Miracle-dz/UniFAR-FTUs huggingface dataset:
Ontologies for Integrating Engineering Applications

In all types of communication, the ability to share information is often hindered because the meaning of information can be drastically affected by the context in which it is viewed and interpreted. This is especially true in manufacturing, because of the growing complexity of manufacturing information and the increasing need to exchange this information among various software applications. Different representations of the same information may be based on different assumptions about the world, and use differing concepts and terminology – and conversely, the same terms may be used in different contexts to mean different things. Often, the loosely defined natural-language definitions associated with the terms will be too ambiguous to make the differences evident, or will not provide enough information to resolve the differences. A solution to this problem is the use of taxonomies or ontologies of manufacturing concepts and terms, because ontologies provide a way to make explicit the semantics (i.e., the meaning) for the concepts used, rather than relying just on the syntax used to encode those concepts. Ontological techniques can be useful for giving unambiguous definitions of product and process capabilities and evolving designs and design requirements, unifying the differences in how knowledge is conceptualized across multiple product and process domains, and translating those definitions into the specialized representation languages of application systems. This paper gives an overview of current research and development on ontologies as it relates to mechanical engineering applications, along with examples of how ontologies can be used to facilitate the exchange of information among manufacturing applications.
Learning Probabilistic Subcategorization Preference by Identifying Case Dependencies and Optimal Noun Class Generalization Level

This paper proposes a novel method of learning probabilistic subcategorization preference. In the method, for the purpose of coping with the ambiguities of case dependencies and noun class generalization of argument/adjunct nouns, we introduce a data structure which represents a tuple of independent partial subcategorization frames. Each collocation of a verb and argument/adjunct nouns is assumed to be generated from one of the possible tuples of independent partial subcategorization frames. Parameters of subcategorization preference are then estimated so as to maximize the subcategorization preference function for each collocation of a verb and argument/adjunct nouns in the training corpus. We also describe the results of the experiments on learning probabilistic subcategorization preference from the EDR Japanese bracketed corpus, as well as those on evaluating the performance of subcategorization preference.
AUTOMATIC POSE ESTIMATION OF IMAGERY USING FREE-FORM CONTROL LINEAR FEATURES

: Automatic Single Photo Resection (SPR) remains to be one of the challenging problems in digital photogrammetry. Visibility and uniqueness of distinct control points in the input imagery limit robust automation of the pose estimation procedure. Recent advances in digital photogrammetry mandate adopting higher-level primitives such as free-form control linear features for replacing traditional control points. Linear features can be automatically extracted from the image space. On the other hand, object space control linear features can be obtained from an existing GIS layer containing 3-D vector data such as road network, or from terrestrial Mobile Mapping Systems (MMS). In this paper, we present a new approach for simultaneously determining the position and attitude of the involved imagery as well as the correspondence between image and object space features. This approach does not necessitate having one to one correspondences between image and object space primitives, which makes it robust against changes and/or discrepancies between them. This characteristic will be helpful in detecting changes between object and image space linear features (e.g. due to temporal effects). The parameter estimation and matching follow an optimal sequential procedure that depends on the magnitude and direction of image space displacements resulting from incremental changes to the Exterior Orientation Parameters (EOP). Experimental results using real data proved the feasibility and robustness of our approach, especially when compared to those obtained through traditional manual procedures. Changes and/or discrepancies between the data sets are detected and highlighted through consistency analysis of the resulting correspondences.
Efficient bottom-up heap analysis for symbolic path-based data access summaries

We propose a heap analysis for extracting data access summaries based on symbolic access paths (SAPs) of methods in object-oriented languages. The analysis takes advantage of the insight that typical programs access dynamic data structures in regular manners. We combine this insight with a bottom-up approach that computes a local summary for each basic block, loop, and method in the program, which is then encapsulated into an abstract block in order to efficiently handle the higher levels of the analysis. We solve the problem of the dependence of local analysis results on the global heap aliasing by inferring the sets of aliases on which the correctness of the local results is predicated. Experimental evaluation for Java shows that for typical programs that use dynamic data structures, our analysis runs in a fast single pass and produces useful results.
Cerebral Sinus and Venous Thrombosis Associated with von Willebrand Factor, Independently of Factor VIII

Background and purpose Previous studies have linked procoagulant factor VIII (F VIII) to an increased risk of venous thrombosis, whereas the relation between plasma von Willebrand factor (VWF) and venous thrombosis remains poorly understood. Elevated VWF levels are frequently found in patients with cerebral sinus and venous thrombosis (CSVT), always in association with high F VIII levels. We describe a patient with CSVT accompanied by elevated VWF levels without high F VIII levels. Case description A 23-year-old healthy man who had headache noticed difficulty in moving the right hand. On the following day, he lost consciousness and had partial seizures of the right hand. After regaining consciousness, weakness of the right extremities developed. The cranial angiogram confirmed occlusion of the superior sagittal sinus. The levels of VWF and F VIII were 238% and 101.9 IU/dl, respectively. We performed balloon percutaneous transluminal angioplasty and mechanical thrombectomy, leading to successful recanalization of the intracranial sinuses. VWF levels were decreased along with radiographic improvement, independently of F VIII. Conclusion VWF may contribute to CSVT and that inhibition of VWF activity potentially has a role in the future treatment of pathological conditions related to venous thrombosis.
Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth

Hamilton's (1989) nonlinear Markovian filter is extend to allow state transitions to be duration dependent. Restrictions are imposed on the state transition matrix associated with a T-order Markov system such that the corresponding first-order conditional transition probabilities are functions of both the inferred current state and also the number of periods the process has been in that state. High-order structure is parsimoniously summarized by the inferred duration variable. Applied to U.S. post-war real GNP growth rates, we obtain evidence in support of nonlinearity, asymmetry between recessions and expansions, as well as strong duration dependence for recessions but not for expansions
Development of Prioritized Handoff Scheme for Congestion Control in Multimedia Wireless Network

The rapid increase in the use of mobile devices demand the need to meet different multimedia application requirements of the users. However, the application demand and allocation could lead to congestion if the network has to maintain such high resources for the quality of service (QoS) requirements of the applications. In this paper, a new admission control policy for wireless mobile multimedia networks is being proposed. Two kinds of traffics are assumed to compete for the access to the limited number of frequency channels available in each cell: Real-time and non-real- time calls. The calls are further categorized as new real- time and non-real-time calls or real-time and non-real- time handoff calls. Hot spot calls are given priority over cold spot calls if the cold spot request is non-real-time. Call of the same cell and priority are served using ticket scheduling. Blocked new real-time and non-real-time calls are lost, while blocked real-time and non-real-time handoff calls can wait in the handoff buffer for channel to be available. The system is modelled by a multi- dimensional Markov chain, and a numerical analysis would be presented to calculate the blocking probabilities of the calls. The scheme would also be simulated using extensive runs to investigate its performance.
Heuristics for the automatic identification of irregularities in spreadsheets

Spreadsheet programs turned out to be the most popular end-user programming environment that has ever been released. Important decisions are based on the results of spreadsheet programs and the list of known errors with large impact is growing daily- although it surely is only the top of an iceberg.One way out of the crisis might be the introduction of software engineering techniques into spreadsheet development. Suggestions for the improvement of spreadsheet development range back as far as into the late eighties, but none has been successful yet. We argue this is either because not enough effort is put into the roll-out of the technique to the users and, mainly, because they neglect the fact that spreadsheet programmers are end-users, not willing or not able to spend any time on learning software engineering methods. We found out that most end users are willing to verify their spreadsheets, but only view have the time and skills to do really systematic testing of spreadsheets.We developed an approach to generate two orthogonal abstract representations of spreadsheet programs that are then displayed to the user by different visualisation techniques to support the auditing process. Usually, irregularities in the visualisation point out hot-spots on the spreadsheet with a high likelihood of erroneous formulas. In this paper we present new heuristics for identifying hot spots that are very efficient for large spreadsheet programs.
A fourth order dual method for staircase reduction in texture extraction and image restoration problems

We propose a novel fourth order dual method for the minimization of the non-smooth semi-norm ∥㥅·∥1 when in amalgamation with a new staircase reducing texture decomposition model of image processing. The proposed model incorporating this high order energy is a variant of the Chambolle Lions denoising model that additionally utilizes a negative Sobolev norm. We claim that the dual method is faster and more stable than the current gradient descent time marching algorithms often used to minimize such energies. Moreover, a proof of convergence of the proposed method, in conjunction with the new model, will be provided. Lastly, we provide guidelines on how the new energy and proposed framework can be naturally incorporated into many popular texture extraction and restoration models of image processing.
High-Level Specification and Code Generation for Service-Oriented Tool Adapters

The development of complex systems requires tool support for the different phases of the system life cycle. To allow for an efficient development process, the involved tools need to be integrated, e.g. by exchanging tool data or providing trace ability between the data. Despite the availability of tool integration platforms and frameworks, it is labor-intensive and costly to build tool integration solutions. Industrial tool integration initiatives such as OSLC (Open Services for Lifecycle Collaboration) demand complex configurations and the adherence to integration standards. This further complicates building an integration solution. We propose an approach that uses formalized specifications to systematize tool integration and specialized code generators to automate the process of building tool adapters. We evaluate our approach with the implementation of a code generator that creates service-oriented tool adapters conforming to the OSLC industry initiative.
Invariant object recognition with trace learning and multiple stimuli present during training

Over successive stages, the ventral visual system develops neurons that respond with view, size and position invariance to objects including faces. A major challenge is to explain how invariant representations of individual objects could develop given visual input from environments containing multiple objects. Here we show that the neurons in a 1-layer competitive network learn to represent combinations of three objects simultaneously present during training if the number of objects in the training set is low (e.g. 4), to represent combinations of two objects as the number of objects is increased to for e.g. 10, and to represent individual objects as the number of objects in the training set is increased further to for e.g. 20. We next show that translation invariant representations can be formed even when multiple stimuli are always present during training, by including a temporal trace in the learning rule. Finally, we show that these concepts can be extended to a multi-layer hierarchical network model (VisNet) of the ventral visual system. This approach provides a way to understand how a visual system can, by self-organizing competitive learning, form separate invariant representations of each object even when each object is presented in a scene with multiple other objects present, as in natural visual scenes.
Use of Local Group Information to Identify Communities in Networks

The recent interest in networks has inspired a broad range of work on algorithms and techniques to characterize, identify, and extract communities from networks. Such efforts are complicated by a lack of consensus on what a “community” truly is, and these disagreements have led to a wide variety of mathematical formulations for describing communities. Often, these mathematical formulations, such as modularity and conductance, have been founded in the general principle that communities, like a G(n, p) graph, are “round,” with connections throughout the entire community, and so algorithms were developed to optimize such mathematical measures. More recently, a variety of algorithms have been developed that, rather than expecting connectivity through the entire community, seek out very small groups of well-connected nodes and then connect these groups into larger communities. In this article, we examine seven real networks, each containing external annotation that allows us to identify “annotated communities. ” A study of these annotated communities gives insight into why the second category of community detection algorithms may be more successful than the first category. We then present a flexible algorithm template that is based on the idea of joining together small sets of nodes. In this template, we first identify very small, tightly connected “subcommunities” of nodes, each corresponding to a single node’s “perception” of the network around it. We then create a new network in which each node represents such a subcommunity, and then identify communities in this new network. Because each node can appear in multiple subcommunities, this method allows us to detect overlapping communities. When evaluated on real data, we show that our template outperforms many other state-of-the-art algorithms.
Control Performance Evaluation of Selected Methods of Feedback Scheduling of Real-time Control Tasks

Feedback scheduling (FS) often refers to the problem of sampling period selection for real-time control tasks that compete for limited computing resources such as processor, network, or battery power. Its goal is to optimize the aggregated control performance achieved by all tasks by efficiently using the scarce resources. In this paperrepresentative existing FS methods are selected, their main features are identified, and a simple control performance evaluation is performed. The latter shows that a) jitters in job executions hide the true performance that can be achieved by the analyzed FS methods, b) after completely removing the degrading effects of jitters, the performance of each FS method dramatically changes, and c) the relative benefit provided by each method depends on the type of perturbations affecting the plants.
Decoupling of CDMA multiuser detection via the replica method

In CDMA, the optimal multiuser detector in mean square sense is the conditional mean estimator (CME) regardless of the input distribution, which outputs the expected value of the transmitted symbols conditioned on the received signal and the channel state (spreading sequences, fading, etc). In this paper, we first note that every multiuser detector can be reformulated as the CME for a certain postulated CDMA channel with a postulated input distribution which may be different from the actual channel and inputs. Using the replica method developed in statistical physics, a class of generalized CME front end applied to randomly spread CDMA is studied in a unified framework in the large-system limit. It is found that for any input distribution, the single-user channel seen at the generalized CME output for each user is equivalent to a Gaussian channel followed by a monotonic decision function. The degradation factor in the effective SNR of the equivalent channel due to multiple access interference is the multiuser efficiency, which is found to satisfy a fixed-point equation. The spectral efficiency of such a system under both joint and separate decoding are derived. Based on a general linear vector channel model, our results are also applicable to MIMO channels such as those arising in multiantenna systems.
Optimum spectral sensitivity functions for single sensor color imaging

A cost-effective and convenient approach for color imaging is to use a single sensor and mount a color filter array (CFA) in front of it, such that at each spatial position the scene information in only one color channel is captured. To estimate the missing colors at each pixel, a demosaicing algorithm is applied to the CFA samples. Besides the filter arrangement and the demosaicing method, the spectral sensitivity functions of the CFA filters considerably affect the quality of the demosaiced image. In this paper, we propose an algorithm to compute the optimum spectral sensitivities of filters in the single sensor imager. The proposed algorithm solves a constrained optimization problem to find optimum spectral sensitivities and the corresponding linear demosaicing method. An important constraint for this problem is the smoothness of spectral sensitivities, which is imposed by modeling these functions as a linear combination of several smooth kernels. Simulation results verify the effectiveness of the proposed algorithm in finding optimal spectral sensitivity functions, which outperform measured camera sensitivity functions.
Transparent fault-tolerance in parallel Orca programs

With the advent of large-scale parallel computing systems, making parallel programs fault-tolerant becomes an important problem, because the probability of a failure increases with the number of processors. In this paper, we describe a very simple scheme for rendering a class of parallel Orca programs fault-tolerant. Also, we discuss our experience with implementing this scheme on Amoeba. Our approach works for parallel applications that are not interactive. The approach is based on making a globally consistent checkpoint from time to time and rolling back to the last checkpoint when a processor fails. Making a consistent global checkpoint is easy in Orca, because its implementation is based on reliable broadcast. The advantages of our approach are its simplicity, ease of implementation, low overhead, and transparency to the Orca programmer.
Pulmonary Complications After Cardiac Surgery

Over the past two decades there has been a steady evolution in the practice of adult cardiac surgery with the introduction of “off-pump” surgery. However, respiratory complications remain a leading cause of postcardiac surgical morbidity and can prolong hospital stays and increase costs. The high incidence of pulmonary complications is in part due to the disruption of normal ventilatory function that is inherent to surgery in the thoracic region. Furthermore, patients undergoing such surgery often have underlying illnesses such as intrinsic lung disease (e.g., chronic obstructive pulmonary disease) and pulmonary dysfunction secondary to cardiac disease (e.g., congestive heart failure) that increase their susceptibility to postoperative respiratory problems. Given that many patients undergoing cardiac surgery are thus susceptiple to pulmonary complications, it is remarkable that more patients do not suffer from them during and after cardiac surgery. This is to a large degree because of advances in anesthetic, surgical and critical care that, for example, have reduced the physiological insults of surgery (e.g., better myocardial preservation techniques) and streamlined care in the immediate postoperative period (e.g., early extubation). Moreover, the development of minimally invasive surgery and nonbypass techniques are further evidence of the attempts at reducing the homeostatic disruptions of cardiac surgery. This review examines the available information on the incidences, consequences, and treatments of postcardiac surgery respiratory complications.
A Naturalistic Treatment for Panic Disorder The Importance of Emotion-Focused Process

Although cognitive-behavior therapy (CBT) has repeatedly demonstrated treatment efficacy for panic disorder [1], establishing the empirical basis for psychodynamic psychotherapy (PD) remains important because CBT is not effective for all panic patients [2, 3]. Busch [4] argues persuasively that diversifying the number of empirically supported psychotherapeutic options available to panic patients is necessary to fully respond to the range of panic patients’ clinical needs. As Busch et al. note, while highly effective for many individuals, CBT does not work for all panic patients [2, 3]. Some patients have difficult executing the exposure-based approaches characterizing CBT approaches for panic disorder. Other patients do not engage in the between-session work that functions as a critical cornerstone of CBT approaches. Investigators [3] note that up to 38% of patients experience no symptom relief or relapse subsequent [5] to treatment discontinuation in closely controlled CBT trials. The concern that cognitive-behavioral treatment will not sufficiently facilitate the exploration of the personal meaning of symptoms leads other patients to reject CBT as their modality of choice. For patients who do seek out and receive CBT, questions regarding the long-term efficacy of these treatments remain. Milrod and Busch [5] underscore the problematic lack of evidence supporting the long-term maintenance of short-term treatment gains in CBT. They also underscore the need for treatments that synergistically target symptom reduction aswell as broader based changes in personality functioning tomaintain treatment gains across time and to effectively address the disruptions across multiple domains that occur for many panic patients [4, 6]. Working to diversify the range of psychotherapeutic treatment options available to panic patients who either do not respond to CBT or who elect to pursue exploratory treatments is