Miracle-dz/UniFAR-FTUs huggingface dataset:
The design of a CORBA group communication service

The common object request broker architecture (CORBA) is becoming a standard for distributed application middleware, and there are increasing needs for enriching the basic functionalities of CORBA. While mechanisms for persistence, transactions, event channels, etc. have been designed and specified for CORBA, no standard support is provided to handle object replication. In this paper we discuss the issue of augmenting CORBA with group communication, which is considered an adequate paradigm to handle replication. We distinguish two main approaches: the integration approach and the service approach. We argue that the service approach is more appropriate to CORBA as it preserves the modularity of the architecture. We describe a proposal for a group communication service and discuss some implementation issues.
Asynchronous Differential TDOA for Sensor Self-Localization

Most methods for sensor self-localization require either synchronization or round trip communications among the networked sensors. A differential time-difference-of-arrival (dTDOA) method is proposed in this paper that does not require such time synchronization nor round trip communications, thus greatly reduces demand on sensor communications resources and makes implementation much easier. Theoretical results are presented for the principle of the new method and simulations are also given that confirm the effectiveness of the proposed method.
Design and real life deployment of a pervasive monitoring system for dementia patients

We present the first phase of a project for monitoring elderly people suffering from dementia in the dasiareal lifepsila environment of an dasiaassisted livingpsila flat associated with a nursing home. Based on monitoring requirements derived in discussions with the nursing staff the system consists of a UBISENSE location system for monitoring location, a sound-system for monitoring vocal interaction, and the TECO dasiaParticlespsila sensor nodes mounted under the beds for sleep monitoring. In this paper we introduce the background and environment of the project, describe the requirements and the system and present some initial data collected in the first deployment period.
Model-based training: an approach supporting operability of critical interactive systems

Operation of safety critical systems requires qualified operators that have detailed knowledge about the system they are using and how it should be used. Instructional Design and Technology intends to analyze, design, implement, evaluate, maintain and manage training programs. Among the many methods and processes that are currently in use, the first one to be widely exploited was Instructional Systems Development (ISD) which has been further developed in many ramifications and is part of the Systematic Approach to Training (SAT) instructional design family. One of the key features of these processes (at least when they are refined) is the importance of Instructional Task Analysis, particularly the decomposition of a job in its tasks and sub-tasks in order to decide what knowledge and skills must be acquired by the trainee. This paper proposes to leverage this systematic approach using model-based approaches currently used for interactive systems engineering in order to design such training programs and thus to improve human reliability. The paper explains how task and interactive systems modeling can be bound to job analysis to ensure that each trainee meets the performance goals required. Such training ensures proper learning at the three levels of the Skills Rule Knowledge (SRK) levels of Rasmussen's. In the case study we describe the process for building a training program for operators of satellite ground segments, which is based on and compatible with the Ground Systems and Operations ECSS standard. Then, we propose to enhance this process with a) the application of a Systematic Approach to Training and b) the use of both a System Model and an Operator Task Model. The system model is build using the ICO notation while operators' goals and tasks are described using HAMSTERS notation.
Factors Influencing Outcomes after Ulnar Nerve Stability-Based Surgery for Cubital Tunnel Syndrome: A Prospective Cohort Study

Purpose Simple decompression of the ulnar nerve has outcomes similar to anterior transposition for cubital tunnel syndrome; however, there is no consensus on the proper technique for patients with an unstable ulnar nerve. We hypothesized that 1) simple decompression or anterior ulnar nerve transposition, depending on nerve stability, would be effective for cubital tunnel syndrome and that 2) there would be determining factors of the clinical outcome at two years. Materials and Methods Forty-one patients with cubital tunnel syndrome underwent simple decompression (n=30) or anterior transposition (n=11) according to an assessment of intra-operative ulnar nerve stability. Clinical outcome was assessed using grip and pinch strength, two-point discrimination, the mean of the disabilities of arm, shoulder, and hand (DASH) survey, and the modified Bishop Scale. Results Preoperatively, two patients were rated as mild, another 20 as moderate, and the remaining 19 as severe according to the Dellon Scale. At 2 years after operation, mean grip/pinch strength increased significantly from 19.4/3.2 kg to 31.1/4.1 kg, respectively. Two-point discrimination improved from 6.0 mm to 3.2 mm. The DASH score improved from 31.0 to 14.5. All but one patient scored good or excellent according to the modified Bishop Scale. Correlations were found between the DASH score at two years and age, pre-operative grip strength, and two-point discrimination. Conclusion An ulnar nerve stability-based approach to surgery selection for cubital tunnel syndrome was effective based on 2-year follow-up data. Older age, worse preoperative grip strength, and worse two-point discrimination were associated with worse outcomes at 2 years.
Improper signaling and symbol extensions: How far can we go with Gaussian P2P codebooks in the interfering MAC with TIN?

Meeting the challenges of 5G demands better exploitation of the available spectrum by allowing multiple parties to share resources. For instance, a secondary unlicensed system can share resources with the cellular uplink of a primary licensed system for an improved spectral efficiency. This induces interference which has to be taken into account when designing such a system. A simple yet robust strategy is treating interference as noise (TIN), which is widely adapted in practice. It is thus important to study the capabilities and limitations of TIN in such scenarios. In this paper, we study this scenario modelled as Multiple Access Channel (MAC) interfered by a Point-to-Point (P2P) channel. Here, we focus on rate maximization and power minimization problems separately. We use improper Gaussian signaling (instead of proper) at the transmitters to increase the design flexibility, which offers the freedom of optimizing the transmit signal pseudo-variance in addition to its variance. Furthermore, we allow correlation among the transmitted signals over orthogonal resource basis (i.e., time or frequency) for the purpose of optimal signaling design over the extended channel. We formulate the rate maximization problem as a semidefinite program, and use semidefinite relaxation (SDR) to obtain a near-optimal solution. Numerical optimizations show that, by improper Gaussian signaling the achievable rates can be improved upto three times depending on the strength of the interfering links. Furthermore, we observe significant benefits in power consumption by improper Gaussian signaling with symbol extensions compared to the traditional proper Gaussian signaling. Interestingly, by minimizing sum power given the solution of the rate maximization problem improves the energy efficiency significantly.
A SIMD optimization framework for retargetable compilers

Retargetable C compilers are currently widely used to quickly obtain compiler support for new embedded processors and to perform early processor architecture exploration. A partially inherent problem of the retargetable compilation approach, though, is the limited code quality as compared to hand-written compilers or assembly code due to the lack of dedicated optimizations techniques. This problem can be circumvented by designing flexible, retargetable code optimization techniques that apply to a certain range of target architectures. This article focuses on target machines with SIMD instruction support, a common feature in embedded processors for multimedia applications. However, SIMD optimization is known to be a difficult task since SIMD architectures are largely nonuniform, support only a limited set of data types and impose several memory alignment constraints. Additionally, such techniques require complicated loop transformations, which are tailored to the SIMD architecture in order to exhibit the necessary amount of parallelism in the code. Thus, integrating the SIMD optimization and the required loop transformations together in a single retargeting formalism is an ambitious challenge. In this article, we present an efficient and quickly retargetable SIMD code optimization framework that is integrated into an industrial retargetable C compiler. Experimental results for different processors demonstrate that the proposed technique applies to real-life target machines and that it produces code quality improvements close to the theoretical limit.
Dataflow based Near-Data Processing using Coarse Grain Reconfigurable Logic

The emergence of 3D-DRAM has rekindled interest in near-data processing research. This article introduces and describes a method for near-data processing using hybrid dataflow techniques implemented with coarse grain reconfigurable logic. We provide an initial evaluation of the concept to justify further development. The melding of these technologies produces increased throughput while dramatically reducing energy needs for suitable classes of algorithms. The benchmarks analyzed in this paper show performance speedups of 1.1 to 13.2 with energy reductions of 88% to 99%.
Land-cover Mapping in the Brazilian Amazon Using SPOT-4 Vegetation Data and Machine Learning Classification Methods

The main objective of this study is to evaluate the feasibility of deriving a land-cover map of the state of Mato Grosso, Brazil, for the year 2000, using data from the 1 km SPOT-4 VEGETATION (VGT) sensor. For this purpose we used a VGT temporal series of 12 monthly composite images, which were further transformed to physicalmeaningful fraction images of vegetation, soil, and shade. Classification of fraction images was implemented using several recent machine learning developments, namely, filtering input training data and probability bagging in a classification tree approach. A 10-fold cross validation accuracy assessment indicates that filtering and probability bagging are effective at increasing overall and class-specific accuracy. Overall accuracy and mean probability of class membership were 0.88 and 0.80, respectively. The map of probability of class membership indicates that the larger errors are associated with cerrado savanna and semi-deciduous forest.
A Tighter Bound on the Uniqueness of Sparsely-Used Dictionaries

In this paper, we consider the sparsely used dictionary learning problem and focus on the case that the dictionary is square with arbitrary entries and the coefficient matrix is a sparse with random entries, which is first proposed and studied by Wang and Spielman et al.[1], [2]. We improve the theoretical results with a tighter bounded uniqueness theorem, which says that O(n) samples are sufficient to uniquely determine the decomposition with probability one when given assumption is satisfied, and the proof is given.
Network Capability in Localizing Node Failures via End-to-End Path Measurements

We investigate the capability of localizing node failures in communication networks from binary states (normal/failed) of end-to-end paths. Given a set of nodes of interest, uniquely localizing failures within this set requires that different observable path states associate with different node failure events. However, this condition is difficult to test on large networks due to the need to enumerate all possible node failures. Our first contribution is a set of sufficient/necessary conditions for identifying a bounded number of failures within an arbitrary node set that can be tested in polynomial time. In addition to network topology and locations of monitors, our conditions also incorporate constraints imposed by the probing mechanism used. We consider three probing mechanisms that differ according to whether measurement paths are: (i) arbitrarily controllable; (ii) controllable but cycle-free; or (iii) uncontrollable (determined by the default routing protocol). Our second contribution is to quantify the capability of failure localization through: 1) the maximum number of failures (anywhere in the network) such that failures within a given node set can be uniquely localized and 2) the largest node set within which failures can be uniquely localized under a given bound on the total number of failures. Both measures in 1) and 2) can be converted into the functions of a per-node property, which can be computed efficiently based on the above sufficient/necessary conditions. We demonstrate how measures 1) and 2) proposed for quantifying failure localization capability can be used to evaluate the impact of various parameters, including topology, number of monitors, and probing mechanisms.
Ksensor: Multithreaded kernel-level probe for passive QoS monitoring

Traffic monitoring is an increasingly important discipline for nowadays networking, as Accounting, Security and Traffic Engineering lay on it. Besides, traffic bandwidth has increased exponentially in the last few years, and high-speed network monitoring has become a challenging task. Performance requirements are highly relevant for passive QoS monitoring systems. A low-level study of the capturing and processing stages on a traffic analysis system (TAS) has shown room for improvement. We provide an architecture able to cope with high-speed traffic monitoring using commodity hardware. Our system is intended to exploit the parallelism available in up-to- date workstations, which also introduces constraints for multithreaded QoS analysis. This paper presents a kernel-level framework (ksensor) that, keeping the previous requirements, removes some issues from user-level processing and effectively integrates QoS algorithms, improving the overall performance.
Formal Certification of Android Bytecode

Android is an operating system that has been used in a majority of mobile devices. Each application in Android runs in an instance of the Dalvik virtual machine, which is a register-based virtual machine (VM). Most applications for Android are developed using Java, compiled to Java bytecode and then translated to DEX bytecode using the dx tool in the Android SDK. In this work, we aim to develop a type-based method for certifying non-interference properties of DEX bytecode, following a methodology that has been developed for Java bytecode certification by Barthe et al. To this end, we develop a formal operational semantics of the Dalvik VM, a type system for DEX bytecode, and prove the soundness of the type system with respect to a notion of non-interference. We then study the translation process from Java bytecode to DEX bytecode, as implemented in the dx tool in the Android SDK. We show that an abstracted version of the translation from Java bytecode to DEX bytecode preserves the non-interference property. More precisely, we show that if the Java bytecode is typable in Barthe et al's type system (which guarantees non-interference) then its translation is typable in our type system. This result opens up the possibility to leverage existing bytecode verifiers for Java to certify non-interference properties of Android bytecode.
Judgements during information seeking: a naturalistic approach to understanding the assessment of enough information

In this article, theories of human judgement and decision making are reviewed and their use by library and information science researchers examined. A different perspective on judgement and decision making is offered by the field of naturalistic decision making (NDM) and the implications of this approach are considered for an expanded understanding of how judgements and decisions are made during information seeking. This discussion is illustrated by a case from a recent empirical investigation into how judgements of enough information are made in the workplace. The article concludes with a critical evaluation of the NDM approach. It is argued that NDM, a recent development in decision theory, offers a new perspective from which to investigate judgements and decisions during information seeking.
Cross-lingual Information Retrieval based on Multiple Indexes

In this paper we present the technical details of the retrieval system with which we participated at the CLEF09 Ad-hoc TEL task. We present a retrieval approach based on multiple indexes for different languages which is combined with a conceptbased retrieval approach based on Explicit Semantic Analysis. In order to create the language-specific indices for each language, a language detection approach is applied as preprocessing step. We combine the different indices through rank aggregation and present our experimental results with different rank aggregation strategies. Our results show that the use of multiple indices (one for each language) does not improve upon a baseline index containing documents in all languages. The combination with concept based retrieval, however, results in better retrieval performance in some of the cases considered. For the bi-lingual tasks the final retrieval results of our system were the 5th best results on the BL dataset and the second best on the BNF dataset.
Electro-hydraulically actuated forestry manipulator: Modeling and Identification

We present results of modeling dynamics of a forestry manipulator, in which we consider its mechanics, as well as its hydraulic actuation system. The mathematical model of its mechanics is formulated by Euler-Lagrange equations, for which the addition of friction forces is straightforward. Dynamics of the hydraulic system is modeled upon first principle laws, which concern flow through orifices and fluid compressibility. These models lead to a set of equations with various unknown parameters, which are related to the inertias, masses, location of center of masses, friction forces, and valve coefficients. The numerical values of these parameters are estimated by the use of least-square methods, which is made feasible by transforming the models into linear representations. The results of simulation tests show a significant correspondence between measured and estimated variables, validating our modeling and identification approach.
Context Aware Middleware Architecture for Wireless Sensor Network

Wireless sensor networks are application specific,data centric networks where different applications run on deployed network. Each application interprets the underlying sensor network differently and each changing event has different effect on running applications.In this paper we have proposed context aware middleware architecture called as ’MidSen’. This architecture bridges the gap between multiple applications running at application level and deployed sensor networks.MidSen architecture handles static as well as dynamically changing network and application components.MidSen has adopted a rule based engine to handle system dynamics. Midsen makes applications flexible by allowing them to update their rules against knowledge base. Our experimental results show that proposed Context Aware Service Discovery (CASD)algorithm gives better recall value and precision compare to previously proposed discovery algorithms.
Association of The Common CYP1A1*2C Variant (Ile462Val Polymorphism) with Chronic Myeloid Leukemia (CML) in Patients Undergoing Imatinib Therapy

Objective Cytochrome P450 is one of the major drug metabolizing enzyme families and its role in metabolism of cancer drugs cannot be less emphasized. The association be- tween single nucleotide polymorphisms (SNPs) in CYP1A1 and pathogenesis of chronic myeloid leukemia (CML) has been investigated in several studies, but the results observed vary based on varied risk factors. The objective of this study was to investigate the risk factors associated with the CYP1A1*2C [rs1048943: A>G] polymorphism in CML patients and its role in therapeutic response to imatinib mesylate (IM) affecting clinico-pathological parameters, in the Indian population. Materials and Methods In this case-control study, CYP1A1*2C was analysed in CML patients. After obtaining approval from the Ethics Committee of oncology hospital, we collected blood samples from 132 CML patients and 140 matched controls. Genom- ic DNA was extracted and all the samples were analysed for the presence of the CYP1A1*2C polymorphism using allele-specific polymerase chain reaction, and we examined the relationship of genotypes with risk factors such as gender, age, phase of the disease and other clinical parameters. Results We observed a significant difference in the frequency distribution of CYP1A1*2C genotypes AA (38 vs. 16%, P=0.0001), AG (57 vs. 78%, P=0.0002) and GG (5 vs. 6%, P=0.6635) between patients and controls. In terms of response to IM therapy, significant variation was observed in the frequencies of AA vs AG in major (33 vs 67%) and poor (62 vs 31%) hematological responders, and AA vs AG in major (34 vs. 65%) and poor (78 vs. 22%) cytogenetic responders. However, the patients with the GG homozygous genotype did not show any significant therapeutic outcome. Conclusion The higher frequency of AG in controls indicates that AG may play a protec- tive role against developing CML. We also found that patients with the AG genotype showed favorable treatment response towards imatinib therapy, indicating that this polymorphism could serve as a good therapeutic marker in predicting response to such therapy.
A Two-Level Multi-Modal Approach for Story Segmentation of Large News Video Corpus

This paper presents an enhanced work from our previous paper [Chaisorn et al. 2002]. The system is enhanced to perform news story segmentation on a large video corpus used in TRECVID 2003 evaluation. We use a combination of features include visual-based features such as color, object-based features such as face, video-text, temporal features such as audio and motion, and semantic feature such as cue-phrases. We employ Decision Tree and specific detectors to perform shot classification/tagging. We use the shot category information along with two temporal features to identify story boundaries using HMM (Hidden Markov Models). A heuristic rules-based technique is applied to classify each detected story into “news” or “misc”.
The design of campus roaming system based on virtual reality technology

The development of virtual roaming system is an important application of virtual reality technology. The purpose of this paper is to implement a three-dimensional virtual environment to display the campus of the College as a reference. During the process we made various models of the campus by using 3ds Max and set up the virtual roaming system by using Cortona VRML. We also discussed a general design and development process of a virtual roaming system based on the virtual reality technology.