Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Smart 3D Object Detection using LiDAR Cloud-Data Collection

Smart cities are made up of autonomous vehicle and they communicate and interact with their environment and require high precision computer vision to maintain driver and pedestrian safety. This paper presents a cost-efficient, non-intrusive and easy to use method for collecting data traffic counts using LiDAR technology. The proposed method incorporates a LiDAR sensor, a Convolutional Neural Network (CNN) and a Hybrid SVM into a single traffic counting framework. As the technology is economical and readily accessible, LiDAR is adopted. The distance data obtained are translated into the signals. Due to the difficulty of urban scenes, automatic detection of objects from remotely sensed data within urban areas is difficult. While recent advances in computer vision have shown that CNNs are very suitable for this task, the design and training of CNNs of this kind remained demanding and time consuming, given the challenge of collecting a large and well-annotated dataset and the specificity of every task. Hybrid SVM is a supervised data classification and regression machine learning tool. In the methodology the Hybrid SVM is used in detection and non-detection cases of highly complex distance data points obtained from the sensor. In order to examine the performance of the proposed method, the test is carried out in three different locations in Alexandria, Egypt. The results of tests show that the pro-imposed method achieves acceptable results in vehicle collection, which results in a precision of 85–89%. The exactness of the method proposed is determined by the colour of a vehicle’s external surface.
A Novel Unified Self-alignment Method of SINS Based on FGO

The self-alignment process can provide an accurate initial attitude of SINS. The conventional two-procedure method usually includes coarse and fine alignment processes. Coarse alignment converges fast because of its batch estimating characteristics and the initial attitude does not influence the results. But coarse alignment is low accuracy without considering the IMU’s bias. The fine alignment is more accurate by applying a recursive Bayesian filter to estimate the IMU’s bias, but the attitude converges slowly as the initial value influence the convergence speed of the recursive filter. Researchers have proposed the unified self-alignment to achieve self-alignment in one procedure, existing unified methods make improvements on the basics of recursive Bayesian filter and those methods are still slow to converge. In this paper, a unified method based on batch estimator FGO (factor graph optimization) is raised, which is converge fast like coarse alignment and accurate than the existing method. We redefine the state and rederivation the state dynamic model first. Then, the optimal attitude and the IMU’s bias are estimated simultaneously through FGO. The fast convergence and high accuracy of this method are verified by simulation and physical experiments on a rotation SINS.
A browser based system for remote evaluation of subjective quality of videos

The evaluation of the quality of videos is posing a significant problem in research on video processing, including compression. Different algorithms and their modifications aim to improve the quality of the video, while keeping the necessary bitrate as low as possible, and every time, the performance of the method must be evaluated. The bitrate can be measured readily, while for quality there are different metrics and, therefore – different results. The ultimate verdict always has to be the subjective opinion about the quality that is expressed by the viewers. For now, the only reliable way to measure the quality of the video is to perform a subjective test with a group of viewers. Subjective tests are difficult to perform – not only one has to gather all viewers in one place, but also the evaluation schemes may be difficult to follow. In the paper we present an implementation of a system that greatly simplifies the process of performing the subjective quality assessment of videos. We discuss strengths and weaknesses of the system when compared to the commonly used procedures. Finally, we also provide the results of a quality assessment for the HEVC video encoder. Presented data proves that the idea of remote quality evaluation together with the usage of the two-level grade is a valid one and provides reliable results.
Pneumococcal Resistance to Antibioticst PREVALENCE AND DISTRIBUTION OF RESISTANT PNEUMOCOCCI IMPACT OF RESISTANCE ON CLINICAL MOLECULAR EVOLUTION OF PENICILLIN RESISTANCE

INTRODUCTION . 171 HISTORICAL PERSPECTIVE . 172 Optochin Resistance. 172 Sulfonamide Resistance . 172 NOTE ON NOMENCLATURE AND CRITERIA OF RESISTANCE . 172 PREVALENCE AND DISTRIBUTION OF RESISTANT PNEUMOCOCCI . 173 Penicillin Resistance. 173 Erythromycin Resistance . 176 TMP-SMZ Resistance . 177 Tetracycline Resistance. 179 Chloramphenicol Resistance . 179 Rifampin Resistance . 179 Multiple Resistance. 179 Resistance to Other Agents. 180 FACTORS ASSOCIATED WITH CARRIAGE OF AND INFECTION WITH DRUG-RESISTANT PNEUMOCOCCI . 181 Serogroups and Serotypes . 181 High-level resistance to penicillin and multiple drug resistance.181 Intermediate resistance to penicillin . 181 Resistance to other antimicrobial agents. 181 Acquisition and Carriage of Pneumococci . 181 Age . 182 Hospitalization. 182 Community Carriage of Resistant Strains. 183 Prior Exposure to Antibiotics. 183 Immunodeficiency and Underlying Disease. 184 THERAPEUTIC CHOICES AND IMPACT OF RESISTANCE ON CLINICAL OUTCOME . 184 Pneumonia and Bacteremia . 184 Meningitis . 185 Other Infections . 185 TREATMENT OF THE CARRIER STATE AND OTHER CONTROL MEASURES . 185 MECHANISMS OF RESISTANCE . 186 Penicillin Resistance. 186 Penicillin Tolerance . 186 Resistance to Other Agents and Multiple Resistance . 187 MOLECULAR EVOLUTION OF PENICILLIN RESISTANCE.188 IDENTIFICATION OF RESISTANT PNEUMOCOCCI . 188 Optochin Resistance. 188 Disk Susceptibility Testing . 188 MICs . 189 CONCLUSIONS . 189 ACKNOWLEDGMENTS . 190 LITERATURE CITED. 190
Organization, Transcription, and Expression of the 5 (cid:57) Region of the ﬂa Operon of Treponema phagedenis and Treponema pallidum

A locus encoding polypeptides associated with ﬂagellar structure and function was identiﬁed, sequenced, and characterized in Treponema phagedenis and Treponema pallidum . This locus includes homologs of the FlgD, FlgE, MotA, MotB, FliL, and FliM polypeptides found in Salmonella typhimurium and Bacillus subtilis . These polypeptides are extensively conserved between the two treponemes. Several additional polypeptides of unknown function, including Tap1, located upstream of FlgD, and ORF4, located between FlgE and MotA, were also identiﬁed. Transcription analysis using RNA PCR indicated that these genes are likely transcribed as part of a single operon and comprise the 5 (cid:42) region of the treponemal ﬂa operon. Primer extension analysis identiﬁed a putative promoter, P ﬂa , preceding T. phagedenis tap1 in a region of divergent transcription. P ﬂa resembles the class II or class III motility-related promoters of S. typhimurium . FlgE and Tap1 were further characterized. Western blotting (immunoblotting) indicated that T. pallidum FlgE exhibited an unusual polypeptide ladder that was similar but not identical to that of T. phagedenis . Triton X-114 phase partitioning of T. phagedenis cells coupled with Western blotting revealed that Tap1 was located in the aqueous phase. Computer analysis indi- cated that Tap1 had no signiﬁcant membrane spanning regions, suggesting that it resides primarily in the cytoplasm. The organization and expression of this operon are similar in both treponemes but different from those of previously described motility-related operons. These results indicate that despite extensive amino acid sequence conservation, the expression of spirochete ﬂagellar polypeptides is different from that in other bacteria. The oligonucleotides were synthesized on the basis of conserved N- and C-terminal amino acid sequences of T. phagedenis and Salmonella typhimurium FlgE (19, 27). The ampliﬁcation reaction conditions were 93 (cid:56) C for 1 min, 45 (cid:56) C for 1 min, and 72 (cid:56) C for 1 min for a total of 30 cycles. The 615-bp DNA product was washed with a Centricon-100 unit (Amicon, Danvers, Mass.) and then digested with Bam HI and Sal I. The digested DNA was puriﬁed by using the Qiaex DNA puriﬁcation resin (Qiagen Corp., Chatsworth, Calif.) and then li- gated to M13mp18 DNA. DNA sequencing of appropriate recombinant clones revealed the sequence of a segment of T. pallidum ﬂgE . A T. pallidum library of genomic DNA in Lambda ZAP Express was screened with this and other probes by using a plaque hybridization assay Additional ﬂanking DNA sequence was obtained by using similar methods and probes speciﬁc for the 5 (cid:57) and 3 (cid:57) ends of known DNA sequence. DNA segments puriﬁed bacteriophages the genomic library subcloned various -mp19,
Normality and shared-value of derivatives

We show that a family F of functions holomorphic in a domain is normal, if for all ƒ ∈ F the derivative ƒ′ and ƒ share the value a(≠0) and if the set of values that ƒ (k+1) takes the zeros of ƒ−a, is bounded. As an application we obtain some new uniqueness theorems of entire functions which improve the former results [Amer. H.H. Al-khaladi (2000). On a question of Yi-Yang. J. Shandong Univ., 35(3), 162–167; G. Jank, E. Mues and L. Volkmann (1986). Meromorphic functionen die mit ihrer ersten und zweiten Ableitung einen endlichen wert teilen. Complex Variables, 6, 51–71; P. Li and C.C. Yang (2001). Uniqueness theorem on entire functions and their derivatives. J. Math. Anal. Appl. , 253, 50–57; W. Lin (2001). Uniqueness theorem and normal criteria with sharing array. Math. Theory Appl. , 21, 9–16 (Chinese); H.X. Yi and C.C. Yang (1995). Uniqueness Theory of Meromorphic Functions, Pure and Applied Math. Monographs No. 32. Science Press, Beiling; H. Zhong (1995). Entire functions that share one values with their derivatives. Kodai Math. J., 18, 250–259, etc].
Sensorless FPPT Tracking Mechanism based on Forecasting Data

The intermittent nature of solar energy with low panel efficiency propel the user to utilize the available solar energy in most efficient way. The Maximum Power Point Tracking (MPPT) enables utmost utilisation of solar power. However, high PV penetration results in several issues such as reverse power flow, overvoltage, frequency fluctuations etc. These problems may be avoided by choosing Flexible Power Point Tracking (FPPT). The operating voltage for MPPT is almost constant. Therefore, once the operating voltage is established, it is maintained at that value irrespective of the level of irradiation. Therefore, costly sensors are not required for implementing the MPPT algorithm. But with FPPT, this is not the case. The operating point varies with the level of irradiation. The knowledge of irradiation from web-based sources enables the user to determine the operating voltage as per the power limit set by the system operator. This paper formulated an algorithm to determine the operating voltage according to the level of irradiation. As the irradiation data is readily made available to the computer, the operating voltage can be predetermined. A simulation is done for a PV system and its operating voltage is calculated to meet the power limit requirements.
Network intrusion detection system using an optimized machine learning algorithm

The rapid growth of the data-communications network for real-world commercial applications requires security and robustness. Network intrusion is one of the most prominent network attacks. Moreover, the variants of network intrusion have also been extensively reported in the literature. Network Intrusion Detection Systems (NIDS) have already been devised and proposed in the literature to handle this issue. In the recent literature, Kitsune, NIDS, and its dataset have received approx. 500 citations so far in 2019. But, still, the comprehensive parametric evaluation of this dataset using a machine learning algorithm was missing in the literature that could submit the best algorithm for network intrusion attack detection and classification in Kitsune. In this connection, two previous studies were reported to investigate the best machine algorithm (these two studies were reported by us). Through these studies, it was concluded that the Tree algorithm and its variants are best suited to detect and classify all eight types of network attacks available in the Kitsune dataset. In this study, the hyper-parameter optimization of the optimized Tree algorithm is presented for all eight types of network attack. In this study, the optimizer functions Bayesian, Grid Search, and Random Search were chosen. The performance has been ranked based on training and testing accuracy, training and testing cost, and prediction speed for each optimizer. This study will submit the best point hyper-parameter for the respective epoch against each optimizer.
Use of Lagrange Expansion for Generating Discrete Generalized Probability Distributions

Considering $g( t )$ and $f( t )$ as two probability generating functions defined on nonnegative integers such that $g( 0 ) \ne 0$, we use Lagrange’s expansion, together with the transformation $t = u \cdot g( t )$, to define families of discrete generalized probability distributions by the name of Lagrange distributions as \[ \begin{gathered} \Pr \,[ {X = 0} ] = L( {g;f;0} ) = f( 0 ), \hfill \\ \Pr \,[ {X = x} ] = L( {g;f;x} ) = \frac{1}{{x! }}\frac{{d^{x - 1} }}{{dt^{x - 1} }}\{ {( {g( t )} )^x \cdot f'( t )} \}|_{t = 0} \hfill \\ \end{gathered} \]for $x = 1,2,3, \cdots $, where the different families are generated by assigning different values to $g( t )$ and $f( t )$. General formulas for writing down the central moments of Lagrange distributions are obtained and it is shown that they satisfy the convolution property. The double binomial family of Lagrange distributions is studied in greater detail as it gives a large number of discrete distributions, including Borel-Tanner distribution, Haight’s distr.
Concept of two-dimensional swing curves for critical dimension prediction and optimization of resist/antireflective coating bilayers in topographic situations

In microlithography, the necessity of using bottom antireflective coatings (BARCs) to reduce linewidth variations resulting from reflective notching and thin film interference effects has been largely demonstrated. We report a new methodology, based on a 2-D swing curve concept, to predict the lithographic performance of resist/BARC bilayers in a topographic situation to optimize the critical dimension (CD) range. Due to inherent planarization effects when coating on topography, both the resist and organic BARC thicknesses vary, as do the final reflectivity and CDs. As a consequence, it is not easy to determine the optimal BARC thicknesses and to predict the lithographic performance, taking into account topography effects over the whole chip. Usually, lithographic performance (CD swing curves) is measured or calculated using modeling over plane wafers. Over the topography of a real chip, however, the resist thickness can cover up to four periods of the swing curve, which means that lithographic performance over a real chip cannot be predicted using swing curves calculated or measured on plane wafers. We therefore propose a new method of representing the reflectivity and CD swing curves in two dimensions to evaluate the lithographic performance of the BARC/resist bilayer. A simulation algorithm is performed that enables the determination of both the optimal BARC thicknesses and the lithographic performance window over the whole chip. Practical examples are given demonstrating the role of such a simulation.
Evaluation of Physicochemical Properties of a Hydroxyapatite Polymer Nanocomposite for Use in Fused Filament Fabrication

Over the last decade, there has been an increasing interest in the use of bioceramics for biomedical purposes. Bioceramics, specifically those made of calcium phosphate, are commonly used in dental and orthopaedic applications. In this context, hydroxyapatite (HA) is considered a viable option for hard tissue engineering applications given its compositional similarity to bioapatite. However, owing to their poor mechanobiology and biodegradability, traditional HA-based composites have limited utilisation possibilities in bone, cartilage and dental applications. Therefore, the efficiency of nano HA (nHA) has been explored to address these limitations. nHA has shown excellent remineralising effects on initial enamel lesions and is widely used as an additive for improving existing dental materials. Furthermore, three-dimensional printing (3DP) or fused deposition modelling that can be used for creating dental and hard tissue scaffolds tailored to each patient’s specific anatomy has attracted considerable interest. However, the materials used for producing hard tissue with 3DP are still limited. Therefore, the current study aimed to develop a hybrid polymer nanocomposite composed of nHA, nanoclay (NC) and polylactic acid (PLA) that was suitable for 3DP. The nHA polymer nanocomposites were extruded into filaments and their physiochemical properties were evaluated. The results showed that the addition of nHA and NC to the PLA matrix significantly increased the water absorption and contact angle. In addition, the hardness increased from 1.04 to 1.25 times with the incorporation of nHA. In sum, the nHA-NC-reinforced PLA could be used as 3DP filaments to generate bone and dental scaffolds, and further studies are needed on the biocompatibility of this material.
Explainable AI for Intrusion Detection Systems: LIME and SHAP Applicability on Multi-Layer Perceptron

Machine learning-based systems have presented increasing learning performance, in a wide variety of tasks. However, the problem with some state-of-the-art models is their lack of transparency, trustworthiness, and explainability. To address this problem, eXplainable Artificial Intelligence (XAI) appeared. It is a research field that aims to make black-box models more understandable to humans. The research on this topic has increased in recent years, and many methods, such as LIME (Local Interpretable Model-Agnostic Explanations) and SHAP (SHapley Additive exPlanations) have been proposed. Machine learning-based Intrusion Detection Systems (IDS) are one of the many application domains of XAI. However, most of the works about model interpretation focus on other fields, like computer vision, natural language processing, biology, healthcare, etc. This poses a challenge for cybersecurity professionals tasked with analyzing IDS results, thereby impeding their capacity to make informed decisions. In an attempt to address this problem, we have selected two XAI methods, LIME, and SHAP. Using the methods, we have retrieved explanations for the results of a black-box model, part of an IDS solution that performs intrusion detection on IoT devices, increasing its interpretability. In order to validate the explanations, we carried out a perturbation analysis where we tried to obtain a different classification based on the features present in the explanations. With the explanations and the perturbation analysis we were able to draw conclusions about the negative impact of particular features on the model results when present in the input data, making it easier for cybersecurity experts when analyzing the model results and it serves as an aid to the continuous improvement the model. The perturbations also serve as a comparison of performance between LIME and SHAP. To evaluate the degree of interpretability increase, and the explanations provided by each XAI method of the model and directly compare the XAI methods, we have performed a survey analysis.
An Algorithm for Localization in Vehicular Ad-Hoc Networks

Positioning a node in Vehicular Ad-Hoc networks is one of the most interested research areas in recent years. In many Ad-Hoc networks such as Vehicular Ad-Hoc networks in which the nodes are considered as vehicles, move very fast in streets and highways. So, to have a safe and fast transport system, any vehicle should know where a traffic problem such as a broken vehicle occurs. GPS is one of the equipments which have been widely used for positioning service. Problem statement: Vehicle can use a GPS receiver to determine its position. But, all vehicles have not been equipped with GPS or they cannot receive GPS signals in some places such as inside of a tunnel. In these situations, the vehicle should use a GPS free method to find its location. Approach: In this study, a new method based on transmission range had been suggested. Results: This algorithm had been compared with a similar algorithm ODAM in same situations. The best performance for Optimized Disseminating Alarm Message (ODAM) is when 40% of nodes are equipped with GPS. Conclusion: We executed our algorithm on this situation and compared it with ODAM results. At the end of this study, we can see our algorithm in compare to ODAM has better results.
Angiogenesis Inhibition by Antioxidants

Reducing cancer morbidity and mortality requires several synergic approaches target on tumoural cells and their environment. Angiogenesis is the development of new blood vessels from the pre-existing vasculature. This process is normally observed only transiently during embryogenesis, and in adulthood, during wound healing and uterus function. However, pathologic angiogenesis is involved in some diseases, including cancer. Tumoural angiogenesis favors cancer invasion and metastasis emission. Normally, endothelial cells are maintained in a latent state, but under determined stimulus they suffer activation, a process called “angiogenic switch”. Among stimulatory angiogenic factors are vascular endothelial growth factor (VEGF), angiopoetin-1 and 2, interleukin-8 (IL-8), fibroblast growth factor basic (bFGF), platelet-derived growth factor (PDGF) and angiotensin II. Furthermore, matrix metalloproteinases (MMPs), especially MMP-2 and MMP-9, play role in angiogenesis. Reactive oxygen species (ROS), as hydrogen peroxide (H2O2), participates in angiogenesis signaling through VEGF receptors, mainly VEGFR2 (Flk-1/KDR), and angiopoietin-I/Tie-2 receptors. The major source of ROS in endothelial cells is the enzyme NAD(P)H oxidase, but the role of nitric oxide (NO•), from endothelial nitric oxide synthase (eNOS), should not be neglected. Moreover, oxidized phospholipids and products from arachidonic acid metabolism can participate in angiogenesis induction. Then, it would be likely that antioxidants could inhibit angiogenesis. Really, a number of studies demonstrated that several antioxidants found in natural products (catechins from teas, resveratrol, polyphenols, flavonoids, isoflavones, lycopene, pigment epithelium-derived factor, glutathione); nutritional components (vitamins C, D, E, β-carotene and selenium); and semi-synthetic and synthetic compounds (N-acetylcysteine, L-NAME, L-NIO, sodium piruvate, pyrrolidine dithiocarbamate, and organoselenium compounds) were able to inhibit angiogenesis. These compounds were tested in several in vitro assays and in vivo animal models and inhibited angiogenesis via redox-sensitive and insensitive mechanisms. Thus, the consumption of antioxidants from natural sources can be recommended in face to benefic effects related to angiogenesis inhibition, while high fat diet can be undesired. In addition, some semi-synthetic and synthetic compounds has potential as future drugs for inhibiting tumoural angiogenesis, but it needs more detailed studies in terms of efficacy and security.