Miracle-dz/UniFAR-FTUs huggingface dataset:
Low Resolution Cell Image Edge Segmentation Based on Convolutional Neural Network

An interesting segmentation method for low-resolution cell images captured by a lens-free imaging system is presented in this paper. The resolution of this cell images is low and its quality has also greatly impacted by the experimental environments, and the traditional cell segmentation methods to solve the original cell images is not robust and sensitive to noise. So based on the convolutional neural network, an optimized CSnet method is proposed in this paper for automatically segmenting cell. In the proposed method, the produced data set will be sent into the convolutional neural network firstly for training to obtain an optimized convolution neural network segmentation model. And then, the pre-divided images acquired by the lens-free imaging system are loaded into the segmentation model to get the segmentation images. Finally, our proposed method in this paper is tested in a neural network framework built in keras. The experimental results show that the accuracy of our proposed method can reach about 96%. At the same time, it also can implement batch segmentation automatically and make the problem of heavy task for segmentation better.
A Chemometrics Approach Comparing Volatile Changes during the Shelf Life of Apple Juice Processed by Pulsed Electric Fields, High Pressure and Thermal Pasteurization

High-Pressure Processing (HPP) and Pulsed Electric Fields (PEF) processing technologies are being used increasingly on a commercial basis, with high-quality labelled fruit juices being one of the most important promotion strategies. Quality-related enzymes, which might still be active after HPP and PEF pasteurization, can cause undesirable aroma changes during storage. This study investigated volatile changes during the shelf life of PEF (15.5 kV/cm and specific energy of 158 kJ/L), HPP (600 MPa for 3 min), and thermally (72 °C for 15 s) pasteurized Jazz apple juices—up to five weeks. To have an increased insight into the volatile changes, an integrated instrumental (GC-MS) and data analysis (chemometrics) approach was implemented. Immediately after pasteurization, PEF processing resulted a better retention of odor-active volatiles, such as (E)-2-hexenal and hexyl acetate, whereas thermal processing lowered their amount. During refrigerated storage, these volatiles have gradually decreased in all processed juices. By the end of storage, the amount of these aroma relevant volatiles appears to still be higher in PEF and HPP pasteurized juices compared to their conventional counterparts. This study demonstrated the potential of advanced chemometric approaches to obtain increased insight into complex shelf life changes.
A Novel Approach to MTPA Tracking Control of AC Drives in Vehicle Propulsion Systems

In today's hybrid or fully electric vehicles, two types of propulsion machines can mainly be found: induction machines (IM) and interior permanent magnet synchronous machines. They are highly utilized and operated in magnetic saturation regions where inductance parameters change nonlinearly. The energy efficiency of both drives depends strongly on the choice of reference currents within field-oriented control. The paper shows two approaches for the determination of well-adjusted current components for both machines. First, model-based optimization is performed. It uses machine models considering saturation and loss models including the inverter. Second, a newly developed online-optimization scheme based on a discrete search method is presented. Simulation results show its advantages over recently published solutions for both machine types. Finally, experimental results at a drive test bench are presented. They prove the fast convergence and correct function of the proposed method.
Comparative genomic analysis of embryonic, lineage-converted and stem cell-derived motor neurons

ABSTRACT Advances in stem cell science allow the production of different cell types in vitro either through the recapitulation of developmental processes, often termed ‘directed differentiation’, or the forced expression of lineage-specific transcription factors. Although cells produced by both approaches are increasingly used in translational applications, their quantitative similarity to their primary counterparts remains largely unresolved. To investigate the similarity between in vitro-derived and primary cell types, we harvested and purified mouse spinal motor neurons and compared them with motor neurons produced by transcription factor-mediated lineage conversion of fibroblasts or directed differentiation of pluripotent stem cells. To enable unbiased analysis of these motor neuron types and their cells of origin, we then subjected them to whole transcriptome and DNA methylome analysis by RNA sequencing (RNA-seq) and reduced representation bisulfite sequencing (RRBS). Despite major differences in methodology, lineage conversion and directed differentiation both produce cells that closely approximate the primary motor neuron state. However, we identify differences in Fas signaling, the Hox code and synaptic gene expression between lineage-converted and directed differentiation motor neurons that affect their utility in translational studies. Highlighted Article: Motor neurons made by stem cell differentiation and lineage conversion are highly similar to their primary counterparts, yet carry distinct differences that can impact their utility in translational studies.
Android Based American Sign Language Recognition System with Skin Segmentation and SVM

People with hearing impairment use sign language for communication. They use hand gestures to represent numbers, letters, words and sentences, which allows them to communicate among themselves. The problem arises when they need to interact with other people. An automation system that can convert sign language to text will make the interaction easier. Recently, many such systems for sign language recognition have been developed. But most of them were executed using laptop and computers, which are impractical to carry due to their weight and size. This article is based on the design and implementation of an Android application which converts the American Sign Language to text, so that it can be used anywhere and anytime. Image is captured by the smart phone camera and skin segmentation is done using YCbCr systems. Features are extracted from the image using HOG and classified to recognize the sign. The classification is done using Support Vector Machine (SVM).
Enhancing Progressive Education through the Use of Serious Games

The increasing body of research is focused on developing tools and applications that aid the learning process of children with or without disabilities. However, learning by gaming is still not recognized by formal educational systems. The author believes that the application of this approach is particularly slow at the level of primary and secondary education in countries with low and middle income, such as Bosnia and Herzegovina. Integrating serious games into curricula in these contexts could significantly benefit the students, as well as the community in general. This work, therefore, promotes technology as one of the crucial educational and pedagogical components. It provides an overview of selected educational games created for pre-school and elementary school children with specific learning intentions revolving around alphabet, colours and elementary science. A pilot study was performed with neuro-typical and neuro-atypical children, and professionals working at an NGO ``EDUS - Education for All''. The findings show that both students and instructors have a positive attitude towards the game design and logic, and more importantly, towards the technology itself. In the end, we believe that the games presented in this paper can be valuable resources for teachers, as well as for children and parents.
Catch Me If You Can: Dynamic Concealment of Network Entities

In this paper, a framework for Moving Target Defense is introduced. This framework bases on three pillars: network address mutation, communication stack randomization and the dynamic deployment of decoys. The network address mutation is based on the concept of domain generation algorithms, where different features are included to fulfill the system requirements. Those requirements are time dependency, unpredictability and determinism. Communication stack randomization is applied additionally to increase the complexity of reconnaissance activity. By employing communication stack randomization, previously fingerprinted systems do not only differ in the network address but also in their communication pattern behavior. And finally, decoys are integrated into the proposed framework to detect attackers that have breached the perimeter. Furthermore, attacker's resources can be bound by interacting with the decoy systems. Additionally, the framework can be extended with more advanced Moving Target Defense methods such as obscuring port numbers of services.
Observer-Based Controller Design for Systems on Manifolds in Euclidean Space

A method of designing observers and observer-based tracking controllers is proposed for nonlinear systems on manifolds via embedding into Euclidean space and transversal stabilization. Given a system on a manifold, we first embed the manifold and the system into Euclidean space and extend the system dynamics to the ambient Euclidean space in such a way that the manifold becomes an invariant attractor of the extended system, thus securing the transversal stability of the manifold in the extended dynamics. After the embedding, we design state observers and observer-based controllers for the extended system in one single global coordinate system in the ambient Euclidean space, and then restrict them to the original state-space manifold to produce observers and observer-based controllers for the original system on the manifold. This procedure has the merit that any existing control method that has been developed in Euclidean space can be applied globally to systems defined on nonlinear manifolds, thus making nonlinear controller design on manifolds easier. The detail of the method is demonstrated on the fully actuated rigid body system.
A Vertically-Polarized Ultra-Wideband, Low-Profile and Folded Half Vivaldi Antenna

A vertically-polarized, ultra-wideband (UWB), low-profile Vivaldi antenna is presented in this paper. Only half of the Vivaldi is placed perpendicularly to the ground plane to achieve vertical polarization. The upper part of the antenna is folded into a right angle to achieve a low-profile. The rectangular slotlines are used to improve VSWR and enhance the gain at the end-fire orientation in the operating frequency band, and a ${50}\boldsymbol{\Omega}$ coaxial probe connects directly with the end of taper slot for feeding purpose. The total sizes are ${100}\ (\text{length})\ \times\ {50} (\text{width})\ \times {16} \text{(height)}\ \text{mm}^{3}$. Simulated results show that the designed antenna exhibits a bandwidth from 3.2 to 24 GHz ${(7.5:1)}$ for $\text{VSWR} < 2.2$, and stable radiation patterns in 3 ~ 16 GHz.
Towards A Secure SDN Architecture

Software Defined Networking (SDN) is an emerging technology which is widely accepted by various enterprises. The SDN mostly involves with a programmatic interface which replaces the control plane on the switch and provides a programmatic interfaces into the controller, to network orchestration in general. SDN was proposed to address some of the issues which are being face by the traditional network. When considering the security aspects of SDN, the most address problem is to secure the SDN from a denial-of-service (DoS) attack. The Distributed DoS attack has now become a common weapon used by cyber terrorist and hackers. Even though a lot of mitigation techniques exist against the DDoS, the threat still remains. The most common way is to perform a control plane saturation attack which takes down the controller hence compromising the network. In this paper, we present our survey and systematic study with experiments, in our attack testbed, few of the existing research on securing the SDN stack. We highlight the state-of-the-art mechanisms related to the analysis, principles and evaluation methods with the observations in our testbed. We analyze how each of the mechanism protects SDN from control plane saturation attacks; data plane flooding & network topology attacks and so on. Also to address the limitations and some of the shortcomings of the existing techniques of SDN, we propose our future work which is a defense layer for the data plane (within the Openvswitch)which does all the basic forwarding of packets from within the switch for a new flow rather than getting the information from the controller. By implementing a defense mechanism layer within the data plane/forwarding layer, which drops & blacklists the malicious flows & hosts, major attack traffic is prevented from entering the SDN stack, hence can increase the performance as well as provide more security in SDN.
A 50V, 1.45ns, 4.1pJ High-Speed Low-Power Level Shifter for High-Voltage DCDC Converters

The level shifter and the floating gate supply for high-side transistors are a major challenge in high-voltage DCDC converters. This paper presents a high-speed and power-efficient level shifter for voltages of up to 50 V, suitable for both PMOS and NMOS power FETs. A switching node falling edge detection allows both, a sensitive and safe signal detection. This enables a robust operation during steep dv / dt transitions and a power consumption as low as 4.1 pJ per switching cycle, which is a reduction of more than 40 % compared to prior art. An active clamping circuit prevents common mode displacement currents into the high-side supply. The level shifter is implemented in a 180 nm BiCMOS technology. Measurements confirm a 50 V 120 MHz high-speed operation of the level shifter with a rising / falling propagation delay of 1.45 ns /1.3 ns, respectively. The dv / dt robustness has been confirmed by measurements for transitions up to 6 V / ns.
Expression of osteoprotegerin and receptor activator for the nuclear factor‐κB ligand in XACB/LV‐bFGF/MSCs transplantation for repair of rabbit femoral head defect necrosis

The aim of this study is to observe the changes in osteoprotegerin (OPG) and receptor activator for the nuclear factor‐κB ligand (RANKL) in a rabbit model, and to explore the therapeutic effect of tissue engineering bone on femoral head necrosis. A total of 60 rabbits were randomly divided into 5 groups. The necrosis model of femoral head defects was created by dexamethasone combined with a horse serum injection. The model of femoral head necrosis was reconstructed by tissue engineering bone. The protein expressions of OPG and RANKL were detected by Western blot analysis. The expression of OPG and the RANKL protein in group E was higher than that in the other 4 groups (P < .05); there was no significant difference between groups C and D ( P > .05). The expression of OPG protein in the rabbit femoral head necrosis group was improved by xenogeneic antigens of cancellous bone/lentiviral‐basic fibroblast growth factor/mesenchymal stem cells, which were expected to be used as an effective tissue engineering material to repair the necrosis of the femoral head.
Comparison of Load Profiles in a Resistive Single Leg Squat

This paper reports the development of the ERIK isokinetic exercise device for the lower limbs, which provided a resistant force laterally to a sliding led during a type of single- limb squat exercise. The muscles of the stance leg during the single leg squat was strongly loaded by the translational load on the sliding leg in the closed kinetic chain style. The training device effectively applied loads to the gluteal muscles, which contribute to decreasing the knee valgus moment, which easily beings anterior cruciate ligament injuries. The four training modes of the ERIK were tested experimentally. ERIK’s performance was confirmed by comparing results with the results from a conventional exercise device. The isokinetic exercise mode was especially superior to the others. While a high resistance was created within the wide motion area and the provision of isokinetic training was achieved by controlling the leg velocity, ERIK had the advantage of safety because of the passive resistive function.
A Comprehensive Overview of Government Hacking Worldwide

There has been an ongoing and heated public policy debate on the appropriate role of and limitations to government hacking in maintaining a proper balance of national security and privacy. Asserting that they are compelled to use government hacking tools to protect their countries and populations, law enforcement and government agencies are increasingly strident in expressing the importance of accessing and intercepting encrypted communication data. However, many non-governmental and civil society organizations and activists strongly oppose government hacking because they consider its methods and techniques are extremely invasive and potentially compromising to the fundamental right of privacy. They are also concerned that the implementation of hacking techniques or similar methods would weaken encryption standards and place the security of the Internet at risk. This paper presents an overview of the current status of government hacking and discusses challenges to lawful interception (LI) technology and rules. The current state of LI and government hacking in five countries is reviewed, and capability is assessed in terms of several widely publicized events, in an effort to analyze the limitations of current solutions. Finally, the open challenges to and future direction of government hacking are highlighted.
Fast Probabilistic Load Flow for non-radial Distribution Grids

To ensure the smooth operation of a distribution grid with a high share of renewable energies, it is important to know the state of the grid at all times. Especially in cases when bus power measurements or estimates are uncertain, the resulting voltage probability distribution is important to assess the situation. This is done using probabilistic load flow methods such as Monte-Carlo simulations. To reduce computational load, a method for a simplified calculation of the probabilistic load flow for grids with a radial structure has been published by the author. This paper extends the algorithm to work also with non-radial grid structures and compares the performance of the calculation at different load scenarios in terms of estimation accuracy and calculation time. It is shown, the extension performs similar compared to the radial grid approximation with an only minor increase in computational load. Keywords—smart grids, power system control, power grids, probability distribution.
Study on Influence of Electromagnetic Disturbance on Wireless Sensor Unit in Substation

This paper mainly focuses on feature of the electromagnetic disturbance generated by power system and influence on wireless sensor unit. Wireless sensor unit works in substation for signal acquisition and transmission. Influence of electromagnetic disturbance, which is generated in substations of different voltage levels and of different insulation types, on wireless sensors is studied in order to ensure reliability and security. After field measurement and analysis, simulation and immunity test are performed based on extensive field measurement data. Statistical characteristics of electromagnetic disturbance are obtained. Immunity of wireless sensor unit in substation is studied.
CT-Blocks: Learning Computational Thinking by Snapping Blocks

Technologies are growing rapidly and its applications are enormous in different strata of society. In this paper especially we are talking about educational technologies. We could see there is a significant change in elementary and secondary education over the past 10 years like classroom teaching, information and communications technology (ICT), and now everything is all about the cloud computing. Cloud computing technologies play a big role in the development of educational technologies. CT-Blocks is a virtual private cloud system developed for K-12 schools. The importance of the word computational thinking makes everyone to the development of educational tools to impart computational thinking to primary, middle and high school students. CT-Blocks is a cloud and block based programming language that reinforces the word computational thinking in all types of users.
News Popularity Prediction with Ensemble Methods of Classification

Online news popularity has become an important issue and a lot of research work is being carried out on the same. Predicting the popularity of an article, a video or any online content can rightly tackle and influence marketing strategies, strengthen the base of any news topic and can also be a valuable asset to the recommendation systems. The aim of this paper is to predict the popularity of news articles for which we have made use of mashable dataset. This paper successfully implements and compares eleven models and found that Gradient Boost works the best on the Online News Popularity dataset with an accuracy of 79.7%. Taking the mean of the shares of all the articles the study concludes that articles with more than 3395 shares are considered popular. The paper provides a detailed analysis of all the models and presented a table at the end comparing the results.
Three-Dimensional Drone-Cell Deployment for Congestion Mitigation in Cellular Networks

Future cellular networks are expected to offload flash crowd traffic in an area (e.g., a stadium with ongoing sporting events). Owing to the temporary characteristic of this traffic, investing in infrastructures may not be financially viable to provide service coverage for this traffic. Resorting to drone-cells (i.e., unmanned aerial vehicles acting as aerial base stations) to offer rapid but temporary service coverage is a promising solution. Although drone-cells provide quick coverage, efficient placement of drones is challenging. In this paper, we model heterogeneous traffic distribution and formulate a three-dimensional (3-D) drone-cell placement problem with a goal of mitigating congestion for future cellular networks under heterogeneous traffic. To make this problem easy to solve, we convert the 3-D drone-cell placement problem into a new 3-D drone-cell placement problem based on our derived theoretical results. We propose four algorithms to solve the new 3-D drone-cell placement problem. In these algorithms, we first develop four types of drone-cell altitude solvers to achieve a drone-cell altitude. With such an altitude, we further convert the new 3-D problem into a mixed-integer quadratic cone optimization problem in 2-D space, which is solvable by an optimization tool. Simulation results show that these algorithms can effectively help deploy a drone-cell to mitigate network congestion.
Improvement in the Transmission Efficiency of EV Wireless Power Transfer System Using a Magnetoplated Aluminum Pipe

The wireless power transfer (WPT) system in an electric vehicle charger uses a litz copper wire (LCW) in the transmission coil to reduce the high-frequency loss at 81–90 kHz. The litz wire improves the performance of the WPT system by increasing the number of strand wires and reducing the diameter while simultaneously increasing the cost. Using a solid wire coil reduces cost, but it causes a high frequency loss that reduces the efficiency. Therefore, this paper proposes the use of a magnetoplated aluminum pipe (MAP) in a transmission coil. Compared to the solid wire, the MAP is light and cheap to manufacture. In our prototype, the transmission efficiencies between coils were 95.67%, 94%, and 92.6% for the LCW, MAP, and aluminum pipe coils, respectively. Therefore, the MAP coil can effectively be used as a replacement for the LCW coil in the transmission coil.