Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Data Augmentation Technique and Deep Learning Model for Web Application Security

Web applications are often exposed to attacks because of the critical information and valuable assets they host. In this study, Bi-LSTM based web application security models were developed in order to detect web attacks and classify them into binary or multiple classes using HTTP requests. A novel data augmentation technique based on the self-adapting noise adding method (DA-SANA) was developed. The DA-SANA method solves the low sensitivity problem caused by imbalanced data and the complex structure of multi-class classification in web attack detection. Experimental evaluations are carried out in detail using two benchmark web security datasets and a newly created dataset within the scope of the study. The achieved worst case detection rates are 98.34% and 93.91% for binary-class and multi-class classifications, respectively. The proposed DA-SANA technique provides an average of 6.52% improvement in multi-class classification for two datasets. These results revealed that the best classification performance values were achieved when compared with previous studies.
A novel N79 filter using solid-mounted A1-mode resonator for 5G applications

In this paper, the authors proposed a solid-mounted (SM)-type A1-mode resonator, with acoustic mirrors under LN plate, to simplify fabrication process and improve heat dissipation and TCF. By thickening SiO2 via adding about ${{}^{1}}\! /\! _{2}\ \lambda$ length of top mirror layer, almost zero TCF (−4 ppm/K) is obtained. Piston method is applied to suppress transverse mode. We designed full-band N79 filter with simulation considering both acoustic effect and electromagnetic effect. The filter achieves a maximum insertion loss level of 1.98 dB, and the rejections in N77 band, 5G WIFI and far band frequency are close to 30 dB. The return losses are better than 12 dB, without any external matching element. The packaged device occupies compact size of $1100^{\star}900\ \mu\mathrm{m}^{2}$ using flip-chip assembly. Under large power (31 dBm), the solid-mounted device demonstrates more uniform temperature distribution and maximum lift is 180°C, about half lower than cavity-type device, showing advantageous in high power operation.
Automated Patch Generation for Fixing Semantic Errors in ATL Transformation Rules

With the growing popularity of the MDE paradigm, model transformations are becoming more and more complex. ATL transformations, in particular, are error-prone due to the declarative nature of the language and the dependency towards the involved metamodels. To alleviate the burden of developers, we propose, in this paper, an approach for fixing semantic errors in ATL transformation rules without predefined patch templates for specific error types. In a first step, our approach determines the rules that are likely to contain errors starting from the discrepancy between the expected and produced outputs of test cases. Then, a second step allows to generate candidate patches for these errors using a multiobjective optimization algorithm, guided by the same test cases. In a preliminary evaluation, we show that our approach can fix most of the errors for transformations with one or two errors. For those with multiple errors, more iterations are necessary to fix some of the errors.
Determinación automática de la hidrofobicidad superficial de aleaciones de titanio usando el método de gota sésil basado en procesamiento de imágenes

This paper presents the design and implementation, completely homemade, of an automated system for hydrophobicity studies of materials based on the sessile drop method. This parameter was evaluated from the measurement of the contact angle between the deposited liquid and the surface of the material. For this purpose, software for digital image processing was implemented using Python programming language in conjunction with the OpenCV library. Through various filters and functions, an adequate segmentation of the acquired images was achieved to identify their contours and make it possible to measure the contact angle. The system was validated using titanium alloys with their modified surface, finding a good agreement between the results obtained and those reported in the literature to evaluate their potential application as an implantable metallic biomaterial.
Improving Contrast of Fundamental Ultrasound Imaging Using a Deep Neural Network

Harmonic imaging is used as default in many ultrasound imaging settings due to its advantages in contrast and resolution compared to fundamental imaging. However, the nonlinear harmonic generation process and higher imaging frequencies induce a strong loss of penetration when using harmonic vs fundamental imaging. It would be ideal to have the best of both worlds: a high-contrast mode with high penetration. We propose a deep learning approach that relies on a convolutional neural network (CNN) to improve the contrast of fundamental images. We used detected, log-compressed image data before scan conversion collected from commercial phantoms for training and validation. We captured fundamental and corresponding harmonic images and taught the network to learn the harmonic image from the fundamental one. We observed the expected increase in the contrast using the proposed CNN method with fundamental inputs. The proposed approach is promising for developing dedicated deep-learning networks to improve the real-time ultrasound image formation process.
Radar Signal Decomposition in Steering Vector Space for Multi-Target Classification

In automotive frequency-modulated continuous wave radar systems, targets with similar ranges and velocities might be detected as a single target because their target information overlaps on the range-velocity (RV) plane. When the information of multiple targets overlaps on the RV plane, target classification cannot be performed accurately. Therefore, we propose a method to decompose the overlapped target information on the RV plane for effective target classification. To separate each target’s radar signal, we use an orthogonal projection, in which the steering vector formed from the angle information of the desired target is projected onto the kernel space composed of other steering vectors. To verify the performance of the proposed method, a convolutional neural network-based target classification is performed on the decomposed radar signals. Compared to the angle-fast Fourier transform (FFT)-based signal decomposition, the orthogonal projection-based signal decomposition shows higher classification accuracy, which implies that the target information overlapped on the RV plane is effectively separated. When information of two targets is overlapped, the classification accuracy of the proposed method is 5.9%p higher than that of the conventional method. Moreover, when the information of three targets is overlapped, the accuracy is improved by 25.5%p.
Novel approach of Internet of Things (IoT) Based Smart Ambulance System for Patient’s Health Monitoring

In countries like India where the density of population is more, it is very difficult to reach the hospital in case of emergency due to heavy traffic. Sometimes the communication to the hospitals for ambulance also may get delayed from the patient's end. Timely treatment is very important for heart attack patients where the delay in the treatment leads to the death of the patient. Advancement in the IoT (Internet of Things) technology motivates to present the proposed work. Here using sensors and microcontrollers, a smart health monitoring system is proposed which can alert the hospitals in case of emergency and further schedules ambulance facilities. Devices are connected to the patient for the purpose of regular health monitoring and alerting the hospitals during emergency.
Energy-Efficient Adaptive Modulated Fixed-Complexity Sphere Decoder

Fixed-Complexity Sphere Decoder (FSD) is an quasi-optimal detector for Multiple-Input Multiple-Output (MIMO) system which is a hardware-friendly parallel tree-search customised to the modulation and antenna scheme employed. However, it is not able to adapt its behaviour for various modulation and antenna schemes, as demanded by modern wireless standard. This restricts its usage in modern adaptive MIMO systems. This paper proposes a solution to this problem. A configurable FSD structure in proposed where normalized higher order modulation schemes can accommodate lower ones. By exploiting clock-gating, FSD of all modulation schemes is equally trimmed to allow power savings of over 30% when implementing on Field Programmable Gate Array (FPGA). This architecture enables the facility to balance the power consumptions with compatible information rate in dynamic, adaptive MIMO communications environments.
People count system using multi-sensing application

A people counting system with human information sensors for use in a multi-sensing application for detecting the number of persons and their directions of movement at a wide door has been developed. The sensor head module of this sensing system consists of a 1-dimensional 8-element detector array fabricated by a sheet forming method of pyroelectric PbTiO/sub 3/ ceramics, a IR-transparent lens and oscillating mechanical chopping parts. The sensor output is binarized by using the background mean method, and the number of passing persons and their directions of movement are recognized by a pattern recognition algorithm. By using this people counting system, the number of passersby at a 200 cm wide door can be detected with more than 95% accuracy.
Friendship-Association Based Anonymous Identical Users Detection System in Multiple SMNs

: Somewhat recently, many sorts of interpersonal interaction locales have arisen and contributed massively to huge volumes of certifiable information on friendly practices. Perceiving unknown, yet indistinguishable clients among numerous SMNs is as yet an obstinate issue. Obviously, cross-stage investigation might assist with tackling numerous issues in friendly processing in both hypothesis and applications. Since the public profiles can be effortlessly copied and handily imitated by clients with various purposes, most current client recognizable proof goals, which basically center around text mining of clients' public profiles, are delicate. A few investigations have endeavored to coordinate with clients dependent on the area and timing of client content. In addition, since online SMNs are very symmetric, existing client ID plans dependent on network structure are not compelling. This present reality companion cycle is profoundly individual and essentially no two clients share a compatible companion cycle. Thusly, it is more exact to utilize a fellowship construction to dissect cross-stage SMNs. Since indistinguishable clients will in general set up halfway comparative fellowship structures in various SMNs. we proposed the Friend Association-Based User Identification (FAUI) calculation. FAUI works out a coordinating with degree for all up-and-comer User Matched Pairs (UMPs), and just UMPs with highest levels are viewed as indistinguishable clients. We likewise foster two suggestions to work on the proficiency of the calculation. Consequences of broad examinations show that FAUI performs far superior to current organization structure-based calculations. We additionally proposed the composing style measurements. Which utilizes Capitalization, normal word length, accentuation, utilization of images, utilization of numerals, dividing, new lines/sections, short structures, utilization of shoptalk, utilization of smileys, common words
Current Trends & Concepts in Prosthodontics

Evolution happens in our everyday life in every field and prosthodontics is no exception to it. A new generation of patients are expected to have new aspirations and desires. In order to fulfil these desires it is our duty to be updated with both knowledge and skills about new trends in prosthodontics, so that these aspirations can be met with. This paper gives an insight about the various trends and concepts applied in the field of prosthodontics.
Who Plays Complex Music? On the Correlations Between Structural and Behavioral Complexity Measures in Sign Boolean Networks

Intuition tells us that highly complex structure should be strongly correlated with highly complex behavior. In this work, we show that, while complex behavior does require complex structure, the converse is not necessarily true. Indeed, structural complexity can be also used to implement robust behavior, or even a variety of different relatively simple behaviors. To obtain these results, we explored the spaces of sign Boolean networks (SBNs) containing 2, 3, and 4 nodes, and we used complexity measures introduced in our previous work to study the relationship between structural and behavioral complexities of these networks.
A Study on Influence of Motivational Factors on Women Entrepreneurs at Mysore District, Mysore, India

In the recent years, women play an important role in entrepreneurial activity. It is witnessed that the increasing in the numbers of women starting business has not only seen in developed countries, but have also been seen in many other developing countries including India. In the last 40 years, there has been increasing number of women entrepreneurs in developing countries. Hence the present study aims to know the motivational factors influencing on women entrepreneurs to take up entrepreneurial activity in Mysore District. The data were collected from 74 women entrepreneurs. The result of the study says that, the very important factor influencing the women entrepreneurs in Mysore district to start their business is their self-accomplishment. They are motivated by the factors like more autonomy and independence, economic independence, control over doing new things, and inspired to become successful entrepreneurs. These factors are influencing them more to start a business.
A NOVEL DETERMINISTIC APPROACH FOR ASPECT-BASED OPINION MINING

: Angle based feeling mining is finding elaborate assessments towards a subject, for example, an item or an occasion. With hazardous development of stubborn messages on the Web, mining viewpoint level conclusions has turned into a promising methods for online general assessment examination. Specifically, the blast of different sorts of online media gives various yet integral data, bringing extraordinary open doors for cross media perspective assessment mining. Along this line, we propose CAMEL, a novel point model for correlative viewpoint based assessment mining crosswise over hilter kilter accumulations. CAMEL picks up data complementarity by demonstrating both normal and explicit perspectives crosswise over accumulations, while keeping all the relating feelings for contrastive examination. An auto-marking plan called AME is likewise proposed to help segregate among angle and conclusion words without elaborative human naming, which is additionally upgraded by including word installing based similitude as another component. Besides, CAMEL-DP, a nonparametric option in contrast to CAMEL is additionally proposed dependent on coupled Dirichlet Processes. Broad tests on genuine world multi-gathering surveys information exhibit the prevalence of our strategies over aggressive baselines. This is especially obvious when the data shared by various accumulations turns out to be genuinely divided. At last, a contextual analysis on the open occasion "2014 Shanghai Stampede" exhibits the down to earth estimation of CAMEL for certifiable application.
TATALAKSANA GAGAL NAFAS AKUT AKIBAT EDEM PARU AKUT PADA PASIEN DENGAN HIPERTENSI

Gagal nafas merupakan kondisi kegagalan fungsi sistem respirasi dalam pertukaran gas di mana PaO2 < 60 mmHg dan/ PaCO2 > 50 mmHg. Telah dilakukan tindakan kepada seorang pasien laki-laki berusia tujuh puluh satu tahun dengan berat badan 70kg yang di bawa ke IGD RSUD Kota Dumai dengan keadaan penurunan kesadaran. Dari alloanamnesa terhadap keluarga pasien, diketahui sebelumnya pasien mengeluhkan sesak nafas yang muncul tiba-tiba. Pasien memiliki riwayat penyakit jantung yang diketahui sejak 6 bulan terakhir dan hipertensi tidak terkontrol. Pasien didiagnosis dengan respiratory failure type 1 et causa cardiogenic pulmonary oedem. Saat di ICU, saturasi O2 pasien turun menjadi 77% sehingga pasien diberikan bagging untuk bantuan nafas kemudian saturasi O2 naik menjadi 90%, kemudian pasien mengalami apneu, asistol dan arteri karotis tidak teraba sehingga dilakukan RJP kompresi: ventilasi 30:2 dengan total 15 siklus dan pasien mengalami ROSC. Pasien kemudian dipasang intubasi dan dibantu ventilator, saturasi O2 menjadi 99%. Sebelumnya pasien diberikan midazolam 15mg di dalam 50ml NaCl melalui syringe pump dan fentanyl 2 ampul dalam 50cc NaCl 50ml melalui syringe pump. Kemudian, pola nafas tidak efektif dan keadaan umum memburuk, ventilator diubah menjadi mode PCAC kemudian pernafasan kembali adekuat dan hemodinamik pasien stabil. Kemudian pada pasien dilakukan weaning ventilator.
Regulation of the Immune Response in Cysticercosis: Lessons from an Old Acquainted Infection

In the last decades, we have learned some critical lessons about the relationship between the human body and its interaction with many infectious diseases, where regularly, the immune system has a major role in protection. We learned to differentiate between the immune response occurring in either an intracellular or extracellular parasitic infection, between innate and adaptive immune response, between either inflammatory or anti-inflammatory responses, and finally, we learned to recognize very particular mechanisms, such as the inability of the immune system to respond during very particular scenarios, such as the inability of T cells to both proliferate and produce cytokines even after their exposure to mitogens or specific-antigens. Along with our increase in the knowledge in immunology, we figured out that immunoregulation and immunosuppression are processes used by many parasites to reduce the capacity of the immune system to eliminate them, and to persist in the host favoring their transmission and also to complete their life cycles. Immunoregulation involves several mechanisms such as anergy, apoptosis, induction of both suppressive cytokines and membrane-bound molecules, as well as specialized cell populations of the immune system like regulatory T cells, Alternative Activated Macrophages, or Myeloid-derived Suppressor Cells, that together modify the outcome of the immune response. In this chapter we will review the general differences between the different types of immunoregulation, the kind of cellular populations of the immune system used by the helminths Taenia solium and Taenia crassiceps to induce immunoregulation and immunosuppression and also, the mechanisms used by these parasites such as mimicking molecules of the immune system to replace directly these mechanisms. Understanding and deciphering all these regulatory mechanisms could be useful to develop new tools to control this infection.
The Effect of Using Peer on Self-Care, Quality of Life, and Adherence in Elderly People with Coronary Artery Disease

Introduction Coronary artery disease is one of the most common diseases and the cause of death among elderly people. Due to the chronic nature of this disease, regular follow-up, lifestyle changes, and adherence to recommendations can reduce the complications and improve the quality of life among elderly individuals. Given the importance of using educational methods that are based on the patient's age and disease stage, the present study aimed to investigate the effect of using a peer group on self-care, adherence, and quality of life in elderly people. Method This single-blind clinical trial was conducted on 30 old patients with coronary artery disease aged 60 years in Shiraz from March to June 2021. The patients were selected using simple random sampling and were then randomly assigned to the peer education and control groups (15 participants in each group) via permuted block randomization. The patients in the peer education group received the necessary education about medications, lifestyle, daily activities, self-care, and adherence through three educational clips by educated peer. The patients in the control group received routine education using two clips by the ward nurses. The levels of self-care, adherence, and quality of life were assessed in the intervention and control groups before and one month after the intervention. Data analysis was performed by SPSS 20 software using an independent t-test, paired sample t-test, and chi-square test. P < 0.05 was considered statistically significant. Findings. The results showed no statistically significant difference between the two groups with respect to the mean scores of self-care and quality of life before the intervention (P > 0.05). Following the educational intervention, however, a statistically significant difference was found between the two groups concerning the mean scores of self-care and adherence (P < 0.05). Moreover, the mean differences between the two groups regarding the three variables were statistically significant before and after the intervention (P < 0.05). Conclusion Education based on multimedia clips by peer was effective in increasing the mean scores of self-care, adherence, and quality of life among the elderly people with coronary artery disease. Given the low cost, high effectiveness, and decrease in the nurses' workload, this method is recommended to be used alongside other methods in order to educate elderly individuals suffering from coronary artery disease.
High-efficiency silicon solar-cell design and practical barriers

A numerical evaluation technique is used to study the impact of practical barriers, such as heavy doping effects (Auger recombination, band gap narrowing), surface recombination, shadowing losses and minority-carrier lifetime (tau), on a high efficiency silicon solar cell performance. A hypothetical case, considering only radiative recombination losses and ignoring technology limited and fundamental losses is evaluated to estimate highest efficiency. Considering a high tau of 1 ms, efficiency of a silicon solar cell of the hypothetical case is estimated to be around 29%. This is comparable with (detailed balance limit) maximum efficiency of a p-n junction solar cell of 30%, estimated by Shockley and Queisser. Value of tau is varied from 1 second to 20 . mu.s. Heavy doping effects, and realizable values of surface recombination velocities and shadowing, are then considered in succession and their influence on cell efficiency is evaluated and quantified. It is shown that these practical barriers cause the cell efficiency to reduce from the maximum value of 29% to the experimentally achieved value of about 19%. Improvement in open circuit voltage (V/sub oc/) is required to achieve cell efficiency greater than 20%. Increased value of tau reduces reverse saturation current and, hence, improves V/sub oc/. Controlmore » of surface recombination losses becomes critical at higher V/sub oc/. Substantial improvement in tau and considerable reduction in surface recombination velocities is essential to achieve cell efficiencies greater than 20%. Lack of available data for minority-carrier mobility, heavy doping effect, tau in thin emitters, surface recombination velocities, etc., are discussed. Limitations of one dimensional numerical analysis for considering two- and three-dimensional cell designs, such as floating emitter and dot junction cells, are pointed out. « less