Miracle-dz/UniFAR-FTUs huggingface dataset:
Biochemical study of alkaline phosphatase in Escherichia coli

The present research aimed to isolate and purify Alkaline phosphatase enzyme from crude protein extract (Lysate supernatant) of Escherichia coli, by using different biotechnologies. To proceed, the following steps were taken: Firstly, The verification of the existence of enzyme in bacteria, the bacteria were diagnosed by using the API 20 stripe that consists of (20) items. the enzyme was isolated to ensure its availability in bacteria within the logarithmic phase and this was done through proliferating them for 18 hours in a nutrient agar. It had been detected that the enzyme was intracellular because of the occurrence of enzyme activity in the lysate supernatant without occurring it in the cell free culture supernatant. Secondly, Enzyme purification, the enzyme had been purified through three stages: precipitation of protein by ammonium sulphate, dialysis and finally, the protein extract was passed through column chromatography by using Sephadex G-100 gel, the estimated enzyme activity after this step was 22.0 in comparison with its activity before the purification processes (crude protein extract). The approximate molecular weight of alkaline phosphatase was 81.000 Dalton estimated by using gel filtration technique.
Influence of Training Times and Sample Size on Results in Visual Try-On with GAN

With online shopping becoming more and more trendy these days, Virtual Try-On Approach is proposed. It is a method of Generative Adversarial Network (GAN) composes of two models: Geometry Matching Module (GMM) and Try-On Module (TOM). It is proposed to solve the inconvenience of customers for not being able to see the fitting effect before receiving the goods. This paper is about finding the relationship between dataset and the effect of the experiment in the GAN experiment. After implementing the models and gaining the result images, we do some observations on the GMM one and try to analyze it and improve the effect. Comparison is made on different aspects: training times of the model and sample size of the training input. Similar trends are shown on the decrease of loss value when the training times or sample size rises. However, the visual effect is not necessarily improved all the time. Compared with the times it has been trained, the improvement from training times is far less than that from the sample size. Finally, we draw the conclusion that the effect is gradually improved as the training times or sample size increases at the beginning. Nevertheless, the improvement cannot be recognized evidently when the training times and sample size have grown large enough. Additionally, the sample size seems to be a more significant factor in the improvement of the visual effect than the training times.
A Review Analysis on Face Recognition System with User Interface System

Face recognition is the most advanced way of authentication and authorization and it has been developed a lot since the last decade and such systems are now popular in fields such as security and commerce. This work revolves around facial recognition based automated user management system with active learning features the proposed work uses a combination of a couple of technologies to build such a system for user keeping which is foolproof and secure it also adds active learning to counter the problem of changing faces in youngsters. The system is recommended for schools, universities, corporate offices, and prisons.
Development trend analysis of variable oxygen concentration combustion research based on bibliometrics

Based on CiteSpace, 955 journal literature related to variable oxygen concentration combustion research collected in the web of Science (WOS) core database were analyzed visually. The results show that: 1 Literature publication trends. According to the total number of published literature, it can be divided into three stages: initial development, steady development, and rapid development. 2. Analysis of the author’s co-occurrence map. The author’s cooperation network in this field is obvious, but the overall cooperation network presents a “core-edge” structure, and the cooperation of academic teams is scattered. 3. Research hotspots, the related research mainly focused on the combustion characteristics of polymer synthetic materials, and chemical cycle combustion related to the field of energy and power engineering. 4. Research on the frontier trend. At present, “mechanical property” and “Nanoparticles” are the keywords representing the latest frontier trend in this field.
The Influence of Grid-connected Distributed Generation on the Power Supply Reliability of Distribution Network

This paper analyzes the typical distribution network structure and the operating characteristics of distributed generation (DG). By analyzing the impact of grid-connected DG on equipment such as reclosing and spare power automatic switching, we calculate the power supply reliability indexs after the DG is connected to the grid under various operation modes such as reclosing, spare power automatic switching, de-sequencing distributed energy and islanding. Finally, the results of the reliability indexs can provide the theory and data for planning and improving the operating mode of grid-connected DG.
Calculation and analysis of interaction flowfield over tiltrotor aircraft in conversion mode

Aiming at solving the complicated aerodynamic interaction problem of conversion mode, the preconditioning method is applied. Combined with the unstructured hybrid technique and the overlapping grid interpolation technique, a numerical simulation method for tiltrotor aircraft in conversion mode is established. On this basis, the validity of the numerical method is verified. Then, with the numerical simulation of isolated rotor, isolated fuselage and tiltrotor aircraft, the laws of the aerodynamic interaction of rotor/fuselage/wing/tail are analyzed with tilting process. The calculation results show that the rule of the influence of the rotor wake on the aerodynamic performance of the wing is different between the inner side and the outer side of the wing. Compared with the isolated rotor, the thrust coefficient of the rotor of the aircraft increases slightly by 0 ∼ 5% during the tilting process due to wing and the fuselage.
Design Strategies of Life Outside and Life Inside for Livable Multi-family Housing Environment

This paper discusses the issue related to social life within the context of a neighbourhood. It takes on the case study of multi-family housing, which its urban forms are generally monofunctional, stand-alone, large scale, spread out and car dependency. This type of urban form may cause inclusivity and isolation to its context and problems in social interactions within its neighbourhood. This study examined the concept of life outside and life inside in multi-family housing design to create a more livable housing environment. The life outside concept aims to create a human-oriented neighbourhood by directing daily human activity towards outdoor space, through the integration of proximity, density, dan diversity. While the life inside concept aims to allow, residents to socialize with others through the design of a high probability of encounter zones in the building. Based on the observation at a multifamily housing complex at Rainbow Springs, Tangerang, this study proposed design criteria and strategies for a livable multi-family housing environment within the neighbourhood and inside the building itself. This study implies that integration between site planning and building design should be taken into consideration to form a livable neighbourhood.
Comparison of different fiducial markers to guide SPECT and CT image registration

Registration and fusion guided by the fiducial markers of SPECT and CT images acquired via distinct equipment is a common practice in several nuclear medicine centres. In this study, five different fiducial configurations were studied and compared for SPECT and CT image acquisitions: iodide-131 (131I) within a needle cap, 131I associated with cotton, a lead and a ceramic aluminium sphere or mixed with an agarose solution. Fiducials that employed agarose mixtures presented the lowest dpr values (between 0.34 and 0.53 mm) and better homogeneous regions in both images to perform registration. In addition, this assembly exhibited the lowest global mean dpr and standard deviations in Gaussian adjustments. In comparison with the other configurations, the agarose dpr was statistically lower than that of cotton, ceramic aluminium and just 131I for all the six landmarks. Despite its similarity with the lead sphere configuration, for five of the landmarks, agarose showed no artefacts in CT and more homogeneous regions of interest in SPECT images. In addition, agarose demonstrated great reproducibility to guide point-based registration processes.
INTELLECTUAL GRAPH MODELS FOR RELATED DATA PROCESSING

In connection with the wide spreading of various intelligent sensors, IoT devices, smartphones, autonomous transport systems, various industrial and home automation systems, an unprecedented amount of data is generated, including those intelligently linked to each other. Linked data allows you to build complex and varied relationships between objects and subjects of the real world. Unfortunately, modern big data processing systems and machine learning models are extremely poorly suited for working with such dynamically linked data, especially in the case of real-time systems. We discuss current and future-proof approaches to working with such data using graph analysis models.
Read Textual features in Images and convert to Editable form by extended use of Artificial Neural Networks, Deep learning and Maximally Stable Extremal Region techniques

Nowadays most of the information is stored in images and there is a need to convert this information into an editable format. The objective of this paper includes the development of a user-friendly tool to extract text from the video or to recognize well-written handwriting in a scanned document to an editable form. The proposed methodology is robust and can provide high-grade performance with layout distortion. The explication utilizes modalities like Optical Character Recognition (OCR), Artificial Neural Networks (ANN), Deep Learning and Maximally Stable Extremal Regions (MSER) techniques for text detection. The video extraction can be attained by using video to frame conversion and then to use the Structural Similarity Index Measure (SSIM). The prototype is developed using MATLAB and provided with a GUI, which is deployable on a workstation. The generated GUI is employed to define Region of Interest (ROI), specify the required text layout, highlighting the specific portions of the image, select the appropriate language and also export the text to a word document or notepad applications where it can be edited.
Single-Site Copper by Incorporation in Ambient Pressure Dried Silica Aerogel and Xerogel Systems: An X-ray Absorption Spectroscopy Study

Copper incorporated silica aerogels and xerogels were prepared by adding the metal during the sol–gel stage and applying the ambient pressure drying (APD) method. The materials were characterized using inductively coupled mass spectrometry (ICP-MS), the Brunauer–Emmet–Teller (BET) method, X-ray diffraction (XRD), thermograviometric analysis–differential scanning calorimetry (TGA–DSC), and in situ diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). The introduction of copper led to changes in the aerogel architecture, seen by considerable expansion of average pore size, while maintaining a hydrophobic nature. The valence state and local chemical environment of copper was studied by X-ray absorption spectroscopy (XAS) before and after annealing to evaluate the interaction with the gel systems. X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) spectra showed that copper was divalent and present in a tetragonally distorted environment in both a.
An effective and universal intensity noise suppression technique for single-frequency fiber lasers at 1.5 μm

We report on an effective and universal technique to fulfill intensity noise suppression for single-frequency fiber lasers (SFFLs) at 1.5 μm. Utilizing a gain-saturated semiconductor optical amplifier and the effective filtering of amplified spontaneous emission, the resultant relative intensity noises of three diverse SFFLs are maintained at −155 dB Hz−1; which is only <0.9 dB from the shot noise limit in the frequency range from 100 kHz to 50 MHz. Refering to the three paradigmatic experimental results, this technology, as a promising external solution of noise suppression, can be modularized to promote the application of SFFLs.
The role of artificial intelligence recognition in metallogenic prediction

Artificial intelligence algorithm has developed rapidly in recent years, and deep learning has become the research hotspot of many scholars. Artificial intelligence algorithm is just developing in geology, especially in metallogenic prediction. In this work, the 1:250000 aeromagnetic data image of a certain area is used to predict the gold deposit, and good research results are obtained.
Preface

2020 International Conference on Mechanical Automation and Computer Engineering in 2020 will be held in Xi’an, Shaanxi Province, China from 28th to 30th October 2020, we will communicate around the latest research areas such as “Mechanical Automation”, and “Computer Engineering”. It aims to provide an international cooperation and exchange platform for experts, scholars and enterprise managers in the fields of the application of mechanical automation and computer engineering to share research results, discuss existing problems and challenges and explore cutting-edge technologies. COVID-19 Update: MACE2020 to go virtual As you know by now, agencies around the world are now issuing restrictions on travel, gatherings, and meetings in an effort to limit and slow the spread of the COVID-19 virus. The health and safety of our participants and members of our research community is of top priority to the MACE2020 Organizing Committee. All MACE2020 accepted papers have been presented virtually during the conference week of October 28–30, 2020. We purchased a third-party professional online meeting service, so the meeting is very good in terms of picture quality and actual hosting effect. During the actual presentations on October 28–30, 2020, Talks have been pre-recorded and submitted as MP4 video files to be replayed during the conference. at least one author has be available online after their videos are played to answer Q&A from conference participants moderated by the respective Session Chairs.
Multi-hazard assessment and shelter allocation in DKI Jakarta: an initial study

Multi-hazard assessment extends the traditional disaster hazard assessment. It provides an exhaustive view of disaster hazard management where all possible disasters are observed. More importantly, the interaction and compounding impact of the concurrent disasters event should be understood thoroughly. Up until now, hazard assessments of all possible disaster events in DKI Jakarta are estimated separately. This study aimed to initiate a multi-hazard assessment of earthquake and flood for urban areas in DKI Jakarta. A scenario-based of a concurrent disaster event is created, that is the sequence of earthquake and flood occurrence, and its impact are studied using multi criteria analysis. The evacuation shelters are proposed within the affected area and the shortest path for disaster reliefs are estimated using the shortest path algorithm. The area with high level multi-hazard should carefully plan their disaster mitigation and recovery management to prepare the society for the concurrent disaster event and ensure their resiliency.
Dielectric properties of Ni and Nb doped CaCu3Ti4O12 ceramics

CaCu2.8Nb0.2Ti4-xNixO12 (x=0.1, 0.2, 0.3) and CaCu3Ti4O12 ceramics were successfully fabricated through the solid-state reaction method. All the samples were methodically examined by X-ray diffraction (XRD), scanning electron microscopy (SEM), impedance and dielectric properties measurements. XRD analyses verified the constitution of a cubic perovskite structure with Im-3 space group. The average grain size of CaCu3Ti4O12 ceramics reduced with Ni and Nb ions doping, especially decreased significantly with the increase of Ni content. Compared with un-doped CaCu3Ti4O12, Ni and Nb ions doped CaCu3Ti4O12 ceramics presented greatly enhanced dielectric constant range from 102 Hz to 106 Hz, illustrating the Ni and Nb ions have great influence on improving the dielectric constant. The CaCu2.8Nb0.2Ti3.8Ni0.2O12 sample achieves the highest dielectric constant, possesses the lowest dielectric loss and acquires the largest grain boundary resistance in the doped samples. Therefore, it has optimal dielectric performance.
EIoU: An Improved Vehicle Detection Algorithm Based on VehicleNet Neural Network

The paper’s primary purpose is to optimize the performance (speed/accuracy) of vehicle detection. The vehicle dataset Vehicle2020 used in this paper is divided into ten different vehicle classes. Intersection over Union (IoU) is usually used as a standard to evaluate the accuracy of vehicle detection in a specific dataset. However, IoU as a performance of the object detection algorithm is still shortcomings. IoU is further improved and called a new algorithm EIoU. Finally, the neural network structure was redesigned, which was called VehicleNet. The experimental results show that EIoU as a performance evaluation algorithm used the vehicle detection framework can improve the performance of vehicle detection. Using the algorithm of this paper shows the performance superiority of vehicle detection.
Quick-clay landslide mitigation using potassium-chloride wells: Installation procedures and effects

Mitigation actions related to quick-clay slopes often induce undesirable changes to the terrain that may have negative impact on developed areas and local biodiversity. Soil improvement may prevent this. Lime-cement piling causes temporarily reduced slope stability and substantial climate-gas emissions. Less climate-gas emissions are associated to the production of potassium chloride (KCl). KCl improves the post-failure properties of quick clay so it renders not quick and may serve as an alternative to current landslide-mitigation. The mechanisms in this chemical process is well documented, but there exist no installation procedures for KCl wells, nor knowledge on cost/benefit or climate-gas emissions. This paper presents two installation procedures of KCl wells, and studies showing that the climate-gas emissions are far less than installing lime-cement piles. Further development of cost-effective installation procedures is needed to justify application of KCl wells in quick-clay areas.
Truth discovery in healthcare prediction using machine learning

Healthcare is one of the core areas of the medical field in today’s digital world. By analyzing large amounts of patient data, healthcare systems are needed to gain insights and help disease prediction. The truth discovery of the Health Recommendation System (TDHRS) is becoming an important platform for medical services. The proposed use of Boltzmann Machine (RBM)-FP-Growth Health Pattern Recognition (RBMG) smart HRS can provide insights into how big data analysis can be used to implement an effective health recommendation engine, and will be used in Transition from a standard solution to a more personalized paradigm in the telemedicine environment. By considering the Root Mean Square Error (RSME) and Mean Absolute Error (MAE) values, the proposed deep learning method (RBM-FP-Growth) exhibits fewer errors than other methods.
Texture based Clustering Technique for Fetal Ultrasound Image Segmentation

Segmentation of fetal ultrasound image is an important and necessary task in the automation of fetal biometric measurement. Fetal ultrasound image segmentation is tedious because of the fuzzy nature and textured appearance of fetal structures. Hence, texture based Clustering is proposed for segmenting fetal ultrasound images. Clustering is performed using texture properties of the images which are used for segmenting ultrasound images of fetus. Texture based clustering technique can be used for segmenting all fetal anatomies specifically abdomen, the boundaries of which are very vague and difficult to delineate. Synthetic, simulated ultrasound images and 120 ultrasound fetal images were used for validating the method achieving an accuracy of 90%.
Interaction between negative corona discharge and droplet emission from liquid Taylor cone

We investigated the behavior of droplets, the Taylor cone tip, and discharge current characteristics in electrospraying with negative corona discharge, and analyzed the interaction among them in the time scale of several micro seconds. Negative corona discharges using 1 wt% sodium dodecyl sulfate solution or ethylene glycol as liquid cathode were investigated, and the discharge current pulse had a distinctive structure with serial pulse trains. The pulse train structure indicated that the discharges from the Taylor cone are in the form of Trichel pulses with a dynamic cathode. We found that the electric field, liquid conductivity, and liquid viscosity had no significant effect on the discharge current characteristics, with the exception of the current peak value, whereas a higher electric field or higher liquid viscosity led to extended pulse train intervals and durations. These effects can be attributed to the change in time scale of the cone tip curvature variation. The above results indicate that the curvature radius of the cone tip dominates the discharges from the Taylor cone. The emission and transfer of droplets between electrodes were observed using back-lit images and Mie-scattered light images taken by a high-speed camera. The droplet emission was synchronized with the leading current in the Trichel pulses. The terminal velocity of the droplets transferring discharge gap was proportional to the revised electric field. The experimental results indicate that the droplet emission mechanism from the Taylor cone with discharges is supposed to differ from that without discharges explained by the Rayleigh limit. The reasonable explanation for the droplet emission mechanism is that the droplets are torn off the liquid cone tip by the strong electric field associated with discharges.
A Review on fusion in Multimodal Biometric Spoofing Attack by Different Materials

Biometric gadgets utilize their physiological or behavioural properties for the confirmation and acknowledgment of people. Spoofing attack can be done by using any spoofing materials. Such features can be arranged into unimodal and multimodal frameworks. Some state-of-the-methods have some drawbacks, which reduce the efficiency of the system. Multimodal biometric detecting frameworks utilize at least two behavioural or physiological attributes. The multimodal system has showed to increase the success rate of identification and authentication meaningfully. Data from different modalities are acquired, pre-handled, removed noise, and contrasted and finally converted into features. At last, selection of features acknowledges the identification of a person. In multimodal biometric identification system, biometric features can club at any of the stages. i.e. sensor level, feature level, score level, rank level, and decision level. This paper presents an effective survey on fusion of features at different level in a multimodal biometric system. It also focuses in the field with a better thoughtful of multimodal biometric sensing and handling systems and research inclinations in this field.