ON THE ACCURACY OF INSPECTORS

Reasons for inspector inaccuracy have been examined in three main groups: reasons of basic individual abilities; of formal organization (training, instructions, physical conditions, the lay-out of the job); and of interpersonal relations and social relations. Without denying the importance of the basic individual abilities of inspectors, which must set the ultimate limits of accuracy, it seems that the actual limits in a working situation are set by the other two groups of reasons. These practical limits may be well inside the limits set by basic psychological and physiological functions. For example, given an inspector who is well equipped with the basic abilities and aptitudes for the actual inspection task itself, he cannot operate more accurately than his instructions, for instance, allow him to. Moreover, even if well selected, well trained and well briefed, he still can be no more accurate than the pressures of interpersonal and other social relations permit. These interpersonal relations do not necessarily make him pass work that should be failed; they may also make him fail work that should be passed. Conversely, the production man will be more eager to ‘ get products past ’, to trick the inspector, when he does not‘ sanction ’ the inspector. This may in turn make the inspector reject more of the work of the man who tries to trick him than is actually bad. These interpersonal and social relations become all the more important when the inspection task is the more ‘ socio-technical ’—involving direct interaction with production.

It seems that when relations between production and inspection are poor. when production feel they can not sanction the inspectors and/or their standards, and when inspection chooses to play its role in a dominant, authoritative, and essentially invidious way. rather than as finding neutral facts, then not only will inspector accuracy be adversely affected, but there will also be strong pressures against inspection supervisors testing their inspector's accuracy.

Although the obvious man to check inspector accuracy is the inspector's own supervisor, there are powerful pressures against his doing this,Not only are there practical difficulties, but also there is the fact that inspection supervisors, and others, tend to become ‘ product-bound ’, even to the neglect of their true supervisory duties. Moreover, the pressures of interdepartmental relations encourage inspection supervisors to see themselves first as inspectors, and only secondarily as supervisors.

The general conclusion is that inspector accuracy, in a working situation, is determined by a wide range of factors. Problems of inaccuracy must then be studied in a wider context than is given by any single approach.     

A tabu search algorithm for the multi-period inspector scheduling problem

This paper introduces a multi-period inspector scheduling problem (MPISP), which is a new variant of the multi-trip vehicle routing problem with time windows (VRPTW). In the MPISP, each inspector is scheduled to perform a route in a given multi-period planning horizon. At the end of each period, each inspector is not required to return to the depot but has to stay at one of the vertices for recuperation. If the remaining time of the current period is insufficient for an inspector to travel from his/her current vertex A to a certain vertex B, he/she can choose either waiting at vertex A until the start of the next period or traveling to a vertex C that is closer to vertex B. Therefore, the shortest transit time between any vertex pair is affected by the length of the period and the departure time. We first describe an approach of computing the shortest transit time between any pair of vertices with an arbitrary departure time. To solve the MPISP, we then propose several local search operators adapted from classical operators for the VRPTW and integrate them into a tabu search framework. In addition, we present a constrained knapsack model that is able to produce an upper bound for the problem. Finally, we evaluate the effectiveness of our algorithm with extensive experiments based on a set of test instances. Our computational results indicate that our approach generates high-quality solutions.     

Factors affecting visual inspection accuracy

A four-fold classification of factors which might influence the extent of inspector accuracy is provided. It is emphasized that the influence of these factors has been mainly evaluated in the context of laboratory tasks which simulate real inspection tasks to a varying degree. For each of the four classes of factors one has been selected to illustrate its contribution to reducing inspector error. These are the inspector's visual acuity, the work-place lighting conditions, the time available for inspection and the provision of feedback or knowledge of results to the inspector. There is now sufficient evidence to confirm the advantages that can follow from careful consideration being given to these factors when designing or modifying industrial inspection tasks.     

嵌入式操作系统进程监测器的设计与实现

为避免嵌入式操作系统的进程受到恶意软件的修改破坏,提出一种适合于嵌入式操作系统的进程监测器。监测器周期性地对系统进程控制块进行检测恢复,通过设置进程检查点为系统提供恢复操作进程,并在Linux上进行实现,给出主要的数据结构和实现过程。实验结果表明,监测器的运行对系统性能影响小,能对系统进程进行有效的检测恢复。     

空间科学实验仪器通用地面检测仪设计

针对目前空间科学实验仪器地面检测设备通用性差的问题,设计一种通用的地面检测仪.该系统具有硬件接口丰富、软件模块化、可重复配置的特点,可用于模拟星上主控平台,实现空间科学实验仪器在发射前的地面检测.结合工程实例对系统性能进行验证,结果表明,该系统能满足多数情况下的地面检测需求.     

Automatic solder joint inspection

The task of automating the visual inspection of pin-in-hole solder joints is addressed. Two approaches are explored: statistical pattern recognition and expert systems. An objective dimensionality-reduction method is used to enhance the performance of traditional statistical pattern recognition approaches by decorrelating feature data, generating feature weights, and reducing run-time computations. The expert system uses features in a manner more analogous to the visual clues that a human inspector would rely on for classification. Rules using these cues are developed, and a voting scheme is implemented to accumulate classification evidence incrementally. Both methods compared favorably with human inspector performance     

超声波传感器在混凝土无损检测系统中的应用研究

设计了一种用于混凝土无损检测的超声波检测仪,介绍了超声波检测的基本原理和系统设计,着重讨论了其发射系统和接收系统的设计方案,进行了无缺陷和有缺陷混凝土灌注桩的测试实验,并对测试数据及波形分析处理.从实验结果表明,该测试仪检测混凝土缺陷快速准确,误差小,具有一定的实用价值.     

Optimum checking request policies

We discuss checking policies, in which an inspector is requested to perform the check, for a ono-unit system. Applying the unique modifications of Markov renewal processes, we analyse the stochastic behaviour of each CR policy (checking request policy) and CRSL policy (checking request and surveillance limit policy), where it is assumed that the failure time for each unit and the inspector's arrival time havo arbitrary distributions. Introducing replacement eosts, the request for the inspector to perform the check, system failure and surveillance, we derive the optimal policies which maximize the cost effectiveness under suitablo conditions for each model. In particular, wo discuss the optimal policies as a non-linear programming problem with two variables.     

A collective I/O implementation based on inspector–executor paradigm

In this paper, we present a novel multiple phase I/O collective technique for generic block-cyclic distributions. The I/O technique is divided into two stages: inspector and executor. During the inspector stage, the communication pattern is computed and the required datatypes are automatically generated. This information is used during the executor stage in performing the communication and file accesses. The two stages are decoupled, so that for repetitive file access patterns, the computations from the inspector stage can be performed once and reused several times by the executor. This strategy allows to amortize the inspector cost over several I/O operations. In this paper, we evaluate the performance of multiple phase I/O collective technique and we compare it with other state of the art approaches. Experimental results show that for small access granularities, our method outperforms in the large majority of cases other parallel I/O optimizations techniques.

Perceptual importance analysis-based rate control method for HEVC

High efficiency video coding (HEVC) has achieved high coding efficiency as the video coding standard. For rate control in HEVC, the conventional R-λ scheme is based on mean absolute difference in allocating bits; however, the scheme does not fully utilize the perceptual importance variation to guide rate control, thus the subjective and objective quality of coded videos has room to improve. Therefore, in this paper, we propose a rate control scheme that considers perceptual importance. We first develop a perceptual importance analysis scheme to accurately abstract the spatial and temporal perceptual importance maps of video contents. The results of the analysis are then used to guide the bit allocation. Utilizing this model, a region-level bit allocation procedure is developed to maintain video quality balance. Subsequently, a largest coding unit (LCU)-level bit allocation scheme is designed to obtain the target bit of each LCU. To achieve a more accurate bitrate, an improved R-λ model based on the Broyden-Fletcher-Goldfarb-Shanno model is utilized to update the R-λ parameter. The experimental results showed that our method not only improved subjective and objective video quality with lower bitrate errors compared to the original RC in HEVC, but also outperformed state-of-the-art methods.

     

Virtual inspector: a flexible visualizer for dense 3D scanned models.

Virtual inspector lets novice users inspect dense 3D models at interactive frame rates on commodity PCs. The system obtains visualization efficiency without sacrificing quality by adopting a continuous level-of-detail representation. Visual inspector's use of XML to encode the GUI's structure and behavior makes it flexible and configurable. We can improve the virtual inspector system by adding new functionality and increasing its efficiency. Few restorers would consider the simple visualization of a digital 3D replica as the ultimate goal for the use of 3D scanning technologies in cultural heritage contexts. Once we can visualize an artifact with great accuracy, the need to map other data on the 3D model will rise. We're working on a slightly extended version of the tool to support mapping and selective visualization of different sources of surface data. We're also developing tools to compute measures. Finally, we're working to more dynamically enrich the data linked to the mesh by letting users add annotations or link multimedia material to selected points of the artifact surface. Our goal is to transform virtual inspector into a more dynamic instrument for cultural heritage research and restoration.     

Subjective measurement of cosmetic defects using a Computational Intelligence approach

This paper presents a Computational Intelligence scheme to deal with subjective human inspection tasks in the industry that are subjective measurements. The scheme is used to solve two cosmetic subjective measurements tasks, classification of cosmetic defects and detection of non-uniform color regions in a translucent film. The first problem is solved with two approaches supervised and unsupervised Artificial Neural Networks. Both techniques yield the same performance, 92.35% of correct classification. Considering that a human inspector has a performance between 85% and 90%, the performance achieved is acceptable. The second problem is faced with a hybrid system based on fuzzy clustering and a Self-Organizing Map. The hybrid approach involves management of uncertainty through fuzzy theory and unsupervised training supported by the SOM. The proposed system is able to find non-uniform color regions with better resolution than a human inspector. The system also showed to be more sensitive than a simple fuzzy clustering approach.     

A system for PCB automated inspection using fluorescent light

Research was performed on the detection of faults such as shorts, cuts, and nicks in a printed circuit board pattern. The possibility was investigated of detecting a pattern by illuminating a printed circuit board with violet or ultraviolet rays and detecting the pattern using the (yellow or other) fluorescent light emitted by the base material consisting of glass-epoxy or glass-polyimide, etc. It was found that the pattern could be detected clearly by selecting an optical fiber that would separate the emitted fluorescent light from the illumination and using a detector consisting of a high-sensitivity TV camera that produces a silhouette image in which the base material is bright and the pattern is dark. A printed-circuit-board pattern inspector using this approach was developed. Test operation of the inspector in a plant demonstrated that it performs consistently good pattern inspections     

支持不规则计算的运行库系统

本文首先采用检查者／执行者的基本方法,提出了支持不规则计算的运行库ＩＣＲＬ系统的设计方案,然后,对系统中的几个关键问题进行了解决,最后使用ＩＣＲＬ函数以结点程序给予了示例。     

Design and implementation of a fine-grained software inspection tool

Although software inspection has led to improvements in software quality, many software systems continue to be deployed with unacceptable numbers of errors, even when software inspection is part of the development process. The difficulty of manually verifying that the software under inspection conforms to the rules is partly to blame. We describe the design and implementation of a tool designed to help alleviate this problem. The tool provides mechanisms for fine-grained inspection of software by exposing the results of sophisticated whole-program static analysis to the inspector. The tool computes many static-semantic representations of the program, including an accurate call graph and dependence graph. A whole-program pointer analysis is used to make sure that the representation is precise with respect to aliases induced by pointer usage. Views on the dependence graph and related representations are supported. Queries on the dependence graph allow an inspector to answer detailed questions about the semantics of the program. Facilities for openness and extensibility permit the tool to be integrated with many software development processes. The main challenge of the approach is to provide facilities to navigate and manage the enormous complexity of the dependence graph.     

Mobile robot interception using human navigational principles: Comparison of active versus passive tracking algorithms

We examined human navigational principles for intercepting a projected object and tested their application in the design of navigational algorithms for mobile robots. These perceptual principles utilize a viewer-based geometry that allows the robot to approach the target without need of time-consuming calculations to determine the world coordinates of either itself or the target. Human research supports the use of an Optical Acceleration Cancellation (OAC) strategy to achieve interception. Here, the fielder selects a running path that nulls out the acceleration of the retinal image of an approaching ball, and maintains an image that rises at a constant rate throughout the task. We compare two robotic control algorithms for implementing the OAC strategy in cases in which the target remains in the sagittal plane headed directly toward the robot (which only moves forward or backward). In the “passive” algorithm, the robot keeps the orientation of the camera constant, and the image of the ball rises at a constant rate. In the “active” algorithm, the robot maintains a camera fixation that is centered on the image of the ball and keeps the tangent of the camera angle rising at a constant rate. Performance was superior with the active algorithm in both computer simulations and trials with actual mobile robots. The performance advantage is principally due to the higher gain and effectively wider viewing angle when the camera remains centered on the ball image. The findings confirm the viability and robustness of human perceptual principles in the design of mobile robot algorithms for tasks like interception. Thomas Sugar works in the areas of mobile robot navigation and wearable robotics assisting gait of stroke survivors. In mobile robot navigation, he is interested in combining human perceptual principles with mobile robotics. He majored in business and mechanical engineering for his Bachelors degrees and mechanical engineering for his Doctoral degree all from the University of Pennsylvania. In industry, he worked as a project engineer for W. L. Gore and Associates. He has been a faculty member in the Department of Mechanical and Aerospace Engineering and the Department of Engineering at Arizona State University. His research is currently funded by three grants from the National Sciences Foundation and the National Institutes of Health, and focuses on perception and action, and wearable robots using tunable springs. Michael McBeath works in the area combining Psychology and Engineering. He majored in both fields for his Bachelors degree from Brown University and again for his Doctoral degree from Stanford University. Parallel to his academic career, he worked as a research scientist at NASA—Ames Research Center, and at the Interval Corporation, a technology think tank funded by Microsoft co-founder, Paul Allen. He has been a faculty member in the Department of Psychology at Kent State University and at Arizona State University, where he is Program Director for the Cognition and Behavior area, and is on the Executive Committee for the interdisciplinary Arts, Media, and Engineering program. His research is currently funded by three grants from the National Sciences Foundation, and focuses on perception and action, particularly in sports. He is best known for his research on navigational strategies used by baseball players, animals, and robots.     

Intelligent virtual agents keeping watch in the battlefield

One of the first areas where virtual reality found a practical application was military training. Two fairly obvious reasons have driven the military to explore and employ this kind of technique in their training; to reduce exposure to hazards and to increase stealth. Many aspects of combat operations are very hazardous, and they become even more dangerous if the combatant seeks to improve his performance. Some smart weapons are autonomous, while others are remotely controlled after they are launched. This allows the shooter and weapon controller to launch the weapon and immediately seek cover, thus decreasing his exposure to return fire. Before launching a weapon, the person who controls that weapon must acquire/perceive as much information as he can, not only from its environment, but also from the people who inhabits that environment. Intelligent virtual agents (IVAs) are used in a wide variety of simulation environments, especially in order to simulate realistic situations as, for example, high fidelity virtual environment (VE) for military training that allows thousands of agents to interact in battlefield scenarios. In this paper, we propose a perceptual model, which seeks to introduce more coherence between IVA perception and human being perception, increasing the psychological coherence between the real life and the VE experience. Agents lacking this perceptual model could react in a non-realistic way, hearing or seeing things that are too far away or hidden behind other objects. The perceptual model, we propose in this paper introduces human limitations inside the agents perceptual model with the aim of reflecting human perception.     

Attention decrease of drivers exposed to vibration from military vehicles when driving in terrain conditions

In this study, we analyzed the phenomenon of reduced attention for 11 subjects using a 6-degree-of-freedom synthetic vibration platform to simulate the vibration from terrain driving. Military vehicles are mainly used in terrain conditions, and drivers are exposed to whole-body vibrations for long periods of time. Drivers not only have trouble with comfort and health, they also suffer decreased attention. This decrease has a negative effect on driving. The vibration signal of a military vehicle on terrain is simulated using a synthetic vibration platform. Eleven subjects experienced these synthesized field-terrain vibrations while on the vibration platform performing a variety of perceptual and cognitive attention tests. The attention tests were divided into perceptual and cognitive, and the decrease in attention caused by vibration exposure and the exposure time was analyzed. From the results, automatic perceptual attention was not affected by vibration exposure. When the complexity of cognitive processing was increased during the attention test, the effects of vibration exposure became significant. The decrease in certain attention mechanisms was found when drivers were exposed to whole-body vibrations. Thus, it is expected that drivers are adversely affected when performing missions. We analyze the correlation between vibration exposure and attention decrease in this study, and the ability of the military vehicle driver to perform his mission can be predicted.     

A machine vision inspector for beer bottle

A machine-vision-based beer bottle inspector is presented. The mechanical structure and electric control system are illustrated in detail. A method based on the histogram of edge points is applied for real-time determination of inspection area. For defect detection of bottle wall and bottle bottom, an algorithm based on local statistical characteristics is proposed. In bottle finish inspection, two artificial neural networks are used for low-level inspection and high-level judgment, respectively. A prototype was developed and experimental results demonstrate the feasibility of the inspector. Inspections performed by the prototype have proved the effectiveness and value of proposed algorithms in automatic real-time inspection.     

Toward an automatic parallelization of sparse matrix computations

In this paper, we propose a generic method of automatic parallelization for sparse matrix computation. This method is based on both a refinement of the data-dependence test proposed by Bernstein and an inspector–executor scheme which is specialized to each input program of the compiler. This analysis mixes compilation process and run-time process.The sparsity of underlying data-structure determines a specific parallelism which increases the degree of parallelism of an algorithm. Such a source of parallelism had already been applied to many numerical algorithms such as the usual Cholesky factorization or LU-decomposition algorithms considered as the gold standards of parallelization based on sparsity. The standard automatic parallelization method cannot tackle such source of parallelism because it is based on the value of cells arrays and not merely on the memory addressing function.Addressing the automatization of this parallelism requires to develop a mixed compile-time and runtime approach integrated in a inspector–executor process. The compilation step provides a dedicated inspector devoted to the analyzed program. The inspector computes the dependence graph at runtime which allows a dynamic parallelization of the execution.As expressed just before, the generic scheme developed in this paper follows the design principles which have been applied, but at each time in an ad hoc way, to many sparse parallelization of numerical algorithms such as Cholesky algorithm. As far as we know, no general formal framework has been proposed to automate such a method of sparse parallelization. In this paper, we propose a generic framework of sparse parallelization (i.e. numerical program independent) which can be applied to any numerical programs satisfying the usual syntactic constraints of parallelization.