Miracle-dz/UniFAR-FTUs huggingface dataset:
Low Probability of Detection Communication: Opportunities and Challenges

LPD communication has recently emerged as a new transmission technology to address privacy and security in wireless networks. Recent studies have established the fundamental limits of LPD communication in terms of the amount of information that can be conveyed from a transmitter to a receiver subject to a constraint on a warden's detection error probability. The established information- theoretic metric enables analytical studies on the design and performance of LPD communication under various channel conditions. In this article, we present the key features of LPD communication and discuss various important design considerations. First, we clarify the differences between LPD communication and well-known physical-layer security. Then, from an information-theoretic point of view, we discuss the optimal signaling strategies for transmitting the message-carrying signal and artificial noise signal for LPD communication. Finally, we identify the key challenges in the design of practical LPD communication systems and point out future research directions in this context. This article provides guidelines for designing practical LPD communication strategies in wireless systems and networks.
XLNet: Generalized Autoregressive Pretraining for Language Understanding

With the capability of modeling bidirectional contexts, denoising autoencoding based pretraining like BERT achieves better performance than pretraining approaches based on autoregressive language modeling. However, relying on corrupting the input with masks, BERT neglects dependency between the masked positions and suffers from a pretrain-finetune discrepancy. In light of these pros and cons, we propose XLNet, a generalized autoregressive pretraining method that (1) enables learning bidirectional contexts by maximizing the expected likelihood over all permutations of the factorization order and (2) overcomes the limitations of BERT thanks to its autoregressive formulation. Furthermore, XLNet integrates ideas from Transformer-XL, the state-of-the-art autoregressive model, into pretraining. Empirically, under comparable experiment settings, XLNet outperforms BERT on 20 tasks, often by a large margin, including question answering, natural language inference, sentiment analysis, and document ranking.
XNAS: Neural Architecture Search with Expert Advice

This paper introduces a novel optimization method for differential neural architecture search, based on the theory of prediction with expert advice. Its optimization criterion is well fitted for an architecture-selection, i.e., it minimizes the regret incurred by a sub-optimal selection of operations. Unlike previous search relaxations, that require hard pruning of architectures, our method is designed to dynamically wipe out inferior architectures and enhance superior ones. It achieves an optimal worst-case regret bound and suggests the use of multiple learning-rates, based on the amount of information carried by the backward gradients. Experiments show that our algorithm achieves a strong performance over several image classification datasets. Specifically, it obtains an error rate of 1.6% for CIFAR-10, 24% for ImageNet under mobile settings, and achieves state-of-the-art results on three additional datasets.
Write-Optimized and Consistent RDMA-based NVM Systems

In order to deliver high performance in cloud computing, we generally exploit and leverage RDMA (Remote Direct Memory Access) in networking and NVM (Non-Volatile Memory) in end systems. Due to no involvement of CPU, one-sided RDMA becomes efficient to access the remote memory, and NVM technologies have the strengths of non-volatility, byte-addressability and DRAM-like latency. In order to achieve end-to-end high performance, many efforts aim to synergize one-sided RDMA and NVM. Due to the need to guarantee Remote Data Atomicity (RDA), we have to consume extra network round-trips, remote CPU participation and double NVM writes. In order to address these problems, we propose a zero-copy log-structured memory design for Efficient Remote Data Atomicity, called Erda. In Erda, clients directly transfer data to the destination address at servers via one-sided RDMA writes without redundant copy and remote CPU consumption. To detect the incompleteness of fetched data, we verify a checksum without client-server coordination. We further ensure metadata consistency by leveraging an 8-byte atomic update in the hash table, which also contains the address information for the stale data. When a failure occurs, the server properly restores to a consistent version. Experimental results show that compared with Redo Logging (a CPU involvement scheme) and Read After Write (a network dominant scheme), Erda reduces NVM writes approximately by 50%, as well as significantly improves throughput and decreases latency.
Clock Synchronization Over Networks: Identifiability of the Sawtooth Model

In this paper, we analyze the two-node joint clock synchronization and ranging problem. We focus on the case of nodes that employ time-to-digital converters to determine the range between them precisely. This specific design choice leads to a sawtooth model for the captured signal, which has not been studied before from an estimation theoretic standpoint. In the study of this model, we recover the basic conclusion of a well-known article by Freris, Graham, and Kumar in clock synchronization. More importantly, we discover a surprising identifiability result on the sawtooth signal model: noise improves the theoretical condition of the estimation of the phase and offset parameters. To complete our study, we provide performance references for joint clock synchronization and ranging using the sawtooth signal model by presenting an exhaustive simulation study on basic estimation strategies under different realistic conditions. With our contributions in this paper, we enable further research in the estimation of sawtooth signal models and pave the path towards their industrial use for clock synchronization and ranging.
Satellite-based links for quantum key distribution: beam effects and weather dependence

The establishment of a world-wide quantum communication network relies on the synergistic integration of satellite-based links and fiber-based networks. The first are helpful for long-distance communication, as the photon losses introduced by the optical fibers are too detrimental for lengths greater than about 200 km. This work aims at giving, on the one hand, a comprehensive and fundamental model for the losses suffered by the quantum signals during the propagation along an atmospheric free-space link. On the other hand, a performance analysis of different quantum key distribution (QKD) implementations is performed, including finite-key effects, focusing on different interesting practical scenarios. The specific approach that we chose allows to precisely model the contribution due to different weather conditions, paving the way towards more accurate feasibility studies of satellite-based QKD missions.
A new approach to forecast service parts demand by integrating user preferences into multi-objective optimization

Service supply chain management is to prepare spare parts for failed products under warranty. Their goal is to reach agreed service level at the minimum cost. We convert this business problem into a preference based multi-objective optimization problem, where two quality criteria must be simultaneously optimized. One criterion is accuracy of demand forecast and the other is service level. Here we propose a general framework supporting solving preference-based multi-objective optimization problems (MOPs) by multi-gradient descent algorithm (MGDA), which is well suited for training deep neural network. The proposed framework treats agreed service level as a constrained criterion that must be met and generate a Pareto-optimal solution with highest forecasting accuracy. The neural networks used here are two Encoder-Decoder LSTM modes: one is used for pre-training phase to learn distributed representation of former generations' service parts consumption data, and the other is used for supervised learning phase to generate forecast quantities of current generations' service parts. Evaluated under the service parts consumption data in Lenovo Group Ltd, the proposed method clearly outperform baseline methods.
Rate-optimal estimation of the Blumenthal–Getoor index of a Lévy process

The Blumenthal-Getoor (BG) index characterizes the jump measure of an infinitely active Levy process. It determines sample path properties and affects the behavior of various econometric procedures. If the process contains a diffusion term, existing estimators of the BG index based on high-frequency observations only achieve rates of convergence which are suboptimal by a polynomial factor. In this paper, a novel estimator for the BG index and the successive BG indices is presented, attaining the optimal rate of convergence. If an additional proportionality factor needs to be inferred, the proposed estimator is rate-optimal up to logarithmic factors. Furthermore, our method yields a new efficient volatility estimator which accounts for jumps of infinite variation. All parameters are estimated jointly by the generalized method of moments. A simulation study compares the finite sample behavior of the proposed estimators with competing methods from the financial econometrics literature.
Video segmentation by hidden Markov model using multimodal MPEG-7 descriptors

We propose a robust video segmentation algorithm for video summary. Exact shot boundary detection and segmentation of video into meaningful scenes are important parts for the automatic video summary. In this paper, we present a shot boundary detection using audio and visual features defined in the MPEG-7 which provides software standard for multimedia description. By using Hidden Markov Model classifier based on statistics of the audio and visual features, exact shot boundary is detected and further over-segmentation could be reduced, which is a common problem in automatic video segmentation.
Computer Simulation Success: On the Use of the End-User Computing Satisfaction Instrument: A Comment

This comment is part of a comprehensive study to develop a contingency model of simulation success. The current study focuses on the psychometric stability of the end-user computing satisfaction (EUCS) instrument by Doll and Torkzadeh (1988) when applied to users of computer simulation. Using a survey of 411 users, the researchers provide evidence that the EUCS instrument is a valid and reliable measure of computer simulation success. Given this evidence, managers and simulation software product developers can confidently apply the instrument in the investigation of competing tools, features, and technologies.
Network design of a bicycle-sharing system

In this report we will be analysing a bicycle-sharing system. If we want to stimulate people to use these systems, we first need to make sure that people have trust in the system. We will be validating two different models that estimate the performance of a bicycle-sharing system with a simulation. We will also use the simulation program Anylogic to gain insight into the system. After the validation we will implement a case study and conclude that the performance of the Equilibrium State Model seems to improve when the system contains more stations and bicycles while the Stochastic Network Flow model is not capable of estimating all cases.
User perceptions of library effectiveness in Malaysian agricultural libraries

This study investigated those factors that contribute positively in shaping users’ perceptions of library effectiveness. A questionnaire‐based survey of five major agricultural libraries in Malaysia was conducted. It was found that the adequacy of collections, services and facilities were closely linked to the perceptions of library effectiveness. Certain other factors contributing positively to the perception of library effectiveness were the adequacy and effectiveness of library promotion, involvement of users in the selection of library materials, convenient library location, participation in user education programmes, availability of assistance for using library resources and facilities, and subject background of library professionals. The paper suggests that for any reliable library effectiveness study, all factors associated with user satisfaction should be investigated together.
Loss aversion with multiple investment goals

This paper presents a time-continuous portfolio selection model with loss averse investors, who possess multiple investment goals at different time horizons. The model assumes partial narrow framing. Investors follow a two-step approach. First, they optimally allocate wealth among investment goals. Second, they determine an optimal investment strategy for each investment goal separately. We show that when loss aversion is according to the experimental findings, investors mainly invest their wealth to reach long-term goals and adopt investment strategies with high leverage to reach short-term goals. The overall strategy also display high leverage. The same patterns is observed when loss aversion is extreme and goals are very ambitious. By contrast, when loss aversion is extreme but goals are not too ambitious, investors mainly invest to reach short-term goals and adopt safe investment strategies for this purpose.
Handbook of Univariate and Multivariate Data Analysis and Interpretation with SPSS

INFERENTIAL STATISTICS AND TEST SELECTION INTRODUCTION TO SPSS MULTIPLE RESPONSE T-TEST FOR INDEPENDENT GROUPS PAIRED-SAMPLES T-TEST ONE-WAY ANALYSIS OF VARIANCE, WITH POST HOC COMPARISONS FACTORIAL ANALYSIS OF VARIANCE GENERAL LINEAR MODEL (GLM) MULTIVARIATE ANALYSIS GENERAL LINEAR MODEL: REPEATED MEASURES ANALYSIS CORRELATION LINEAR REGRESSION FACTOR ANALYSIS RELIABILITY MULTIPLE REGRESSION STRUCTURAL EQUATION MODELING NONPARAMETRIC TESTS APPENDIX: Summary of SPSS Syntax Files References
Computerised self-evaluation of performance in professional English

Purpose – the focus of this article is to explore self-evaluation of performance in professional English that students have to do in university studies. It is clear that students can have various problems in learning English and make mistakes in listening, speaking, reading, writing, and vocabulary. Speaking and listening are the skills that are more common on an everyday basis than reading and writing. Speaking and listening skills have been known to be more difficult to master. English vocabulary presents another problem for language learners. At the university level, students study professional English, also called English for Specific Purposes (ESP). Students will need it for their future profession, so it is important for them to be able to evaluate their achievements in learning. Methodology/approach – the research paper adopts the qualitative research approach. The questionnaire on learner perceptions of computerized self-evaluation of various activities was administered to students of three different specializations. Students‘ perceptions of success or failure in their performance were analyzed. Findings . The results indicated that attitudes to computerized self-evaluation depended on the difficulty of tasks and chosen future specialization. The findings show that respondents of three investigated specializations encounter similar difficulties, but to a different degree. There are no specific problems in performance due to the complexity of the professional vocabulary that students must learn. The computations of Pearson’s correlations coefficients demonstrate that there are good correlational relationships within each specialization. The ratings of Psychology (PS) students reveal higher mean values and lower scattering of Standard Deviations in Moodle tasks than the ratings of Internet Management and Communication (IMC) students. Research limitations . The investigated samples contain the limited number of respondents, which might raise a question of the reliability of the findings. The statistical computation of the reliability of the obtained responses will prove whether the data are reliable and may be extended beyond the studied samples. The hypothesis for the research: students’ performance might depend on their specialization. Practical implications . The respondents were asked to indicate the degree of difficulty in performing various online tasks on the Likert’s scale ranging from “very difficult” to “very easy”. The analysis of the responses by a means of the Statistical Package for the Social Sciences (SPSS) software proves that despite the limited number of the respondents, the results may be extended beyond the studied samples. It means that self-evaluation of computerized activities by students studying professional English is recommended at the university level. Originality/Value . The value of this study encompasses the statistical processing of the responses, which should prove whether the findings are reliable or not. Research type : research paper.
Processes of Change and Nonsuicidal Self-Injury: A Qualitative Interview Study With Individuals at Various Stages of Change

Nonsuicidal self-injury (NSSI) is a pervasive and potentially lethal behavior that affects many youth and adolescents. Effective treatment and prevention efforts are critical but often lack a nuanced understanding of the behavior change process. To address this gap, this research employs a stage of change model to identify and understand the most salient and widespread processes that facilitate NSSI behavior change. Thirty-one semi-structured interviews were conducted with individuals with current or past self-injury. Individuals were recruited to represent all stages of change including those who have not thought about changing behavior to those who have been NSSI-free for years. We employ a directed content analysis to code for dimensions derived from the model and an inductive approach to surface more nuanced change levers. Four organizing dimensions emerged: relational, behavioral, self-knowledge, and barriers. Common change levers of value in clinical practice or in intervention modalities are discussed.
Reverse Total Shoulder Arthroplasty for Geriatric Proximal Humerus Fracture Dislocation With Concomitant Nerve Injury

Introduction: Preoperative axillary nerve palsy is a contraindication to reverse total shoulder arthroplasty (rTSA) due to the theoretical risk of higher dislocation rates and poor functional outcomes. Treatment of fracture-dislocations of the proximal humerus with rTSA is particularly challenging, as these injuries commonly present with concomitant neurologic and soft tissue injury. The aim of the current study was to determine the efficacy of rTSA for this fracture pattern in geriatric patients presenting with occult or profound neurologic injury. Methods: A retrospective case series of all shoulder arthroplasty procedures for proximal humerus fractures from February 2006 to February 2018 was performed. Inclusion criteria were patients aged greater than 65 years at the time of surgery, fracture-dislocations of the proximal humerus, and treatment with rTSA. Patients with preoperative nerve injuries were compared to patients without overt neurologic dysfunction. Forward elevation, Quick Disabilities of the Arm, Shoulder, and Hand (QuickDASH), Visual Analog Scale (VAS), and Subjective Shoulder Value (SSV) were obtained at final follow-up. Results: Forty-six rTSA for acute fracture were performed during the study period, 16 patients met the inclusion criteria and 5 (31%) presented with overt preoperative nerve injuries. At mean 3.1 years follow up, there were no postoperative complications including dislocations and final forward elevation was similar between study groups. Patients with overt nerve palsy had higher QuickDASH and VAS scores with lower SSV and self-rated satisfaction. Discussion: In the majority of patients with or without overt nerve injury, rTSA reliably restored overhead function and led to good or excellent patient-rated treatment outcomes. Overt nerve palsy did not lead to higher complication rates, including dislocation. Despite greater disability and less satisfaction, complete or partial nerve recovery can be expected in the majority of patients. Conclusion: Nerve injury following proximal humeral fracture dislocation may not be an absolute contraindication to rTSA.
Association between VDR gene FokI polymorphism and renal function in patients with IgA nephropathy

Background Studies have shown that the occurrence and development of IgA nephropathy (IgAN) are genetically susceptible, but the relationship between vitamin D receptor (VDR) gene polymorphisms and renal function in IgAN patients is unclear. Methods We investigated the relationship between VDR FokI (rs2228570) single nucleotide polymorphism (SNP) and renal function and related clinicopathologic parameters in IgAN patients. Clinical and pathological data of 282 IgAN patients treated at the First Affiliated Hospital of Guangxi Medical University were collected, and FokI genotypes were determined by PCR and direct sequencing. Patients were divided into the renal dysfunction group and normal renal function (control) group by estimated glomerular filtration rate (eGFR) and serum creatinine level. Results Frequencies of TT genotype and T allele in the renal dysfunction group were higher than those of the control group. Blood urea nitrogen, serum phosphorus (P), proportions of mesangial cell proliferation, interstitial fibrosis/tubular atrophy and crescents in T allele carriers were higher than those in non-T allele carriers, while eGFR and 25-Hydroxyvitamin D3 were lower in T allele carriers than non-T allele carriers. Multiple linear regression analysis showed that eGFR was affected by FokI genotypes in IgAN patients. Logistics regression analysis showed that middle and elderly age, elevated P, intact parathyroid hormone and TT genotype were independent risk factors for renal dysfunction in IgAN patients; the odds ratio of carrying the TT genotype was as high as 84.77 (P < 0.05 for all). Conclusions IgA nephropathy patients carrying the VDR FokI TT genotype have an increased risk of renal dysfunction. VDR FokI SNP is closely related to renal function, calcium-phosphate metabolism, and related pathological damage in IgAN patients.
Developing manufacturing ontologies for knowledge reuse in distributed manufacturing environment

The use of ontologies for knowledge sharing and distributed collaboration has been widely recognised in the knowledge modelling community, but the lack of a systematic and constructive methodology for developing manufacturing ontologies has impeded their wide usage for knowledge reuse in distributed manufacturing environments. This paper presents a constructive, two-level knowledge modelling approach to systematically develop manufacturing ontologies using both software engineering and Semantic Web paradigms. The UML/OCL (Unified Modeling Language/Object Constraint Language)-based object modelling is used first to serve as a graphical and structured basis for conceptual communication between domain experts and knowledge engineers. The OWL/SWRL (Web Ontology Language/Semantic Web Rule Language)-based ontology modelling then extends the UML/OCL-based object models with added semantics using a progressive, semantics-oriented knowledge acquisition method. An illustrative example for manufacturing ontology development in the manufacturing industry for producing electronic connectors is used to demonstrate the practicality of the proposed approach.