms have got much attention in recent years due to increase of attacks. In this paper, mobile vulnerabilities were examined based on attack types. In order to prevent or detect these attacks machine learning methods used were analyzed and papers published in between 2009 and 2014 have been evaluated. Most important mobile vulnerabilities implementation format for these threats, detection methods and prevention approaches with the help of machine learning algorithms are presented. The obtained results are compared from their achievements were summarized. The results have shown that selecting and using datasets play an important role on the success of the system. Additionally, supervised learning techniques produce better results while compared with unsupervised ones in intrusion detection.
Multiple Level Nested Array: An Efficient Geometry for $2q$th Order Cumulant Based Array Processing

Recently, direction-of-arrival estimation (DOA) algorithms based on arbitrary even-order (2<i>q</i>) cumulants of the received data have been proposed, giving rise to new DOA estimation algorithms, namely the 2<i>q</i> MUSIC algorithm. In particular, it has been shown that the 2<i>q</i> MUSIC algorithm can identify <i>O</i>(<i>Nq</i>) statistically independent non-Gaussian sources. However, in this paper, it is demonstrated that the processing power of the 2<i>q</i>th-order cumulant based methods can potentially be even larger. It will be shown that the 2<i>q</i>th-order cumulant matrix of the data is directly related to the concept of a 2<i>q</i>th-order difference co-array which can potentially have <i>O</i>(<i>N</i><sup>2</sup><i>q</i>) virtual sensors, leading to identification of <i>O</i>(<i>N</i><sup>2</sup><i>q</i>) statistically independent non-Gaussian sources using 2<i>q</i> th-order cumulants. However, the number of actually realizable virtual elements in the 2<i>q</i> th-order difference co-array depends on the geometry of the physical array. In order to ensure that the co-array indeed has the desired degrees of freedom, a new generic class of linear (one dimensional) nonuniform arrays, namely the 2<i>q</i>th-order nested array, is proposed, whose 2<i>q</i> th-order difference co-array is proved to contain a uniform linear array with <i>O</i>(<i>N</i><sup>2</sup><i>q</i>) sensors. In order to exploit these increased degrees of freedom of the co-array, a new algorithm for DOA estimation is also developed, which acts on the same 2<i>q</i> th-order cumulant matrix as the earlier methods and can yet identify <i>O</i>(<i>N</i><sup>2</sup><i>q</i>) sources. It is proved that the proposed method can identify the maximum number of sources among all methods that use 2<i>q</i> th-order cumulants.
Feature adapted convolutional neural networks for downbeat tracking

We define a novel system for the automatic estimation of downbeat positions from audio music signals. New rhythm and melodic features are introduced and feature adapted convolutional neural networks are used to take advantage of their specificity. Indeed, invariance to melody transposition, chroma data augmentation and length-specific rhythmic patterns prove to be useful to learn downbeat likelihood. After the data is segmented in tatums, complementary features related to melody, rhythm and harmony are extracted and the likelihood of a tatum being at a downbeat position is computed with the aforementioned neural networks. The downbeat sequence is then extracted with a flexible temporal hidden Markov model. We then show the efficiency and robustness of our approach with a comparative evaluation conducted on 9 datasets.
AN EFFICIENT FPGA IMPLEMENTATION OF AES ALGORITHM

The Advanced Encryption Standard can be programmed in software or built with pure hardware. But Field Programmable Gate Arrays (FPGAS) offer a faster and more customizable solution, since the entire algorithm can be executed in a single tick of clock cycle. This research deals with the implementation of AES algorithm in FPGA using Verilog Language. Software is used for simulation and optimization of the synthesizable Verilog code. All the transformations of both Encryption and Decryption are simulated using an iterative design approach for minimizing the hardware consumption. The design uses an iterative looping approach with block and key size of 128 bits and lookup table implementation of S-box. The FCSR used for key generation make the algorithm more secure, and the usage of Vedic multipliers instead of normal multipliers increases the throughput. This gives low complexity architecture and easily achieves low latency.
Productive Efficiency and its Convergence Across Firms: The Case of State Road Transport Undertakings in India

The motive of this study is to put forward new information concerning the productive efficiency of the State Road Transport Undertakings (STUs) in India. A well-known multilateral index procedure proposed by Caves, Christensen, and Diewert (1982) is used to compute the growth and relative levels of gross productivity of the STUs during the sample period. Productive efficiency estimates are calculated by separating the effects of variations in the variables beyond managerial control from the gross productivity measures. We also examined the temporal relationship of the cross-sectional rankings of individual STUs' productive efficiency estimates. To address this issue, we calculated Kendall's index of rank concordance along with coefficient of variation of productive efficiency estimates for the sample period. Annual data for a sample of twenty one STUs that operated during the period 1983-84 to 1996-97 are used for the purpose of estimation. We find that there is wide disparity among STUs according to their productive efficiency levels and growth. On an average, small size STUs are more productive than their larger counterparts. Also, by and large, Tamil Nadu STUs seem to be more productive than their counterparts operating in other states of the country. The distribution of ranks of STUs with respect to their productive efficiency levels has remained broadly unchanged over the years.
Online Learning of Portfolio Ensembles with Sector Exposure Regularization

We consider online learning of ensembles of portfolio selection algorithms and aim to regularize risk by encouraging diversification with respect to a predefined risk-driven grouping of stocks. Our procedure uses online convex optimization to control capital allocation to underlying investment algorithms while encouraging non-sparsity over the given grouping. We prove a logarithmic regret for this procedure with respect to the best-in-hindsight ensemble. We applied the procedure with known mean-reversion portfolio selection algorithms using the standard GICS industry sector grouping. Empirical Experimental results showed an impressive percentage increase of risk-adjusted return (Sharpe ratio).
On the Evolution of Random Geometric Graphs on Spaces of Negative Curvature

We study a family of random geometric graphs on hyperbolic spaces. In this setting, N points are chosen randomly on the hyperbolic plane of curvature −ζ 2 and any two of them are joined by an edge with probability that depends on their hyperbolic distance, independently of every other pair. In particular, when the positions of the points have been fixed, the distribution over the set of graphs on these points is the Boltzmann distribution, where the Hamiltonian is given by the sum of weighted indicator functions for each pair of points. The weight is proportional to a real parameter β > 0 (interpreted as the inverse temperature) as well as to the hyperbolic distance between the corresponding points. The N points are distributed according to a quasi-uniform distribution which is a distorted version of the uniform distribution and depends on a parameter α > 0 – when α = ζ it coincides with the uniform distribution. This class of random graphs was proposed by Krioukov et al. [17] as a model for complex networks. We provide a rigorous analysis of aspects of this model for all values of the ratio ζ/α, focusing on its dependence on the parameter β. We show that a phase transition occurs around β = 1. More specifically, let us assume that 0 < ζ/α < 2. In this case, we show that when β > 1 the degree of a typical vertex is bounded in probability (in fact it follows a distribution which for large values exhibits a power-law tail whose exponent depends only on ζ and α), whereas for β < 1 the degree is a random variable whose expected value grows polynomially in N. When β = 1, we establish logarithmic growth. For the case β > 1, we establish a connection with a class of inhomogeneous random graphs known as the Chung-Lu model. We show that the probability that two given points are adjacent is expressed through the kernel of this inhomogeneous random graph. We also consider the case ζ/α ≥ 2.
Expression of apoptosis regulatory genes by retinal pericytes after rapid glucose reduction.

PURPOSE Retinal capillary pericytes underwent apoptosis in vitro after they had been exposed long-term to high levels of glucose followed by a rapid glucose reduction. The present work was designed to study the expression of bcl-2 family members and apoptosis regulatory genes and to determine the status of oxidative stress induced by high concentrations of glucose in this in vitro apoptosis model. METHODS Pericytes were grown in normal or high glucose concentrations (5, 20, 30, and 40 mM) for 10 days and then exposed to a rapid reduction of glucose to 0.5 mM or 5 mM. Pericyte cell death was evaluated by determining the loss of cell viability and the fragmentation of DNA using agarose gel electrophoresis. In parallel, the quantitative reverse transcription-polymerase chain reaction technique was used to determine the expression of bcl-2, bax, p53, and glutathione peroxidase (GSH-Px) genes. The intracellular level of glutathione (GSH) and the DNA fragmentation were determined simultaneously for pericytes treated with or without exogenous GSH monoethylester. Retinal capillary endothelial cells, experiencing the same glucose variation, were studied as a comparison. RESULTS For pericytes, downregulation of bcl-2 was observed as early as 24 hours after rapid glucose reduction, whereas DNA fragmentation was not detectable at that time. After 72 hours, a decreased protein ratio of Bcl-2 to Bax was concomitant to evident loss of pericyte viability. During the period of high glucose and the following glucose reduction, p53 expression essentially was unchanged. Decreased levels of GSH induced by high concentrations of glucose (>30 mM) became further depleted when the glucose levels were rapidly reduced. Addition of GSH monoethylester to the medium restored the level of GSH in pericytes and prevented pericyte apoptosis induced by glucose variation. Moreover, the mRNA levels of GSH-Px were significantly elevated. By contrast, with the same glucose reduction endothelial cells did not undergo apoptosis. Their mRNA levels of bcl-2, bax, and GSH-Px essentially were unchanged. CONCLUSIONS High levels of glucose and rapid reduction of glucose modulate the expression of bcl-2 family genes in retinal pericytes. Upregulation of GSH-Px and depletion of GSH indicate a reparative process of accelerated elimination of reactive oxygen species following rapid glucose reduction. These findings indicate that the aggravated oxidative stress and the weakened antioxidant defense induced by the combined effects of high levels of glucose and subsequent rapid glucose reduction cause pericyte apoptosis. Prevention of DNA fragmentation of pericytes by exogenous GSH further supports this notion. Because endothelial cells did not show similar pathologic changes, this proposed mechanism seems to be specific to pericytes.
Longitudinal dynamics modeling of the RIOL robot

This paper describes the longitudinal dynamics modeling of the RIOL robot. This robot is designed to move hanging on a suspended cable in applications such as the inspection of electric power lines and aerial monitoring/surveillance. The main characteristics of the robot are described along with simulation results for full and reduced models of the longitudinal dynamics and respective comparison using L2 gain estimates.
Pulmonary atresia with ventricular septal defect: a case for central venous pressure and oxygen saturation monitoring.

A 21-year-old patient with pulmonary atresia and ventricular septal defect (PA-VSD) was admitted to the hospital for tubal ligation. Invasive arterial and central venous (CVP) pressure, pulse oximetric oxygen saturation (SpO2), and (from the tip of oximetric central venous catheter) central venous oxygen saturation (ScvO2) and oxygen extraction rate (ExO2) were continuously monitored. Heart rate (range: 68-75 beat/min), mean arterial pressure (80-90 mmHg), CVP (7-10 mmHg), SpO2 (79-90 percent), ScvO2 (57-70 percent), and ExO2 (21-30 percent) remained stable during epidural anesthesia and transvaginal sterilization. Following an overnight stay (peak SpO2 92 percent; peak ScvO2 71 percent; through ExO2 21 percent), the oxygen data returned to baseline on awakening (SpO2 < 80 percent, ScvO2 < 55 percent, ExO2 > 35 percent), and the patient was discharged. In PA-VSD, a single-outlet double-ventricle anomaly, CVP reflects the preload of systemic ventricle. As the mixed venous oxygen saturation cannot be defined, ScvO2 is the best available indicator of the whole body oxygen consumption. Continuous monitoring of CVP, ScvO2 and ExO2 in the superior vena cava may provide more insight into the response to anesthesia and surgery in patients with PA-VSD. ImagesFigure 1