Detecting Floating-Point Errors via Atomic Conditions

This paper tackles the important, difficult problem of detecting program inputs that trigger large floating-point errors in numerical code. It introduces a novel, principled dynamic analysis that leverages the mathematically rigorously analyzed condition numbers for atomic numerical operations, which we call atomic conditions, to effectively guide the search for large floating-point errors. Compared with existing approaches, our work based on atomic conditions has several distinctive benefits: (1) it does not rely on high-precision implementations to act as approximate oracles, which are difficult to obtain in general and computationally costly; and (2) atomic conditions provide accurate, modular search guidance. These benefits in combination lead to a highly effective approach that detects more significant errors in real-world code (e.g., widely-used numerical library functions) and achieves several orders of speedups over the state-of-the-art, thus making error analysis significantly more practical. We expect the methodology and principles behind our approach to benefit other floating-point program analysis tasks such as debugging, repair and synthesis. To facilitate the reproduction of our work, we have made our implementation, evaluation data and results publicly available on GitHub at https://github.com/FP-Analysis/atomic-condition.ISSN:2475-142

Automatic re-contouring of repair-welded tool moulds

The process of repairing damaged tool moulds is conducted manually in the industry. This results in long process times as well as a high dependence of the repair result on the experience of the worker. After a visual inspection, the detected damages are removed by metal cutting and the missing material is filled by a build-up welding process. Afterwards, the target geometry is restored via machining re-contouring process. Because of the individual tool mould surface and welded seam, each repair case requires an individual machining strategy as well as toolpaths and process control parameters to ensure high surface quality and shape accuracy. This paper introduces an innovative design for re-contouring of repair-welded tool moulds, which takes into consideration the individual mould surface, repair welding and material properties. For that purpose, the actual geometry of the tool mould is measured directly in the CNC machine using an optical profile line sensor. Based on the measurement, the re-contouring process is planned automatically by means of a computer aided manufacturing (CAM) software. A material removal simulation with cutting force prognosis is carried out to adapt the process parameters individually with regard to repair time and surface quality. To set up the force and surface simulation model with high model quality, re-contouring experiments are carried out on welded seams made of 1.2343 (AISI H11) as well as on Toolox 44 and 1.2343 workpieces for comparison

Technology assessment of advanced automation for space missions

Six general classes of technology requirements derived during the mission definition phase of the study were identified as having maximum importance and urgency, including autonomous world model based information systems, learning and hypothesis formation, natural language and other man-machine communication, space manufacturing, teleoperators and robot systems, and computer science and technology

The relationship of aptitude and vocational interest to achievement of soldiers in advanced individual training, U.S. Arny Quarter master School

The purpose of the study was to examine the relationship of aptitude and vocational interest to academic achievement of soldiers in entry-level job training programs at the US Army Quartermaster School. The study was designed to distinguish between soldiers who passed all course examinations and those who did not. The soldiers were expected to differ on selected measures of aptitude and vocational interest.;The courses were selected for study because approximately 50% of the soldiers enrolled failed one or more examinations on the first attempt and thus required some form of retraining. The Quartermaster School is committed to reducing retraining costs (remedial instruction, study hall, and academic counseling by instructors). It was anticipated in the study that optimum job assignments lead to better performances in training for jobs, more often, when assignments are consistent with the ability and vocational preferences of soldiers.;It was hypothesized that the pass group would exceed the nonpass group on aptitude and vocational interest in both courses. It was concluded that aptitude and vocational interest made only a small contribution to the achievement of soldiers. The pass group exceeded the nonpass group on different measures of aptitude and interest for each course.;Further study should examine a broader set of predictors for selection and classification. In addition, the factors which account for the large unexplained portion of the variance between the pass and nonpass groups should be determined

Last Time Buy and Control Policies With Phase-Out Returns: A Case Study in Plant Control Systems

This research involves the combination of spare parts management and reverse logistics. At the end of the product life cycle, products in the field (so called installed base) can usually be serviced by either new parts, obtained from a Last Time Buy, or by repaired failed parts. This paper, however, introduces a third source: the phase-out returns obtained from customers that replace systems. These returned parts may serve other customers that do not replace the systems yet. Phase-out return flows represent higher volumes and higher repair yields than failed parts and are cheaper to get than new ones. This new phenomenon has been ignored in the literature thus far, but due to increased product replacements rates its relevance will grow. We present a generic model, applied in a case study with real-life data from ConRepair, a third-party service provider in plant control systems (mainframes). Volumes of demand for spares, defects returns and phase-out returns are interrelated, because the same installed base is involved. In contrast with the existing literature, this paper explicitly models the operational control of both failed- and phase-out returns, which proves far from trivial given the nonstationary nature of the problem. We have to consider subintervals within the total planning interval to optimize both Last Time Buy and control policies well. Given the novelty of the problem, we limit ourselves to a single customer, single-item approach. Our heuristic solution methods prove efficient and close to optimal when validated. The resulting control policies in the case-study are also counter-intuitive. Contrary to (management) expectations, exogenous variables prove to be more important to the repair firm (which we show by sensitivity analysis) and optimizing the endogenous control policy benefits the customers. Last Time Buy volume does not make the decisive difference; far more important is the disposal versus repair policy. PUSH control policy is outperformed by PULL, which exploits demand information and waits longer to decide between repair and disposal. The paper concludes by mapping a number of extensions for future research, as it represents a larger class of problems.spare parts;reverse logistics;phase-out;PUSH-PULL repair;non stationary;Last Time Buy;business case