Miracle-dz/UniFAR-FTUs huggingface dataset:
NLOS Identification and Weighted Least-Squares Localization for UWB Systems Using Multipath Channel Statistics

Non-line-of-sight (NLOS) identification and mitigation carry significant importance in wireless localization systems. In this paper, we propose a novel NLOS identification technique based on the multipath channel statistics such as the kurtosis, the mean excess delay spread, and the root-mean-square delay spread. In particular, the IEEE 802.15. 4a ultrawideband channel models are used as examples and the above statistics are found to be well modeled by log-normal random variables. Subsequently, a joint likelihood ratio test is developed for line-of-sight (LOS) or NLOS identification. Three different weighted least-squares (WLSs) localization techniques that exploit the statistics of multipath components (MPCs) are analyzed. The basic idea behind the proposed WLS approaches is that smaller weights are given to the measurements which are likely to be biased (based on the MPC information), as opposed to variance-based WLS techniques in the literature. Accuracy gains with respect to the conventional least-squares algorithm are demonstrated via Monte-Carlo simulations and verified by theoretical derivations.
Detecting Periodicity in Fission Yeast Cell Cycle Gene Expression Using

Cyclic patterns of gene expression have been known and studied under various criteria like cell division, circadian rhythms, etc. Microarrays allow us to do such studies on a genome-wide scale. Several methods have been proposed to computationally determine and rank the (genes with) strongly cyclic expression profiles, as distinguished from those that are weak/not cyclic, from thousands of genes under consideration. However, in practice it is Fourier Analysis that has always been exclusively used for the purpose irrespective of its possible disadvantages in situations where there could me many missing entries. Lomb-Scargle method has been used to analyze situations with missing and unevenly spaced points. We applied this method to analyze the cell cycle-regulated genes of the yeast Schizosaccharomyces Pombe and found some promising results.
Index of CD34+ Cells and Mononuclear Cells in the Bone Marrow of Spinal Cord Injury Patients of Different Age Groups: A Comparative Analysis

Introduction. Recent evidence of safety and efficacy of Bone Marrow Mononuclear Cells (BMMNC) in spinal cord injury makes the Bone Marrow (BM) CD34+ percentage and the BMMNC count gain significance. The indices of BM that change with body mass index and aging in general population have been reported but seldom in Spinal Cord Injury (SCI) victims, whose parameters of relevance differ from general population. Herein, we report the indices of BMMNC in SCI victims. Materials and Methods. BMMNCs of 332 SCI patients were isolated under GMP protocols. Cell count by Trypan blue method and CD34+ cells by flow cytometry were documented and analysed across ages and gender. Results. The average BMMNC per ml in the age groups 0–20, 21–40, 41–60, and 61–80 years were 4.71, 4.03, 3.67, and 3.02 million and the CD34+ were 1.05%, 1.04%, 0.94%, and 0.93% respectively. The decline in CD34+ was sharp between 20–40 and 40–60 age groups. Females of reproductive age group had lesser CD34+. Conclusion. The BMMNC and CD34+ percentages decline with aging in SCI victims. Their lower values in females during reproductive age should be analysed for relevance to hormonal influence. This study offers reference values of BMMNC and CD34+ of SCI victims for successful clinical application.
LBP-based Hierarchical Sparse Patch Learning for Face Recognition

Local Binary Pattern (LBP) features and its variants are computed on the patches with the fixed positions and a fixed size in images, while the limited variety of the size and position cannot accurately measure the nature of face image. In this paper, we propose a new learning method, Hierarchical Sparse Patch Learning (HSPL), to select face patches with different positions and sizes for face recognition. HSPL employs a sparse learning model to hierarchically select patches at two levels: in level 1 the optimal patch candidates are figured out, while in level 2 the optimal patches from the candidates are obtained. LBP features are extracted from the optimal patches to recognize faces. Experimental results show that the proposed method is more efficient and achieves higher recognition rate than the other two compared methods.
A Novel Ant Colony Optimization Based Intelligent Routing Algorithm

Distance Vector Routing (DVR) has successfully tackled multiple routing problems, but it still suffers from certain drawbacks; slow convergence, limited scalability and routing loops. In this paper, we propose an adaptive routing algorithm which is loosely based on Original AntNet algorithm. From the paper, it shall be clear that our proposed algorithm exhibits better performance than the traditional routing algorithm as it will solve the problems encountered in distance vector routing like premature convergence, count to infinity problem, slow updating problem.
Making Sense of Gigabytes: A System for Knowledge-Based Market Analysis

Market researchers are looking more and more to point-of-sale scanners in retail outlets as a rich source of high-quality and timely sales data. Unfortunately, the sheer volume of such data makes analysis and interpretation an overwhelming task. Consequently, there is a demand for software tools that can automatically provide an analysis of large volumes of data. SPOTLIGHT is a knowledge-based product that enables A. C. Nielsen clients to understand what is significant in databases of point-of-sale scanner data. Using SPOTLIGHT, manufacturers and retailers track the sale and movement of products, assess the effectiveness of various promotional strategies, and compare the performance of competing products and product segments. SPOTLIGHT provides an alternative to the classical approach, where market analysts provide custom interpretations and reports, typically using spreadsheet tools such as Lotus as aids. SPOTLIGHT turns a task that takes 2 to 4 weeks into a task of 15 minutes to several hours depending on data volumes. Although previous attempts were made to automate the analysis of market data, within this domain, SPOTLIGHT represents the first commercial use of an expert system shell and the first deployment of sophisticated analytic capabilities directly onto a large number of widely distributed personal computer (PC) platforms.
Quality Level Control for Multi-User Sessions in Future Generation Networks

Real-time multimedia sessions are now present in our daily live experience, and will be among the most important applications in future generation networks. The distribution of those sessions, towards fixed and mobile users, with Quality of Experience (QoE) assurance is important to attract and keep customers, while increasing the profits of providers. This paper proposes the Quality Level Control for Multi-user Session (QUALITIS) approach to assure the quality level of sessions shared by multiple users (multi-users) in future generation networks. QUALITIS aims to keep sessions with an acceptable quality level and to avoid session blocking. The QUALITIS control is achieved by coordinating Quality of Service (QoS) mapping, QoS adaptation, resource allocation and mobility mechanisms. Performance evaluation was carried out based on simulation experiments and verified the QUALITIS impact on the user's expectation and on the performance of the network.
Assessment of factors for e-learning: an empirical investigation

Purpose The growth of internet, cloud technology, and mobile usage in the present scenario has spread in every aspect of human life. The usage of e-learning (electronic-learning) has been stretching wings in every sector and creating many opportunities. The education market has significantly developed over the past few years and e-learning has emerged as a major contributor toward the development of the education sector. The purpose of this paper is to study the perception of students of different universities in Uttar Pradesh and National Capital Region (India) toward e-learning usage. Design/methodology/approach With the help of exploratory factor analysis followed by confirmatory factor analysis, factors of e-learning were explored through a survey of 298 students involved in the e-learning process. Findings Six factors were explored and validated. These six factors are: supportive factors, system quality, learners’ perspective, instructor perspective, information quality, and service quality. Practical implications Policymakers and future researchers need to focus on the facilitation of e-learning in rural and urban areas of India. Originality/value Results will be useful in the implementation of e-learning applications.
Research on the Design of the Effective Transmission SchedulingAlgorithm Based on the Factory Wireless Sensor Network

In order to make the sensing data in the monitoring equipment's sensor nodes reach to the monitoring center as soon as possible and deal with the equipment which has some problems, the network time delay should be guaranteed in the accessible Time Delay Bound. The paper mainly researches the transmission scheduling algorithm with the chain framework, which adopts the Token to do the transmission in the chain and then arranges the transmission order in each node for avoiding the occurrence of the collision and offering the guarantee of the time delay. The node order in each chain is the order of data packets which are transmitted by nodes, while the route of the data packet transmission is ac- cording to the shortest route in the Sink Tree for reducing the time delay.
Cerita Rakyat Timun Emas: Gambaran Runtuhnya Ideologi Patriarkal

Patriarchal ideology puts women as subordinate and feel inferior in various facets of life. thought it was getting counter-discourse presented by the text tale of Timun Emas. In the text, described the loss of the role of men as the highest authority in live. The role of men is represented by four figures; the husband, Ki Butakala, Ki Pertapa, and the Prince. They have superiority , but then lost control of the two rival of women; Nyi Niken and Timun Emas. In the text implied that Nyi Niken and Timun Emas does not need a male figure in their lives. In accordance with the above description, analysis tale of Timun Emas uses feminist approach to look at the differences in the function and role of the human (between of man and woman). So it can be concluded that the tale of Timun Emas events that indicate a loss of patriarchal ideology
Smooth Muscle–Selective Inhibition of Nuclear Factor‐κB Attenuates Smooth Muscle Phenotypic Switching and Neointima Formation Following Vascular Injury

Background Vascular proliferative diseases such as atherosclerosis are inflammatory disorders involving multiple cell types including macrophages, lymphocytes, endothelial cells, and smooth muscle cells (SMCs). Although activation of the nuclear factor‐κB (NF‐κB) pathway in vessels has been shown to be critical for the progression of vascular diseases, the cell‐autonomous role of NF‐κB within SMCs has not been fully understood. Methods and Results We generated SMC‐selective truncated IκB expressing (SM22α‐Cre/IκBΔN) mice, in which NF‐κB was inhibited selectively in SMCs, and analyzed their phenotype following carotid injury. Results showed that neointima formation was markedly reduced in SM22α‐Cre/IκBΔN mice after injury. Although vascular injury induced downregulation of expression of SMC differentiation markers and myocardin, a potent activator of SMC differentiation markers, repression of these markers and myocardin was attenuated in SM22α‐Cre/IκBΔN mice. Consistent with these findings, NF‐κB activation by interleukin‐1β (IL‐1β) decreased expression of SMC differentiation markers as well as myocardin in cultured SMCs. Inhibition of NF‐κB signaling by BAY 11‐7082 attenuated repressive effects of IL‐1β. Of interest, Krüppel‐like factor 4 (Klf4), a transcription factor critical for regulating SMC differentiation and proliferation, was also involved in IL‐1β‐mediated myocardin repression. Promoter analyses and chromatin immunoprecipitation assays revealed that NF‐κB repressed myocardin by binding to the myocardin promoter region in concert with Klf4. Conclusions These results provide novel evidence that activation of the NF‐κB pathway cell‐autonomously mediates SMC phenotypic switching and contributes to neointima formation following vascular injury.
Effects of Targeted Promotions: Evidence from Field Experiments

The prevalence and widespread usage of email has given businesses a direct and cost effective way of providing consumers with targeted promotional offers. While targeted promotions are expected to increase the demand for the promoted products, are these promotions effective in increasing revenues? Do they have effects beyond acting as price reductions? We study these questions using individual-level data from 70 randomized experiments run by a large online ticket resale platform. We measure the impact of emailed promotions by comparing purchases by individuals who received the experimental promotions with purchases by those who did not receive the offers because of the experimental randomization. We find that the offers cause the average expenditure to increase by $3.03 (a 37.2% increase) during the promotion window. However, ninety percent of these gains are not through redemption of the offers. Interestingly, the promotion causes carryover to the week after the promotion expires; we find that spending increases by $1.55 in the week after the offer expires. Additionally, we find evidence for cross category spillovers to non-promoted products--offers not applicable to a ticket genre cause an increase in spending in that genre. We conclude that emailed promotions can serve as a form of "advertising" for the firm's products.
Free-viewpoint Video for Interactive Character Animation

Conventional 2D video production provides a fixed-view reproduction of a recorded event in which a director defines every moment to be viewed. Multiple camera studio systems are now being developed to capture real-world events from multiple viewpoints to replay the event in 3D as a freeviewpoint video. Free-viewpoint video provides the consumer the flexibility to interact with a scene by changing the viewpoint in replaying the event. The challenge in computer vision and computer graphics remains to capture real world events for both replay and to provide the director or consumer the freedom to synthesize new unseen content. In this paper we explore the use of free-viewpoint video in content synthesis by re-using captured scenes of people. Our work combines image based scene reconstruction and video-based animation techniques to provide a new approach that allows interactive character animation from free-viewpoint video.
Generation of West Nile Virus Infectious Clones Containing Amino Acid Insertions Between Capsid and Capsid Anchor

West Nile virus (WNV) is a positive-sense RNA arbovirus responsible for recent outbreaks of severe neurological disease within the US and Europe. Large-scale analyses of antiviral compounds that inhibit virus replication have been limited due to the lack of an adequate WN reporter virus. Previous attempts to insert a reporter into the 3’ untranslated region of WNV generated unstable viruses, suggesting that this region does not accommodate additional nucleotides. Here, we engineered two WNV infectious clones containing insertions at the Capsid (C)/Capsid Anchor (CA) junction of the viral polyprotein. Recombinant viruses containing a TAT(1-67) or Gaussia Luciferase (GLuc) gene at this location were successfully recovered. However, rapid loss of most, if not all, of the reporter sequence occurred for both viruses, indicating that the reporter viruses were not stable. While the GLuc viruses predominantly reverted back to wild-type WNV length, the TAT viruses retained up to 75 additional nucleotides of the reporter sequence. These additional nucleotides were stable over at least five passages and did not significantly alter WNV fitness. Thus, the C/CA junction of WNV can tolerate additional nucleotides, though insertions are subject to certain constraints.
NVthreads: Practical Persistence for Multi-threaded Applications

Non-volatile memory technologies, such as memristor and phase-change memory, will allow programs to persist data with regular memory instructions. Liberated from the overhead to serialize and deserialize data to storage devices, programs can aim for high performance and still be crash fault-tolerant. Unfortunately, to leverage non-volatile memory, existing systems require hardware changes or extensive program modifications. We present NVthreads, a programming model and runtime that adds persistence to existing multi-threaded C/C++ programs. NVthreads is a drop-in replacement for the pthreads library and requires only tens of lines of program changes to leverage non-volatile memory. NVthreads infers consistent states via synchronization points, uses the process memory to buffer uncommitted changes, and logs writes to ensure a program's data is recoverable even after a crash. NVthreads' page level mechanisms result in good performance: applications that use NVthreads can be more than 2× faster than state-of-the-art systems that favor fine-grained tracking of writes. After a failure, iterative applications that use NVthreads gain speedups by resuming execution.
Passenger estimation system using Wi-Fi probe request

Public transportation is a popular means of travel for many urban residents. However, users may not know the location and number of people on a vehicle, which results in uncertainty and wasted time while waiting. To help users manage their time more efficiently, a passenger estimation system that can provide the location and occupancy of each vehicle would be useful. The location can be determined accurately by using GPS data, while it is noted that most passengers on a vehicle typically use smartphones, which are equipped with wireless systems that can be monitored to estimate the number of users in that area. Smartphones with Wi-Fi enabled always send out probe requests that contain unique MAC addresses. By monitoring these probe requests, the number of passengers on the vehicle can be estimated. The time period and signal strength from each probe request, along with the location of the vehicle, is used to categorize a group of smartphone users as passengers or non-passengers. The device is implemented and evaluated on the shuttle bus system of Thammasat University, Thailand.
Reproducibility of In-Vivo OCT Measured Three-Dimensional Human Lamina Cribrosa Microarchitecture

Purpose To determine the reproducibility of automated segmentation of the three-dimensional (3D) lamina cribrosa (LC) microarchitecture scanned in-vivo using optical coherence tomography (OCT). Methods Thirty-nine eyes (8 healthy, 19 glaucoma suspects and 12 glaucoma) from 49 subjects were scanned twice using swept-source (SS−) OCT in a 3.5×3.5×3.64 mm (400×400×896 pixels) volume centered on the optic nerve head, with the focus readjusted after each scan. The LC was automatically segmented and analyzed for microarchitectural parameters, including pore diameter, pore diameter standard deviation (SD), pore aspect ratio, pore area, beam thickness, beam thickness SD, and beam thickness to pore diameter ratio. Reproducibility of the parameters was assessed by computing the imprecision of the parameters between the scans. Results The automated segmentation demonstrated excellent reproducibility. All LC microarchitecture parameters had an imprecision of less or equal to 4.2%. There was little variability in imprecision with respect to diagnostic category, although the method tends to show higher imprecision amongst healthy subjects. Conclusion The proposed automated segmentation of the LC demonstrated high reproducibility for 3D LC parameters. This segmentation analysis tool will be useful for in-vivo studies of the LC.
Audio-visual Keyword Spotting for Mandarin Based on Discriminative Local Spatial-Temporal Descriptors

Although keyword spotting (KWS) technologies have been successfully applied to some applications, most KWS systems have a common problem of noise-robustness when applied to real-world environments. Audio-visual keyword spotting (AVKWS) using both acoustic and visual information is a solution to complementarily solve the problem. Most existing audio-visual speech recognition (AVSR) systems extract geometric features as visual features, which heavily rely on accurate and reliable detection and tracking of facial feature points. To avoid this defect of geometric features, an appearance-based discriminative local spatial-temporal descriptor (disCLBP-TOP) is proposed in this paper, which devotes to extracting robust and discriminative patterns of interest. Besides, a parallel two-step recognition based on both acoustic and visual keyword searching and re-scoring is conducted, which complementarily makes the best of two modalities under different noisy conditions. Adaptive weights for decision fusion are generated using a sigmoid function based on reliabilities of the two modalities, capable of adapting to various noisy conditions. Experiments show that our proposed parallel AVKWS strategy based on decision fusion significantly improves the noise robustness and attains better performance than feature fusion based audio-visual spotter. Additionally, disCLBP-TOP shows more competitive performance than CLBP-TOP.
Using genetic algorithms for query reformulation

Nowadays, searching information in the web or in any kind of document collection has become one of the most frequent activities. However, user queries can be formulated in a way that hinders the recovery of the requested information. The objective of automatic query transformation is to improve the quality of the recovered information. This paper describes a new genetic algorithm used to change the set of terms that compose a user query without user supervision, by complementing an expansion process based on the use of a morphological thesaurus. We apply a stemming process to obtain the stem of a word, for which the thesaurus provides its different forms. The set of candidate query terms is constructed by expanding each term in the original query with the terms morphologically related. The genetic algorithm is in charge of selecting the terms of the final query from the candidate term set. The selection process is based on the retrieval results obtained when searching with different combination of candidate terms. The algorithm shows improvement over some other using standard collections.