Ball-burnishing effect on deep residual stress on AISI 1038 and AA2017-T4

Ball-burnishing induces compressive residual stresses on treated materials by the effect of plastic deformation. The result is an increase in the fatigue life of the treated part, retarding the initiation of cracks on the surface. Compressive residual stresses have been previously measured by X-ray diffraction near the surface, revealing considerably high values at the maximum analyzed depth, in relation to other finishing processes such as shot peening. However, the maximum analyzed depth is very limited by using this technique. In this paper, the incremental hole drilling (IHD) technique is tested to measure residual stresses, being able to reach a 2-mm measuring depth. To that objective, a commercial strain gage is used and calibrated using finite element model simulations. A second Finite Element Model based on material removal rate is developed to obtain the equations to calculate the strain release through IHD. Finally, residual stresses are measured experimentally with that technique on two different materials, confirming that ball-burnishing increases the compressive residual stresses in layers up to 0.5?mm deep for the testing conditions, which is a good response to industrial needs. The method proves to be suitable, simple and inexpensive way to measure the value of these tensions.     

Stability and electronic properties of armchair boron nitride/carbon nanotubes

In this work are studied the electronic and structural properties of armchair boron nitride/carbon nanotubes using first principles calculations. The density functional within the generalized gradient approximation (HSEh1PBE-GGA) is used. For each composition, different bonding schemes for the construction of the hybrid systems were employed. Among them, structural stability with neutral charge was determined for the following compositions: T1: B₄₀N₃₅C₇₅H₂₀, T2: B₃₅N₄₀C₇₅H₂₀, T3: B₃₇N₃₈C₇₅H₂₀, T4 : B₃₇N₃₇C₇₆H₂₀, and T7: B₃₅N₃₅C₈₀H₂₀. All these hybrid nanotubes have high polarity; the T3, T4 and T7 are semiconductors: whereas T1 and T2 are conductor in character. The formers also have magnetic behavior. These properties together with a low-chemical potential suggest applications as nano-vehicle for drug delivery. These mixed nanotubes also have potential applications in the electronic devices based on the small work function.     

Utility of 18 F‐FDG PET/CT scan to diagnose the etiology of fever of unknown origin in patients on dialysis

Introduction: Studies on fever of unknown origin (FUO) in patients of chronic kidney disease and end stage renal disease patients on dialysis were not many. In this study, we used 18 F‐FDG PET/CT scan whole body survey for detection of hidden infection, in patients on dialysis, labelled as FUO. Methods: In this retrospective study, 20 patients of end stage renal disease on dialysis were investigated for the cause of FUO using 18F‐FDG PET/CT scan. All these patients satisfied the definition of FUO as defined by Petersdorf and Beeson. Any focal abnormal site of increased FDG concentration detected by PET/CT, either a solitary or multiple lesions was documented and at least one of the detected abnormal sites of radio tracer concentration was further examined for histopathology. Findings: All patients were on renal replacement therapy. Of these, 18 were on hemodialysis and two were on peritoneal dialysis. 18F‐FDG PET/CT scan showed metabolically active lesions in 15 patients and metabolically quiescent in five patients. After 18F‐FDG PET/CT scan all, but one patient had a change in treatment for fever. Anti‐tuberculous treatment was given in 15 patients, antibiotics in four patients and anti‐malaria treatment in one patient. Discussion: The present study is first study of 18F‐FDG PET/CT scan in patients of end stage renal disease on dialysis with FUO. The study showed that the 18 F FDG PET/CT scan may present an opportunity to attain the diagnosis in end stage renal disease patients on dialysis with FUO.     

Some questions on the corrosion of steel in concrete—Part I: when,how and how much steel corrodes

It is widely accepted that concrete-embedded steel is in a passive state. However, there are some exceptional circumstances that induce corosion in an active state within concrete structures, thereby severely reducing their durability. This two-part paper analyses some major questions which, however elementary they may be, are still controversial in scientific, technical and economic terms. The first part provides answers to the following questions on the steel/concrete/environment system:

1. How does steel in concrete normally behave?
2. What are the initiating factors for depassivation?
3. What are the effects of corrosion?
4. What is the morphology of corrosion in the active state? and
5. What is the corrosion rate threshold above which the durability of reinforced concrete structures is impaired? The answers to these questions are provided in light of experimental results, most of which were obtained by the authors themselves.

     

Malware detection using assembly and API call sequences

One of the major problems concerning information assurance is malicious code. To evade detection, malware has also been encrypted or obfuscated to produce variants that continue to plague properly defended and patched networks with zero day exploits. With malware and malware authors using obfuscation techniques to generate automated polymorphic and metamorphic versions, anti-virus software must always keep up with their samples and create a signature that can recognize the new variants. Creating a signature for each variant in a timely fashion is a problem that anti-virus companies face all the time. In this paper we present detection algorithms that can help the anti-virus community to ensure a variant of a known malware can still be detected without the need of creating a signature; a similarity analysis (based on specific quantitative measures) is performed to produce a matrix of similarity scores that can be utilized to determine the likelihood that a piece of code under inspection contains a particular malware. Two general malware detection methods presented in this paper are: Static Analyzer for Vicious Executables (SAVE) and Malware Examiner using Disassembled Code (MEDiC). MEDiC uses assembly calls for analysis and SAVE uses API calls (Static API call sequence and Static API call set) for analysis. We show where Assembly can be superior to API calls in that it allows a more detailed comparison of executables. API calls, on the other hand, can be superior to Assembly for its speed and its smaller signature. Our two proposed techniques are implemented in SAVE) and MEDiC. We present experimental results that indicate that both of our proposed techniques can provide a better detection performance against obfuscated malware. We also found a few false positives, such as those programs that use network functions (e.g. PuTTY) and encrypted programs (no API calls or assembly functions are found in the source code) when the thresholds are set 50% similarity measure. However, these false positives can be minimized, for example by changing the threshold value to 70% that determines whether a program falls in the malicious category or not.     

Tetra-trees properties in graphic interaction

The localization of the components of an object near to a device before obtaining the real interaction is usually determined by means of a proximity measurement to the device of the object’s features. In order to do this efficiently, hierarchical decompositions are used, so that the features of the objects are classified into several types of cells, usually rectangular.In this paper we propose a solution based on the classification of a set of points situated on the device in a little-known spatial decomposition named tetra-tree. Using this type of spatial decomposition gives us several quantitative and qualitative properties that allow us a more realistic and intuitive visual interaction, as well as the possibility of selecting inaccessible components. These features could be used in virtual sculpting or accessibility tasks.In order to show these properties we have compared an interaction system based on tetra-trees to one based on octrees.     

Using knowledge of misunderstandings to increase the robustness of spoken dialogue systems

This paper proposes a new technique to increase the robustness of spoken dialogue systems employing an automatic procedure that aims to correct frames incorrectly generated by the system’s component that deals with spoken language understanding. To do this the technique carries out a training that takes into account knowledge of previous system misunderstandings. The correction is transparent for the user as he is not aware of some mistakes made by the speech recogniser and thus interaction with the system can proceed more naturally. Experiments have been carried out using two spoken dialogue systems previously developed in our lab: Saplen and Viajero, which employ prompt-dependent and prompt-independent language models for speech recognition. The results obtained from 10,000 simulated dialogues show that the technique improves the performance of the two systems for both kinds of language modelling, especially for the prompt-independent language model. Using this type of model the Saplen system increases sentence understanding by 19.54%, task completion by 26.25%, word accuracy by 7.53%, and implicit recovery of speech recognition errors by 20.3%, whereas for the Viajero system these figures increase by 14.93%, 18.06%, 6.98% and 15.63%, respectively.     

A proposal for student modeling based on ontologies and diagnosis rules

The advances in the educational field and the high complexity of student modeling have provoked it to be one of the aspects more investigated in Intelligent Tutoring Systems (ITSs). The Student Models (SMs) should not only represent the student’s knowledge, but rather they should reflect, as faithfully as possible, the student’s reasoning process. To facilitate this goal, in this article a new approach to student modeling is proposed that benefits from the advantages of Ontological Engineering, advancing in the pursue of a more granular and complete knowledge representation. It’s focused, mainly, on the SM cognitive diagnosis process, and we present a method providing a rich diagnosis about the student’s knowledge state – especially, about the state of learning objectives reached or not. The main goal is to achieve SMs with a good adaptability to the student’s features and a high flexibility for its integration in varied ITSs.     

An educational exercise examining the role of model attributes on the creation and alteration of CAD models

Computer-aided design (CAD) is a ubiquitous tool that today’s students will be expected to use proficiently for numerous engineering purposes. Taking full advantage of the features available in modern CAD programs requires that models are created in a manner that allows others to easily understand how they are organized and alter them in an efficient and robust manner. The results of a class-based exercise are presented to examine the role of model attributes on model creation, alteration, and student perception. Two popular CAD programs are used for the exercise: SolidWorks and Pro|Engineer. General results from both programs are reported. Fewer more complex features are found to be correlated with reduced modeling time. Simple features are shown to be positively correlated with the number of features retained without change. More complex features are found to be negatively correlated with the number of new features. Student perceptions of model quality and intuitiveness are positively correlated with the amount of feature reuse. Student survey data shows a preference for simpler features, the naming of features, and the use of reference geometry. The results do not allow for a generic approach regarding feature complexity to be prescribed. Overall, properly conveying design intent is shown to be positively correlated with design retention and negatively correlated with alteration time.     

EDUCA: A web 2.0 authoring tool for developing adaptive and intelligent tutoring systems using a Kohonen network

This paper presents a Web 2.0 Learning Environment, for a systematic creation of adaptive and intelligent tutoring systems. Authoring contents is made by a community of users including teachers and students. The tutoring systems adapt the contents according to the best learning style using self-organizing maps (SOMs). The SOM was trained for classifying Felder–Silverman learning styles. The most important advantage of these unsupervised neural networks is that they do not require an external teacher for presenting a training set. The approach was implemented under an authoring tool that allows the production of personalized learning material to be used under collaborative and mobile learning environments. The tutoring systems together with the neural network can also be exported to mobile devices. We present different results to the approach working under the authoring tool.