Miracle-dz/UniFAR-FTUs huggingface dataset:
Supernode-based reverse labeling algorithm: QoS support on mobile ad hoc networks

We present a supernode-based reverse labeling (SRL) algorithm for quality-of-service (QoS) provisioning, specifically bandwidth and delay, in mobile ad hoc networks (MANETs). SRL utilizes a hierarchical structure, which is formed by dynamically electing supernodes through simple algorithms, to perform effective route discovery and local route information management. The SRL QoS routing computation has three key components: virtual route discovery, reverse link labeling and dynamic route repairing. SRL not only considers bandwidth and delay provisioning together on MANETs, it also reacts quickly and effectively to the dynamics of MANETs as well. Simulation results show that SRL is efficient in terms of the packet delivery ratio and average end-to-end delay. The robust end user connection reduces the packet loss ratio and route request overhead that are invoked by node mobility.
Solving Go on a 3x3 Board Using Temporal-Difierence Learning

Go is a fascinating board game that originated from China more than 3000 years ago. Even after decades of research and lots of programming time spent on Go, the best computer Go is still playing at a modest level. On the other hand, other computer board games, such as chess, checkers, Othello and backgammon have attained grandmaster level. There are two reasons associated with the computer Go’s unsuccessful performance. The first reason is the enormous search space for Go, which is approximately 10 states, and the second and main reason is due to the absence of a good evaluation function that is able to accurately describes the Go state. Many AI techniques that were used and worked on other board games were attempted on Go but without equivalent success. Following the successful application of TD-learning on backgammon, researchers began studies applying TD-learning to Go. Their learning programs with no prior knowledge encoded managed to acquire ‘genuine’ knowledge and managed to achieve the level of a low level playing Go commercial program. This motivated our investigation into the applications of TD-learning on Go. As Go on small boards, such as 2 x 2, 3 x 3, and 4 x 4 were solved using game tree search, we attempted to solve a 3 x 3 board using another approach — TD-learning. We developed learning agents using TD(0), the simplest form of TD(λ), and TD-directed(0) each with a lookup table, and trained these against some selfdeveloped training agents. After 60000 training games, we observed that all agents were learning and some even managed to secure a 100% win ratio against a non-prefect test agent. We discuss further enhancements that can be made to improve the performance of the learning Go program for solving small boards, and possible extensions to solve bigger boards.
Alignment of matrices when using XOR-based hashing

To reduce the number of conflicts in caches, hash function are used. One family of hash function that has been reported to perform well in the presence of stride patterns are based on XORing address bits together. We show that, in contrast to traditional modulo-2m-based hashing, for XOR-based hashing the alignment of a stride pattern has a significant impact. We present some properties that allow to quickly determine an optimal base address.
Flexible motion of pull-out-work by articulated robot arm based on forcefree control

Flexible motion of an industrial articulated robot arm is realized by using force-free control, in which the flexible motion means that the robot arm is actuated by external force passively. Force-free control enables the natural motion of the industrial articulated robot arm as if the robot arm exists in a circumstance of non-gravity and non-friction condition. The effectiveness of the force-free control was assured by the application of pull-out-work on a 2-degree-of-freedom articulated robot arm.
A performance model for ATM switches with internal speedup

In this paper we study a non-blocking ATM switch with internal speedup. Modifying the model in Cao (1995), we can obtain the maximum throughput of the switch; approximating the output process by a discrete-time Markov modulated process, we can calculate the cell loss probabilities at the output buffers. In our approach, the incoming traffic is considered to have correlated destinations and asymmetric routing probabilities. Simulation results illustrate that the approach is very accurate.
SMART IMAGE PROCESSING OF FLOW VISUALIZATION

The purpose of this study is to develop an application of the smart visualized image processing to turbulent flow images and PIV (Particle Image Velocimetry) technique in order to improve the temporal resolution of images. Flow images consist of a set of sequentially discretized images in time domain. The smart visualized image processing can convert the discretized images into continuous images based on Helmholtz equation. In this paper the turbulent wake images and standard PIV images were used to evaluate the smart visualized information processing. Images of a turbulent wake with higher temporal resolution were generated, which were used to analyze the mechanism of wake flow. The PIV results obtained from the generated PIV images agreed with the accurate solution. One can say that the smart visualized image processing technique is effective in both flow image analysis and PIV system.
E-LEARNING 3.0 = E-LEARNING 2.0 + WEB 3.0?

Web 3.0, termed as the semantic web or the web of data is the transformed version of Web 2.0 with technologies and functionalities such as intelligent collaborative filtering, cloud computing, big data, linked data, openness, interoperability and smart mobility. If Web 2.0 is about social networking and mass collaboration between the creator and user, then the Web 3.0 is referring to intelligent applications using natural language processing, machine-based learning and reasoning. From the perspective of advancements in e-Learning, the Web 2.0 technologies have transformed the classroom and converted a passive learner into an active participant in the learning process. This paper posits that the way both previous generations of e-Learning (1.0 and 2.0) have emerged with the prevalent technologies in their kin Web versions (1.0 and 2.0, respectively), it can be argued that e-Learning 3.0 will provide all earlier generations’ capabilities enhanced with the Web 3.0 technologies. Furthermore, in this paper, reviewing all the theories of learning and examining closely the theory of connectivism (considered to be the theory of learning for the digital age), it is argued that since most of the technologies that are to be a part of e-Learning 3.0 are addressed by these principles, a call for a new learning theory for e-Learning 3.0 is not justified. Finally, a review of the secondary literature shows that there will be various challenges and issues related to prevalence and adoption of e-Learning 3.0 technologies, for example increased privacy and security risks, web accessibility, readiness of the users, requirement for further standardization of e-Learning technologies and social issues in term of increase of the digital divide.
UNIVERSITÁ DEGLI STUDI DI UDINE

The scale and scope of robotics continues to expand, and so also software for robotic applications has to follow this growth. As the number of robotic platforms available for research and development continue to increase, code reusability and extensibility appear as a major challenge that needs to be overcome. On top of this, the size of the required experience must contain a deep stack starting from driver-level software and continuing up through higher levels of abstraction. Since the required expertise is well beyond the capabilities of single researcher, robotics software architectures must also support large-scale software integration efforts. To meet these challenges, many researchers created a wide variety of frameworks, manage complexity and facilitate prototyping of software for experiments. Furthermore, when writing a code, many individuals have preferences for some programming languages or environments above others. These preferences are the result of personal tradeoffs between programming time, ease of debugging, syntax, runtime efficiency, and a lots of other reasons, both technical and cultural. Each of these frameworks was designed for a particular purpose, perhaps in response to perceived weakness of other available frameworks, or to place emphasis on aspects which were seen as most important in the design process. The field of robotics is far too broad for a single solution; it’s up to every researcher or student to find which is the better way to follow to realize at best his own project.
Transporting jobs through a two‐machine open shop

We consider the two‐machine open shop scheduling problem in which the jobs are brought to the system by a single transporter and moved between the processing machines by the same transporter. The purpose is to split the jobs into batches and to find the sequence of moves of the transporter so that the time by which the completed jobs are collected together on board the transporter is minimal. We present a $ {7 \over 5} $‐approximation algorithm. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009
Attention coupling as a prerequisite for social interaction

This paper proposes, "attention coupling", that is spatio-temporal coordination of each other's attention, as a prerequisite for human-robot social interaction, where the human interactant attributes mental states to the robot, and possibly vice versa. As a realization of attention coupling we implemented on our robots the capability of eye-contact (mutually looking into each other's eyes) and joint attention (looking at a shared target together). Observation of the interaction with human babies/children showed that the robots with the attention coupling capability facilitated in the babies/children social behavior, including showing, giving, and verbal interactions like asking questions.
A Matlab based Face Recognition GUI system Using Principal Component Analysis and Artificial Neural Network

With the advances in use of face recognition techniques for the security and surveillance system, it has become a challenging task to develop a system of face recognition which is highly efficient in use. Face images are similar in overall configuration and so face recognition is difficult. Humans are very powerful in recognizing the faces that they see often. With the advent of very high performance computing, a computer can be made to mimic large amount of interconnections and networking that exist between all the nerve cells in a human brain. This can be done by implementing a network of artificial neurons which functions in the same way as of actual neural network of human brain. Of all the biometrics applications face recognition is more important as it does not require any physical interaction of the person to be recognized. Face recognition system can be used and developed in two ways: the identification or the verification. Identification corresponds to one to many recognition i.e. the unknown face is matched with the many faces given in the database and the matched one is displayed as the output. Verification corresponds to one to one interaction i.e. the unknown face is verified as whether it is face of the specified person or not. In this paper, we have dealt with the identification of the unknown faces using ORL database. Face recognition techniques can be approached in two ways. (i) Appearance based (ii) Feature based. In the appearance based techniques, the whole face image is considered and the features are extracted through it. In the feature based technique, some of the features of face (like eyes, nose, mouth etc) are being considered for feature extraction. The feature based approaches include elastic bunch graph etc. The appearance based includes PCA, LDA, ICA etc. Compared to appearance based, feature based techniques of face recognition are less sensitive to variations in illumination. The eigenface approach or the Principal component analysis is the appearance based technique.
Strong Universal Consistency of Neural Network Classifiers

In statistical pattern recognition, a classifier is called universally consistent if its error probability converges to the Bayes-risk as the size of the training data grows for all possible distributions of the random variable pair of the observation vector and its class. It is proven that if a one-layered neural network with properly chosen number of nodes is trained to minimize the empirical risk on the training data, then a universally consistent classifier results. It is shown that the exponent in the rate of convergence does not depend on the dimension if certain smoothness conditions on the distribution are satisfied. That is, this class of universally consistent classifiers does not suffer from the curse of dimensionality. A training algorithm is presented that finds the optimal set of parameters in polynomial time if the number of nodes and the space dimension is fixed and the amount of training data grows. >
Frame synchronization for spontaneous transmission

A novel technique for frame synchronization that takes advantage of the information buried in the preamble preceding the actual data frame is described. This technique can not only be applied to uncoded data, but it is extremely efficient when used in conjunction with a convolutional code and Viterbi-decoding. In this case the error-correcting capabilities of the code affect not only the actual data but also the synchronizer (coded synchronizer). A class of convolutional codes that allow the application of the coded synchronizer are presented. The gain of the method may be up to 4 dB. <<ETX>>
Software Component Certification: 10 Useful Distinctions

Abstract : Using software components to develop mission-critical systems poses a number of technical, organizational, and economic challenges. One persistent and largely unaddressed challenge is how the consumers of software components-that is, the developers of mission-critical systems-can obtain a meaningful level of trust in the runtime behavior of software components. The most frequently cited concerns are centered on issues of security; for example, trust that a component does not contain malicious code or exhibit vulnerabilities that can be exploited by malicious code. There are, however, other concerns about software component behavior that can be just as important. For example, in an embedded weapon system, it may be crucial to trust that a component will always execute a function within a particular time bound or never introduce unbounded priority inversion. Certification is a practical, proven means of establishing trust in various sorts of things in other disciplines and is, therefore, a natural contender for developing trust in software components. This technical note does not propose a particular certification regimen for components. Rather, it introduces a series of 10 distinctions that can help in understanding different aspects of certification in the context of software components.
Identification-compensation approach for unknown disturbances via the estimate model of numerical differentiation

Researching the characteristic of macroscopical motion, numerical differentiation is introduced to describe the dynamics of an unknown kinematic process, then the estimation model of numerical differentiation (NDEM) is constructed. Robust and simple models can be created by this approach for various applications, and it is easy to select suitable estimation algorithms to satisfy estimate quality. In the paper, NDEM is established for the guidance process of spacecraft rendezvous and docking (RVD) disturbed by unknown inputs, the kinematic parameters of RVD are captured for guiding outputs, and the unknown disturbances are estimated for active compensation. Simulation results show that NDEM is a robust model for obtaining accurate state estimation, and the precision of RVD guidance is immune from the unknown disturbances by the compensated control law.
A Structural Health Monitoring Framework Using 3D Visualization and Augmented Reality in Wireless Sensor Networks

These days structure health monitoring (SHM) plays an important role in assessing the integral safety of structures like various types of buildings and bridges, both during the process of and after construction. A lot of research related to the structural health monitoring for building construction is progressing because of increasing industrial accidents and disasters at construction sites. In order to provide more efficient SHM solution in construction sites, wireless sensor networks (WSN) has risen as one of the advanced candidate technologies. In this paper, we proposed WSN monitoring framework based on 3D Visualization and Augmented Reality in Mobile Devices. The proposed system applied 3D visualization and AR technology to camera-enabled mobile devices in WSN environment in order to gather much more information than before. Based on the proposed system, we made an experiment to validate the effectiveness of 3D and AR mode using collected data in IEEE 802.15. 4-based WSN. In addition, we demonstrated the fire alarm detection experiment in three-story building miniature as a real implementation scenario.
Comparison of Concurrency Frameworks for the Java Virtual Machine

Zusammenfassung Due to Multi-core CPUs, concurrent programming is increasingly important when developing responsive and scalable applications. The programming language Java provides low-level building blocks such as threads and monitors. Multiple frameworks provide higher abstractions for concurrent programming and enable alternative concurrency paradigms on the Java virtual machine. This thesis provides a survey of such frameworks and their appropriate use cases. The thesis introduces the most relevant frameworks in more detail and evaluates their use in different concurrent applications.
Task-Based Oral Computer-Mediated Communication and L2 Vocabulary Acquisition

The present study adds to the computer-mediated communication (CMC) literature by exploring oral learner-to-learner interaction using Skype, a free and widely used Internet software program. In particular, this task-based study has a two-fold goal. Firstly, it explores possible differences between two modes of oral CMC (audio and video) and traditional face-to-face (FTF) interaction in terms of L2 vocabulary development. This study also investigates participants’ perceptions regarding these computer-mediated modes of communication. A within groups experimental design was employed in which a total of fifty-eight third semester college students of Spanish participated. Twenty-nine conversational dyads were assigned to one of three different groups: face-to-face, video CMC, and audio CMC. Repeated measures ANOVA analyses were conducted on the scores of the final pool of participants (N=47) in production, recognition, and aural comprehension tests to investigate possible differences. Furthermore, descriptive analyses were carried out of participants’ answers to a debriefing questionnaire that tapped into their perceptions toward these CMC modes. Results showed no significant differences among the groups for production or written recognition measures. All participants, however, were able to retain their recognition ability (but not their production ability) after two weeks. Finally, a significant difference was found among the groups in aural comprehension measures: the audio CMC group outperformed both other groups. Regarding participants’ attitudes toward the CMC modes used in this study, they had generally positive attitudes, which may be exploited in the L2 classroom.
Robust nonlinear predictive control using feedback linearization and linear matrix inequalities

This paper combines two features that has proven to be valuable in robust and nonlinear predictive control, namely feedback linearization and LMI-based predictive controller design. The algorithm consists of three steps, first a feedback linearization, secondly the derivation of an uncertainty description and finally the LMI-based optimization. A simulation example shows the effect of the feedback linearization step.
Issues and Challenges in Ubiquitous Computing

A fundamental measure of progress in computing involves rendering it as an inseparable part of our everyday experience while simultaneously making it disappear [2]. Radical improvements in microprocessor cost-performance ratios have pushed this process forward while drastically reducing computing-device form factors, enabling us to embed computers in many parts of our environments. In 40 years this change has transformed the early large “computing machines” into compact devices that enable, mediate, support, and organize our daily activities.
GENETIC BASED SPOT DETECTION METHOD IN TWO-DIMENSIONAL ELECTROPHORESIS IMAGES

The image analysis of two-dimensional electrophoresis images is a difficult task were authors were not able to find any other work in the literature handling with evolutionary computation in combination with a second order operator for edge detection. In this work, a novel Genetic Algorithm-based protein detection method from two-dimensional electrophoresis gel images is presented. Such a method makes use of a second order operator for edge detection by means of a Genetic Algorithm-based technique. The proposed method is able to detect proteins in two-dimensional gel images, but a reduction in the False Positive ratio is necessary. A manually selection process should be done by the clinicians to reduce this ratio; this represents a bottleneck due to the number of proteins in each imagein order to discriminate real proteins detected. The goal here was to avoid the loss of time caused by the manual revision of proteins detected by the image analysis software packages. To decrease this ratio, binary and real coded Genetic algorithms were probed and BLX-alpha crossover function was chosen. A comparative test with Z3 and Melanie 3.0, two-dimensional electrophoresis image analysis software packages, is done in order to check the accuracy of the proposed method. All images used for these tests are available on the Internet (http://www.umbc.edu/proteome).
Standard Verilog-VHDL interoperability

During the last few years HDLs have become the driver behind the move to top down design in the electronic design industry. Two HDLs, VHDL and Verilog HDL have become the dominant de facto industry standard HDLs. Since the industry has made a huge investment in both HDLs and there is every indication that each will retain significant market share for the foreseeable future, it is critical that there exist a standard methodology for interoperability between the two languages. This paper describes the relevant issues for interoperability and suggests solutions where they currently exist. It further summarizes the work which needs to be done for a complete solution and the groups who are involved in achieving this goal. The emphasis in this paper is on simulation since the semantics of the two languages are specified only for that discipline. While the importance of other disciplines such as logic synthesis cannot be underestimated in the top down design process, the lack of standard language semantics makes general analysis problematic. <<ETX>>