Miracle-dz/UniFAR-FTUs huggingface dataset:
Resource Allocation in 5G and Beyond Networks for Mu-MIMO Systems

—The resource allocation problem focuses on finding an optimal allocation of a specific number of resources to maintain Quality of Service (QoS). That is where Multiple-Input Multiple-Output (MIMO) come in as a radio antenna technology. In order to optimize data speed, minimize errors and improve the radio transmission capacity, MIMO utilizes multiple antennas at both the transmitter and the receiver. This technology uses a variety of antennas and paths that carry the data. Each antenna uses different paths. Multi-user MIMO (mu-MIMO) stands for a technology that allows routers to communicate simultaneously with multiple endpoint devices and it is the next evolutionary step of single user MIMO. Over the past decade, significant advances have been made to improve the performance of mu- MIMO. Although non-negligible progress has been achieved so far, optimal algorithms for Resource Allocation (RA) will help better the performance of mu-MIMO by increasing the system’s performance in terms of throughput, fairness, and QoS. The purpose of this paper is to provide a comparison of different beamforming techniques used for resource allocation and list them in ascending order depending on their efficiency.
Transfer Learning followed by Transformer for Automated Audio Captioning

Automated Audio Captioning (AAC) automatically creates captions that can explain the given audio sound data using machine learning techniques. Researchers investigate the solutions for AAC on DCASE 2021 audio captioning challenge. In the challenge, a model is required to generate natural language descriptions of a given audio signal. We use pre-trained models trained using AudioSet data, a large-scale dataset of manually annotated audio events. A large amount of audio events data would help capturing important audio feature representation. To use the learned feature from Au-dioSet data, we utilize CNN14 or ResNet54 network pre-trained on AudioSet, which achieved state-of-the-art audio pattern recognition performance. Our proposed sequence-to-sequence model consists of a CNN14 or ResNet54 encoder and a Transformer decoder. Experiments show that the proposed model can achieve a SPIDEr score of 0.246 and 0.285 on audio captioning performance. We further experiment the use of three different voice features, log-mel spectrogram, constant Q transform spectrogram, and gammatone ﬁlter spectrogram.
Few-Shot Table Understanding: A Benchmark Dataset and Pre-Training Baseline

Few-shot table understanding is a critical and challenging problem in real-world scenario as annotations over large amount of tables are usually costly. Pre-trained language models (PLMs), which have recently flourished on tabular data, have demonstrated their effectiveness for table understanding tasks. However, few-shot table understanding is rarely explored due to the deficiency of public table pre-training corpus and well-defined downstream benchmark tasks, especially in Chinese. In this paper, we establish a benchmark dataset, FewTUD, which consists of 5 different tasks with human annotations to systematically explore the few-shot table understanding in depth. Since there is no large number of public Chinese tables, we also collect a large-scale, multi-domain tabular corpus to facilitate future Chinese table pre-training, which includes one million tables and related natural language text with auxiliary supervised interaction signals. Finally, we present FewTPT, a novel table PLM with rich interactions over tabular data, and evaluate its performance comprehensively on the benchmark. Our dataset and model will be released to the public soon.
The Universal Anaphora Scorer

The aim of the Universal Anaphora initiative is to push forward the state of the art in anaphora and anaphora resolution by expanding the aspects of anaphoric interpretation which are or can be reliably annotated in anaphoric corpora, producing unified standards to annotate and encode these annotations, deliver datasets encoded according to these standards, and developing methods for evaluating models carrying out this type of interpretation. Such expansion of the scope of anaphora resolution requires a comparable expansion of the scope of the scorers used to evaluate this work. In this paper, we introduce an extended version of the Reference Coreference Scorer (Pradhan et al., 2014) that can be used to evaluate the extended range of anaphoric interpretation included in the current Universal Anaphora proposal. The UA scorer supports the evaluation of identity anaphora resolution and of bridging reference resolution, for which scorers already existed but not integrated in a single package. It also supports the evaluation of split antecedent anaphora and discourse deixis, for which no tools existed. The proposed approach to the evaluation of split antecedent anaphora is entirely novel; the proposed approach to the evaluation of discourse deixis leverages the encoding of discourse deixis proposed in Universal Anaphora to enable the use for discourse deixis of the same metrics already used for identity anaphora. The scorer was tested in the recent CODI-CRAC 2021 Shared Task on Anaphora Resolution in Dialogues.
Fake news detection on Twitter

Purpose Owing to the increased accessibility of internet and related technologies, more and more individuals across the globe now turn to social media for their daily dose of news rather than traditional news outlets. With the global nature of social media and hardly any checks in place on posting of content, exponential increase in spread of fake news is easy. Businesses propagate fake news to improve their economic standing and influencing consumers and demand, and individuals spread fake news for personal gains like popularity and life goals. The content of fake news is diverse in terms of topics, styles and media platforms, and fake news attempts to distort truth with diverse linguistic styles while simultaneously mocking true news. All these factors together make fake news detection an arduous task. This work tried to check the spread of disinformation on Twitter. Design/methodology/approach This study carries out fake news detection using user characteristics and tweet textual content as features. For categorizing user characteristics, this study uses the XGBoost algorithm. To classify the tweet text, this study uses various natural language processing techniques to pre-process the tweets and then apply a hybrid convolutional neural network–recurrent neural network (CNN-RNN) and state-of-the-art Bidirectional Encoder Representations from Transformers (BERT) transformer. Findings This study uses a combination of machine learning and deep learning approaches for fake news detection, namely, XGBoost, hybrid CNN-RNN and BERT. The models have also been evaluated and compared with various baseline models to show that this approach effectively tackles this problem. Originality/value This study proposes a novel framework that exploits news content and social contexts to learn useful representations for predicting fake news. This model is based on a transformer architecture, which facilitates representation learning from fake news data and helps detect fake news easily. This study also carries out an investigative study on the relative importance of content and social context features for the task of detecting false news and whether absence of one of these categories of features hampers the effectiveness of the resultant system. This investigation can go a long way in aiding further research on the subject and for fake news detection in the presence of extremely noisy or unusable data.
Admissible frequency domain response functions of dielectrics

Few empirical formulae produced to represent the complex dielectric constant in the frequency domain are discussed here from the view point of the possibility of their representation in the time domain. Because a generic function of the frequency does not necessarily admit an inverse Fourier transform, it is not always possible to obtain the corresponding time domain representation of the constant defined in the time frequency. With the use of the fractional derivatives, we introduce a tentative model of the dielectric constant including a linear term, the complex dielectric constant with its loss, and the loss of the direct current electrical conductivity. With appropriate values of the parameters, the system reproduces in the frequency domain the K. Cole and R. Cole model, without the contribution of the loss of the direct current electrical conductivity, which is studied by an autonomous constitutive equation. Copyright © 2014 John Wiley & Sons, Ltd.
Length weight relationship, condition factor and length distributions of Cynoglossus senegalensis (Kaup, 1958) off the south coast of Cameroon

Cynoglossus senegalensis (Kaup, 1958) is a valuable species in the artisanal fisheries and has been identified as overexploited in many African countries. The main aim of this study is to determine its basic biological knowledge on the exploitation status in terms of length-weight relationship (LWR), condition factor, and the depth of information on size structure in the Cameroonian coast. A total of 553 samples were collected monthly from March 2021 to February 2022 from beach seine catches along the coastal waters off the south coast of Cameroon. The collected samples were analyzed for growth patterns using Excel 2016 in PC windows 10. The results showed: (1) LWR was W=0.0042(TL) 3.0038 indicating an isometric growth pattern (R 2 =0.9844, t-Test, P>0.05, df=552); (2) a mean Fulton’s condition factor K=0.43 indicating that fishes were not in good condition; (3) a year-round presence of C. senegalensis with highest number of fishes in April and a lowest in August; (4) a trimodal size distribution with a highest length frequency class of ]8~10] and a lowest class of ]2~4]. The results suggest that: (1) the south coast of Cameroon might be a nursery and spawning areas for C. senegalensis ; (2) the fishery perimeters of the beach are concentrated mostly on juveniles and immature specimens. The findings would be useful for fishery biologists and fishery managers in future studies on the population dynamics, the stock assessment, the sustainable management and the impact of fishing gear on the C. senegalensis . Our results will contribute to filling the knowledge gap of C. seneglensis in the south coast of Cameroon.
A NOVEL MRAC ALGORTHIM FOR MAXIMUM POWER POINT TARCKING

A MRAC method for Maximum Power Point Trackingin PV system is presented. By combining the robustness of RCC and MRAC with the accuracy of fractional order, this paper proposed method can improve the tracking accuracy in the conventional MPPT. First the ripple correlation control level and then the model reference adaptive control of second level architecture can reduce the complexity of the system in the environment of photovoltaic systems. When the MPP is approached there the small oscillations are eliminate at the MPP. To improve the MPPT in this paper proposed multilevel adaptive control algorithms and mainly focused on MRAC algorithm, it also compensate underdamped characteristics of the conversion systems. MATLAB/Simulink software is used to simulate a PV power system and verify the system with the proposed algorithms with various simulation models. An enhanced MPPT algorithm, implemented on a field programmable gate array. At the end a boost DC-DC converter, carried out is to evaluate, performance of the system. The experimental simulation results are shown that this method can improve the performance simultaneously.
AiRO - an Interactive Learning Tool for Children at Risk of Dyslexia

This paper presents the AiRO learning tool, which is designed for use in classrooms and homes by children at risk of developing dyslexia. The tool is based on the client-server architecture with a graphical and auditive front end (providing the interaction with the learner) and all NLP-related components located at the back end (analysing the pupil’s input, deciding on the system’s response, preparing speech synthesis and other feedback, logging the pupil’s performance etc). AiRO software consists of independent modules for easy maintenance, e.g., upgrading the didactics or preparing AiROs for other languages. This paper also reports on our first tests ‘in vivo’ (November 2021) with 49 pupils (aged 6). The subjects completed 16 AiRO sessions over a four-week period. The subjects were pre- and post-tested on spelling and reading. The experimental group significantly out-performed the control group, suggesting that a new IT-supported teaching strategy may be within reach. A collection of AiRO resources (language materials, software, synthetic voice) are available as open source. At LREC, we shall present a demo of the AiRO learning tool.
Attitudes and Reflections of Moroccan High School Science Teachers towards the Language(s) of Instruction in Regards to the Teaching of Scientific Subjects: A Mixed Approach Study

ne of the thorniest issues regarding language in education in the majority of post-colonial countries is the issue of the language(s) of instruction. This study examines how Moroccan high school science teachers perceive the language of instruction when teaching scientific subjects. The Frame Law 51 17, which stipulates the use of foreign languages in the teaching of scientific subjects, is the point of departure. As such, the study main objective is to explore the appropriate language(s) of instruction in regards to the teaching of scientific subjects from high school science teachers’ perspective. In this study, a questionnaire was administered to 66 high school science teachers randomly chosen. The questionnaires were analyzed by SPSS. In parallel, interviews were conducted with nine science teachers which were analyzed using Braun and Clarke’s 2006 Thematic Analysis. Different results were revealed most importantly the positive attitudes that science teachers have towards English as a means of instruction, the incompatibility of language planning and policy (LPP) with the teaching/learning process needs inter alia. These results can be seen of great importance for syllabus designers, researchers in the field and teachers to understand more the nature of the issue. Accordingly, some recommendations to better the teaching/learning process regarding scientific subjects are suggested.
A Primal-Dual Heuristic for the Traveling Salesman Problem

In this thesis we provide a Linear Programming (LP) formulation and a heuristic for the symmetric Traveling Salesman Problem (TSP) on certain complete graphs having the triangle inequality. TSP models cities and their pairwise connections as vertices and edges between them in a graph. The distances are represented by cost values on edges, and the goal is to find a minimum weight tour that visits every vertex exactly once. In symmetric cases all connections are undirected both directions have the same cost. This problem is NP-Complete, so there is no polynomial time exact algorithm known for it. We present three major points in this thesis. Inspired by an LP formulation of perfect matching, we develop a relaxation for TSP, and prove that our relaxation is equivalent to the path form of the well-known Held-Karp formulation. Then, based on this relaxation we construct a heuristic, hoping it can approach a constant factor 4/3 of the optimal objective value given by the LP relaxation. At last, we adopt the matroid idea. It's already known that TSP can be modeled as minimum weight intersection of three matroids, but solving that is also NP-Complete. Vle present in this thesis the attempt to approach it using only two matroids, and analyze the difficulty.
New characterization of b-m2 developable surfaces

In this paper, b-m2 developable surfaces of biharmonic b-slant helices in the special three- dimensional − φ Ricci symmetric para-Sasakian manifold P is studied. Explicit parametric equations of b-m2 developable surfaces of biharmonic b-slant helices in the special three-dimensional − φ Ricci
Nitrogen use efficiency, yield and other characteristics of sunflower ( Helianthus annuus L.) hybrids as affected by different levels of nitrogen

To assess the nitrogen use efficiency of hybrid sunflower ( Helianthus annuus L .), an experiment was conducted at New Developmental Farm, Khyber Pakhtunkhwa, Agricultural University Peshawar-Pakistan. Randomized complete block (RCB) design with split plot arrangement, replicated four times, was used. Sunflower hybrids (Suncross, Gulshan-98, Aritar-93, and Peshawar-93) were allotted to main plots while nitrogen levels (0, 45, 90, 135, 180, and 225 kg ha -1 ) to the sub-plots. Statistical analysis of the data revealed that nitrogen had significant effects (P ≤ 0.05) on all parameters under study. Days to button formation and flowering decreased with increase in nitrogen levels. The delayed button formation (35.63) and flowering (52.06) were observed in controlled plots, while earlier button formation (31.94) and flowering (48.56) were noted when 225 kg N ha -1 was applied to the crop. Among hybrids Peshawar-93 took less days (45.29), while Gulshan-98 took more days (56.42) to flowering. Maximum plant height (87.54 cm), seed yield ha -1 (1302.75 kg) and leaf area plant -1 (9909.5 cm 2 ) was recorded in plots with highest dose of nitrogen (225 kg ha -1 ). Maximum leaf area plant -1 (8777.53 cm 2 ) has produced by Suncross. Values of nitrogen use efficiency were higher in controlled plots (342) and lower (5.83) in plots with highest dose of nitrogen (225 kg ha -1 ). Out of tested hybrids, Suncross produced maximum yield with maximum dose of nitrogen. It is therefore suggested that Suncross should be sown in Peshawar Valley by farmers with N application at the rate of 225 kg ha -1 .
Evaluation of Geo-SPEBH algorithm based on Bandwidth for Big Data retrieval in Cloud Computing

The fast increase in volume and speed of information created by mobile devices, along with the availability of web-based applications, has considerably contributed to the massive collection of data. Approximate Nearest Neighbor (ANN) is essential in big size databases for comparison search to offer the nearest neighbor of a given query in the ﬁ eld of computer vision and pattern recognition. Many hashing algorithms have been developed to improve data management and retrieval accuracy in huge databases. However, none of these algorithms took bandwidth into consideration, which is a signi ﬁ cant aspect in information retrieval and pattern recognition. As a result, our work created a Geo-SPEBH algorithm to solve this basic gap. The paper then assesses the performance of the Geo-SPEBH algorithm in terms of bandwidth in a distributed computing environment. Geo-performance SPEBH ' s was compared to existing state-of-the-art approaches using a network analyzer called Wire shark. The simulation results reveal that during retrieval, the same kb/sec of data is carried from source to destination and from destination to user. When the coding length is 8bit, the ﬁ ndings show that 0.091 kb/s of data is required to transport data from source to destination. Each algorithm with the same bit code requires the same amount of bandwidth to convey data.
Early Treatment with IL-5/IL-5R antibodies in patients with severe eosinophilic Asthma and COPD

Background: Anti-eosinophilic therapy represents an established treatment for patients with severe eosinophilic asthma (SEA) but did not show clinical efficacy in patients with chronic obstructive pulmonary disease (COPD). Objective: To evaluate treatment response to anti-eosinophilic antibody therapy in patients with Asthma and COPD. Methods: A retrospective comparison of pulmonary function testing, oral corticosteroid intake, quality of life and pulmonary symptom control in patients with SEA and COPD and 1:1 propensity score matched patients suffering from SEA alone was performed. All patients received treatment with either mepolizumab or benralizumab. Data were assessed prior to antibody treatment start and after 6 months of therapy. Results: Data from 84 patients (42 patients with SEA and COPD and 42 patients with SEA) were analysed. After 6 months of treatment, patients in both groups showed improved forced expiratory volume in one second (improvement by 11% [IQR 5; 18] in the SEA and COPD group vs. 15 % [IQR -3; 23]; p=0.637) and decreased oral corticosteroid dosages (median reduction by 3 mg in the SEA and COPD group vs. 5 mg; p=0.070), without significant differences between groups. Pulmonary symptom control and quality of life improved in both groups. A significant decrease in eosinophils could be measured in both groups with similar cell numbers prior to treatment initiation (600 cells/µl in the SEA and COPD group vs. 500 cells/µl). Conclusion : Anti-eosinophilic therapy with interleukin-5/interleukin-5-receptor antibodies shows clinical efficacy in patients with SEA and COPD comparable to treatment response in patients with SEA alone. P-values derived using t-test, if not otherwise: 2 -Test, # data from n=56 patients available, † data from n=45 patients
THE EFFECT OF SPECIAL EXERCISES IN LEARNING SOME BASIC SKILLS IN VOLLEYBALL AND SOME BIOMECHANICAL VARIABLES ACCORDING TO MAGNETIC RESONANCE MEASUREMENTS OF THE UPPER LIMBS

Objectives: Identifying the effect of special exercises in learning some basic skills in volleyball, as well as the extent of improvement by inferring them through biomechanical variables(Fleisig, 2010), in addition to identifying the differences between players in the level of skill performance based on some special measurements of muscles (the shoulder deltoid, biceps brachii, triceps brachii ) and tendons and tendon fusion points in the bon(Journal et al., 2020). Design: The study adopted the experimental method by designing the pre and post-tests. Methods: The study relied on the use of magnetic resonance imaging (MRI)(Cagnie et al., 2011) technology to identifying some measurements of the length, size and mass of the muscles under study, as well as tendons and fusion points(Ammar et al., 2018). As well as adopting recommended tests for the purpose of identifying kinetic expectation as a criterion for the stability of kinetic behavior in terms of mechanical variables(Takei et al., 2020). The two-dimensional kinematic analysis technique was also adopted using digital cameras at a speed of (120 puls / sec), and the use of the kinetic analysis program (Kenovea) to reach the results of the biomechanical variables in the specified tests(Peter M McGinnis, 2013). Results: The results showed significant differences in favor of the post-tests through the application of special educational exercises. It was found that there are indications associated with some structural standards of muscles and tendons that support the process of rapid learning and the stability of kinetic behavior(Journal et al., 2020), which can contribute to strengthening the work of athletes and coaches.
Microlensing and Variability in the Bulge of M31

For the past five seasons, the Angstrom Project, an international microlensing collaboration, has been making observations of the central bulge of M31, the Andromeda galaxy, searching for microlensing events. This thesis describes the work that has been done to develop an automatic candidate selection pipeline which enables lensing candidates to be found even if they are blended with periodic variable baseline, something which has never been attempted before in the same way. As a by-product of this process, many variable stars are found and their properties are investigated and characterised. The results of the investigations to date are presented. The final selection of microlensing candidates selected from the most recent Angstrom lightcurve data set is shown, and a separate more detailed investigation into one particularly interesting microlensing candidate of very short duration is described.