scholarly journals Optimizing Implementations of Lightweight Building Blocks

2017 ◽  
pp. 130-168 ◽  
Author(s):  
Jérémy Jean ◽  
Thomas Peyrin ◽  
Siang Meng Sim ◽  
Jade Tourteaux
Keyword(s):  
State Of The Art ◽  
Building Blocks ◽  
The State ◽  
Fine Tuning ◽  
Implementation Cost ◽  
Cryptographic Primitives ◽  
Small Functions ◽  
Hardware Implementations ◽  
Non Linear

We study the synthesis of small functions used as building blocks in lightweight cryptographic designs in terms of hardware implementations. This phase most notably appears during the ASIC implementation of cryptographic primitives. The quality of this step directly affects the output circuit, and while general tools exist to carry out this task, most of them belong to proprietary software suites and apply heuristics to any size of functions. In this work, we focus on small functions (4- and 8-bit mappings) and look for their optimal implementations on a specific weighted instructions set which allows fine tuning of the technology. We propose a tool named LIGHTER, based on two related algorithms, that produces optimized implementations of small functions. To demonstrate the validity and usefulness of our tool, we applied it to two practical cases: first, linear permutations that define diffusion in most of SPN ciphers; second, non-linear 4-bit permutations that are used in many lightweight block ciphers. For linear permutations, we exhibit several new MDS diffusion matrices lighter than the state-of-the-art, and we also decrease the implementation cost of several already known MDS matrices. As for non-linear permutations, LIGHTER outperforms the area-optimized synthesis of the state-of-the-art academic tool ABC. Smaller circuits can also be reached when ABC and LIGHTER are used jointly.

An experimental study on feature-based SLAM for multi-legged robots with RGB-D sensors

2017 ◽  
Vol 44 (4) ◽  
pp. 428-441 ◽  
Author(s):  
Michał R. Nowicki ◽  
Dominik Belter ◽  
Aleksander Kostusiak ◽  
Petr Cížek ◽  
Jan Faigl ◽  
...  
Keyword(s):  
Performance Metrics ◽  
State Of The Art ◽  
Building Blocks ◽  
Bundle Adjustment ◽  
The State ◽  
Legged Robots ◽  
Evaluation Methodology ◽  
Walking Robots ◽  
Content Type ◽  
Feature Based

Purpose This paper aims to evaluate four different simultaneous localization and mapping (SLAM) systems in the context of localization of multi-legged walking robots equipped with compact RGB-D sensors. This paper identifies problems related to in-motion data acquisition in a legged robot and evaluates the particular building blocks and concepts applied in contemporary SLAM systems against these problems. The SLAM systems are evaluated on two independent experimental set-ups, applying a well-established methodology and performance metrics. Design/methodology/approach Four feature-based SLAM architectures are evaluated with respect to their suitability for localization of multi-legged walking robots. The evaluation methodology is based on the computation of the absolute trajectory error (ATE) and relative pose error (RPE), which are performance metrics well-established in the robotics community. Four sequences of RGB-D frames acquired in two independent experiments using two different six-legged walking robots are used in the evaluation process. Findings The experiments revealed that the predominant problem characteristics of the legged robots as platforms for SLAM are the abrupt and unpredictable sensor motions, as well as oscillations and vibrations, which corrupt the images captured in-motion. The tested adaptive gait allowed the evaluated SLAM systems to reconstruct proper trajectories. The bundle adjustment-based SLAM systems produced best results, thanks to the use of a map, which enables to establish a large number of constraints for the estimated trajectory. Research limitations/implications The evaluation was performed using indoor mockups of terrain. Experiments in more natural and challenging environments are envisioned as part of future research. Practical implications The lack of accurate self-localization methods is considered as one of the most important limitations of walking robots. Thus, the evaluation of the state-of-the-art SLAM methods on legged platforms may be useful for all researchers working on walking robots’ autonomy and their use in various applications, such as search, security, agriculture and mining. Originality/value The main contribution lies in the integration of the state-of-the-art SLAM methods on walking robots and their thorough experimental evaluation using a well-established methodology. Moreover, a SLAM system designed especially for RGB-D sensors and real-world applications is presented in details.

scholarly journals A Decentralised Approach to Intersection Traffic Management

2018 ◽  
Author(s):  
Huan Vu ◽  
Samir Aknine ◽  
Sarvapali D. Ramchurn
Keyword(s):  
Quality Of Life ◽  
Waiting Time ◽  
Traffic Congestion ◽  
Traffic Management ◽  
State Of The Art ◽  
The State ◽  
Management Mechanism ◽  
Traffic Conditions

Traffic congestion has a significant impact on quality of life and the economy. This paper presents a decentralised traffic management mechanism for intersections using a distributed constraint optimisation approach (DCOP). Our solution outperforms the state of the art solution both for stable traffic conditions (about 60% reduced waiting time) and robustness to unpredictable events. 

scholarly journals Smoothing vs. sharpening of colour images: Together or separated

2017 ◽  
Vol 2 (1) ◽  
pp. 299-316 ◽  
Author(s):  
Cristina Pérez-Benito ◽  
Samuel Morillas ◽  
Cristina Jordán ◽  
J. Alberto Conejero
Keyword(s):  
Image Denoising ◽  
Gaussian Distribution ◽  
State Of The Art ◽  
Visual Quality ◽  
The State ◽  
Art Methods ◽  
Efficiency And Effectiveness

AbstractIt is still a challenge to improve the efficiency and effectiveness of image denoising and enhancement methods. There exists denoising and enhancement methods that are able to improve visual quality of images. This is usually obtained by removing noise while sharpening details and improving edges contrast. Smoothing refers to the case of denoising when noise follows a Gaussian distribution.Both operations, smoothing noise and sharpening, have an opposite nature. Therefore, there are few approaches that simultaneously respond to both goals. We will review these methods and we will also provide a detailed study of the state-of-the-art methods that attack both problems in colour images, separately.

Streaming Coded Video in P2P Networks

2017 ◽  
pp. 188-222
Author(s):  
Muhammad Salman Raheel ◽  
Raad Raad
Keyword(s):  
Quality Of Service ◽  
Approximation Algorithms ◽  
Video Coding ◽  
State Of The Art ◽  
Scalable Video Coding ◽  
The State ◽  
P2p Network ◽  
Scalable Video ◽  
Adequate Quality

This chapter discusses the state of the art in dealing with the resource optimization problem for smooth delivery of video across a peer to peer (P2P) network. It further discusses the properties of using different video coding techniques such as Scalable Video Coding (SVC) and Multiple Descriptive Coding (MDC) to overcome the playback latency in multimedia streaming and maintains an adequate quality of service (QoS) among the users. The problem can be summarized as follows; Given that a video is requested by a peer in the network, what properties of SVC and MDC can be exploited to deliver the video with the highest quality, least upload bandwidth and least delay from all participating peers. However, the solution to these problems is known to be NP hard. Hence, this chapter presents the state of the art in approximation algorithms or techniques that have been proposed to overcome these issues.

The Playout Control Management

2011 ◽  
pp. 689-702
Author(s):  
Mirko Luca Lobina ◽  
Luigi Atzori ◽  
Fabrizio Boi
Keyword(s):  
Quality Of Service ◽  
Service Provider ◽  
Service Providers ◽  
State Of The Art ◽  
Main Idea ◽  
The State ◽  
Ip Telephony ◽  
Open Standard ◽  
Control Management

IP Telephony provides a way for an enterprise to extend consistent communication services to all employees, whether they are in main campus locations, at branch offices, or working remotely, also with a mobile phone. IP Telephony transmits voice communications over a network using open standard-based Internet protocols. This is both the strength and weakness of IP Telephony as the involved basic transport protocols (RTP, UDP, and IP) are not able to natively guarantee the required application quality of service (QoS). From the point of view of an IP Telephony Service Provider this definitely means possible waste of clients and money. Specifically the problem is at two different levels: i) in some countries, wherelong distance and particularly international call tariffs are high, perhaps due to a lack of competition or due to cross subsidies to other services, the major opportunity for IP Telephony Service Providers is for price arbitrage. This means working on diffusion of an acceptable service, although not at high quality levels; ii) in other countries, where different IP Telephony Service Providers already exist, the problem is competition for offering the best possible quality. The main idea behind this chapter is to analyze specifically the state of the art playout control strategies with the following aims: i) propose the reader the technical state of the art playout control management and planning strategies (overview of basic KPIs for IP Telephony); ii) compare the strategies IP Telephony Service Provider can choose with the aim of saving money and offering a better quality of service; iii) introduce also the state of the art quality index for IP Telephony, that is a set of algorithms for taking into account as many factors as possible to evaluate the service quality; iv) provide the reader with examples on some economic scenarios of IP Telephony.

scholarly journals Dialogue Generation: From Imitation Learning to Inverse Reinforcement Learning

2019 ◽  
Vol 33 ◽  
pp. 6722-6729 ◽  
Author(s):  
Ziming Li ◽  
Julia Kiseleva ◽  
Maarten De Rijke
Keyword(s):  
Reinforcement Learning ◽  
State Of The Art ◽  
The State ◽  
Experimental Results ◽  
Imitation Learning ◽  
Local Optimum ◽  
Inverse Reinforcement Learning ◽  
High Quality ◽  
Overall Performance

The performance of adversarial dialogue generation models relies on the quality of the reward signal produced by the discriminator. The reward signal from a poor discriminator can be very sparse and unstable, which may lead the generator to fall into a local optimum or to produce nonsense replies. To alleviate the first problem, we first extend a recently proposed adversarial dialogue generation method to an adversarial imitation learning solution. Then, in the framework of adversarial inverse reinforcement learning, we propose a new reward model for dialogue generation that can provide a more accurate and precise reward signal for generator training. We evaluate the performance of the resulting model with automatic metrics and human evaluations in two annotation settings. Our experimental results demonstrate that our model can generate more high-quality responses and achieve higher overall performance than the state-of-the-art.

scholarly journals Modified Deep Neural Networks for Dog Breeds Identification

2018 ◽  
Author(s):  
Aydin Ayanzadeh ◽  
Sahand Vahidnia
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
State Of The Art ◽  
The State ◽  
Fine Tuning ◽  
Test Accuracy ◽  
Data Sets ◽  
Data Set

In this paper, we leverage state of the art models on Imagenet data-sets. We use the pre-trained model and learned weighs to extract the feature from the Dog breeds identification data-set. Afterwards, we applied fine-tuning and dataaugmentation to increase the performance of our test accuracy in classification of dog breeds datasets. The performance of the proposed approaches are compared with the state of the art models of Image-Net datasets such as ResNet-50, DenseNet-121, DenseNet-169 and GoogleNet. we achieved 89.66% , 85.37% 84.01% and 82.08% test accuracy respectively which shows thesuperior performance of proposed method to the previous works on Stanford dog breeds datasets.

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