Land Cover/Land Use Mapping Using Soft Computing Techniques with Optimized Features

The chapter discusses soft computing techniques for solving complex computational tasks. It highlights some of the soft computing techniques like fuzzy logic, genetic algorithm, artificial neural network, and machine learning. The classification of the remotely sensed images is always a tedious task. So, here we explain how these soft computing techniques could be used for image classification. Image classification mainly concentrates on the feature’s extraction process. The features extracted in an efficient manner improve classification accuracy. Hence, the different kinds of features and different methods for these extractions are explained. The best extracted features are selected using genetic algorithm. Various algorithms are shown and comparisons are made. Finally, the results are verified using a hypothetical case study

IST Austria Thesis

In this thesis we present a computer-aided programming approach to concurrency. Our approach helps the programmer by automatically fixing concurrency-related bugs, i.e. bugs that occur when the program is executed using an aggressive preemptive scheduler, but not when using a non-preemptive (cooperative) scheduler. Bugs are program behaviours that are incorrect w.r.t. a specification. We consider both user-provided explicit specifications in the form of assertion statements in the code as well as an implicit specification. The implicit specification is inferred from the non-preemptive behaviour. Let us consider sequences of calls that the program makes to an external interface. The implicit specification requires that any such sequence produced under a preemptive scheduler should be included in the set of sequences produced under a non-preemptive scheduler. We consider several semantics-preserving fixes that go beyond atomic sections typically explored in the synchronisation synthesis literature. Our synthesis is able to place locks, barriers and wait-signal statements and last, but not least reorder independent statements. The latter may be useful if a thread is released to early, e.g., before some initialisation is completed. We guarantee that our synthesis does not introduce deadlocks and that the synchronisation inserted is optimal w.r.t. a given objective function. We dub our solution trace-based synchronisation synthesis and it is loosely based on counterexample-guided inductive synthesis (CEGIS). The synthesis works by discovering a trace that is incorrect w.r.t. the specification and identifying ordering constraints crucial to trigger the specification violation. Synchronisation may be placed immediately (greedy approach) or delayed until all incorrect traces are found (non-greedy approach). For the non-greedy approach we construct a set of global constraints over synchronisation placements. Each model of the global constraints set corresponds to a correctness-ensuring synchronisation placement. The placement that is optimal w.r.t. the given objective function is chosen as the synchronisation solution. We evaluate our approach on a number of realistic (albeit simplified) Linux device-driver benchmarks. The benchmarks are versions of the drivers with known concurrency-related bugs. For the experiments with an explicit specification we added assertions that would detect the bugs in the experiments. Device drivers lend themselves to implicit specification, where the device and the operating system are the external interfaces. Our experiments demonstrate that our synthesis method is precise and efficient. We implemented objective functions for coarse-grained and fine-grained locking and observed that different synchronisation placements are produced for our experiments, favouring e.g. a minimal number of synchronisation operations or maximum concurrency

Equality elimination for the inverse method and extension procedures

We demonstrate how to handle equality in the inverse method using equality elimination. In the equality elimination method, proofs consist of two parts. In the first part we try to solve equations obtaining so called solution clauses. Solution clauses are obtained by a very refined strategy — basic superposition with selection function. In the second part, we perform the usual sequent proof search by the inverse method. Our approach is called equality elimination because we eliminate all occurrences of equality in the first part of the proof. Unlike the previous approach proposed by Maslov, our method uses most general substitutions, orderin

Artificial Intelligence(AI) application in Library Systems in Iran: A taxonomy study

With introducing and developing AI logic, this science as a branch of computer science could impact and improve all sciences which used computer systems. LIS also could get benefit from AI in many areas. This paper survey applications of AI in library and information science and introduce the potential of library system to apply AI techniques. Intelligent systems have contributed for many librarian purposes like cataloging, indexing, information retrieval, reference, and other purposes. We applied Exploratory Factor Analysis (EFA) as a primer method for identification of the most applicable AI techniques categories in LIS. ESs are the most usable intelligent system in LIS which mimic librarian expert’s behaviors to support decision and management. AI also can utilize in many areas such as speech recognition, machine translation and librarian robots. In this study four criteria for the application of AI in the library systems in Iran was considered and it is determined in three area included public services, technical services, and management services. Then, degree of development these services was studied using taxonomy method. The results showed that most developed Recommender Systems (RM) in library systems in Iran and Natural Language Processing (NLP) is the most undeveloped criterion

Business rules based legacy system evolution towards service-oriented architecture.

Enterprises can be empowered to live up to the potential of becoming dynamic, agile and real-time. Service orientation is emerging from the amalgamation of a number of key business, technology and cultural developments. Three essential trends in particular are coming together to create a new revolutionary breed of enterprise, the service-oriented enterprise (SOE): (1) the continuous performance management of the enterprise; (2) the emergence of business process management; and (3) advances in the standards-based service-oriented infrastructures. This thesis focuses on this emerging three-layered architecture that builds on a service-oriented architecture framework, with a process layer that brings technology and business together, and a corporate performance layer that continually monitors and improves the performance indicators of global enterprises provides a novel framework for the business context in which to apply the important technical idea of service orientation and moves it from being an interesting tool for engineers to a vehicle for business managers to fundamentally improve their businesses

HCM: Hardware-Aware Complexity Metric for Neural Network Architectures

Convolutional Neural Networks (CNNs) have become common in many fields including computer vision, speech recognition, and natural language processing. Although CNN hardware accelerators are already included as part of many SoC architectures, the task of achieving high accuracy on resource-restricted devices is still considered challenging, mainly due to the vast number of design parameters that need to be balanced to achieve an efficient solution. Quantization techniques, when applied to the network parameters, lead to a reduction of power and area and may also change the ratio between communication and computation. As a result, some algorithmic solutions may suffer from lack of memory bandwidth or computational resources and fail to achieve the expected performance due to hardware constraints. Thus, the system designer and the micro-architect need to understand at early development stages the impact of their high-level decisions (e.g., the architecture of the CNN and the amount of bits used to represent its parameters) on the final product (e.g., the expected power saving, area, and accuracy). Unfortunately, existing tools fall short of supporting such decisions. This paper introduces a hardware-aware complexity metric that aims to assist the system designer of the neural network architectures, through the entire project lifetime (especially at its early stages) by predicting the impact of architectural and micro-architectural decisions on the final product. We demonstrate how the proposed metric can help evaluate different design alternatives of neural network models on resource-restricted devices such as real-time embedded systems, and to avoid making design mistakes at early stages

Profile of On-Line Anatomy Information Resources: Design and Instructional Implications

This study is based on a review of 40 on-line anatomy web resources compiled from sites selected from our own searches as well as sites reviewed and published by an external group (Voiglio et al., 1999, Surg. Radiol. Anat. 21:65-68; Frasca et al., 2000, Surg. Radiol. Anat. 22:107-110). The purpose of our survey was to propose criteria by which anatomy educators could judge the characteristics of the currently available web-based resources for incorporation into the courses they teach. Each site was reviewed and scored based on a survey matrix that included four main categories: 1). site background information, 2). content components, 3). interactivity features, and 4). user interface design components. The average score of the reviewed sites was 3.3 of the total possible score of 10, indicating the limited use of computer-based design features by the majority of sites. We found, however, a number of programs in each of the survey categories that could serve as prototypes for designing future on-line anatomy resources. From the survey we conclude that various design features are less important than the comprehensiveness, depth, and logical organization of content. We suggest that the content should be sufficient for supporting explicitly defined educational objectives, which should target specific end-user populations. The majority of anatomy programs currently accessible on-line fall short of these requirements. There is a need for a coordinated and synergistic effort to generate a comprehensive anatomical information resource that is of sufficient quality and depth to support higher levels of learning beyond the memorization of structure names. Such a resource is a prerequisite for meaningful on-line anatomy education