Miracle-dz/UniFAR-FTUs huggingface dataset:
Mtens: A New Simulator for the Design of MPLS Networks with Traffic Engineering Support

Abstract In a multi-service IP/MPLS network, it is a key challenge to provide Quality of Service (QoS) to end-users applications while effectively using network resources and providing reliable services. In this framework, native TE mechanisms can be used to improve network performance, whereas a set of procedures that protects the traffic flows carried on different paths enforces resilience techniques. The paper presents the main functionalities of MTENS (MPLSTE network simulator), a new NS2-based simulator, specifically developed to facilitate the design of MPLS networks with TE support. Moreover, to highlight the effectiveness of MTENS in the design of MPLS-TE networks, the paper shows a case study concerning the performance evaluation of different recovery strategies when path computation algorithms with QoS constraints are used for primary and backup label switched paths.
Validating the design of real-time systems using a formal specification method

This paper proposes a method for validating the design of a real-time system. The method is based on the formal specification of the target system and the verification of its timing requirements. The main contribution consists in introducing the design issues (e.g. the tasks parameters or the scheduling algorithm) in the system specification. It will allow to check how these design issues may affect the stated timing requirements.
Mathematical Morphology in Image Processing

Presents the statistical analysis of morphological filters and their automatic optical design, the development of morphological features for image signatures, and the design of efficient morphological algorithms. Extends the morphological paradigm to include other branches of science and mathematics. ;This book is designed to be of interest to optical, electrical and electronics, and electro-optic engineers, including image processing, signal processing, machine vision, and computer vision engineers, applied mathematicians, image analysts and scientists and graduate-level students in image processing and mathematical morphology courses.
A Quantitative Investigation Of Software Metrics Threshold Values At Acceptable Risk Level

Object-Oriented metrics are more beneficial for the software engineers. Object-oriented design and development is becoming very popular in software development environment. Object oriented development requires not only a different approach to design and implementation, it requires a different approach to software metrics. In the current paper, we use logistic regression to investigate the threshold values against the bad smell for the Chidamber and Kemerer(CK) metrics at five different levels. Two versions of jfreechart were used as a dataset to validate the study. Only the significantly associated metrics were considered for finding the threshold values. The results indicate that the CK metrics have threshold effects at various risk levels and some metrics have useful threshold value at different levels to identify the bad smell.
Energy Efficient Decentralized Cluster Based Protocol Using Cooperative MIMO

Recent development in microelectronics and signal processing enable more efficient use of wireless sensor network. The different challenges of a wireless channel are bit error rate, signal attenuation and fading that occur in a wireless channel due to its unpredictable nature. Apart from this, using sensors for data transmission lots of energy is being consumed due to various mentioned constrained of wireless channel. Thus lots of researches have been done at various layer of communication to reduce the energy consumption of a sensor during the communicating the sense data. In this paper a scheme has been proposed to implement virtual MIMO system in a decentralized weighted cluster based protocol and the impact of various cooperative communication strategies and coding schemes on energy consumption is also analysed . The results shows that cooperative communication techniques provides a significant amount of energy savings to the conventional clustering protocols.
NUI Design and Realization for Game Content Control

With the development of information technology, a variety of content platforms including computer have been popularized and a number of studies on more convenient and natural interface are in progress. This study suggests how to design and display motion-based interface using Kinect sensor to control game content for the purpose that the existing controlling method in GUI environment is shaped to be fitted in NUI setting.
Transistor Implementation of D Flip-Flop Using Reversible Logic Circuit

Reversible logic circuit is receiving attention of researchers for low power design. Flip Flop is the basic element for the sequential circuits, most of the part of the IC is built from sequential circuit, and hence it is needed to design low power flip-flop. The work is done on designing a reversible D – flip flop from a reversible Fredkin gate using GDI technique in 0.180um TSMC process, which can be used for low power design, and fault preventing circuit. Keyword —Reversible D flip-flop; GDI
Adaptive Probabilities in Stochastic Optimization Algorithms

Stochastic optimization methods have been extensively studied in recent years. In some classification scenarios such as text document categorization, unbiased methods such as uniform sampling have negative effects on the convergence rate, because of the effects of the potential outlier data points on the estimator. Consequently, it would take more iterations to converge to the optimal value for uniform sampling than non-uniform sampling, which normally allocates larger probability to samples with larger norm. Based on the intuition of non-uniform sampling, we investigate adaptive sampling in which we change the probability per iteration or per epoch during the execution of the algorithm. In this thesis, we start by introducing non-uniform sampling with Stochastic Gradient Descent (SGD), and then study the impact of different choices of stepsize on convergence rate as well as derive theorems for the convergence rate. We analyze Stochastic Dual Coordinate Ascent (SDCA) and obtain the upper bound on the number of iterations to reach a specific level of optimality. This is followed by investigation of adaptive strategies which change the probabilities according to some historical information. We provide theoretical analysis to prove that they further reduce the number of iterations needed to reach the same level of optimality. The adaptive variants of SGD and SDCA are discussed and compared to the existing counterparts. The results show that both AdaSGD and AdaSDCA outperform the existing models. We also provide two online variants which update the probabilities immediately to perform adaptive sampling without the need of additional passes through the data.
Simulation Of Microsystems Using A BehaviouralHybrid Simulator Alecsis

A behavioural hybrid simulator Alecsis is utilized for simulation of microelectromechanical systems (MEMS). Alecsis allows modelling of devices of different physical nature, and simulation of systems where instances of such models are invoked. As an example, a pressure sensing system comprising both micromechanical and electronic components is simulated. In this way consistent simulation results are obtained for the system as a whole, since effects of both mechanical and electrical coupling are modelled.
Measurement of Inductive Coupling in Wireless Superconnect

An inductive inter-chip wireless communication scheme in three-dimensional (3D) stacked chip has been reported to achieve high-speed, low-power, and low-cost inter-chip communication. In this scheme, inductive coupling becomes a fundamental of communication and it should be modeled to realize communication. In inter-chip communication, it is considered that eddy current effect and the reflection of electromagnetic field degrade transmission power. However, there is as yet no report on inter-chip inductive coupling showing these effects. In this study, the scattering parameter of inductive coupling in 3D stacked chip has been measured under three conditions. The first measurement is carried out by changing the inductance alignment vertically and horizontally to verify the estimation scheme of coupling coefficient. The second measurement is carried out to evaluate ground mesh effect on inductive coupling. The third measurement is carried out by changing bulk thickness with constant communication distance to evaluate eddy current effect in bulk. The results show that eddy current does not become a problem and power grid degrades communication efficiency.
Above and beyond: seL4 noninterference and binary verification

In 2009, the L4.verified project completed the world’s first verification of functional correctness for a general-purpose OS kernel [2], seL4. Functional correctness here was embodied by a formal theorem of refinement, which stated that the behaviour of the C code that implemented the kernel accorded with an abstract specification of how the kernel was meant to function. A cynic would say that this result proves only that the kernel has no bugs that are not present in its abstract specification or the C compiler. Specifically, while seL4 was designed for security, the functional correctness proof did not rule out the abstract specification specifying insecure behaviour. Further, there was no guarantee that the compiler used to compile the kernel’s C code would produce a binary whose behaviour matched its formal C semantics from the functional correctness proof: the proof did nothing to rule out compiler bugs. Therefore, two obvious questions remained. Firstly, how do we know that the abstract specification correctly specifies the kernel we want? Secondly, how do we know that the compiler will honour the formal C semantics of seL4? We present new results on both of these fronts. First, we discuss the recent proof of the classical security property of noninterference for seL4 over its abstract specification [3]. By virtue of the functional correctness proof, we obtain this result automatically for the kernel’s implementation— a world first for a general purpose kernel. Coupled with an earlier proof of integrity for seL4 [5], we now know that it is secure: seL4 provably enforces confidentiality and integrity. Second, we discuss recent work on applying translation validation to seL4, to formally verify that the binary produced by the compiler adheres to the formal C semantics used in the functional correctness proof [4]. Here, we interpret the binary against a formal model of the ARM ISA developed by Fox et al. [1] to give it a formal semantics, which is then matched-up against the formal semantics of the kernel’s C code, and the match automatically proved by SMT solving. Combined, these results give us security theorems that apply to the kernel binary; neither the abstract specification nor the compiler need be trusted anymore. seL4 has now become the world’s most deeply verified general-purpose kernel, and so serves as an ideal base for the construction of trustworthy systems. Importantly, system builders can make use of the high level security theorems to obtain system-wide guarantees without needing to trust their kernel or compiler. No other system provides this level of assurance.
Design a PID controller for active queue management

As an enhancement mechanism for the end-to-end congestion control, active queue management (AQM) can keep smaller queuing delay and higher throughput by purposefully dropping the packets at the intermediate nodes. Comparing with RED algorithm, although the PI (proportional-integral) controller for AQM designed by C. Hollot improves the stability, the transient performance of the PI controller is not perfect, such as the regulating time is too long. In order to overcome this drawback, in this paper, the PID (proportional-integral-differential) controller is proposed to speed up the responsiveness of AQM system. The controller parameters are tuned based on the determined gain and phase margins. The simulation results show that the integrated performance of the PID controller is obviously superior to that of the PI controller.
Design of Self-Adjusting algorithm for Twitter Sentiment Analysis

—Social Media is emerged as an open platform that people use it to share/exchange information. Data captured from social media is generated in different formats, different sources, varies in real time i.e. data generated has big data properties like velocity, volume, variety. For class of machine learning algorithms, large scale data processing frameworks like Hadoop, MapReduce are insufficient as they requires intermediate results across multiple executions. Also they have to dealtwith skewness, diversity of data to adapt changes in real time. For example Social media site, Twitter generates approximately 6000 tweets per second and these are according to trends that changes over time. As success of any machine learning algorithm like Sentiment Analysis is depend upon how well it is trained on training set, domain-specific information and corpus of training set. To overcome these problems we have proposed Selfie,Self-adjusting algorithm in [12]. In this paper we have discussed preparing domain –specific corpus according to change in trends in real time by using self-adjusting computation. We have implemented Splay tree with trends as tree node and trends near to root of the tree are the most talked/tweeted trends. Each trend node contributes towards domain–specific corpus according to height of tree.
A comparison between theoretical and practical planning approaches for DVB-T2 single frequency networks

This paper presents a comparison between two planning approaches to DVB-T2 Single Frequency Networks (SFN). The first technique is regarded as theoretical and it is based on theoretical hexagonal lattices, where terrain impact is disregarded, the transmitting power and equivalent height are constant parameters over the entire service area. The second one is based on the use of commercial network planning tools that include all the terrain, population, network infrastructure databases as well as propagation related parameters. The paper highlights the motivation for each one of the planning procedures and presents a comparison between them using the planning example of a wide service area in the south of Germany. In general, the hexagon model is able to describe some broad network characteristics but fails to describe the coverage situation in detail, leading to too optimistic results. The differences are associated mainly to effective height and terrain impact on propagation calculations.
Cooperative and intelligent control of multi-robot systems using machine learning

This thesis investigates cooperative and intelligent control of autonomous multi-robot systems in a dynamic, unstructured and unknown environment and makes significant original contributions with regard to self-deterministic learning for robot cooperation, evolutionary optimization of robotic actions, improvement of system robustness, visionbased object tracking, and real-time performance. A distributed multi-robot architecture is developed which will facilitate operation of a cooperative multi-robot system in a dynamic and unknown environment in a selfimproving, robust, and real-time manner. It is a fully distributed and hierarchical architecture with three levels. By combining several popular AI, soft computing, and control techniques such as learning, planning, reactive paradigm, optimization, and hybrid control, the developed architecture is expected to facilitate effective autonomous operation of cooperative multi-robot systems in a dynamically changing, unknown, and unstructured environment. A machine learning technique is incorporated into the developed multi-robot system for self-deterministic and self-improving cooperation and coping with uncertainties in the environment. A modified Q-learning algorithm termed Sequential Q-learning with Kalman Filtering (SQKF) is developed in the thesis, which can provide fast multi-robot learning. By arranging the robots to learn according to a predefined sequence, modeling the effect of the actions of other robots in the work environment as Gaussian white noise and estimating this noise online with a Kalman filter, the SQKF algorithm seeks to solve several key problems in multi-robot learning. As a part of low-level sensing and control in the proposed multi-robot architecture, a fast computer vision algorithm for color-blob tracking is developed to track multiple moving objects in the environment. By removing the brightness and saturation information in an image and filtering unrelated information based on statistical features and domain knowledge, the algorithm solves the problems of uneven illumination in the environment and improves real-time performance.
Robust Facial Expression Recognition Using Local Binary Patterns and Gabor Filters

Facial expressions and gestures provide intuitional cues for interpersonal communication. Imparting intelligence to computer for identifying facial expressions is a crucial task. Facial expressions and emotions are governed by identification of facial muscle movement by visual cortex and training a machine to identify these highly in-situ movements is our primary interest. This thesis presents robust facial expression analysis algorithms for static images as well as an efficient extension to sequence of images. We present an efficient preprocessing method which eliminates the effect of illumination on the detected face images thus making them efficient for feature extraction. Robust Local Binary Patterns and Gabor filters are implemented for feature extraction which are known to provide efficient face representation and analysis.LBP facial features are represented in form of weighted histograms which are best classified using Kullback Leibler divergence measure . Artificial Neural Network classifier is also tested for classification of fused Gabor and LBP features. Further expressions are rarely defined by static images as their complete essence lies in a sequence of images. So further exploration is concentrated on analyzing expressions from a sequence of images. To eliminate head pose variations in consecutive frames and register images to keep the spatial information intact which is necessary for LBP feature representation we adopted SIFT flow alignment procedure and further tested the resultant image classification with implemented algorithms. The classification accuracy resulted in 95.24% for static expression images and 86.31% for sequence of images which is indeed appreciable when compared to other standard methods.
Erron: A Phrase-Based Machine Translation Approach to Customized Spelling Correction

Spellcheckers such as ASPELL and Microsoft Word 2007 were designed to correct the spelling errors of native writers of English (NWEs). While they are widely used and fairly effective at this task, they do not perform well when used to correct the spelling errors in English text written by Japanese writers of English (JWEFLs). The first contribution of this thesis is a comprehensive analysis of the English spelling errors of Japanese writers of English as a foreign language (JWEFLs) with the goal of finding differences from NWE spelling errors that would cause such poor spellchecker performance. In addition to describing the patterns of characteristic JWEFL errors I also provide hypotheses for why each error is observed. I find that JWEFL errors are 2-3 times more likely to have a mistake in the first letter and 4-5 times more likely to have more than one mistake in them than NWE spellings errors. These facts make it very difficult for widely-used English spellcheckers to correct JWEFL errors, because they are designed to exploit patterns in NWE spelling errors which simply are not present in Japanese learner text. I assert, however, that while JWEFL spelling errors do not have the same patterns as NWE errors, they do display patterns that can be exploited to make a custom spellchecker for JWEFL users. This thesis describes the creation of a spellchecker customized for Japanese writers of English as a foreign language. Traditionally, spellcheckers have used edit distance to determine which words to include in a list of suggestions for the user. At its core, this method transforms the word on a letter-by-letter basis, using statistics and heuristics collected by examining large corpora
USB Connection Vulnerabilities on Android smartphones

In this work, we enumerate a series of vulnerabilities in the USB connection of Android, specially vulnerabilities related with the customization done by the Android manufacturers. The crux of the discovered vulnerabilities is a consequence of the vendor customization of Android, where the serial AT commands processed by the cellular modem are extended to allow other functionalities. With this, we are able to flash a boot partition on the smartphone and obtain several objectives, including root access. These found vulnerabilities allow us to develop several attack vectors, which are ordered according with its efficacy, the objective in building an hierarchy that is able to produce the maximum efficacy attack according to the device. We develop a proof of concept and an attack scenario specially designed for USB attacks on Android. We made some tests with popular anti-virus for Android, to examine if they can prevent or detect the attacks. Finally, we develop an application capable of mitigating the discovered vulnerabilities, unfortunately the application needs root access to be activated. In case there is no root access, we prompt a warning to the user, notifying the dangers he may be in.
Sensing and recognizing affective touch in a furry zoomorphic object

Over the last decade, the surprising fact has emerged that machines can possess therapeutic power. Due to the many healing qualities of touch, one route to such power is in haptic emotional interaction, which in turn requires sophisticated touch sensing and interpretation. We explore the development of affective touch gesture recognition technologies in the context of a furry artificial lap-pet, with the ultimate goal of creating therapeutic interactions by sensing human emotion through touch. We design, construct, and evaluate a low-cost, low-tech furry lap creature prototype equipped with 2 types of touch-sensing hardware. The first of these hardware types is our own design for a new type of touch sensor built with conductive fur, invented and developed as part of this research. The second is an existing design for a piezoresistive fabric pressure sensor, adapted to three dimensions for our robotbody context. Combining features extracted from the time-series data output of these sensors, we perform machine learning analysis to recognize touch gestures. In a study of 16 participants and 9 key affective gestures, our model averages 94% gesture recognition accuracy when trained on individuals, and 86% accuracy when applied generally across the entire set of participants. The model can also recognize who out of the 16 participants is touching the prototype with an accuracy of 79%. These results promise a new generation of emotionally intelligent machines, enabled by affective touch gesture recognition.