Miracle-dz/UniFAR-FTUs huggingface dataset:
28.3 A 125MHz-BW 71.9dB-SNDR VCO-based CT ΔΣ ADC with segmented phase-domain ELD compensation in 16nm CMOS

High-BW continuous-time ΔΣ modulators (CTDSMs), which directly inject excess loop delay compensation (ELDC) at the quantizer input, suffer from the over-range issue due to the 1+αz−1 transfer function of the local feedback loop, where α is the zero-order path coefficient [1–2]. For example, the swing or number of quantization levels will be doubled if α=1 is chosen. On the other hand, injecting the compensation current at the input of the last integrator requires an additional DAC and extra power to minimize excess phase shift [3]. The phase-feedback VCO-based integrating quantizer (VCOIQ) in [4] suggests a unique feature to compensate ELD in the phase domain. In this work, the VCO outputs are rotated directly in the digital domain to implement phase-domain ELDC (PD-ELDC) [5] without overloading any previous stages. Though VCOIQ is essentially a time-domain flash quantizer with a potentially higher number of quantization levels than voltage-domain counterparts, prior work utilized 5b or less when embedded within a CTDSM. The requirement of the low-complexity thermometric DAC limits the maximum number of bits that can be used to fulfill the SQNR specification. In this work, rotating splitters (RSPT) and a segmented DAC are used to increase the VCOIQ resolution to 7b. This arrangement decouples VCOIQ optimization from DAC design constraints and fully exploits the advantage of time-domain quantization. By leveraging the techniques mentioned above, this CTDSM achieves 125MHz BW while operating at 2.15GHz. The measured SNDR/DR are 71.9dB/74.8dB at the input frequency of 1/3 BW.
Adaptive interaction robot control with estimation of contact force

Abstract This paper deals with a new adaptive force-position control of a robotic manipulator based on force estimation. First, an adaptive position controller is derived with contact force component as estimated parameters. Second, a supervisory external loop is added in order to regulate the contact force to the desired value. Extensive simulations with 2-DOF manipulator illustrate the followed approach.
STEM and Educational Robotics Using Scratch

Educational robotics applied to STEM (Science, Technology, Engineering, and Mathematics) activities combined with a project-based learning (PBL) methodology provides quite good results. Throughout this work it is described how to make use of Scratch, a visual programming environment, as a cost-effective tool with great potential for students to work on concepts related to robotics. When students work with Scratch, they can develop animations or video games in which real life applications are simulated. In this paper you can find the description of the intermediate Scratch module. This module is part of an introductory robotics course consisting of the use of three tools (Scratch, Crumble and Arduino) and three difficulty levels (basic, intermediate and advanced). In addition, the results obtained for the Intermediate Scratch module and a discussion of the most important aspects related to the findings obtained are also provided.
Computational Modeling of the Atomizing of a Gas Stream from a Pneumatic Nozzle

Atomizing of liquid is widely used in modern technology. Atomizing occupies an extremely important place in power engineering, when burning liquid fuels. In this work provides verification of the method for modeling the atomizing of a gas-liquid stream from a pneumatic nozzle. Primary atomization is modelled using Large Eddy Simulation model (LES) and The Volume Of Fluid model (VOF). The results of the calculations show an acceptable agreement with experiment on the main characteristics of the spray. The results of calculations can be very useful for estimations, since they allow qualitatively correct determination of the structure of a two-phase flow, parameters and shape of droplets, and the speed and direction of their motion, which in principle can not be obtained by other methods.
A Secure Data Getting/Transmitting protocol for WSN in IoT Using Revocable Storage Identity Based Cryptography

Security is one of the important properties and it plays a vital role in all area even in human life. Wireless Sensor Node (WSN) is connected by means of the Internet of Things (IoT). The IoT is very keen towards the area of security research. In our work, we clearly discuss the concept of data transmission in IoT devices or IoT systems. When a data get transmitted from sensor node to client it can be theft by some intruders there exist lack of security. In order to overcome this issue, the security concept of revocable storage identity-based encryption was defined and used here. The wireless sensor nodes were employed here with the internet for data transfer and there exist some security protocol to avoid interrupting. We had proposed a system called revocable storage identity-based encryption technique where it provides a valid secret key to transfer data from sensor node to client for a particular session period. The main advantage of using this concept which will reduce the complexity of the encryption process for both the sensor node and the client. With the help of this technique, the system gets protected and high level of security is enhanced.
A study of network infrastructure optimization for data center servers

Data center plays an important role in cloud computing. Cloud computing provides novel perspectives in Internet technologies and raises issues in the architecture, protocol, and implementation of existing networks and data centers. Although various cloud-based data center architectures have been proposed in recent years, some challenging issues, e.g., congestion control, load balancing and energy efficiency, still need to be addressed. In this paper, we present the designs of network architecture for data center servers, and then analyze and compare several promising solutions to tackle those challenging problems.
Influence Maximization Problem Approach to Model Social Networks

One of the significant problems in Social Net-works (SN) analysis is how to find the best influential members. This problem was proved to be non-deterministic polynomial (NP-hard). The influence maximization (IM) problem in SNs aims to maximize the spread of influence in the network. It represents an optimization problem. IM is a fundamental research problem in social networks. Influence maximization problem is the problem of assigning a subset of k users as (seed nodes) in a graph that could maximize the spread of influence by maximizing the expected number of influenced users. It represents a key algorithmic problem in social influence analysis. In this study, centrality-based methods are utilized to select top k nodes of high centrality values. The degree centrality is used to select the opinion leaders, while the between-ness and Eigenvector centrality is used to select the early adopters. The degree discount (as a heuristic approach) is proposed to replace the Greedy algorithms applied in other studies to avoid the time complexity. A mixed diffusion model (replacing the linear threshold and independent cascade) is utilized to be main diffusion model in this study.
Comparison between Classic Control Systems Techniques against Adaptive and Nonlinear Control Techniques in a Lower Limb Prostheses

Foot prosthesis have been well documented, not one has successfully developed and verified that such a prosthesis can improve amputee gait compared to a conventional passive A Previous Work elastic prosthesis. One of the main hurdles that hinder such a development is the challenge of building an ankle-foot prosthesis that matches the size and weight of the intact ankle, but still provides a sufficiently large instantaneous power output and torque to propel an amputee [1–2]. A large number of motorized prototypes have been developed in prosthetic systems, the actuators, sensors and architectures developed have improved the performance of these for human walking in users who have this motor impairment, however the surgical technique used for amputation as well as the control techniques implemented have not had notable progress. This paper presents the design and simulation of the control system for a lower limb prostheses. Three control methods were compared (PD Classic Controller, Model Reference Adaptative Control (MRAC), and sliding mode control) and the behavior of the model was studied after its linearization and its identification through the matlab toolbox.
An Intrusion Detection Approach Based On Analysis Of Cluster Heterogeneity

The security of prodigious proportion of variegated information available in computers, connected by a network, can be procured by the employment of suitable Intrusion Detection Systems (IDS). In this paper, a novel intrusion detection approach has been presented that relies on analysing the heterogeneity of clusters formed by reducing the dimensions of data points. The class dominance in each cluster devises the premise of initial classification, which is followed by the appraisal of cluster confidence and cluster spread. The final refined detection is ensured based on the criteria, formulated by these parameters. Experiment conducted on the widely documented KDD Cup '99 dataset infers the efficacy of the approach in terms of high accuracy and low false alarm rates. The robustness and effectiveness is also parametrized by the run time analysis of the system.
Content Popularity Prediction Methods - A Survey

Prediction or the forecasting is the way of describing the future event in an efficient manner. Prediction can be used in actuarial science, marketing, child protection, financial services, travel, insurance, telecommunications, retail, mobility, healthcare, pharmaceuticals, capacity planning and other fields. One of the most widely used areas is social networking.So, Social media has an explosive growth of information allowing more users to become content creators and distributors of the web content. So, there exists an online competition, since a few items are getting popular and the remaining items are getting unpopular.Predicting the popularity is very useful in network dimensioning such as caching and replication. In this paper, we present a survey about content popularity methods in various network architectures with various functionalities and present the features that have good forecasting capacity.
Performance and Reliability Aspects of Clock Synchronization Techniques for Industrial Automation

Modern distributed control systems comprise multiple intelligent devices capable of performing complex time and mission-critical tasks both independently of each other or partly jointly with each other. To do so, they strongly depend on an accurate common notion of time as well as a reliable shared communication medium for timely data exchange. Traditional legacy communication technologies (field bus systems) supported time transport to a certain extent or provided at least a common frequency. Due to its numerous undisputed advantages, Ethernet has become the only viable communication medium effectively replacing such systems. Being inherently asynchronous time and frequency transfer has to be accomplished using a packet-based approach when moving to Ethernet. After explaining the basic principles of packet-based time transfer, the most common standards are explained compared with each other with respect to their intended application domains. Special emphasis will be put on the Precision Time Protocol (PTP) as defined in the underlying IEEE 1588 standard and its variant IEEE 802.1AS used for time-sensitive networks. Maintaining a highly accurate common notion of time under all circumstances is a crucial prerequisite for most distributed systems. Although PTP has proven to provide sub-microsecond accuracies, it can cope only with a limited number of error conditions. This paper describes all major sources that can either deteriorate the accuracy or cause a total loss of synchronization altogether. Selected countermeasures and enhancements are presented, which can greatly improve the resilience of PTP against errors as well as malicious attacks. This paper concludes by presenting the selected measurements’ results of a novel proposed method.
Design of linear observers for a class of linear hybrid systems

This paper deals with the design of linear observers for a class of linear hybrid systems. Such systems are composed of continuous-time and digital substates and possess, in general, coupling dynamics between both substates. The discrete extended state is composed of the sampled values of the continuous substate at sampling instants and the digital substate. The estimation of the continuous substate in between sampling instants is made by using the plant parametrization and the sampled prediction error at the preceding sampling instant. The continuous-time state estimates are re-initialized at each new sampling instant by taking values from the corresponding components of the discretized substate of the observer of the auxiliary discrete extended system. The exponential convergence to zero of both prediction and observation errors may be ensured under observability and detectability assumptions in both observation prototypes. Furthermore, prescribed pole-placement of the state estimation error is achieved under observability of the discrete extended plant. Also, prescribed pole-placement of the combined dynamics of the extended plant and observation error can be obtained.
Replay Attack Detection in Speaker Verification Using non-voiced segments and Decision Level Feature Switching

This paper proposes a novel approach for replay attack detection, using reverberation and channel information from non-voiced (silence and unvoiced) segments of utterances. The non-voiced segments are determined using a voice activity detector. These non-voiced segments are likely to contain reverberation and channel information. Multiple feature representations are used to capture the remnant vocal tract information in non-voiced segments. Gaussian mixture models are used to build three different baseline systems corresponding to that of three different features. Voting is performed to decide whether a given input utterance is replayed or not. Equal error rate (EER) is computed using the likelihood ratio of the genuine and spoofed model from the best baseline system. Evaluation on the ASV-Spoof-2017 challenge dataset shows that the proposed approach outperforms the best baseline system with a relative improvement of 37% in terms of EER.
Estimating Confidence for Deep Neural Networks through Density modeling

State-of-the-art Neural Networks can be easily fooled into providing incorrect high-confidence predictions for images with small amounts of adversarial noise. Does this expose a flaw with deep neural networks, or do we simply need a better way to estimate confidence? In this paper we consider the problem of accurately estimating predictive confidence. We formulate this problem as that of density modelling, and show how traditional methods such as softmax produce poor estimates. To address this issue, we propose a novel confidence measure based on density modelling approaches. We test these measures on images distorted by blur, JPEG compression, random noise and adversarial noise. Experiments show that our confidence measure consistently shows reduced confidence scores in the presence of such distortions - a property which softmax lacks.
Ferroresonance Mitigation in an Inductive Voltage Transformer Using Memristor Emulator

The development of advanced digital technologies often struggle in their promising performances. The failure report of a substation includes the performance of instrument transformers definitely. The overvoltages and overcurrents developed during transients especially ferroresonance, marked the degrading performance of a voltage transformer though it has a suppression circuit. Memristors are nonlinear resistors capable of remembering their previous resistance, which might help to replace the system resistors in many applications. In this paper, this hopeful technology of the future has been attempted to mitigate the ferroresonance phenomenon of inductive voltage transformers. A single phase 100 VA, (11kV/✓3)/ (110V/✓3) Inductive Voltage Transformer (IVT) was used to analyze the ferroresonance performance. The jump up and down phenomenon observed was the indicator of the ferroresonance inception. An overvoltage of 1.34 pu was developed and suppressed using a memristor emulator successfully. The mitigation results of the memristor emulator proved its better performance when compared with that of a linear resistor.
A Result Evaluation Based On Privacy Preserving Using Unified Security Methods (PPUSM)

Cloud computing is defined as a model to access shared computing resources through network in a manner which is ubiquitous, on demand, requires less time for provision and release of resources and requires minimum intervention of management authorities. With such flexibility there arise two problems of data privacy and data security which are open research problem. The first problem of privacy says that how a user’s data can be stored such that only authorized persons gets access to it. The problem of security demands the security of data in such a manner that not only on storage but also in between transition of data on network the data will be useless for intruders. In this paper we address both of the problems simultaneously. Specifically, we present a model for privacy and security such that the security is provided by encrypting the data at the owner end and then putting it on the cloud while the privacy is provided by a secured key exchange between the owner and the user. Our model is such that the data remains in the encrypted form throughout the cloud, including network access and hence there is no chance of its misuse.
The “Bachelor Project”: Project Based Computer Science Education

One of the challenges of educating the next generation of computer scientists is to teach them to become team players, that are able to communicate and interact not only with different IT systems, but also with coworkers and customers with a non-it background. The “bachelor project” is a project based on team work and a close collaboration with selected industry partners. The authors hosted some of the teams since spring term 2014/15. In the paper at hand we explain and discuss this concept and evaluate its success based on students’ evaluation and reports. Furthermore, the technology-stack that has been used by the teams is evaluated to understand how self-organized students in IT-related projects work. We will show that and why the bachelor is the most successful educational format in the perception of the students and how this positive results can be improved by the mentors.
Re-Architecting NFV Ecosystem with Microservices: State of the Art and Research Challenges

Network Function Virtualization (NFV), considered a key enabler of network "softwarization", promises to reduce capital and operational expenditures for network operators by moving packet processing from purpose-built hardware to software running on commodity servers. However, the state-of-the-art in NFV is merely replacing monolithic hardware with monolithic VNFs, the software that realizes different network functions (e.g., firewalls, WAN optimizers, and so on). Although this is a first step toward deploying NFV, common functionality is repeatedly implemented in monolithic VNFs. Repeated execution of such redundant functionality introduces processing overhead when VNFs are chained to realize Service Function Chains and leads to sub-optimal usage of infrastructure resources. This stresses the need for re-architecting the NFV ecosystem, from VNFs to their orchestration, through modular VNF design and flexible service composition. In that perspective, we make the case for using the microservice software architecture, proven to be effective for building large-scale cloud applications from reusable and independently deployable components, to re-architect the NFV ecosystem. We also discuss the state-of-the-art in realizing modular VNFs from both industry and academia. Finally, we outline a set of research challenges for microservice-based NFV platforms.
Probabilistic Occupancy Filter for Parking Slot Marker Detection in an Autonomous Parking System Using AVM

Many car makers have examined parking assistance systems and auto parking systems that automatically find free parking spaces and can park a car. The around view monitoring (AVM) can compensate for the disadvantages of distance-sensor-based detection because it can recognize parking spaces based on parking slot markers instead of empty spaces. However, in the case of AVM-based parking marker recognition, false-positive (FP) features can be detected from 3-D objects and shadows, and the parking slot marker is occluded by the vehicle on which the AVM camera is attached. In this paper, we propose a probabilistic occupancy filter to detect parking slot markers. This filter uses a series of AVM images and onboard sensors to improve the occlusion problem and reduce the FPs from other objects. Each pixel of an AVM image has an occupancy probability of parking slot marker features. The occupancy probability compensates for using vehicle motion and updates using the error model of the AVM system and the performance indicator of the feature extractor.
A Knowledge Based System for Automated Assessment of Short Structured Questions

Assessment is a key tool of the educational system to gauge the level of understanding of students. Assessment is traditionally carried out through various mediums ranging from written evaluations to oral evaluations or even through practical sessions in some cases. Over the years, it has been noticed that the level of education is escalating and that academic competition is growing fiercer. Thus, educational institutes are faced with the need to upgrade their process of assessment. Although assessment is an essential part of the educational process, the correction of structured questions represents a substantial portion of an instructor’s worktime. Besides, with the increase in cohort size throughout institutions and the popularity of Massive Open Online Courses (MOOCs), this problem seems to worsen. Teachers are therefore faced with a conundrum; they can either devote their time to the correction of scripts or to teaching activities. According to research, computerized marking give rise to faster correction and it saves staff time in terms of supervising and marking. In this context, a knowledge based automated assessment system has been developed to help correction and grading of short structured questions online. The system will compare the meaning of two sentences by taking into account both semantic and syntactic content and the corresponding grade will be returned.
Bit Error Rate Measurements for distance and household impact on PLC link

Power Line Communication (or PLC) enables the construction of a computer network on the electrical network. This work aims to study the impact of the electrical network topology on the performance of the Power Line Communication link in terms of different parameters that are achieved by using a measurement test bed. This measurement test bed consists of assessing the frequency channel response over the electrical network for several scenarios. These channel's responses will be convolved to an OFDM frame in order to evaluate performances in term of Bit Error Rate (BER). These scenarios aim to study the influence of the relative distance between the transmitter and receiver, and the number of howsehold loads connected to the electrical network, for MIMO and SISO cases.