Miracle-dz/UniFAR-FTUs huggingface dataset:
Taking into account semantic similarities in correspondence analysis

Term-document matrices feed most distributional approaches to quantitative textual studies, without consideration for the semantic similarities between terms, whose presence arguably reduce the content variety. This contribution presents a formalism remedying this omission, and makes an explicit use of the semantic similarities as extracted from WordNet. A case study in similarity-reduced correspondence analysis illustrates the proposal.
SCMA Codebook Based on Optimization of Mutual Information and Shaping Gain

Sparse code multiple access (SCMA) is a promising non-orthogonal multiple access (NOMA) technique for the fifth generation (5G) and beyond wireless networks. The performance of the SCMA-based NOMA system is sensitive to the codebook design. Since there is no optimum method of codebook design, these are designed, in general, using sub-optimal methods. The high values of the mutual information and the shaping gain of the multidimensional constellation points improve the SCMA codebook's performance. Hence, in this paper, we design an SCMA codebook by optimizing the mutual information and the shaping gain of constellation points with the constraints of fixed minimum Euclidean distance and average power. Simulation results show that the SCMA system with the proposed codebook outperforms those with the existing codebooks. Further, it is observed that the message passing algorithm converges faster to successful detection with the proposed codebook.
Scheduling Variable Field-of-View Sensors for Tracking Multiple Objects

We propose the FOV of a sensor as a parameter to be controlled in real time to improve tracking performance. In contrast to earlier contributions, we take into account the measurement origin uncertainty in selecting the on-line sensor schedule. Two objects and two viewing modes are considered. The trace of the sum of approximations to the predicted covariances of the objects are used to select the mode at each instant of time; these approximations take into account the probability of target detection and the probability of false alarm. Simulations illustrate the superiority of the policy in comparison with fixed policies.
Using Adversarial Noises to Protect Privacy in Deep Learning Era

The unprecedented accuracy of deep learning methods has earned themselves as the foundation of new AI-based services on the Internet. At the same time, it presents obvious privacy issues. The deep learning aided privacy attack can dig out sensitive personal information not only from the text but also from unstructured data such as images and videos. In this paper, we proposed a framework to protect image privacy against the deep learning tools. We also propose two new metrics to measure the image privacy. Moreover, we propose two different image privacy protection schemes based on the two metrics, utilizing the adversarial example idea. The performance of our schemes is validated by simulation on a large-scale dataset. Our study shows that we can protect the image privacy by adding a small amount of noise, while the added noise has a humanly imperceptible impact on the image quality.
Attributing Authors of Emirati Tweets

Electronic text Author Attribution (AA) is a well known stylometry problem that attempts to infer the identity of authors of disputed electronic texts by solely analyzing the texts. This is important for various applications such as forensics and market analysis. However, currently the state of the art in author identification has never been evaluated against Emirati social media electronic texts. This is partly due to the fact that no evaluation dataset exists that is suitable for evaluating author identification methods in the domain of Emirati social media electronic texts. This paper presents the first of such evaluations, along with the release of the Khonji-Iraqi Emirati Tweets author identification evaluation dataset with 30 authors (KIT30). Additionally, novel definitions of grams are introduced, namely compound grams, which demonstrate that decision models that make use of them can achieve higher classification accuracies than the alternative case when classical definitions of grams are followed. The findings also indicate that, when suitable data representation is used, the degradation in the classification accuracy, as the space of suspect authors increases, is not necessarily as sharp as previously reported in the literature. This suggests that AA problem solvers can be significantly more scalable as previously evaluated.
A Comparison of Reception Methods for Visible Light Communication Using High-Speed Stereo Cameras

In-vehicle cameras can be used as receivers for visible light communication in addition to their primary functions: for viewing assistance and object recognition. Most studies with this design perform tests via a single high-speed camera that is used as the receiver, but this study employs a receiver that uses a high- speed stereo camera. The reception method developed in this paper effectively utilizes left and right stereo images to improve communication performance. Although the selective diversity reception method proposed in previous work improved communication performance, it cannot deal with cases wherein both the left and right cameras introduce errors. To further improve the communication performance of this system, maximal ratio combining (MRC) diversity is applied to the high-speed stereo camera in this study. Communication performance is then evaluated comparing to the selective diversity reception and conventional single-camera reception by experimental tests conducted under static and driving conditions.
Transferring the Full-Duplex Radio Technology from Wireless Networking to Defense and Security

Classically, the in-band full-duplex (IBFD) radio technology that has recently been revolutionizing modern wireless communications was used in the form of same-frequency simultaneous transmit and receive (SF-STAR) operation in continuous-wave radars. Thus far, the main motivation for IBFD operation in commercial wireless communication systems has been to improve their spectral efficiency. In this invited paper, we suggest that IBFD/SF-STAR radios could bring about a paradigm shift in defense applications in the form of a multifunction military full-duplex radio (MFDR) by integrating tactical communications, signals intelligence, and electronic warfare as well as investigate the prospects of transferring the concept to civilian/commercial security and privacy applications in the form of a radio shield.
Integrated ICN and CDN Slice as a Service

In this article, we leverage Network Function Virtualization(NFV) and Multi-Access Edge Computing (MEC) technologies, proposing a system which integrates ICN (Information-Centric Network) with CDN (Content Delivery Network) to provide an efficient content delivery service. The proposed system combines the dynamic CDN slicing concept with the NDN(Named Data Network) based ICN slicing concept to avoid core network congestion. A dynamic CDN slice is deployed to cache content at optimal locations depending on the nature of the content and the geographical distributions of potential viewers. Virtual cache servers, along with supporting virtual transcoders,are placed across a cloud belonging to multiple-administrativedomains, forming a CDN slice. The ICN slice is, in turn, usedfor the regional distribution of content, leveraging the amebased access and the autonomic in-network content caching.This enables the delivery of content from nearby network nodes,avoiding the duplicate transfer of content and also ensuringshorter response times. Our experiments demonstrate that integratedICN&#x002F;CDN is better than traditional CDN in almost allaspects, including service scalability, reliability, and quality ofservice.
Electrodeposition of Aluminum from AlCl3-1-Ethyl-3- Methylimidazolium Fluoride

The electrodeposition of aluminum was successfully achieved in AlCl 3 -1-ethyl-3-methylimidazolium fluoride (EmimF) at a potential of –0.3V (vs. Al/Al 3+ ) and a temperature of 90 ℃ . Cyclic voltammetry, chronopotentiometry and chronoamperometry were used to investigate the electrochemical behavior of Al 2 Cl 7- . Cyclic voltammetry and chronopotentiometry measurements indicate that the reduction of Al 2 Cl 7- to metallic Al in AlCl 3 -EmimF (molar ratio 2.7) is a one-step three-electron transfer and irreversible diffusion-controlled process. The chronoamperometry results show that the deposition of aluminum on a Pt electrode involves instantaneous three-dimension nucleation. In addition, X-ray diffraction (XRD) analysis confirmed that the deposit is pure aluminum, while scanning electron microscope (SEM) images reveal that dense and compact deposits were obtained at a more negative potential.
Game- Theoretic Modeling and Analysis of Multi-Relay Selection in Energy-Harvesting Wireless Networks

In this paper, the problem of distributed multirelay selection in energy-harvesting cooperative wireless networks is studied and modeled as an Indian Buffet Game (IBG). Particularly, the IBG is utilized to model the multi-relay selection decisions of network source nodes, while taking into account the negative network externality. Since the relays are energy-harvesting (and thus intermittently harvest random amounts of energy), the accumulated energy at each relay is unknown to the source nodes, leading to uncertain relays' energy states. In turn, a non-Bayesian learning algorithm is devised for source nodes to learn the relays' energy states. After that, a distributed best-response multi-relay selection (BR-MRS) recursive algorithm is proposed to allow source nodes to make multi-relay selections, while guaranteeing subgame perfect Nash equilibrium. Simulations results are presented to verify the efficacy of the proposed algorithm when compared to other multi-relay selection schemes, and illustrate that it yields comparable rate improvement (and utility) to the centralized multi-relay selection.
Improved Differential Fault Analysis on LED with Constraint Equations: Towards Reaching Its Limit

The block cipher LED is well suited for resource-constrained scenarios. However, it is vulnerable to the recent fault attacks and different results have been achieved even under the same fault model. In this paper, a comprehensive investigation is conducted on the fault analysis on LED. A novel differential fault analysis is proposed, which is based on the so-called constraint equations. The proposed attack can combine constraint equations at different levels, pushing the differential fault analysis on LED towards its limit in terms of the time complexity, the data complexity and the remained key search space. Under random nibble fault model, SINGLE fault injection can reduce the key search space of LED-64 to 27.90within 1.89s, compared to 217.65within 7 minutes in prior finest contributions. As to DFA on LED-128, TWO fault injections can reduce the key search space to 215.82 within 247.88s, compared to 221.96within 16 minutes in previous work. To the best of our knowledge, the scheme that we proposed is the most efficient fault attack on LED cryptosystems.
Machine Learning Prediction Based CSI Acquisition for FDD Massive MIMO Downlink

In this paper, we propose a simple and efficient approach to reduce the overhead of downlink channel estimation and feedback using linear regression (LR) and support vector regression (SVR) in machine learning. Specifically, we divide the indexes of the antennas at the base station (BS) into two sets. We first use some well estimated channel samples to train a regression model, where the channel state information (CSI) corresponding to one set is used as input while the other is output. In the online channel estimation phase, only the CSI of the antennas in one set needs to be estimated and the CSI of the antennas in the other set can be predicted by inputting the estimated CSI into the trained regression model. Numerical results show the proposed approach can reduce the overhead of both downlink pilot and uplink feedback considerably and thus can improve the downlink achievable rate significantly compared with the existing schemes.
Profit Maximization of NFV-Enabled Request Admissions in SDNs

Network Function Virtualization (NFV) and Software-Defined Networking (SDN) have been envisioned an essential milestone in the evolution of communication networks. Their integration provides a more flexible and easier manageable software-based network environment that induces high expectations for reducing capital expenditures (CAPEX) and operational costs (OPEX) of network service providers. They also introduce technical challenges. One such challenge is to manage the placement of VNFs and to steer the data traffic of each NFV-enabled request through its specified network functions. In this paper, we opportunistically adopt the flexibility and cost-efficiency of VNF and SDN for NFV-enabled request admissions in SDNs and formulate profit maximization problems for static and dynamic NFV-enabled request admissions. We first provide an integer linear programming (ILP) solution to the problem in the static version if the problem size is small; otherwise, we devise a fast approximation algorithm with a provable approximation ratio for the static request admissions. We then propose an efficient online algorithm for dynamic request admissions, by leveraging VNF instance migrations and idle VNF releases back to the system. We finally evaluate the performance of the proposed algorithms through experimental simulations. Simulation results demonstrate that the proposed algorithms are very promising.
CYP3A4 inhibition and induction studies coupled to parallel artificial membrane permeability assay (PAMPA) for improved prediction of in-vitro botanical-drug interactions

ii Acknowledgments . iv List of Figures . x List of Tables . xii List of Abbreviations . xiii Chapter 1: Introduction . 1 1.1 Botanical-drug interactions . 1 1.1.1 Use of botanical dietary supplement among U.S. cancer patients . 1 1.1.2 Concomitant botanical dietary supplements consumption with anticancer drugs . 2 1.1.3 Botanical-drug pharmacokinetic interactions . 2 1.1. 4 CYP3A4-mediated botanical-drug interaction . 3 1.2 Reasons causing the discrepancy between in-vivo and in-vitro botanical-drug interaction studies . 4 1.2. 1 Solvent selection . 4 1.2. 2 Intestinal metabolism . 5 1.2. 3 Absorption profiles . 6 1.2. 4 Liver metabolism . 7 1.3 Project rationale . 8
Mobility Improves NOMA Physical Layer Security

Physical layer security of non-orthogonal multiple access (NOMA) systems has attracted great attentions. However, the impact of mobility on physical layer security of NOMA systems has not been well studied. In this paper, to fill this gap, we investigate the impact of random mobility on physical layer security of NOMA systems. Considering scenarios where a base station (BS) or access point (AP) communicates to two random mobile users with a passive eavesdropper in two concentric circles, we study the secrecy performance with combinations of two typical random mobility models: random waypoint (RWP) and random direction (RD). A general analytical framework to numerically calculate the average secrecy rates of NOMA mobile users under steady state is provided. By comparing secrecy performance of mobile users with static users, we find that RWP mobile users can achieve higher average secrecy rates than the users with other mobility combinations. Meanwhile, two types of secrecy fairness for mobile users are fully considered and we propose a novel sum average secrecy rate maximization problem, subject to average power limits and users' QoS (quality of service) requirements. Considering eavesdropper's channel state information (CSI) is unknown to BS, we propose a threshold power allocation strategy to improve the sum average secrecy rate of NOMA mobile users. Extensive numerical simulations are conducted to validate our model and theoretical analysis.
Health Topics Mining in Online Medical Community

With the development of medical informatization, more and more patients actively obtain health information from online medical communities. The traditional methods based on statistical analysis are inefficient in dealing with growing mass of medical texts. Based on the Latent Dirichlet Allocation (LDA), we propose the Medical of Sentence LDA (MS-LDA) for short online medical texts with distribution features of medical words in online medical communities. Disease-related hot topics are assumed to be generated by sentences, the Gaussian function is employed to fit word distribution, and the correlation weight is exploited to modify word frequency for the information extension in sentences. Furthermore, Unified Medical Language System (UMLS) is introduced to cluster the topic recognition results from disease-related hot topics. Experiments on three representative disease boards from www.MedHelp. org show that the perplexity value and word relevance in topics are significantly improved by MS- LDA. Besides, hot topics concerned by members are automatically mined and texts in online medical community are automatically classified.
N-Ethyl-N-propylpyrrolidinium Bis(fluorosulfonyl)amide Ionic Liquid Electrolytes for Sodium Secondary Batteries: Effects of Na Ion Concentration

A hybrid inorganic–organic ionic liquid based on sodium bis(fluorosulfonyl)amide (Na[FSA]) and [N-ethyl-N-methylpyrrolidinium][FSA] ([C2C1pyrr][FSA]) is investigated as an electrolyte for sodium se.
Exploiting Code Diversity to Enhance Code Virtualization Protection

Code virtualization built upon virtual machine (VM)technologies is emerging as a viable method for implementing code obfuscation to protect programs against unauthorized analysis. State-of-the-art VM-based protection approaches use a fixed set of virtual instructions and bytecode interpreters across programs. This, however, exposes a security vulnerability where an experienced attacker can use knowledge extracted from other programs to quickly uncover the mapping between virtual instructions and native code for applications protected under the same scheme. In this paper, we propose a novel VM-based code obfuscation system to address this problem. The core idea of our approach is to obfuscate the mapping between the opcodes of bytecode instructions and their semantics. We achieve this by partitioning each protected code region into multiple segments where the mapping of opcodes and their semantics is randomized in different ways in different segments. In this way, each bytecode instruction will be translated into different native code in different sections of the obfuscated code. This significantly increases the diversity of the program behavior. As a result, the knowledge of bytecode to native code mappings obtained from other programs will be less useful when targeting a new program. We evaluate our approach on a set of real-world applications and compare it against two state-of-the-art VM-based code obfuscation approaches. Experimental results show that our approach is effective, which provides stronger protection with comparable runtime overhead and code size.
Doppler Effect Assisted Interference Mitigation for Wireless Communication

Doppler effect is a fundamental phenomenon that appears in wave propagation, where a moving observer experiences dilation or contraction of wavelength of a wave. It also appears in radio frequency (RF) wireless communication when there exists a relative movement between the transmitter and the receiver, and is widely considered as a major impairment for reliable wireless communication. The current paper proposes a wireless receiver that carefully exploits Doppler effect for cochannel interference mitigation. The proposed system-termed as DAIM to stand for Doppler Assisted Interference Mitigation-exploits the propagation environment and the network topology, and consists of an access point with a rotating drum antenna. The rotating drum receive antenna is designed in such a way that it shifts the interference signals away from the desired signal band. This paper includes a detailed system model and a simulation study. The results show that under favorable fading conditions, co-channel interference can be significantly reduced if not eliminated. Therefore, it is anticipated that more sophisticated wireless systems and networks can be designed by extending the basic system proposed herein.
IncastGuard: An Efficient TCP-Incast Mitigation Mechanism for Cloud Networks

TCP's internet-centric design is oblivious to the composite nature of the data center traffic, and in the presence of small switch buffers and other long-lived flows (elephants), short-lived (mice) flows often experience “Incast” congestion events that significantly affect their flow completion time (FCT). In this paper, we implement a switch- assisted Incast congestion mitigation system that takes into consideration the existence of other elastic traffic in data center networks (DCNs). The so-called IncastGuard system does not require any changes to the TCP protocol at the sender nor at the receiver and is shown to be effective in mitigating the effects of incast congestion via a prototype implementation in NetFPGA and experiments in a small-scale cluster testbed.
Towards beyond Visual Line of Sight Piloting of UAVs with Ultra Reliable Low Latency Communication

In this paper, we propose a model for beyond visual line of sight (BVLOS) operation for remote piloting of unmanned aerial vehicles (UAVs), which utilizes different technologies such as mobile edge computing and augmented reality. Ultra reliable low latency communication (URLLC) is a key service of 5G that enables safe BVLOS operation. Since message size of piloting signal is finite and communication channel is altitude dependent, we study reliability and latency under finite blocklength regime for different altitudes. In our numerical study, we find that for message sizes 30 and 50 bits, coded packet size, i.e., blocklength, should be in the range of 200 and 300 bits to enable BVLOS operation. We also found that minimum distance between UAVs to avoid any crash should be around 0.2 m for 15 m&#x002F;s UAV speed and different altitudes ranging from 1.5 m to 120 m. According to our study, BVLOS operation of UAVs can be realized by URLLC by providing error probability in the vicinity of $10^{-3}$, and latency on the order of milliseconds for downlink communication with blocklength of tens to hundred bits. &#8203;
Energy Modeling and Evaluation of NB-IoT with PSM and eDRX

Large-scale deployment and management of Internet of Things (IoT) devices will become a critical issue in the near future. The 3rd Generation Partnership Project (3GPP) has proposed NarrowBand - Internet of Things (NB-IoT) as a new radio technology standard to enable Internet connectivity for a massive number of low-throughput devices. It supports better coverage and lower energy consumption than traditional Long-Term Evolution (LTE). The NB-IoT specification adopts the Power Saving Mode (PSM) and Extended Discontinuous Reception (eDRX) mechanisms to achieve a long battery life. In this paper, we present an energy consumption model for NB-IoT devices using PSM and eDRX, with a Poisson arrival process for uplink and downlink data transmissions. The model is compared to NS-3 simulation results. We analyze NB-IoT energy consumption for different PSM timers, eDRX timers and packet Inter-Arrival Times (IATs) based on the proposed model. Additionally, we have simulated the battery life for an NB-IoT use case on tracking shared bicycles. Comparison of the analytical model and simulation results shows consistency in the results with an average error of 11.82%. Our results also showed that with a 5 Wh battery, a device lifetime of more than 12 years can be achieved when transmitting at most one packet per day, and when properly confiauring the PSM and eDRX timers.