Miracle-dz/UniFAR-FTUs huggingface dataset:
Linear precoding in large scale MIMO under 3D channel model

Large scale MIMO is a new field for wireless communication. Theoretical analysis was usually done with independent distributed complex Gaussian channels and unlimited antennas. In this work, we exhibit the performance of linear precoding under the three dimension (3D) channel model calibrated by 3GPP in the 3D-UMÌ scenario. Considering the multi-cell multiuser MIMO (MU-MIMO), we assume that the base station (BS) has perfect channel state information (CSI) due to the reciprocity of TDD system. The BS is equipped with two dimension (2D) antenna array and the transmitted signal will experiences 3D radio propagation. We compare two linear precoding, maximum ratio transmission (MRT) and zero forcing (ZF), when the number of antennas is 16, 32 64 and 128. Also the polynomial expansion linear detector (PELD) method here is leveraged. Simulation results show that under the 3D channel model, as the number of antennas goes larger, the performance of both linear precoding goes better. Due to the limited number of antennas and the 3D propagation channel model, the inter-beam interferences deteriorate the performance of MRT. The performance of ZF is obviously better than MRT. Though the ZF precoding can eliminate the inter-beam interference, processing complexity is huge. The PELD precoding can achieve a suitable performance as a tradeoff between MRT and ZF.
Architecture of Automation Control Model for Robotics

robot is a device which is behaved like an artificial agent and it is also called as an electro mechanical machine which based on autonomous control. As the robotic based on various control paths which controls the robots by planning, Electronic sensor, Digital signals, Computer mechanics, Coordination, Actuation, Learning and adaptation. In this paper presents the new robot control architecture for Intelligent Robot navigation to navigate its different direction of the wall avoiding obstacle. In contrast to standard formulation of robot behaviors, in proposed architecture presented which shows the modeling of robot behaviors with using the Autonomous robot Control.
Designing families of data types using exemplars

Designing data types in isolation is fundamentally different from designing them for integration into communities of data types, especially when inheritance is a fundamental issue. Moreover, we can distinguish between the design of families—integrated types that are variations of each other—and more general communities where totally different but cohesive collections of types support specific applications (e.g., a compiler). We are concerned with the design of integrated families of data types as opposed to individual data types; that is, on the issues that arise when the focus is intermediate between the design of individual data types and more general communities of data types. We argue that design at this level is not adequately served by systems providing only class-based inheritance hierarchies and that systems which additionally provide a coupled subtype specification hierarchy are still not adequate. We propose a system that provides an unlimited number of uncoupled specification hierarchies and illustrate it with three: a subtype hierarchy, a specialization/generalization hierarchy, and a like hierarchy. We also resurrect a relatively unknown Smalltalk design methodology that we call programming-by-exemplars and argue that it is an important addition to a designer's grab bag of techniques. The methodology is used to show that the subtype hierarchy must be decoupled from the inheritance hierarchy, something that other researchers have also suggested. However, we do so in the context of exemplar-based systems to additionally show that they can already support the extensions required without modification and that they lead to a better separation between users and implementers, since classes and exemplars can be related in more flexible ways. We also suggest that class-based systems need the notion of private types if they are to surmount their current limitations. Our points are made in the guise of designing a family of List data types. Among these is a new variety of lists that havenever been previously published: prefix-sharing lists. We also argue that there is a need for familial classes to serve as an intermediary between users and the members of a family.
Recovery of Images with Missing Pixels using a Gradient Compressive Sensing Algorithm

This paper investigates the possibility of reconstruction of images considering that they are sparse in the DCT transformation domain. Two approaches are considered. One when the image is pre-processed in the DCT domain, using 8x8 blocks. The image is made sparse by setting the smallest DCT coefficients to zero. In the other case the original image is considered without pre-processing, assuming the sparsity as intrinsic property of the analyzed image. A gradient based algorithm is used to recover a large number of missing pixels in the image. The case of a salt-and-paper noise affecting a large number of pixels is easily reduced to the case of missing pixels and considered within the same framework. The reconstruction of images affected with salt-and-paper impulsive is compared with the images filtered using a median filter. The same algorithm can be used considering transformation of the whole image. Reconstructions of black and white and colour images are considered.
A Low-Power mmWave CML Prescaler in 65nm SOI CMOS Technology

A 5-stage CML prescaler operating up to 84 GHz is presented. The prescaler requirements, design considerations, simulations, and performance measurements are presented. The first divide-by-2 stage consumes 17.7mW at 1.8V, or 26.40 power-delay product per gate. The prescaler's phase noise gain degeneration at the sensitivity curve boundary is reported for the first time.
Do Organizations Really Gain Without Pain?

The positive psychology movement involves putting an emphasis on investigating positive qualities of individuals. The movement has also affected work psychology domain. One of the most outstanding topics in the work psychology domain has been work engagement. Work engagement, defined as a positive state of mind, characterized by vigor, dedication, and absorption, has been studied in relation to individual resources and performance indicators. Primary objective of this chapter is to provide assumptions on the dark side of work engagement. In this respect, the dark side of employee engagement, which has not received great attention in the literature, will be discussed in order to inspire a more balanced focus for future studies and organizational settings. The recommendation section includes avenues for future studies and suggestions for gatekeepers/managers.
MP28-07 DEVELOPMENT AND VALIDATION OF LNCRNAS–BASED NOMOGRAM FOR PREDICTION OF BIOCHEMICAL RECURRENCE IN PROSTATE CANCER BY BIOINFORMATICS ANALYSIS

INTRODUCTION AND OBJECTIVES: Early biochemical recurrence (BCR) was considered as a sign for clinical recurrence and metastasis of prostate cancer (PCa). The purpose of the present study was to identify a lncRNA-based nomogram that can predict BCR of PCa accurately. METHODS: Bioinformatics analysis, such as propensity score matching (PSM) and differentially expressed genes (DEGs) analyses were used to identify candidate lncRNAs for further bioinformatics analysis. LASSO Cox regression model was used to select the most significant prognostic lncRNAs and construct the lncRNAs signature for predicting BCR in discovery set. Additionally, a nomogram based on our lncRNAs signature was also formulated. Both lncRNAs signature and nomogram were validated in test set. GSEA was carried out to identify various lncRNAs sets which share a common biological function, chromosomal location, or regulation. RESULTS: A total of 457 patients with sufficient BCR information were included in our analysis. Finally, a five lncRNAs signature significantly associated with BCR was identified in discovery set (HR=0.44, 95%CI: 0.27-0.72, C-index = 0.63) and validated in test set (HR=0.22, 95%CI: 0.09-0.56, C-index = 0.65). Additionally, the lncRNAs-based nomogram showed significant performance for predicting BCR in both discovery set (C-index = 0.74) and test set (C-index = 0.78). CONCLUSIONS: In conclusion, our lncRNAs-based nomogram is a reliable prognostic tool for BCR in PCa patients. In addition, the present study put forward the direction for the further investigation on the mechanism of PCa progression. Figure. No caption available. Figure. No caption available. Source of Funding: none
Sparse Bayesian prediction of disordered residues and disordered regions based on amino-acid composition

This paper presents some initial results of an investigation into the use of machine learning methods to detect natively disordered regions in proteins from sequence information. A committee of Relevance Vector Machines is used to select the optimal window size for residue-by-residue prediction of disordered regions, based on local amino-acid composition. The minimal error rate of ≈ 15% is achieved using very long (205 residue) window lengths, with the classifier making little use of more local sequence information. This suggests that disorder arises principally due to large scale diffuse changes in mean hydropathy and to a lesser extent mean charge. We also demonstrate that the proportion of proteins having long disordered regions in operational conditions cannot be reliably estimated using a classifier trained on a balanced dataset.
Usability versus privacy instead of usable privacy: Google's balancing act between usability and privacy

A smartphone is an indispensible device that also holds a great deal of personal and private data. Contact details, party or holiday photos and emails --- all carried around in our pockets and easily lost. On Android, the most widely-used smartphone operating system, access to this data is regulated by permissions. Apps request these permissions at installation, and they ideally only ask for permission to access data they really need to carry out their functions. The user is expected to check, and grant, requested permissions before installing the app. Their privacy can potentially be violated if they fail to check the permissions carefully. In June 2014 Google changed the Android permission screen, perhaps attempting to improve its usability. Does this mean that all is well in the Android eco-system, or was this update a retrograde move? This article discusses the new permission screen and its possible implications for smartphone owner privacy.
Variation in general practice medical admission rates for elderly people.

BACKGROUND Emergency medical admissions are rising, particularly in the elderly. Variation in admission rates between general practices has received little attention, and requires explanation. METHODS A retrospective review was carried out of emergency medical admissions to the District General Hospital (DGH) and the Community Hospitals (CHs) in West Gloucestershire in subjects over 75 years of age during 3 years. A survey of general practitioner (GP) attitudes to emergency admissions was carried out. RESULTS A five-fold spread in DGH and CH admission rates for elderly medical emergencies was found, and a three-fold spread of overall admission rates. Rates were consistent within a practice each year. The spreads of practice mortality rates and myocardial infarction admission rates were smaller. The variation between practices was not explained by the Jarman Index or by attitudes identified in GPs. Practices with high admission rates had slighter higher annual hospital mortality rates, but lower episode fatality rates. CONCLUSION Admission rates show considerable variation between practices, which is only partly explained by morbidity rates, and consistency over 3 years.
Online Mining of Changes from Data Streams: Research Problems and Preliminary Results

As data streams are gaining prominence in a growing number of emerging applications, advanced analysis and mining of data streams is becoming increasingly important. While there are some recent studies on mining data streams, we would like to ask the following essential question: What are the distinct features of mining data streams compared to mining other kinds of data? In this paper, we take the following position: online mining of the changes in data streams is one of the core issues. We propose some interesting research problems and highlight the inherent challenges. Moreover, we sketch some preliminary results.
A robot leg based on mammalian muscle architecture

Most legged robots to date use individual motors at the joints for actuation. However, the muscle structure of vertebrate legs incorporates both a flexor-extensor architecture and biarticular muscles — muscles that span two joints. Flexor-extensor architecture enables the joint to swing freely when muscles are relaxed, while biarticular muscles have been shown to play an important role in transferring power from proximal to distal body parts, enabling high-powered motions such as running and jumping. In this paper, we present a robot leg based on the muscle structure of the human leg, incorporating biarticular muscles and a flexor-extensor architecture. We demonstrate that this robot leg is able to use it's biarticular “muscles” to transfer power from the upper limb to the ankle, mimicking key characterisitics of the human leg.
Introduction and Comparison of Three Evolutionary-Based Intelligent Algorithms for Optimal Design

Engineering design studies can often be cast in terms of optimization problems. However, for such an approach to be worthwhile, designers must be content that the optimization approaches employed is fast convergence. Usefulness of heuristic algorithm as the search method for diverse optimization problems is examined. Evolutionary algorithms (EAs) are stochastic search methods that mimic the natural biological evolution and/or the social behavior of species. Such algorithms have been developed to arrive at near-optimum solutions to large-scale optimization problems, for which traditional mathematical techniques may fail. This paper compares the formulation and results of three evolutionary-based algorithms: genetic algorithm, clonal selection algorithm and particle swarm optimization. A brief description of each algorithm is presented. Benchmark comparisons among these algorithms are presented optimization problems, in terms of processing time, convergence speed, and quality of the results. The simulation results show that compared with genetic algorithm and clonal selection algorithm, the proposed particle swarm optimization based algorithm can improve the quality of the solution while speeding up the convergence process. Three words can summarize the main features of the proposed approach: faster, cheaper, and simpler.
Decoding vestibular migraine for easier diagnosis

Background: Due to the absence of a unified set of diagnostic criteria, vestibular migraine is always an underdiagnosed entity. This study was undertaken to find specific pointers in the diagnostic protocol which can help in diagnosing vestibular migraine and also to assess our treatment module for vestibular migraine.Methods: An elaborate proforma was prepared for evaluating each patient at our vertigo clinic for a time period of two years. A detailed history is followed by general examination, ENT examination, specific tests for eyes, tests for vestibulospinal tract, and also a few more tests such as Doppler, pure tone audiogram, ECHO etc. when the diagnosis was in doubt. A total of 206 patients were evaluated. Vestibular migraine cases were started on our drug regimen of Tab flunarizine once daily and subjected two follow ups (at 4 weeks and 12 weeks). Results: Total of 20 patients (9.7%) diagnosed as vestibular migraine. There was a slight preponderance to female population. A positive history of recurrent headache and neck pain were definitive clinchers in diagnosing vestibular migraine. All 20 patients had alleviation of symptoms with regards to severity and frequency of episodes.Conclusions: Detailed history and elaborate vestibular examination alone is necessary for diagnosing vestibular migraine. Flunarizine regimen for a period of 3 months is found to be effective in relieving the symptoms. Adjuvant vestibular rehabilitation exercises mandatory for total alleviation of symptoms.
Urinary kidney injury molecule-1 as an early diagnostic biomarker of obstructive acute kidney injury and development of a rapid detection method

The aim of the present study was to investigate whether urinary kidney injury molecule-1 (KIM-1) presents a suitable early diagnostic biomarker of obstructive nephropathy-induced acute kidney injury (AKI), and to develop a rapid detection method for urinary KIM-1. Obstructive AKI was induced in an experimental rat model by a unilateral ureteral obstruction (UUO) operation. Macro- and micromorphological kidney alterations were determined by visual observation and hematoxylin and eosin (HE) staining, respectively. Kidney functions were evaluated by detecting urea nitrogen and creatinine levels in rat urine and blood. Urinary KIM-1 levels were measured using an enzyme-linked immunosorbent assay, and the protein expression levels of KIM-1, α-smooth muscle actin (α-SMA) and vimentin in kidney tissues were detected using immunohistochemical assays. In order to measure KIM-1 levels, colloidal gold immunochromatographic strips were developed based on the colloidal gold immunochromatographic assay. The results indicated that KIM-1 levels were significantly higher in the UUO group when compared with the Sham group. KIM-1 levels in the urine and kidney tissues exhibited a time-dependent increase, together with increasing obstructive AKI in the UUO group. In addition, KIM-1 levels were demonstrated to be a more sensitive biomarker of early obstructive AKI, when compared with α-SMA and vimentin. A colloidal gold-based immunochromatographic strip was developed, whereby the detection of urinary KIM-1 could be completed within 5–10 min. In conclusion, results of the present study demonstrated that urinary KIM-1 may be a valuable biomarker for the early diagnosis of obstructive AKI, and the use of a colloidal gold immunochromatographic strip may be a promising method for the rapid detection of urinary KIM-1.
Standard bases for affine SL(n)-modules

We give an elementary and easily computable basis for the Demazure modules in the basic representation of the affine Lie algebra ! sln (and the loop group " SLn). A novel feature is that we define our basis “bottom-up” by raising each extremal weight vector, rather than “top-down” by lowering the highest weight vector. Our basis arises naturally from the combinatorics of its indexing set, which consists of certain subsets of the integers first specified by Jimbo et. al. in terms of crystal operators. We give a new way of defining these special sets in terms of a recursive but very simple algorithm, the roof operator, which is analogous to the left-key construction of Lascoux-Schutzenberger. The roof operator is in a sense orthogonal to the crystal operators. The most important representation of the affine Kac-Moody algebra ŝln (or of the loop group ŜLn) is the basic representation V (Λ0), the highest-weight representation associated to the extra node of the extended Dynkin diagram A n−1. The infinite-dimensional space V (Λ0) is filtered by the finite-dimensional Demazure modules Vw(Λ0) for w an element of the affine Weyl group: these are modules for a Borel subgroup of the loop group. There are several general constructions for irreducible representations and their Demazure modules, such as Lusztig’s canonical basis and Littelmann’s contracting modules. However, they are extremely difficult to compute explicitly, and even the combinatorial indexing set for a basis is very intricate. We will give an elementary and easily computable basis for V (Λ0) and its Demazure modules. We work inside the Fock space F , an infinite wedge product which contains V (Λ0), analogously to the space ∧C which realizes a fundamental representation of SLnC. The Fock space has a natural basis indexed by certain infinite subsets of integers. The combinatorial part of our problem amounts to defining which of these subsets will index basis elements of Vw(Λ0) for a given w. We describe these special subsets in terms of a recursive but very simple algorithm, the roof operator on subsets. This is analogous to the left-key construction of Lascoux-Schutzenberger [11], which distinguishes the Young tableaux indexing a basis of a given Demazure module of SLnC. The roof operator is more elementary (and much more efficient) than the crystal graph operators, and is in some sense orthogonal to them. One may think of the roof operator as jumping across the crystal graph, moving each vertex down to an extremal weight vertex w(Λ0), but not along edges of the crystal graph. The combinatorics of the roof operator lead naturally to the definition of our standard basis, in analogy to the method of Raghavan-Sankaran [16]. A novel feature is that we define our basis “bottom-up” by raising each extremal weight
Illumination Invariant Three-Stage Approach for Face Alignment

Localization of facial components is very important for many pattern recognition and computer vision applications such as face recognition, tracking of face expressions. This paper addresses the problem of precisely finding facial components, such as the eyes, the mouth, the nose etc. We present an illumination invariant three-stage approach for face alignment. This paper combines the concept of component-based approach and face alignment and develops component-based active appearance model (AAM) method for fine face alignment. We propose a new image representation to improve AAM segmentation accuracy for illumination invariant face alignment.
Multi-Modal Biometric Verification Based on FAR-score Normalization

Summary Fusion different biometrics is an effective way to design a biometric system with robust performance. To do this, normalization functions are employed. However, these functions can not follow the distributions of scores from distinct classifiers. Consequently different normalization errors are introduced. In this paper, the scores from different classifiers are converted into the corresponding false accept rate (FAR), which introduces smaller normalization error than traditional methods, and makes the fusion more operable. To further enhance the fusion result, a dynamic selection of fusion rule is implemented based on the discrepancy between scores of different classifiers. Experiments conducted on a multi-modal biometric system composed of face and fingerprint verification system show our methods are superior to conventional approaches.