Miracle-dz/UniFAR-FTUs huggingface dataset:
Foundations for level crossing analysis of handoff algorithms

An analytic model has recently been presented for evaluating the effect of averaging and hysteresis on handoff algorithms in cellular radio networks. For the case of a mobile moving from one base station to another, the results obtained using the Poisson model showed a certain bias with respect to simulations which was not numerically significant for the situation under consideration. The authors analyze in depth the causes of the bias and discuss the applicability of the Poisson model under various conditions. Though the Poisson model works well near the cell boundaries where most of the handoffs occur, there can be areas where it does not apply. An alternative technique based on large excursions of Gaussian processes is presented for computing handoff algorithm characteristics in these regions. <<ETX>>
Notes from the Unit Commitment Linear Programming Project

The Unit Commitment Problem (UCP) is a computational bottleneck in electrical grid optimization. The problem bears a close resemblance to a similar problem in High Performance Computing: the Dynamic Voltage/Frequency Scheduling (DVFS) problem. In my earlier work I successfully tranformed the DVFS into a closely related problem amenable to a linear programming solution and was thus able to schedule problem instances several orders of magnitude larger than any that had been attempted before. This technical report details my unsuccessful efforts to derive a similar transformation for the UCP. The problem proved impossible not because generators were either on or off, but because the state of an earlier timeslice constrains the states of latter timeslices in ways that cannot be sufficiently well approximated for useful solutions.
A Method for Cyber-Physical System Behavior Modeling and Safety Verification Based on Extended Hybrid System Description Language

The safety of Cyber-physical system(CPS) is up to its behavior, and it is a key property for CPS to be applied in critical application fields. A method for CPS behavior modeling and safety verification is put forward in this paper. The behavior model of CPS is described by extended hybrid system description language(EHYSDEL). The formal definition of hybrid program(HP) is given, and the behavior model is transformed to HP based on the definition. The safety of CPS is verified by inputting the HP to KeYmarea. The advantage of the approach is that it models CPS intuitively and verify it’s safety strictly avoiding the state space explosion
Ship and ship wake detection in the ERS SAR imagery using computer-based algorithm

A computer-based algorithm for ship and ship wake detection in SAR imagery is being developed to monitor ship traffic near Singapore waters. This paper presents current progress made on the algorithm. In particular, issues on the elimination of false targets are addressed. The morphological filter, half Radon (Hough) transform, and other wake criterion tests are applied to strengthen the detecting capability.
Integrated power control for circuit & packet switched traffic in wireless networks

We investigate a set of novel distributed channel access schemes for wireless networks supporting both circuit-switched and packet-switched traffic. The dissimilar nature of each traffic type calls for differentiated treatment by the network: circuit-switched or streamed traffic requires constant rate bit flows across the wireless links, hence the network shall maintain the effective traffic rate of operational/active links at all times (link protection). , packet-switched or elastic traffic is intermittent and delay-tolerant. Hence, it is more efficient to buffer the incoming packets, and transmit them when appropriate, rather than reserving wireless resources for each individual flow. Past research in power-control looked at the problem of supporting each traffic type in isolated, separate networks, and has come up with the distributed algorithms of DPC/ALP (N. Bambos et al., 2000) and PCMA (N. Bambos et al., 2002) [S. Kandukuri et al., 2001], respectively. In this work, we propose a framework which integrates these two algorithms into a single set of access schemes to allow the sharing of the wireless resources to both traffic types and to new hybrid schemes.
A language for generic programming

The past decade of software library construction has demonstrated that the discipline of generic programming is an effective approach to the design and implementation of large-scale software libraries. At the heart of generic programming is a semi-formal interface specification language for generic components. Many programming languages have features for describing interfaces, but none of them match the generic programming specification language, and none are as suitable for specifying generic components. This lack of language support impedes the current practice of generic programming. In this dissertation I present and evaluate the design of a new programming language, named G (for generic), that integrates the generic programming specification language with the type system and features of a full programming language. The design of G is based on my experiences, and those of colleagues, in the construction of generic libraries over the past decade. The design space for programming languages is large, thus this experience is vital in guiding choices among the many tradeoffs. The design of G emphasizes modularity because generic programming is inherently about composing separately developed components. In this dissertation I demonstrate that the design is implementable by constructing a compiler for G (translating to C++) and show the suitability of G for generic programming with prototypes of the Standard Template Library and the Boost Graph Library in G . I formalize the essential features of G in a small language and prove type soundness.
Designing the Sakai Open Academic Environment: A distributed cognition account of the design of a large scale software system

GAP evaluation of architectural model in light of software performance 7.2. 5. Making components work together: the kernel team’s approach to development Participants of the kernel team also engaged with server-side software in an anticipatory manner, for the purpose of design, even if these activities did not figure in their accounts. My concern here will be the overall outline of their approach in constructing the architectural model of server-side technologies. A central aspect of this approach was engaging with actual software with the goal of getting things to work. Understanding emerged as coupled with this practical engagement. Assessment, planning and insight
Anti-Collision Warning Algorithm based on Visual Perception in Front of Vehicle

The vehicles’ driving safety plays an important role in the transportation safety’s development, and it’s a necessary requirement in intelligent transportation and intelligent vehicle. The point that is suggested in this paper is that vehicles’ collision warning system which is based on computer vision, and the system is built on computer vision, pattern recognition, machine learning and some other artificial intelligent theory and techniques, discerning the vehicles which is in front of your vehicle and measure the security range, warning the possible danger timely to make sure your drive safe. We use the characteristic which is called haar of the samples to train in the classifier to get a cascaded classifier named Boosted, loading the classifier and image of the vehicles marked and calculating the distance and relative speed. In the last, we do a lot of system simulation experiments, verifying the accuracy and the effectiveness of the system from vehicle outline detection results and safe vehicle determination.
Mediating connectors

We have developed a technology for mediating all shared library calls. These mediators can be dynamically installed and removed during execution. They can be used as an instrument for these interfaces, to monitor their behavior, to integrate legacy components together, or to encapsulate potentially harmful or unreliable components. Since modern commercial operating systems promote packaging third party functionality as shared libraries and are themselves composed of shared libraries the ability to mediate these interfaces provides access to the broad range of services available on that platform. An implementation of this technology is available for Windows NT.
A single-chip 900 MHz CMOS receiver front-end with a high performance low-IF topology

An analog receiver front end chip realized in a 0.7 /spl mu/m CMOS technology is presented. It uses a new, high performance, downconverter topology, called double quadrature downconverter, that achieves a phase accuracy of less than 0.3/spl deg/ in a large passband around 900 MHz, without requiring any external component or any tuning or trimming. A high performance low-IF receiver topology is developed with this double quadrature downconverter. The proposed low-IF receiver combines the advantages of both the classical IF receiver and the zero IF receiver: an excellent performance and a very high degree of integration. In this way, it becomes possible to realize a true fully integrated receiver front-end that does not require a single external component and which is, different from the zero-IF receiver, nonetheless totally insensitive to parasitic baseband signals and self-mixing products.
Enhancing the discrimination of speaker independent hidden Markov models with corrective training

Corrective training is a recently proposed method of improving hidden Markov model parameters. Corrective training and related algorithms are applied to the domain of small-vocabulary, speaker-independent recognition. The contribution of each parameter of the algorithm is examined. Results confirm that corrective training can improve on the recognition rate achieved by maximum-likelihood training. However, the algorithm is sensitive to selection of parameters. A heuristic quantity is proposed to monitor the progress of the corrective training algorithm, and this quantity is used to adapt a parameter of corrective training. An alternative training algorithm is discussed and compared to corrective training. It yielded open test recognition rates comparable to those of maximum-likelihood training, but inferior to those of corrective training. <<ETX>>
Understanding idea flow: applying learning analytics in discourse

ABSTRACT The assessment and understanding of students’ ideas in discourse have often been a difficult problem for teachers to tackle. Recent innovations and technologies such as text mining can provide a partial solution by generating an estimated count of important keywords which are representative of ideas within discourse. However, investigating idea development and flow within discourse is a much more challenging task, and requires elaborate processing and analysis. In this study, a method for analysing idea flow was proposed and tested: (1) text mining and network analysis are employed to identify and validate ideas from textual discourse; (2) identified ideas are grouped together and mapped to relevant learning objectives; (3) groups of ideas are then aggregated using a binning method and scored; (4) a flow diagram is generated using the aggregated scores to visualise idea flow within discourse. By understanding how ideas flow within discourse, discussed key ideas can be monitored and any lapses in student understanding can be identified so that teachers will have information to provide timely interventions to support and scaffold learning.
Modelling of Eyeball with Pan/Tilt Mechanism and Intelligent Face Recognition Using Local Binary Pattern Operator

This paper describes the vision system for a humanoid robot, which includes the mechanism that controls eyeball orientation and blinking process. Along with the mechanism designed, the orientation of the camera, integrated with controlling servomotors. This vision system is a bio-mimic, which is designed to match the size of human eye. This prototype runs face recognition and identifies, matches with a face in the database. Recognition of face leads to capture the facial image and synchronize with the face. As the individual shows any motion, the system also moves according to it.
A hybrid algorithm for the path center problem

Let a graph G = (V,E) be given. In the path center problem we want to find a path P in G such that the maximum weighted distance of P to every vertex in V is minimized. In this paper a genetic algorithm and a hybrid of genetic and ant colony algorithms are presented for the path center problem. Some test problems are examined to compare the algorithms. The results show that for almost all examples the hybrid method results better solutions than genetic algorithm.
A STUDY ON ABILITY IN USING ACADEMIC WORDS IN WRITING REPORT TEXT BY SECOND YEAR STUDENTS OF SMAN 9 PEKANBARU

Abstract: The aims of this study was to find out (1) the percentage of academic words being used in writing report text by second year students at SMAN 9 Pekanbaru and (2) the level of the academic words being used in writing report text by second year students at SMAN 9 Pekanbaru. This study is a descriptive research by using cluster model sampling to choose the sample that was 30 students of eleventh science 5 class. The analysis was based on Academic Word List (AWL) Highlighter classified into 10 levels of frequency, from the highest (level 1) to the lowest (level 10). From the 30 written texts, it was found the most academic words used is in level 7 (22 of 64 words or 34,37%) and the leasts are level 3 and level 6 (3 words of 64 or 4,68%). And based on number of students, there are 4 of 30 (13%) students that do not use any academic words in their writing. Last, based on part of speech, the most part of speech that used is verb part of speech (39 of 64 or 61,29%) and the lowest one is adverb part of speech (1 of 64 or 1,56%). It can be concluded that the students of second year of SMAN 9 Pekanbaru has been used academic words in their writing although in a low level frequency (level 7). Therefore, it is expected for teachers to more remind the students about academic words, even for the highlevel and futur researchers to conduct similar research for improving the ability of using academic words of students. Keywords : Writing, academic words, Report text
Deep learning for sequence modelling : applications in natural languages and distributed compressive sensing

The underlying data in many machine learning tasks have a sequential nature. For example, words generated by a language model depend on the previously generated words, behavior of a user in a social network evolves over different snapshots of the social graph over time, different speech frames in a speech recognition system depend on the previously generated frames, etc. The main question is, how can we leverage the sequential nature of data to extract better features for the target machine learning task? In an effort to address this question, this thesis presents three important applications of deep sequence modelling methods. The first application is sentence modelling for web search task where the question addressed is: How to create a vector representation for a natural language sentence, aimed at a specific task such as web search? We propose Long Short-Term Memory Deep Structured Semantic Model (LSTM-DSSM), a model for information retrieval on click-through data with significant performance gains compared to existing state of the art baselines. The proposed LSTM-DSSM model sequentially takes each word in a sentence, extracts its relevant information, and embeds it into a semantic vector. The second application involves distributed compressive sensing, where the main questions addressed are: (a) How to relax the joint sparsity constraint? (b) How to exploit the structural dependency of a group of sparse vectors to reconstruct them better from down-sampled measurements (structures besides sparsity)? (c) How to exploit available offline data during sparse reconstruction at the decoder? We present a deep learning approach to distributed compressive sensing and show that it addresses the above three questions and is almost as fast as greedy methods during reconstruction. The third application is related to speech recognition. The question addressed here is: How to build a recurrent acoustic model for the task of phoneme recognition? We present a Recurrent Deep Stacking Network (R-DSN) architecture for this task. Each module in the R-DSN is initialized with an Echo State Network (ESN), and then all connection weights within the module are fine tuned.
A Comparison of the Efficiency of Applying Association Rule Discovery on Software Archive using Support - Confidence Model and Support - New Confidence Model

Software archives contain historical information about the development process of a software system. Using Association rule discovery, the development patterns can be extracted from these archives. This information is useful to support software modification activities, as indicated to software developers which modules are usually modified together during software maintenance or evolution. All previous works focused on mining associations with classical interestingness measure, support-confidence, where some disadvantage existed. The new Interestingness Measure, named as support-new confidence, was proposed by Liu et al. to improve the classical method. In this research, we present the comparison of the efficiency of applying association rule discovery on software archive using classical model and Liu et al.'s model. The experiments were conducted on software archive of KMyMoney software, an open source financial software project. The results show that the efficiency of the rules obtained in new model is higher than the rules obtained in classical model in navigation scenario.
Learning to localize itself-vision-motor association for legged robot

Presents a method that acquires a vision-motor association for a legged robot as a bottom-up technique for self-localization by action based perception categorization. By the method, the legged robot can move to the position where it can capture the desired view. The validity of the method is shown by a preliminary experiment, and future work is described.
Non-invasive Continuous Blood Pressure Monitoring Based on PWTT

Most non-invasive continuous blood pressure measurements are based on oscillometric methods that use electronic pump, oscillometric electronic sensor and computer aided analysis to display blood pressure. This device is inconvenience for patience due to prolong pumping activities. Several studies have shown that regression model, a function of pulse wave transit time (PWTT), is adequate to estimate systolic blood pressure (SBP). However, the model is unique for each person hence not suitable for general use for continuous measurement of BP. This paper proposed a new generalized regression model that is based on average slopes of those regression models. It has been shown that the proposed model is not unique to a person and adequate to estimate the SBP for various subjects. Thus, the proposed model may be used for non-invasive continuous SBP monitoring.
Onboard Real-time System for Digitizing and Geo-referencing of 3D Urban Environments

The onboard real-time system for three-dimensional environment reconstruction consists of an instrumented vehicle equipped with a 2D laser range scanner for data mapping, and GPS, INS and odometers for vehicle positioning and attitude information. The advantage of this system is its ability to perform data acquisition during the robot or vehicle navigation; the sensor needed being a basic 2D scanner with opposition to traditional expensive 3D sensors. Real-time data fusion is performed using an onboard software platform called RTMAPS. This system integrates the laser raw range data with the vehicle’s internal state estimator and is capable of reconstructing the 3D geometry of the environment by real-time geo-referencing instead of traditional pose estimation and data fusion approaches.
The ELSA wafer scale integration project

Outlines some of the technology, successful and unsuccessful, of part of a large European project in wafer scale integration (WSI). The work described is an attempt to build a 64 by 64 array processor on a 4-in wafer. Such a processor would have a computing power in excess of 10 billion operations per second. A test chip and a demonstration system, which achieves such a processing power, is also described. >
Robust Impedance Control of High-DOF Robot Based on ISMC and DOB

본 논문은 고자유도의 로봇에 대한 강인한 임피던스제어를 제안한다. 자유도가 높은 로봇에 대해서 동특성기반으로 제어하기 위해서는 해석적인 로봇의 동특성확보가 거의 불가능하기 때문에 수치해석적인 모델을 사용하게 된다. 이에 근본적으로 모델링오차가 존재하고 작업공간에서 임피던스제어기를 설계하는 경우에 많은 개수의 관절의 움직임의 영향을 받기 때문에 강인제어의 필요성이 더욱 절실하다. 이에 모델링 불확실성과 외란의 존재와 상관없이 원하는 임피던스를 유지하기 위해서는 공칭계통의 동특성에 슬라이딩모드의 강인성을 추가할 수 있는 적분슬라이딩모드제어를 도입하였고 입력외란의 영향을 제거할 수 있는 외란 관측기를 동시에 적용한 강인한 임피던스제어기를 제안하였다. 외란과 모델 불확실성이 존재함에도 불구하고 공칭계통을 기반으로 한 임피던스제어기의 특성을 그대로 유지할 수 있는 제어기가 설계되었다.
Towards Unified Conceptual Modeling and Integrated Analysis in Joint Applications of Project Management, Business Process Management and Simulation

This work proposes a systematic approach for model building and analysis of the product lifecycle processes of complex systems development, products and/or services, making use of Project Management, Business Process Management and Simulation techniques in an integrated and unified way. The approach is demonstrated making use of an academic model, describing an online Bookshop, but it envisages real systems applications and its use in Product Lifecycle Management in general. The modeling process starts with the creation of a unified reference process model, which is used for the development of multifaceted and cross consistent representations, each one related with a different view and discipline, aiming at the achievement of the complementary benefits resulting from their joint application. Keywords-unified conceptual modeling; product lifecycle management; business process management; project management; process simulation; process science and
A built-in RMS-to-DC converter for power supply monitoring of analog/mixed-signal circuits

Recently, the interest in analog and mixed-signal IC test has been raised dramatically. The development of high speed and high performance analog/mixed-signal circuits embedded in a single chip with their digital peer keeps posing new challenges to V L S I test engineers. Buil t in self-test (BIST) schemes have been recognized as capable of bringing improvements to analog and mixed-signal circuits testing. The power supply current monitoring as a structural testing methodology, which is applicable to both digital and analog/mixed-signal circuits testing, has recently been attracting more attention from both academia and industry. In this thesis, the power supply monitoring of analog and mixed-signal circuits testing is reviewed. A BIST scheme is presented for power supply rms current testing. A new builtin rms-to-dc converter is proposed. The R M S t o D C computation is carried out in the current domain. The system generates a digital signature proportional to the R M S value of the supply current. The digital signature is critical for an effective on-chip decision. A new M O S current squarer/divider circuit required in the converter is also proposed and implemented in a standard 0.18 pm C M O S technology. Silicon measurement results illustrate that the total harmonic distortion is less than 1.1%. The R M S t o D C converter has been implemented in the standard 0.35 p m C M O S technology. The total on-chip capacitance is only 74 pF. The effectiveness of the R M S t o D C converter has been verified by simulation. The simulated relative error of the R M S t o D C converter is less than 1% with a 100 K H z sinusoidal input signal. This circuit is suitable for B I S T applications on analog and mixed-signal ICs.