Miracle-dz/UniFAR-FTUs huggingface dataset:
3D Reconstruction and Visual SLAM of Indoor Scenes for Augmented Reality Application

The indoor environments are usually considered as GPS-denied areas, which make the localization of mobile devices a challenging task. The visual SLAM (simultaneous localization and mapping) is a commonly adopted technique for indoor localization and 3D reconstruction. It processes the image information of the scene to derive the location of the camera-equipped device and the 3D structure of the environment. Moreover, many modern mobile devices come with multiple built-in sensors. The integration of multi-sensor information is able to provide more robust localization results compared to the monocular camera based methods. In this paper we implement an indoor augmented reality system based on Project Tango developed by Google. This system is able to construct the 3D environment and reuses the constructed data to relocalize the mobile device. The constructed 3D point cloud can be transformed to the map data, and let the system estimate the navigation path. With the accurate pose estimation provided by Tango, the augmented reality content can keep the original position after a long distance movement.
All Roads Lead to UD: Converting Stanford and Penn Parses to English Universal Dependencies with Multilayer Annotations

We describe and evaluate different approaches to the conversion of gold standard corpus data from Stanford Typed Dependencies (SD) and Penn-style constituent trees to the latest English Universal Dependencies representation (UD 2.2). Our results indicate that pure SD to UD conversion is highly accurate across multiple genres, resulting in around 1.5% errors, but can be improved further to fewer than 0.5% errors given access to annotations beyond the pure syntax tree, such as entity types and coreference resolution, which are necessary for correct generation of several UD relations. We show that constituent-based conversion using CoreNLP (with automatic NER) performs substantially worse in all genres, including when using gold constituent trees, primarily due to underspecification of phrasal grammatical functions.
Discovering Organizational Elements for IT Service Brokering from a Literature Review

New technological trends and models are allowing organizations to easily access to specialized external IT services. As a consequence, IT areas are developing fewer and fewer IT services and relying more on external providers to achieve their customers’ objectives. In this new context, the IT function should move from its traditional role of service builder and operator to a new role of service integrator and broker. However, IT areas are not aware of the organizational elements that need to be implemented to adopt this new role. In order to compensate this lack, this work presents a review of the existing literature intended to identify IT capabilities, roles, skills and strategies that can help IT organizations to act as a service broker. Our findings aim at establishing the basis for a complete approach.
LIPI: A Custom Object Oriented Interpreted Programming Language

In Computer Science jargon, an interpreter typically implies a computer program that prosecutes the instructions written in a particular programming language. A Computer programming language provides the necessary rudimentary rules and norms to be employed to draft a set of instructions that will be executed using an interpreter in this case. Lipi is a programming language designed to demonstrate paradigms not found in other programming languages. Lipi incorporates the functionality as that of Java coupled with simple syntax like Python. Lipi is different and better from the existing programming languages in the sense that it provides the developer with a sense of freedom and flexibility in developing a piece of code with the inclusion of features like advanced generics bounding, pluggable reserved words, superior reflection with system listeners, custom lambda declarations coupled with a comprehensive object-oriented nature. We believe that this language would be complete when it will be able to parse itself. From the successful implementation of the initial phase of the language, we are confident that this language will be adopted by experienced as well as novice programmers for development purposes in near future.
Forecasting Stock Price Using Partial Least Squares Regression

Financial markets are systems where buyers and sellers interact and various transactions of ownership claims (stocks) takes place. These transactions are made with the base purpose of earning profits, but the biggest problem with these transactions is that the profit depends on the rise in the prices of the stock and one may suffer loss if the price goes below the price at which the stock was initially purchased. The objective of preparing this model is to treat the market as a mathematical problem and try and use statistical algorithms to make the behavior of the market somewhat predictable and since data mining tools can be very effective in predicting future trends and preferences allowing decision makers to make forecasting on the data from the past. This study describes a model built for predicting the behavior of certain stocks based on their behavior in past.
Stabilization of Time-Delayed Power System With Combined Frequency-Domain IQC and Time-Domain Dissipation Inequality

Time delay is prejudicial to power system stability and generally worsens the performance of a control system. In this paper, the approaches for stability analysis and stabilization of a power system consisting of time-varying delay are established. The paper starts with the modeling of the power system according to time-delay differential algebraic equations. An integral quadratic constraints (IQC) method is constructed to guarantee the stability of the proposed feedback controller. The frequency-domain IQC and time-domain dissipation inequality are effectively combined to perform stability analysis and stabilization of the power system considering time delays, without complex numerical computation. A two-area four-machine system, an IEEE 10-machine 39-bus system, and a WECC 179-bus system are employed to support the stability criteria and the IQC method. The simulation results indicate that the combined methods effectively damp the oscillation and improve the performance.
A Comparative Study of Security Features Provided by Different Cloud Services to Enterprises

Cloud computing is a rapidly growing technology which offers enterprises to outsource their data and software to the cloud server while enabling them to respond to the changes occurring in technology and operational environment. Organizations are expected to pay as per their use while utilizing the service offered by cloud service providers (CSP). But the main concern while outsourcing their data to the CSP is security which needs to be addressed since their data will be processed by the third party cloud. This paper presents comparison of the services provided by three renowned CSP. Also this research study facilitates an enterprise to choose the best CSP based on the most important security parameter.
Short-term colour vision plasticity on the reef: changes in opsin expression under varying light conditions differ between ecologically distinct fish species

ABSTRACT Vision mediates important behavioural tasks such as mate choice, escape from predators and foraging. In fish, photoreceptors are generally tuned to specific visual tasks and/or to their light environment, according to depth or water colour to ensure optimal performance. Evolutionary mechanisms acting on genes encoding opsin, the protein component of the photopigment, can influence the spectral sensitivity of photoreceptors. Opsin genes are known to respond to environmental conditions on a number of time scales, including short time frames due to seasonal variation, or through longer-term evolutionary tuning. There is also evidence for ‘on-the-fly’ adaptations in adult fish in response to rapidly changing environmental conditions; however, results are contradictory. Here, we investigated the ability of three reef fish species that belong to two ecologically distinct families, yellow-striped cardinalfish (Ostorhinchus cyanosoma), Ambon damselfish (Pomacentrus amboinensis) and lemon damselfish (Pomacentrus moluccensis), to alter opsin gene expression as an adaptation to short-term (weeks to months) changes of environmental light conditions, and attempted to characterize the underlying expression regulation principles. We report the ability for all species to alter opsin gene expression within months and even a few weeks, suggesting that opsin expression in adult reef fish is not static. Furthermore, we found that changes in opsin expression in single cones generally occurred more rapidly than in double cones, and identified different responses of RH2 opsin gene expression between the ecologically distinct reef fish families. Quantum catch correlation analysis suggested different regulation mechanisms for opsin expression dependent on gene class. Summary: Opsin expression in adult specimens of three reef fish species belonging to two ecologically distinct families show different adaptive mechanisms to changes in available environmental light.
Stator Winding Internal Thermal Monitoring and Analysis Using In Situ FBG Sensing Technology

This paper reports a novel thermal monitoring scheme for on-line internal temperature measurement in low-voltage random wound machine stator windings. The scheme is based on utilizing electrically nonconductive and electromagnetic interference immune fiber optic sensing technology embedded in close proximity of hot spots of interest to create a robust distributed thermal monitoring network within the machine windings. The key design and implementation features of the proposed system are presented and applied on a prototype mains-fed induction motor. The on-line thermal monitoring performance is examined in a number of typical continuous and periodic running duty tests, as defined by the relevant IEC standards for rating and performance of rotating electrical machines. It is shown that the presented scheme has the potential to provide competent on-line measurement of critical machine thermal hot spots that are largely beyond the effective reach of conventional thermal monitoring solutions. Furthermore, the proposed scheme underpins a higher fidelity understanding of the distribution and propagation of winding thermal stress, demonstrated by the experimental analysis reported in the paper.
Investigating Attributes that Characterize Important Classes in Object Oriented Systems

Software engineers can do tasks of maintenance and evolution of complex software systems only after they understand well the existing code. Our goal is to build automatic tools to help program comprehension by detecting and recommending the most important classes of the system. In this work we identify all the attributes that characterize important classes in object oriented systems and evaluate which attributes can be used with best results for identifying these classes.
Performance Evaluation of Batch Scheduling Strategy with Precedence Constraints for Computational Grid

Computational grid is computation platform of geographically distributed heterogeneous computational machines which can be accessed by needy users via a single interface. Efficient scheduling is the core concern in computational grid for achieving the user's need with optimizing Quality of Service (QoS) parameters. The mapping problem of batch of jobs onto computational nodes with heterogeneities optimizing QoS with precedence constraints in grid had been manifested as NP-Complete. Present study presented the Precedence based Batch Scheduling Strategy (PBSS) in which independent jobs in the batch are considered of having noncommunicating modules with precedence constraints represented by Direct Acyclic Graph (DAG). A comparative performance analysis is done to evaluate the significance of PBSS with its peers for the middleware.
Network Reconstruction and Controlling Based on Structural Regularity Analysis

From the perspective of network analysis, the ubiquitous networks are comprised of regular and irregular components, which makes uncovering the complexity of network structures to be a fundamental challenge. Exploring the regular information and identifying the roles of microscopic elements in network data can help us recognize the principle of network organization and contribute to network data utilization. However, the intrinsic structural properties of networks remain so far inadequately explored and theorised. With the realistic assumption that there are consistent features across the local structures of networks, we propose a low-rank pursuit based self-representation network model, in which the principle of network organization can be uncovered by a representation matrix. According to this model, original true networks can be reconstructed based on the observed unreliable network topology. In particular, the proposed model enables us to estimate the extent to which the networks are regulable, i.e., measuring the reconstructability of networks. In addition, the model is capable of measuring the importance of microscopic network elements, i.e., nodes and links, in terms of network regularity thereby allowing us to regulate the reconstructability of networks based on them. Extensive experiments on disparate real-world networks demonstrate the effectiveness of the proposed network reconstruction and regulation algorithm. Specifically, the network regularity metric can reflect the reconstructability of networks, and the reconstruction accuracy can be improved by removing irregular network links. Lastly, our approach provides an unique and novel insight into the organization exploring of complex networks.
Biopolymers for Sensor and Electrical Applications

Using biopolymers for electrical applications is a fast-growing field. In this area, little work was published concerning the biopolymer collagen or its denaturized form gelatin. However, these biopolymers have interesting properties and a commercially competitive price. In the paper at hand, we engage the development of electrical conductive biopolymers for electrical applications as a part of the research project bioESens at the University of Applied Science Dresden. The focus of our research is the examination of sensory effects and the usability in the thick film- and blade coating technology. To be more precisely, we discuss the possibility of a new setup to measure the electrical conductivity of sensor samples and present results of our development of a conductive collagen/gelatin system. In a first stage, the low intrinsic conductivity of this biopolymer should be increased. One approach is to use conductive additives like Carbon black [1]. Our goal is to achieve a minimum conductivity level of 10−2 S/m. However to optimize the viscosity of the additive biopolymer composition, investigations are necessary to assess the processability of a filled polymer. Furthermore, the impedance shall be examined, which can be dependent on temperature or humidity. For that, it is necessary to investigate possible disturbance values. One of this is the contact resistances between the polymer and the cooper pads. Therefore, a measurement setup was constructed. It allows testing of the conductivity of sensor samples with a broad variety of contact setup for subsequent investigations.
Network-In-a-Box: A Survey About On-Demand Flexible Networks

One of the key features of next-generation mobile networks is the ability to satisfy the requirements coming from different verticals. For satisfying these requirements, 5G networks will need to dynamically reconfigure the deployment of the network functions. However, the current deployments of mobile networks are experiencing difficulties in exhibiting the required flexibility. At the same time, the research on connectivity provisioning in use cases such as after-disaster scenarios or battlefields has converged toward the idea of Network-In-a-Box. This idea revolves around fitting all software and hardware modules needed by a mobile network in a single or a handful of physical devices. A Network-In-a-Box inherently offers a high level of flexibility that makes it capable of providing connectivity services in a wide range of scenarios. Therefore, the Network-In-a-Box concept represents an alternative approach for satisfying the requirements of next-generation mobile networks. In this survey, we analyze the state-of-the-art of Network-In-a-Box solutions proposed by academia and industry in the time frame starting from 1998 up to early 2017. First, we present the main use cases around which the concept has been conceived. Then, we abstract the common features of the Network-In-a-Box implementations, and discuss how different proposals offer these features. We then draw our conclusions and discuss possible future research directions, including steps required to reach an even higher level of flexibility. The aim of our analysis is twofold. On one hand, we provide a comprehensive view of the idea of Network-In-a-Box. On the other hand, through the analysis, we present the features that future mobile networks should exhibit to achieve their design goals. In particular, we show how the Network-In-a-Box fosters the transition toward the next-generation mobile networks.
Consensus-Based Droop Control of Isolated Micro-Grids by ADMM Implementations

Due to low inertia, high penetration of renewable generators in isolated micro-grids may result in poor frequency and voltage response under large disturbances. In order to overcome this difficulty, the distributed average consensus algorithm has been studied recently by extending local droop control mechanisms of power converters into distributed droop control. However, its convergence rate and the resilience to noises are still not satisfactory. In this paper, two implementations of consensus-based distributed droop control by the alternating direction multipliers method are proposed. It can be shown that the closed-loop system is described by the second-order vector differential equation, and the stability of every trajectory can be analyzed by the energy function approach under certain mild conditions. Real-time digital simulations are performed to validate the effectiveness of the proposed distributed droop control mechanism.
Active Haptic Control for a Biologically Inspired Gripper in Reconfigurable Assembly Systems - Testing Active Haptic Control through Force Feedback

Haptic feedback for flexible grippers enhances control over human-machine interaction and object manipulation. Force feedback control through a haptic sensory system enables gripping sensitivity for the grasping of fragile components. The development of intelligent gripping systems has the potential to be implemented in Reconfigurable Assembly Systems, (RAS), for on-demand production lines. Advancements in object control and successful object handling for assembling systems were investigated. An active haptic control system was developed to assess the adaptability of gripper appendage grip force through a dynamic pick and place movement. The aim was to determine the force output from a self-adjusting grasping procedure using a haptic feedback control sensory system. The force output data was empirically collected and plotted on a signal verse time graph. The voltage signal representing the actual grasp force throughout a gripping procedure. The testing was performed on a previously manufactured gripper based on a biologically inspired phenomenon called the Fin Ray Effect®. Conclusions and recommendations were made in relation to effective grip force control.
E- learning based on Cloud Computing technology

Today and during the recent years, Cloud computing is growing rapidly, with applications in almost any area, including education. Internet now a days is accessible from maximum telecommunication devices like desktops, laptops, tablets, mobiles, Music players, I-Pad, I-Pods etc making it more distributed compare to any centralized entity. E learning systems usually require many hardware and software resources and the cloud computing offer all facilities that the E_learning needs and it an ideal technology to use in the learning Cloud computing has helped the facades of Elearning functions particularly in achieving flexibility, efficiency and costly like never before. the cloud computing is the good choice for Elearning to provide the facilities and services of the learning.
Survival of Campylobacter jejuni and Campylobacter coli water isolates in lake and well water

The role of water for transmission of Campylobacter jejuni and C. coli to humans might be underestimated, as factors important for bacterial viability in water are largely unknown. We have studied water survival of seven C. jejuni and eight C. coli isolates originally isolated from Swedish waters, together with selected reference strains, over eight days at 4 °C in the dark in untreated water collected from a local lake and a private well. To study seasonality, lake water samples were collected during spring and autumn. Samples for culturable bacterial counts were taken on days 2, 4, 6, and 8 and compared to the start inoculum. For C. jejuni, a significantly better survival was observed in autumn than in spring lake water. Furthermore, C. jejuni had a significantly better survival than C. coli in autumn lake and well water samples; the rate of culturability loss was almost double for C. coli in autumn lake water. These findings contribute to a better understanding on the seasonality of waterborne Campylobacter infections and the general predominance of C. jejuni.
Using Measured Hysteresis Loop Family in Calculating the Eddy Current Losses

In the paper, the effect of hysteresis on the macroscopic eddy current losses is tested. Usually, the macroscopic eddy current losses are calculated with nonlinearity and magnetic hysteresis phenomenon neglected. The aim of the research was to check how magnetic hysteresis affects the eddy current losses. To achieve this, an algorithm able to take into account the hysteresis was previously constructed. The tests on various magnetic materials showed that the algorithm was only convergent for electrical sheets of small enough thickness. Moreover, the hysteresis loops in the algorithm have to be regular enough in order to convert between Band $H$ fields in the way ensuring the convergence. In this paper, an enhanced algorithm is presented, which is able to take into account a wider class of hysteresis loop families and its convergence is improved. The results of calculations show that including the measured hysteresis loop family into calculations yields usually noticeably smaller eddy current losses than those predicted with use of the classical formula.
Mixed Reality Glasses: Low-Power IoT System for Digital Augmentation of Video Stream in Visual Recognition Applications

Mixed Reality (MR) is a promising technology in the scope of Internet of Things for a number of visual recognition applications including professional training, medical applications and geodesy. However, the state-of-the-art approaches require extra facilities for the visualization and positioning of the virtual objects in the real world. In this work, we propose the approach for video stream augmentation which relies solely on the positioning of virtual objects referenced to the absolute reference frame. This approach can be applied to a dynamic platform with six dimensions of freedom. For testing purposes, we design fully autonomous MR glasses based on low-power embedded systems and demonstrate the representation of a dot, line and cube in the glasses. Experimental results demonstrate that the proposed approach is successfully realized on the experimental testbed.