2017. 3rd Issue

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PAPERS FROM OPEN CALL

István Pelle, Felicián Németh and András Gulyás
A Little Less Interaction, A Little More Action: A Modular Framework for Network Troubleshooting  
Requirements of an ideal network troubleshooting system dictate that it should monitor the whole network at once, feed results to a knowledge-based decision making system and suggest actions to operators or correct the failure, all these automatically. Reality is quite the contrary, though: operators separated in their cubicles try to track down complex networking failures in their own way, which is generally a long sequence of manually edited parallel shell commands calling rudimentary tools. This process requires operators to be "masters of com- plexity" (which they often are) and continuous interaction. In this paper we aim at narrowing this huge gap between vision and reality by introducing a modular framework capable of (i) formalizing troubleshooting processes as the concatenation of executable functions [called troubleshooting graphs (TSGs)], (ii) executing these graphs via an interpreter, (iii) evaluating and navigating between the outputs of the functions and (iv) sharing troubleshooting know-hows in a formalized manner.
 

Sagar Arun More and Pramod Jagan Deore
View-Invariant Person Identification by Orthogonal View Gait Signature and Fusion of Classifiers  
In this paper, we proposed the use of three orthogo- nal views of gait signature for view-invariant person identification system. We also experimented the fusions of classifiers in order to improve the recognition performance. Two classifiers used corresponding to two LDA spaces. The first classifier used for angle classification followed by second classifier for person identification. The proposed mechanism of selective kNN (s-kNN) has boosted the recognition performance and found very effective. We got 97.07% maximum rank-1 angle classification accuracy and 93% maximum rank-1 person identification accuracy.
 

Haiqing Liu, Shuhua Hao, Yuancheng Li, Xiang Li and Jie Ma
Live face detection method based on local binary pattern and bandelet  
Face recognition system is exposed to video replay attacks and photo spoofing attacks along with the extensive use of identity authentication technology. Spoofing attack happens when an attacker tries to disguise as a legitimate user with permissions to spoof authentication system by replaying the recorded videos of legitimate users or utilizing the printed photos of legitimate users. Inspired by the differences between image acquisition and playback, printing properties, and light emission models, this paper proposes a live face detection method based on local binary pattern and Bandelet. The replayed video images and the printed face images usually contain characteristics that are easy to be detected by texture detection and frequency domain analysis. The proposed method analyzes the differences between live faces and photo faces in texture, at the same time it utilizes Bandelet to analyze face images with multi-scale analysis and extracts the high-frequency sub band coefficients as feature vectors to train Extreme Learning Machine (ELM) to classify and recognize. The algorithm is verified on the public CASIA_FASD, print-attack and replay-attack datasets, well known Face Anti-Spoofing Databases, and the experimental results show that the method reduces the computational complexity and improves the detection accuracy.
 

PAPERS OF APPLIED RESEARCH

Tamás Helfenbein, Roland Király, Márton Törőcsik, Emil Tóth and Sándor Király
Extension of RFID Based Indoor Localization Systems With Smart Transponders  
The indoor localization problem is a method of identifying and finding position (co-ordinates) of requested objects in a well defined area of interest (AoI) in buildings. Beside identification, localization is an important task in several complex industrial environments. Assigning unique Radio Frequency IDentifier (RFID) tags to the objects both the identification and the localization problem can be solved.
In this paper, RFID based indoor localization systems, methods, and protocols are analysed. A novel Smart Tag platform called Blackforest with integrated self localization capabilities is introduced. This device can be in either transmitter or receiver role to ensure fast prototyping of localization environments. Higher temporal positioning possibilities and sensor fusion techniques are introduced using the BlackForest nodes. The radiofrequency (RF) characteristcs of the device were analyzed and a localization system was built using Blackforrest nodes. The localization architecture, methods and system configurations are described. After calibration, the suitable accuracy of RFID indoor localization using BlackForest Smart Tags is proven in an indoor office scenario.
A hierarchical localization protocol stack is introduced in order to extend existing indoor RFID localization systems using intelligent and co-operative antenna systems with novel Smart-Tags.
 

 

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2017. 2nd Issue

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PAPERS FROM OPEN CALL

Dmitrii I. Popov and Sergey M. Smolskiy
Optimization of the digital rejection filter  
The digital rejection filter (RF) is offered in the form of the device for substraction of weighted samples in the non-delayed channel and results of group accumulation of samples in the delayed channel. The RF optimization task is considered with the group sample accumulation in the delayed channel. The optimal relationships between RF parameters and correlation properties of interference are discussed, which corresponds to minimum of interference remainders. The influence of bit grid finiteness of the analog-to-digital converter (ADC) on effectiveness of interference rejection is studied. The expression is suggested for the minimal number of bits, which can be used for a choice of ADC type with account of given losses in effectiveness of interference rejection and required operation speed. The RF adaptation principles under condition of a priori uncertainty of interference correlation parameters are discussed. The analysis of the adaptive RF effectiveness is carried out depending on correlation properties of interference and the volume of the learning sample. From relations obtained, it follows that losses in effectiveness of  interference rejection, which are caused by adaptation errors, can be restricted in advance by the given value by means of appropriate choice of the learning sample volume.
 

Csaba Simon, Miklós Máté, Markosz Maliosz and Norbert Bella
Ethernet with Time Sensitive Networking Tools for Industrial Networks  
In currently deployed networks the time critical and/or real time traffic is sent over dedicated networks, requiring the operation of a separate infrastructure. This is especially true for Industrial Networks, which use technologies and protocols that are designed particularly for that purpose. The IEEE 802.1Q Time-Sensitive Networking (TSN) task group introduced a set of  standards by defining QoS mechanisms, also known as TSN features, so that standard Ethernet networks could provide precise timing for critical flows. We have implemented two mature TSN features, frame preemption and time gated queuing, in a simulator, and on multiple network topologies we have  evaluated the end-to-end delay and packet delay variation as the main QoS metrics and important design considerations in industrial networking setups. Our simulation results have shown that the QoS guarantees provided by TSN are strong enough for industrial use cases, but we have also identified some design and configuration pitfalls that TSN-adopters need to be cautious about.
 

Roland Király, Tamás Helfenbein, Sándor Király, Emőd Kovács and Tamás Balla
Novel concepts and devices in RFID based indoor localization using Smart Reader Networks and Intelligent Antennas  
Industrial, logistic, and several other applications require the discovery, localization, and tracking of objects using existing passive radio frequency identification (RFID) based sys- tems. We have analysed system concepts, methods, and protocols to enhance accuracy and coverage of RFID localization systems in order to find a moving transponder in an area with high precision over time using reading parameters and also to estimate the location of the transponder with low error rate if the reading information is not available. This research is also focusing on the infrastructure requirements of determining or recovering the location or path of the tag. The extension of the RFID localization beyond the area covered by the RFID reader system could be a solution. This can be carried out by using a special device called "Nodding antenna" or by supplying the transponders and antennas with the information on how to determine or store their respective positions. Advantages and application areas of the Location-on-Tag (LoT) concept and a novel localization method based on intelligent antennas that can enhance reliability and robustness of indoor RFID localization systems and ensure inter- building tag path tracking are introduced in this paper.

 

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