An algebraic theory of object-oriented systems

The paper presents an algebraic specification of net objects. By net objects we mean those that are defined in object-oriented paradigms and those defined with nested relations in complex database models. An algebraic specification is set up that involves structures of net objects, accesses of net objects, and some features of object-oriented programming, such as multiple inheritance and polymorphism. Objects and their relationships are then characterized formally in the modeling, which utilizes the hierarchical approach in the algebraic theory of abstract data types, and is further developed by adding mechanisms from existing object systems. Categories of net objects are presented with the properties of accesses among them     

Phosphorus Inputs to Lake Simcoe from 1990 to 2003: Declines in Tributary Loads and Observations on Lake Water Quality

Total phosphorus (TP) inputs to Lake Simcoe have led to hypolimnetic dissolved oxygen (DO) depletion and loss of cold water fish habitat. Since 1990, efforts have been made to reduce the total TP input to the lake below a defined target of 75 t/year, which was predicted to lead to reductions in spring TP concentration and improvements in end-of-summer hypolimnetic DO concentrations. The total TP load to the lake during the most recent period of record (1998/99-2003/04) ranged from 53 to 76 t/yr and averaged 67 t/yr, compared to an average of 114 t/yr estimated between 1990/91 and 1997/98 (range 85-157 t/yr). Reductions in TP loads from the catchment via tributary discharge (∼26 t) accounted for the majority of the decrease in total load between the two time periods. Total P concentrations decreased significantly in four out of six long-term monitored tributaries; however, concentrations in all six tributaries remain above the level recommended to avoid nuisance plant growth (30 μg/L). Although TP loads to the lake are currently below the target 75 t/yr, excessive growths of filamentous algae and macrophytes continue to be a problem in the nearshore zone. End-of-summer minimum hypolimnetic DO concentrations (average 4.3 mg/L, 1998/99-2003/04) remain substantially below the level (7 mg/L) that is considered protective of lake trout. Efforts to reduce TP loads to the lake therefore need to continue.     

Automated derivation of time bounds in uniprocessor concurrentsystems

The successful development of complex real-time systems depends on analysis techniques that can accurately assess the timing properties of those systems. This paper describes a technique for deriving upper and lower bounds on the time that can elapse between two given events in an execution of a concurrent software system running on a single processor under arbitrary scheduling. The technique involves generating linear inequalities expressing conditions that must be satisfied by all executions of such a system and using integer programming methods to find appropriate solutions to the inequalities. The technique does not require construction of the state space of the system and its feasibility has been demonstrated by using an extended version of the constrained expression toolset to analyze the timing properties of some concurrent systems with very large state spaces     

The ChaLearn gesture dataset (CGD 2011)

This paper describes the data used in the ChaLearn gesture challenges that took place in 2011/2012, whose results were discussed at the CVPR 2012 and ICPR 2012 conferences. The task can be described as: user-dependent, small vocabulary, fixed camera, one-shot-learning. The data include 54,000 hand and arm gestures recorded with an RGB-D \(\hbox {Kinect}^\mathrm{TM}\) camera. The data are organized into batches of 100 gestures pertaining to a small gesture vocabulary of 8–12 gestures, recorded by the same user. Short continuous sequences of 1–5 randomly selected gestures are recorded. We provide man-made annotations (temporal segmentation into individual gestures, alignment of RGB and depth images, and body part location) and a library of function to preprocess and automatically annotate data. We also provide a subset of batches in which the user’s horizontal position is randomly shifted or scaled. We report on the results of the challenge and distribute sample code to facilitate developing new solutions. The data, datacollection software and the gesture vocabularies are downloadable from http://gesture.chalearn.org. We set up a forum for researchers working on these data http://groups.google.com/group/gesturechallenge.     

Executive Perspectives on Top Risks for 2015

This article summarizes the results of Executive Perspectives on Top Risks for 2015, a study conducted by North Carolina State University’s ERM Initiative and Protiviti. For more information, visit www.protiviti.com/TopRisks.     

Composite web QoS with workflow conditional pathways using bounded sets

In our previous work (Dillon and Mansour 2009), a stochastic reliability model of atomic web services was proposed. Using the well-known classic two-state bounded set technique, we developed a service-oriented model that dynamically calculates the reliability of composite web services with rollback recovery (Mansour and Dillon in IEEE Trans Serv Comput 4(4), 2011). In order to improve the Quality of Service, fault tolerance techniques have been introduced using recovery block adaptation. Our workflow was based on series-parallel structures that constitute parts of existing structures. It is worth mentioning that major service-oriented systems contain larger and more complex structures than the simple series and parallel ones. This is a limitation in our previous approach. In order to consider more realistic service-oriented systems, other main structures, such as AND, XOR and Loop, should be included into our model. In this article, our previous structures are generalized to include AND, XOR and Loops. In addition to generalized structures, we extended the existing two-state bounded set technique to include three-state systems. This extension was especially motivated by XOR-based structures. A comparative study between bounded set techniques and a new stochastic model is also presented. Our simulation results accurately reflect the performance of the new proposed model and confirm our theoretical studies. Furthermore, Monte Carlos simulations were performed and the results obtained clearly validate our stochastic model.     

Automated speech recognition for spreadsheet tasks: Performance effects for experts and novices

The performance of spreadsheet users was compared for two modes of input to the computer, keyboard and automated speech recognition (ASR). Subjects from both an expert group and a novice group were also classified by decision style. Dependent measures were task completion time, accuracy, keystroke count, correction count, and user confidence. Results for a speaker‐dependent, discrete‐word recognizer showed that, for both simple data input and more complex analytical spreadsheet tasks, neither the experts nor the novices performed more effectively using ASR. However, both groups expressed the desirability of having speech input as an option for desktop computing.     

Multimodal Intelligent Eye-Gaze Tracking System

This article presents a series of user studies to develop a new eye-gaze tracking–based pointing system. We developed a new target prediction model that works for different input modalities and combined the eye-gaze tracking–based pointing with a joystick controller that can reduce pointing and selection times. The system finds important applications in cockpit of combat aircraft and for computer novice users. User studies confirmed that users can perform significantly faster using this new eye-gaze tracking–based system for both military and everyday computing tasks compared to existing input devices. As part of the study it was also found that the amplitude of maximum power component obtained through Fourier Transform of pupil signal significantly correlates with selection times and perceived cognitive load of users in terms of Task Load Index scores.     

Principal motion components for one-shot gesture recognition

This paper introduces principal motion components (PMC), a new method for one-shot gesture recognition. In the considered scenario a single training video is available for each gesture to be recognized, which limits the application of traditional techniques (e.g., HMMs). In PMC, a 2D map of motion energy is obtained per each pair of consecutive frames in a video. Motion maps associated to a video are processed to obtain a PCA model, which is used for recognition under a reconstruction-error approach. The main benefits of the proposed approach are its simplicity, easiness of implementation, competitive performance and efficiency. We report experimental results in one-shot gesture recognition using the ChaLearn Gesture Dataset; a benchmark comprising more than 50,000 gestures, recorded as both RGB and depth video with a Kinect?camera. Results obtained with PMC are competitive with alternative methods proposed for the same data set.