Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy Efficient Beamforming Design for Non-Orthogonal Multiple Access Systems: A Curiosity-Driven Approach

In this work, beamforming design and resource allocation for overload non-orthogonal multiple access (NOMA) systems is investigated. Based on this, a pure-NOMA framework is proposed to benefit from the non-orthogonal resources. In addition, an energy efficiency (EE) maximizing problem is formulated by jointly designing the beamforming, user grouping, as well as power allocation of users. Reinforcement learning (RL) has been shown to be very effective in tackling this kind of joint optimization in wireless communication networks. However, the high dimensionality and coupling non-convex mixed integer nonlinear programming (MINLP) problem makes conventional RL methods hard to get an ideal reward in practice. Given this challenge, a curiosity-driven solution is proposed to meet the MINLP challenge. Numerical results indicate that: 1) the pure-NOMA framework provides extra room for DoF and capacity improvement, which results in 31.58% and 25% reward gain of DRL-based method and curiosity-driven method; 2) The curiosity-driven approach enabled 14.78% and 13.33% reward gain compared with the DRL-based method in hybrid-NOMA and pure-NOMA schemes separately; 3) Simulations in scenarios with various quality of service (QoS) requirements demonstrated the maximum gain at 82.98% time with extra time cost less than 5%.
Effect of free fatty acids on blood amino acid levels in human.

Raised plasma free fatty acid (FFA) levels effectively impede glucose uptake in vivo, thereby conserving plasma glucose and sparing glycogen. To test whether FFA have any effect on blood amino acid levels, we infused Intralipid plus heparin or saline into healthy volunteers under four different experimental conditions: A) overnight fast; B) euglycemic hyperinsulinemia (approximately 100 microU/ml); C) hyperglycemic (approximately 200 mg/100 ml) hyperinsulinemia (approximately 50 microU/ml); and D) hyperglycemic (approximately 300 mg/100 ml) normoinsulinemia (approximately 20 microU/ml). In the fasting state (A), lipid infusion was associated with lower blood levels of most amino acids, both branched chain and glucogenic. This effect, however, could not be ascribed to lipid infusion alone, because plasma insulin levels were also stimulated. The clamp studies (B, C, and D) allowed to assess the influence of lipid on blood amino acid levels at similar plasma insulin and glucose levels. It was thus observed that lipid infusion has a significant hypoaminoacidemic effect of its own under both euglycemic (B) and hyperglycemic (C) conditions; this effect involved many glucogenic amino acids (alanine, glycine, phenylalanine, serine, threonine, and cystine) but none of the branched-chain amino acids (leucine, isoleucine, and valine). In marked contrast, normoinsulinemic hyperglycemia (D), with or without lipid infusion, caused no change in the blood level of any measured amino acid. We conclude that lipid infusion has a hypoaminoacidemic action. We also suggest that this action is permitted by insulin and may involve specific metabolic interactions (e.g., reduced availability of glucose-derived pyruvate or glycerophosphate) as well as enhanced uptake by the liver.
J oint Optimization of Digital Beamforming and RF Interference Cancellation for SBFD

Subband non-overlapping full duplex (SBFD) re-cently has been proposed to enhance uplink coverage and reduce latency of conventional time division duplex (TDD) systems by allocating frequency non-overlapping uplink (UL) and downlink (DL) subbands within a TDD band. However, if sufficient interference cancellation (IC) is not provided in the spatial and radio frequency (RF) domain, the self-interference (SI) signal from the DL subband will block the UL receiver. In this paper, we propose a two-stage joint optimization of beamforming and RF IC in SBFD systems, specifically tailored for base station deployment. In the first stage, the RF SI canceller is designed based on the SI channel. Two feasible realizations of the RF SI canceller are provided to reduce the number of taps connecting the Tx and Rx RF chains. In the second stage, the baseband precoding is optimized based on the equivalent residual SI channel and the user channel. Simulation results show that the proposed algorithm can support up to 4 layers of precoding with a maximum rate loss of 20.11% in the DL and up to 5 layers of precoding with a rate loss of less than 10% in the UL.
Hot Spot Area Identification of Online Car-Hailing Based on RNN-DBSCAN

The identification of hot spot areas of online car hailing can provide support for improving the operational efficiency of online car hailing. Taking the order data of Didi Express in Chengdu as samples, the reverse nearest neighbor clustering algorithm (RNN-DBSCAN) process, including travel order data processing, location coordinate transformation, and travel hotspot identification, is designed. Based on the sample data, the empirical analysis of the locations of hot spots and centers of online ride-hailing trips at different times of working days and weekends within the research scope is given. The results show that the improved algorithm overcomes the shortcomings of the traditional DBSCAN algorithm, which has arbitrary parameter Settings and cannot distinguish large density variable clusters, and provides a feasible scheme for data-driven ride-hailing travel characteristics analysis.
Quadcopter Design and Development for Precision Agriculture Implementation in a Rice Field

The advantage of quadcopters in remote sensing is obtaining data more efficiently and affordable than conventional airplanes or satellites. However, there are still several challenges, including flight time, data accuracy, and payload capacity. In a case study involving a quadcopter designed for capturing images and geotagging data in a rice field, with an 800mm frame diagonal, 2.6:1 thrust-to-weight ratio, and inwardly tilted propellers at a 5-degree angle was built. The autopilot system utilizes a Pixhawk 6C controller and a 22.2V 13000mAH battery. Equipped with an Orange-Cyan-NearInfrared camera, the images were captured and then processed using the Agisoft Metashape and QGIS applications. With the quadcopter weight of 4,492 grams, achieved a flight time of 18.30 minutes and the navigation deviation ranges from 0.06 to 0.4 meters. Although the quadcopter's vegetation index allows for the classification of plants and inanimate objects, it is not sufficient for assessing the plants' health. On the other hand, the resulting geolocation data is fairly accurate, with an estimated total error of 0.73 meters in longitude, 0.79 meters in latitude, and 1.28 meters in altitude. However, the ground-level elevation has a root mean square error of 18.99 meters, indicating poor accuracy in this aspect.
Real Time Facial Expression Recognition on Raspberry Pi Using DeepFace Framework

Facial expression is a common type of non-verbal communication. It is one of the main components while interacting with others, enabling individuals to deduce the thoughts and feelings of their speakers. Facial expression play an important role in understanding a person's emotions, intentions, personality and psychology can be identified [1]. Emotion has an important role in influencing the performance of one's activities so it is important to learn about. For example, with happy emotions, performance in carrying out activities will tend to be better than sad emotions.
Optimizing the Performance of LoRaWAN Range Extenders in Sparse and Unconventional Contexts

This paper presents a comprehensive analysis of methods to enhance the performance of a LoRaWAN Range Extender (RE) in areas with scarce cellular coverage, including unconventional environments such as underground caves. We propose innovative techniques to fine-tune the RE's functionality, with a focus on their real-world implications for future Internet of Things (IoT) communications. Our exploration delves into two operational modes of the RE, shedding light on their potential to fortify security, increase energy efficiency, and optimize spectrum usage. We also present findings from our rigorous experiments on the RE, demonstrating that by decoding received frames, the RE can formulate new parameter values, thereby improving network efficiency. The aim of this paper is to provide valuable insights on effectively employing the LoRaWanarchitecture in isolated or sparsely populated regions, as well as unconventional locations like underground caves. It underscores the potential of these advancements to transform IoT communications, enabling IoT deployments in environments previously considered challenging, thus expanding the realm of IoT applications.
Explaining Unwanted Behaviours in Context

Mobile malware has been increasingly identified based on unwanted behaviours like sending premium SMS messages. However, unwanted behaviours for a group of apps can be normal for another, i.e., they are contextsensitive. We develop an approach to automatically explain unwanted behaviours in context and evaluate the automatic explanations via a user-study with favourable results. These explanations not only state whether an app is malware but also elaborate how and in what kind of context a decision was made.
Artificial Intelligence and Sentiment Analysis in YouTube Comments: A Comprehensive Overview

The rapidly evolving landscape of sentiment analysis applied to Y ouTube comments presents a dynamic and challenging domain. Analyzing these comments encompasses the daunting task of handling vast volumes of diverse content on a dynamic platform. Recent advancements, such as deep learning models and advanced natural language processing techniques, have significantly enhanced sentiment analysis accuracy. Nevertheless, persistent challenges involve effectively addressing multilingual comments, context awareness, and capturing nuanced sentiment expression. Here, the primary research objective is to establish a comprehensive overview of state-of-the-art techniques and methodologies. Critically assessing existing challenges in data preprocessing, model development, and result interpretation provides valuable insights for future research endeavors. This effort aims to guide the development of more robust solutions for sentiment analysis within the intricate context of Y ouTube comments.
Improving the CNN Model for Arabic Crime Tweet Detection Based on an Intelligent Dictionary

Rising crime rates in Iraq and the Arab World pose significant challenges for law enforcement, exacerbated by vast data on criminal activity, technological advances, and high population density. This research aims to extract credible information from this data to understand crime better and assist in future prevention efforts. One challenge is the complexity of the Arabic language in crime detection. The study introduces an innovative approach using deep learning techniques, including creating an intelligent dictionary for detecting crime-related content in Arabic tweets. This method employs the Aho-Corasick algorithm to address the dynamic nature of language and evolving criminal terminology. The methodology applies deep learning and machine learning techniques, emphasizing natural language processing (NLP) for preprocessing and extracting relevant tweet characteristics. Created a labeled tweet dataset and classified it into various crime-related categories. Deep learning models, such as an improved CNN model based on chi-square testing and Grid search, were trained and evaluated using precision, recall, F1-score, accuracy, and MAP accuracy metrics. The analysis of an Arabic tweet dataset, comprising 18,493 tweets with ten features, demonstrated that the improved CNN model achieved a high accuracy of 99.25% and a macro F1-score of 99.9%. These results indicate that the proposed deep learning model outperforms others regarding accuracy.
Effect of Temperature on Mortality and Behavioural Responses in Freshwater Catfish , Heteropneustes fossilis ( Bloch ) Exposed to Dimethoate

Temperature has significant influence on physio-chemical responses of all living organisms including fish. The present study was conducted to evaluate the effect of temperature on dimethoate toxicity (96 h static bioassay) to freshwater catfish Heteropneustes fossilis. Fish mortality data were recorded at 24, 48, 72 and 96 h and analysed using EPA Probit analysis, Version 1.5, software based on Finney's Probit Analysis method to calculate LC values. The 96 h LC values at temperatures, 17.16±0.78°C (January) and 27.50±1.50°C 50 50 (August) were found to be 14.39 mg l and 2.98 mg l respectively. Alterations in behavioural responses, 1 1 especially the schooling, surfacing, mucus secretion, skin colour, eyelid condition and opercular movement were also studied. The increase in fish mortality at higher temperature indicated in the present study may be helpful to determine season specific toxicant concentration for field applications to avoid adverse effect on non target organisms.
Aqueous garlic extract attenuates hepatitis and oxidative stress induced by galactosamine/lipoploysaccharide in rats

Injection of D‐galactosamine and lipopolysaccharide (DGaIN/LPS) is useful as an experimental model of acute hepatic damage. Juvenile rats were used for investigation. The hepatoprotective activity of aqueous garlic (Allium sativum) extract (AGE) at a dose of 300 mg/kg body weight for 14 days, intraperitoneal (i.p.) prior to the induction of DGalN/LPS, was investigated against DGalN/LPS‐induced hepatitis in rats. DGalN/LPS (300 mg/kg body weight/30 µg/kg body weight, i.p.), induced hepatic damage that was manifested by a significant increase in the activities of marker enzymes [alanine transaminase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), lactate dehydrogenase (LDH) and gamma glutamyl transferase (γGT)], bilirubin, lipid peroxides (LPO), tumor necrosis factor (TNF‐α) and myeloperoxidase (MPO) activity level in serum. Also, the lipid profile in serum and liver homogenate including total cholesterol, triglycerides, free fatty acids and phospholipids were significantly deteriorated. The antioxidant enzyme activities (superoxide dismutase, SOD; reduced glutathione, GSH; catalase, CAT and glutathione peroxidase, GPX) in liver homogenate were significantly decreased in the DGalN/LPS. Pretreatment of rats with AGE reversed these altered parameters near to normal control values. Results of this study revealed that AGE could afford a significant protection in the alleviation of DGalN/LPS‐induced hepatic damage. Copyright © 2008 John Wiley & Sons, Ltd.
Tissue factor deficiency increases alveolar hemorrhage and death in influenza A virus‐infected mice

Essentials H1N1 Influenza A virus (IAV) infection is a hemostatic challenge for the lung. Tissue factor (TF) on lung epithelial cells maintains lung hemostasis after IAV infection. Reduced TF‐dependent activation of coagulation leads to alveolar hemorrhage. Anticoagulation might increase the risk for hemorrhages into the lung during severe IAV infection.
A Novel Backprojection Algorithm Based on Aperture Compression for SAR Imaging

Synthetic aperture radar (SAR) is an important remote sensing technique and SAR imaging is one of the core steps in SAR data processing. In order to improve the SAR imaging efficiency, a novel backprojection (BP) algorithm based on aperture compression is proposed. The aperture is first compressed based on a well-designed filter in azimuth dimension. Then, the coherent integration operation is employed to accumulate the signal along new aperture. Finally, both simulation and spaceborne SAR data experiments are performed to verify the effectiveness of the proposed BP algorithm.
metaTED: a Corpus of Metadiscourse for Spoken Language

This paper describes metaTED ― a freely available corpus of metadiscursive acts in spoken language collected via crowdsourcing. Metadiscursive acts were annotated on a set of 180 randomly chosen TED talks in English, spanning over different speakers and topics. The taxonomy used for annotation is composed of 16 categories, adapted from Adel(2010). This adaptation takes into account both the material to annotate and the setting in which the annotation task is performed. The crowdsourcing setup is described, including considerations regarding training and quality control. The collected data is evaluated in terms of quantity of occurrences, inter-annotator agreement, and annotation related measures (such as average time on task and self-reported confidence). Results show different levels of agreement among metadiscourse acts (α ∈ [0.15; 0.49]). To further assess the collected material, a subset of the annotations was submitted to expert appreciation, who validated which of the marked occurrences truly correspond to instances of the metadiscursive act at hand. Similarly to what happened with the crowd, experts revealed different levels of agreement between categories (α ∈ [0.18; 0.72]). The paper concludes with a discussion on the applicability of metaTED with respect to each of the 16 categories of metadiscourse.
A cost efficient scheduling strategy to guarantee probabilistic workflow deadlines

Today, workflows are widely used to model business processes. A recent trend is to use them to model applications in heterogeneous, large-scale distributed systems. In such systems, many, possibly mobile, providers offer independent and interchangeable services that can be used to satisfy the different activities of a workflow. Due to varying server loads, failures, and changing network characteristics, the response time of these services is highly volatile. Thus, it is hard to ensure the timely and reliable execution of workflows depending on such services. A common approach is to invoke several services in parallel to increase the probability of success. This, however, can easily lead to overprovisioning and high cost when needlessly invoked services have to be compensated. In this paper, we investigate the search space between parallel and sequential invocation of services. We propose to invoke independent services staggered over time to ensure timely workflow execution at minimal cost. Evaluations show that our approach reduces the execution cost by up to 85% while it guarantees to fulfill activity deadlines with 99.9 % probability.
Riffle

Abstract Existing anonymity systems sacrifice anonymity for efficient communication or vice-versa. Onion-routing achieves low latency, high bandwidth, and scalable anonymous communication, but is susceptible to traffic analysis attacks. Designs based on DC-Nets, on the other hand, protect the users against traffic analysis attacks, but sacrifice bandwidth. Verifiable mixnets maintain strong anonymity with low bandwidth overhead, but suffer from high computation overhead instead. In this paper, we present Riffle, a bandwidth and computation efficient communication system with strong anonymity. Riffle consists of a small set of anonymity servers and a large number of users, and guarantees anonymity among all honest clients as long as there exists at least one honest server. Riffle uses a new hybrid verifiable shuffle technique and private information retrieval for bandwidth- and computation-efficient anonymous communication. Our evaluation of Riffle in file sharing and microblogging applications shows that Riffle can achieve a bandwidth of over 100KB/s per user in an anonymity set of 200 users in the case of file sharing, and handle over 100,000 users with less than 10 second latency in the case of microblogging.
Software testing fundamentals - methods and metrics

A highly anticipated book from a world-class authority who has trained on every continent and taught on many corporate campuses, from GTE to Microsoft First book publication of the two critically acclaimed and widely used testing methodologies developed by the author, known as MITs and S-curves, and more methods and metrics not previously available to the public Presents practical, hands-on testing skills that can be used everyday in real-life development tasks Includes three in-depth case studies that demonstrate how the tests are used Companion Web site includes sample worksheets, support materials, a discussion group for readers, and links to other resources
A comparison of the hydrochloride salts of lignocaine and prilocaine for epidural analgesia.

Lumbar epidural blockade has been used in 317 subjects to compare the analgesic properties of the hydrochloride salts of lignocaine and prilocaine in 2 per cent and 3 per cent concentrations, with and without 1/200,000 adrenaline. Prilocaine has a slower onset and spread of analgesia than lignocaine. Duration of action and intensity of motor blockade is greater with plain prilocaine than with plain lignocaine in both 2 and 3 per cent concentrations. Addition of a vasoconstrictor improves the duration and quality of blockade of both prilocaine and lignocaine, but the effect on the latter is greater than on the former. The proportionate effect is such that the intensity of motor block and duration become practically the same in the 2 and 3 per cent solutions of both drugs when 1/200,000 adrenaline is present. At any given age all the test solutions, except 3 per cent plain prilocaine, produce the same degree of segmental spread. The dose-requirements of 3 per cent plain prilocaine are about 40 per cent greater than the other solutions at 20 years, but this difference decreases with age, and disappears by the ninth decade. Three per cent lignocaine with adrenaline produces the most efficient blockade of all the test solutions. However, the lower toxicity of prilocaine makes 3 per cent prilocaine with adrenaline the solution of choice in most instances.
On obfuscating point functions

We investigate the possibility of obfuscating point functions in the framework of Barak et al. from Crypto '01. A point function is a Boolean function that assumes the value 1 at exactly one point. Our main results are as follows:We provide a simple construction of efficient obfuscators for point functions for a slightly relaxed notion of obfuscation, for which obfuscating general circuits is nonetheless impossible. Our construction relies on the existence of a very strong one-way permutation, and yields the first non-trivial obfuscator under general assumptions in the standard model. We also obtain obfuscators for point functions with multi-bit output and for prefix matching.Our assumption is that there is a one-way permutation wherein any polynomial-sized circuit inverts the permutation on at most a polynomial number of inputs. We show that a similar assumption is in fact necessary, and that our assumption holds relative to a random permutation oracle.Finally, we establish two impossibility results which indicate that the limitations on our construction, namely simulating only adversaries with single-bit output and using nonuniform advice in our simulator, are in some sense inherent.Previous work gave negative results for the general class of circuits (Barak et al., Crypto '01) and positive results in the random oracle model (Lynn et al., Eurocrypt '04) or under non-standard number-theoretic assumptions (Canetti, Crypto '97). This work represents the first effort to bridge the gap between the two for a natural class of functionalities.