Miracle-dz/UniFAR-FTUs huggingface dataset:
Location-Aware Two-Phase Coding Multi-Channel MAC Protocol (LA-TPCMMP) for MANETs

In classical code division multiple access (CDMA) based multi-channel medium access control (MAC) protocols for mobile ad hoc networks (MANETs), numerous exchanges of neighborhood information are required for code assignment such that nodes within a two-hop separation will adopt different transmission codes and therefore avoid the hidden terminal problem (HTP). However, such expensive communication overhead for code assignment is not desirable since it will cause an under-utilization of bandwidth, energy inefficiency and longer delays, which can significantly degrade the network performance. In this paper, a novel location-aware multi-channel MAC protocol is presented for a large-scale dense MANETs based on a scalable two-phase coding scheme, where the first-phase code is used for differentiating adjacent cells and the second-phase code is employed for distinguishing nodes in one specific cell. A node knows its first-phase code from its location information and requests its second-phase code from its cell leaden. This protocol eliminates the HTP during data transmission without the periodical exchange of neighborhood information. Furthermore, the mechanism of collision resolution in the control channel is described. The performance of the proposed protocol is analyzed in terms of the control overhead and delay. The theoretical results are confirmed by extensive simulations and it is shown that the new protocol significantly outperforms the classical CDMA-based multi-channel MAC protocols
IRDO: Iris Recognition by Fusion of DTCWT and OLBP

Iris Biometric is a physiological trait of human beings. In this paper, we propose Iris an Recognition using Fusion of Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP) Features. An eye is preprocessed to extract the iris part and obtain the Region of Interest (ROI) area from an iris. The complex wavelet features are extracted for region from the Iris DTCWT. OLBP is further applied on ROI to generate features of magnitude coefficients. The resultant features are generated by fusing DTCWT and OLBP using arithmetic addition. The Euclidean Distance (ED) is used to compare test iris with database iris features to identify a person. It is observed that the values of Total Success Rate (TSR) and Equal Error Rate (EER) are better in the case of proposed IRDO compared to the state-of-the art techniques.
Mild decrease in estimated glomerular filtration rate and proteinuria are associated with all-cause and cardiovascular mortality in the general population.

BACKGROUND A recent collaborative meta-analysis by Kidney Disease: Improving Global Outcomes reported that an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m(2) and an albumin-to-creatinine ratio of ≥ 10 mg/g were independent predictors for mortality in the general population. However, selection bias, heterogeneity of the cohorts and measurement issues could be limitations. METHODS We analyzed the relationship of eGFR and proteinuria with mortality in the Korean general population, represented by 112,115 participants, aged ≥ 20 years, who had a voluntary health check-up with homogenous calibration of creatinine measurement from 2003 to 2009. Proteinuria (trace or more) was determined by urine dipstick. RESULTS eGFR and proteinuria were independently associated with all-cause mortality (ACM) and cardiovascular mortality (CVM), and progressive increases in risks for mortality were noted according to eGFR level and the presence of proteinuria. Compared with eGFR 90-105 mL/min/1.73 m(2), hazard ratio (HRs) for ACM were 1.60 [95% confidence interval (CI) 1.12-2.30] for eGFR 60-74 mL/min/1.73 m(2) and 3.54 (2.20-5.68) for eGFR <60 mL/min/1.73 m(2) in participants with no proteinuria. In participants with proteinuria, HRs for ACM were 2.10 (1.41-3.12) for eGFR 75-89 mL/min/1.73 m(2), 2.30 (1.50-3.53) for eGFR 60-74 mL/min/1.73 m(2) and 3.77 (2.15-6.38) for eGFR <60 mL/min/1.73 m(2). Similar findings were observed for CVM. CONCLUSIONS eGFR <75 mL/min/1.73 m(2) and urine dipstick trace or more were independent risk factors of ACM and CVM. The risks of adverse outcomes are greater in the general population with mild renal impairment or mild proteinuria.
Sentiment analysis for various SNS media using Naïve Bayes classifier and its application to flaming detection

SNS is one of the most effective communication tools and it has brought about drastic changes in our lives. Recently, however, a phenomenon called flaming or backlash becomes an imminent problem to private companies. A flaming incident is usually triggered by thoughtless comments/actions on SNS, and it sometimes ends up damaging to the company's reputation seriously. In this paper, in order to prevent such unexpected damage to the company's reputation, we propose a new approach to sentiment analysis using a Naïve Bayes classifier, in which the features of tweets/comments are selected based on entropy-based criteria and an empirical rule to capture negative expressions. In addition, we propose a semi-supervised learning approach to relabeling noisy training data, which come from various SNS media such as Twitter, Facebook, blogs and a Japanese textboard called `2-channel'. In the experiments, we use four data sets of users' comments, which were posted to different SNS media of private companies. The experimental results show that the proposed Naïve Bayes classifier model has good performance for different SNS media, and a semi-supervised learning effectively works for the data consisting of long comments. In addition, the proposed method is applied to detect flaming incidents, and we show that it is successfully detected.
Design of Quadrature Mirror Filter Banks Using Complex Half-Band Filters

This paper presents the theory and design examples for a new class of quadrature mirror filter banks. Two-channel filter banks are considered as a single filter with complex coefficients. The alias-free condition for the conventional two-channel quadrature mirror filter bank is analyzed and expressed in complex arithmetic. For any real coefficient digital filter, a phase shift in frequency domain produces a complex coefficient digital filter. In particular, a 90 degree phase shift for half-band digital filters results in a complex coefficient version. Such filters generate analytic output signals, and may be decomposed into the sum of an identity operation and a Hilbert transformer. Quadrature mirror filter banks based on complex half-band filters are investigated using the above complex arithmetic technique. Design examples and their associated polyphase realizations are included for the cases of linear phase FIR and elliptic IIR filter banks.
“ The Customer ’ s Perception of Tourism Accreditation ”

There have been numerous suggestions that the long term viability of the Australian tourism industry depends on the ability of tourism operators to provide a quality service that meets, if not exceeds, the needs and expectations of its clients. The tourism industry has taken up this challenge over the last decade and increased its focus on quality of tourism products and services. One aspect of this has been the introduction of accreditation programs at the state and, more recently, at the national level. The Australian Tourism Accreditation Authority was established in 1998 under the auspices of Tourism Council Australia (TCA) and is charged with responsibility to encourage operators around the country to become accredited. While research on accreditation is very limited, that which has occurred focuses on the operators. We now have a reasonably clear picture of what operators believed they would gain through accreditation as well as an understanding of what actually occurred. What is missing is the perspective of consumers. This paper outlines some work that is currently under way to determine the level of awareness regarding tourism accreditation amongst consumers. A survey of 155 tourists was conducted to find out if tourism accreditation has any meaning to them and whether it has influenced their purchase decisions. It also sought to identify which aspects of accredited operations they consider to be important and whether there was any difference in the views of certain sub-groups of tourists such as domestic and international or ‘experienced’ and ‘non-experienced’ travellers.
A Mode of Operation with Partial Encryption and Message Integrity

At the recent AES Modes of Operation Conference, several modes of operation were proposed for using a block cipher to provide both con dentiality and authentication. These modes require only a little more work than the cost of encryption alone, and come with proofs of security. However, these modes require the entire message to be sent in encrypted form. This can cause problems in situations where some of the message neeeds to be sent in plaintext while still being authenticated. This paper describes a simple variation that allows any choice of message blocks to be sent in plaintext form rather than in encrypted form. This mode, Partial Encryption with Message Integrity (PEMI), is shown to be secure for message integrity and message secrecy.
Particle Grid Tracking System Stereovision Based Obstacle Perception in Driving Environments

This paper presents an occupancy grid tracking system based on particles, and the use of this system for dynamic obstacle detection in driving environments. The particles will have a dual nature they will denote hypotheses, as in the particle filtering algorithms, but they will also be the building blocks of our modeled world. The particles have position and speed, and they can migrate in the grid from cell to cell depending on their motion model and motion parameters, but they will also be created and destroyed using a weighting-resampling mechanism specific to particle filter algorithms. An obstacle grid derived from processing a stereovision-generated elevation map is used as measurement information, and the measurement model takes into account the uncertainties of the stereo reconstruction. The dynamic occupancy grid is used for improving the quality of the stereovision-based reconstruction as oriented cuboids. The resulted system is a flexible, real-time tracking solution for dynamic unstructured driving environments, and a useful tool for extracting intermediate dynamic information that can considerably improve object detection and tracking.
Research Statement: towards Detailed Recognition of Visual Categories

As humans, we have a remarkable ability to perceive the world around us in minute detail purely from the light that is reflected off it – we can estimate material and metric properties of objects, localize people in images, describe what they are doing, and even identify them. Automatic methods for such detailed recognition of images are essential for most human-centric applications and large scale analysis of the content of media collections for market research, advertisement, and social studies. For example, in order to shop for shoes in an on-line catalogue, a system should be able to understand the style of a shoe, the length of its heels, or the shininess of its material. In order to support visual demographics analysis for advertisement, a system should be able to not only identify the people in a scene, but also to understand what kind (style and brand) of clothes they are wearing, whether they are wearing any accessories, and so on. Despite several successes, such detailed recognition is beyond the current computer vision systems. This is a challenging task, and to make progress we have to make advances on several fronts. We need better representations of visual categories that can enable fine-grained reasoning about their properties, as well as machine learning methods that can leverage 'big-data' to learn such representations. In order to enable benchmarks for evaluating recognition tasks and to guide learning and inference in models that solve challenging problems, we need to develop better ways of human-computer interaction. My research touches upon several such themes in the intersection of computer vision, machine learning, and human-computer interaction including: • Machine learning for computer vision, which includes classifiers that offer better tradeoffs between representation power and efficiency, leading to orders of magnitude savings in memory and training time on large-scale data [11]. Other examples are efficient classification techniques that are exponentially faster for commonly used classifiers in computer vision [12], techniques to speed-up object detection in images using part-based models [11], methods for efficiently combining high-level and low-level information for semantic segmentation [18], and learning and inference in structured models [6, 7]. • Rich representations of visual categories based on novel parts called 'poselets' that are currently the state of the art for person detection, segmentation, and estimation of fine-grained properties such as pose, action, gender, clothing style, and other attributes [1, 2, 3, 14]. Recently, we have developed methods to …
The Effect of Habitual Exercise on Daytime Sleepiness and Mood of US Navy Sailors

As part of a broader study, this work investigates if habitual exercise protects against mood deterioration and daytime sleepiness in Sailors during underway operations. Previous work has shown that unfavorable watchstanding schedules have negative effects on sleep quality, subjective levels of fatigue, mood, and psychomotor vigilance performance. The participants were crewmembers of a U.S. Navy aircraft carrier (N=193), working on two different watchstanding schedules. Epworth Sleepiness Scale (ESS) and profile of mood state (POMS) scores were compared between participants who reported exercising < 3 times/week and ≥3 times/week. During the course of the underway, ESS and POMS scores changed more favorably for the crewmembers who exercised 3 or more times/week compared to their peers who exercised less. The effect of working out was more prominent in the less favorable shift schedule. These results suggest that habitual exercise can be a protective buffer against some of the negative effects of watchstanding while underway.
A co-simulation framework for Smart Grid wide-area monitoring networks

The next generation of the electrical power grid, called the Smart Grid, overcomes the deficiencies of the existing system using several Information and Communication Technology (ICT) mechanisms. One such mechanism is wide-area grid monitoring based on phasor measurement units (PMU). The data from these units are communicated to several applications (such as control, market brokerage, etc.) using a communication network framework called the North American Synchro-Phasor Initiative Network (NASPInet). To understand the performance and to guide design decisions of wide-area monitoring based Smart Grid applications, there is a need for a simulator that has both power system and communication system simulation capabilities. In this paper, we present a co-simulation framework developed using two existing public-domain simulators (OpenDSS and OMNET++ respectively for power systems and communication networks simulation). The former is based on continuous-time and the latter on discrete-time simulation. The proposed framework also deals with the time synchronization between these two systems. This framework has been implemented at IIT Madras for public use. A hybrid state estimation application, a voltage monitoring application and a renewable energy integration application are implemented over this framework. The results obtained from the applications verify their field correctness and also validate the correctness of the co-simulation framework.
On noise-induced synchronization and consensus of nonlinear network systems under input disturbances

This paper is concerned with the study of synchronization and consensus phenomena in complex networks of diffusively-coupled nodes subject to external disturbances. Specifically, we make use of stochastic Lyapunov functions to provide conditions for synchronization and consensus for networks of nonlinear, diffusively coupled nodes, where noise diffusion is not just additive but it depends on the nodes' state. The sufficient condition we provide, wich links together network topology, coupling strength and noise diffusion, offers two interesting interpretations. First, as suggested by {\em intuition}, in order for a network to achieve synchronization/consensus, its nodes need to be sufficiently well connected together. The second implication might seem, instead, counter-intuitive: if noise diffusion is {\em properly} designed, then it can drive an unsynchronized network towards synchronization/consensus. Motivated by our current research in Smart Cities and Internet of Things, we illustrate the effectiveness of our approach by showing how our results can be used to control certain collective decision processes.
A CONSISTENCY LEMMA IN STATISTICAL PHYLOGENETICS

= T). Let θbe a vector of continuous parameters – including the branch lengthsof T, along with possibly other continuous parameters required to specify a model of characterevolution on T. Let Θ denote the set of values θ may take. Branch lengths, in particular,are assumed to be strictly positive and ﬁnite; and in general Θ will be some open subset ofEuclidean space. Consider any stochastic process (e.g. Markov process, or mixture of Markovprocesses) which assigns to each pair (T,θ) a probability distribution s = s(T,θ) on discrete,ﬁnite-state characters at the tips of the tree. We assume throughout that the map θ→ s(T,θ) iscontinuous. Such models are central to statistical phylogenetics and methods for reconstructingphylogenetic trees from aligned genetic (e.g. DNA) sequences. A tree reconstruction method ψisany method that reconstructs a set of one or more unrooted phylogenetic trees from any givendistribution ˆf of site pattern frequencies. Suppose we generate ksites i.i. d. from (T,θ), and let ˆsbe the random variable equal to the resulting proportion of site patterns (character types). Themethod ψis a statistically consistent estimator of the unrooted topology of Tif the probabilitythat ψ(ˆs) = {T
Study of Prioritization Techniques Using Students as Subjects

In many software development projects there are more candidate requirements. Most projects are also constrained by budget and time; therefore it is often difficult to implement all requirements that have been elicited for a system. For prioritization purposes, many approaches have been proposed so far to help the process. Several empirical studies have been conducted to analyze characteristics of the available approaches, but their results are often difficult to compare. In this paper, a study designed at evaluating two requirements prioritization techniques, AHP and Numeral assignment technique is discussed. The study used students as subjects to prioritize requirements from an estate agency system and a library information system. Two groups of students, one from requirements engineering classroom and another group consists of research students participate in the study. The results reaffirm previous study that AHP gives more accurate and more informative result than the numeral assignment technique.
Electron Tomography Reveals Posttranscriptional Binding of Pre-Mrnps to Specific Fibers in the Nucleoplasm

Using electron tomography, we have analyzed whether the Balbiani ring (BR) pre-mRNP particles in transit from the gene to the nuclear pore complex (NPC) are bound to any structure that could impair free diffusion through the nucleoplasm. We show that one-third of the BR particles are in contact with thin connecting fibers (CFs), which in some cases merge into large fibrogranular clusters. The CFs have a specific protein composition different from that of BR particles, as shown by immuno-EM. Moreover, we have identified hrp65 as one of the protein components of the CFs. The sequencing of hrp65 cDNA reveals similarities with hnRNP proteins and splicing factors. However, hrp65 is likely to have a different function because it does not bind to nascent pre-mRNA and is not part of the pre-mRNP itself. Taken together, our observations indicate that pre-mRNPs are not always freely diffusible in the nucleoplasm but interact with fibers of specific structure and composition, which implies that some of the posttranscriptional events that the pre-mRNPs undergo before reaching the NPC occur in a bound state.
Drinking in social groups. Does ‘groupdrink’ provide safety in numbers when deciding about risk?

Abstract Aims To investigate the impact of alcohol consumption on risk decisions taken both individually and while part of a four‐ to six‐person ad‐hoc group. Design A 2 (alcohol: consuming versus not consuming alcohol) × 2 (decision: individual, group) mixed‐model design; decision was a repeated measure. The dependent variable was risk preference, measured using choice dilemmas. Setting Opportunity sampling in campus bars and a music event at a campus‐based university in the United Kingdom. Participants A total of 101 individuals were recruited from groups of four to six people who either were or were not consuming alcohol. Measurements Participants privately opted for a level of risk in response to a choice dilemma and then, as a group, responded to a second choice dilemma. The choice dilemmas asked participants the level of accident risk at which they would recommend someone could drive while intoxicated. Findings Five three‐level multi‐level models were specified in the software program HLM 7. Decisions made in groups were less risky than those made individually (B = −0.73, P < 0.001). Individual alcohol consumers opted for higher risk than non‐consumers (B = 1.27, P = 0.025). A significant alcohol × decision interaction (B = −2.79, P = 0.001) showed that individual consumers privately opted for higher risk than non‐consumers, whereas risk judgements made in groups of either consumers or non‐consumers were lower. Decisions made by groups of consumers were less risky than those made by groups of non‐consumers (B = 1.23, P < 0.001). Conclusions Moderate alcohol consumption appears to produce a propensity among individuals towards increased risk‐taking in deciding to drive while intoxicated, which can be mitigated by group monitoring processes within small (four‐ to six‐person) groups.
Prognostic and predictive value of VHL gene alteration in renal cell carcinoma: a meta-analysis and review

The von Hippel-Lindau (VHL) gene is often inactivated in sporadic renal cell carcinoma (RCC) by mutation or promoter hypermethylation. The prognostic or predictive value of VHL gene alteration is not well established. We conducted this meta-analysis to evaluate the association between the VHL alteration and clinical outcomes in patients with RCC. We searched PUBMED, MEDLINE and EMBASE for articles including following terms in their titles, abstracts, or keywords: ‘kidney or renal’, ‘carcinoma or cancer or neoplasm or malignancy’, ‘von Hippel-Lindau or VHL’, ‘alteration or mutation or methylation’, and ‘prognostic or predictive’. There were six studies fulfilling inclusion criteria and a total of 633 patients with clear cell RCC were included in the study: 244 patients who received anti-vascular endothelial growth factor (VEGF) therapy in the predictive value analysis and 419 in the prognostic value analysis. Out of 663 patients, 410 (61.8%) had VHL alteration. The meta-analysis showed no association between the VHL gene alteration and overall response rate (relative risk = 1.47 [95% CI, 0.81-2.67], P = 0.20) or progression free survival (hazard ratio = 1.02 [95% CI, 0.72-1.44], P = 0.91) in patients with RCC who received VEGF-targeted therapy. There was also no correlation between the VHL alteration and overall survival (HR = 0.80 [95% CI, 0.56-1.14], P = 0.21). In conclusion, this meta-analysis indicates that VHL gene alteration has no prognostic or predictive value in patients with clear cell RCC.