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This paper seeks to discuss a grant‐funded digitization project for unique Afghanistan gray literature. It aims to address the digitization tasks, workflow, challenges, and solutions. Persistent identifiers, file‐naming conventions, page‐naming rules, and a digitization management system are discussed in detail since they were critical to the success of the project.

The paper describes the unique requirements of the project, and analyzes difficult issues related to the separation of pre‐digitization and post‐digitization in two remote locations. The approach includes persistent identifiers, file‐naming rules, page‐naming conventions and a digitization management system. After one and a half years of operation, the approach has been effective and efficient.

The paper analyzes the unique challenges for a long‐distance collaboration on digitization. Pre‐digitization and digital imaging were carried out in Kabul, Afghanistan, with all the physical materials located there, while post‐digitization and quality control were performed in Tucson, Arizona. The paper found that several components such as persistent identifiers, file‐naming conventions, page‐naming rules, and digitization management system were critical to the success of the project.

The project demonstrates an approach to address a unique digitization project due to the separation of pre‐digitization and post‐digitization. In addition, the approach has served other digitization projects well.

The paper was written for both project managers and technical staff. Project managers can find out the usefulness of a digitization management system and understand digitization issues; while technical staff can find interests in a persistent identifier scheme, file‐naming conventions and page‐naming rules.

Applying brand names to international markets remains a challenge to multinational corporations. Consumers’ sociolinguistic backgrounds shape their responses to brand names. This paper uses a sociolinguistic approach as a conceptual framework in understanding brand naming and translating in the Chinese market. The approach promotes that sociolinguistics a) recognizes linguistic competence, b) advances symbolic values imbedded in linguistic forms, and c) renders attached social valence to cultural scrutiny. Three brand‐naming cases in China are presented for discussion, which may benefit multinational corporations on brand decisions involving Chinese consumers.

To advance Java programming educations, the authors have developed a Java Programming Learning Assistant System (JPLAS) as a web application system. JPLAS provides fill-in-blank problems for novices to study the grammar and basic programming skills through code reading.

To select the blank elements with grammatically correct and unique answers from a given Java code, the authors have proposed the graph-based blank element selection algorithm. Then, the code for this problem should be highly readable to encourage novice students to study it. Because code readability can be improved by proper names for identifiers, the authors have also proposed the naming rule testing algorithm to identify codes with correct names.

In this paper, the authors present a fill-in-blank problem workbook by collecting suitable Java codes from textbooks and Web sites and applying these algorithms with several extensions. The workbook consists of 16 categories with a considerable number of problems that follow the conventional learning order of Java programming.

The proper set of ready-made fill-in-blank problems is effective in enhancing the usability of JPLAS both for teachers and students. For the preliminary evaluation, the authors assign a few problems to students. In coming semesters, the authors will use this workbook in the course to verify the adequacy of the proposal for novices.

This paper presents several research issues associated with the PNtalk language that is based on a certain kind of object‐oriented Petri nets (OOPNs) and intended mainly for modelling, prototyping, and verifying concurrent and distributed applications. The paper reviews the main concepts of PNtalk and OOPNs followed by a proposal of a system allowing prototypes based on PNtalk to be run in a distributed way. Furthermore, the first step made towards state spaces‐based formal analysis and verification over PNtalk OOPNs are also briefly mentioned in the paper.

The upper three OSI layers support communication requirements of applications. To communicate meaningfully, applications must share a common understanding of various aspects. This is achieved through the use of several OSI‐related concepts described in this article, including application association, application context, and abstract syntax. The Application layer is concerned with semantics and not encoding. The presentation protocol is concerned with the coupling of semantics with a particular encoding. The session protocol provides for organized and synchronized data exchange. Several application protocols are described in this article, and a sidebar about the File Transfer, Access, and Management protocol is included.

Hundreds of thousands of deaths each year in the world are caused by breast cancer (BC). An early-stage diagnosis of this disease can positively reduce the morbidity and mortality rate by helping to select the most appropriate treatment options, especially by using histological BC images for the diagnosis.

The present study proposes and evaluates a novel approach which consists of 24 deep hybrid heterogenous ensembles that combine the strength of seven deep learning techniques (DenseNet 201, Inception V3, VGG16, VGG19, Inception-ResNet-V3, MobileNet V2 and ResNet 50) for feature extraction and four well-known classifiers (multi-layer perceptron, support vector machines, K-nearest neighbors and decision tree) by means of hard and weighted voting combination methods for histological classification of BC medical image. Furthermore, the best deep hybrid heterogenous ensembles were compared to the deep stacked ensembles to determine the best strategy to design the deep ensemble methods. The empirical evaluations used four classification performance criteria (accuracy, sensitivity, precision and F1-score), fivefold cross-validation, Scott–Knott (SK) statistical test and Borda count voting method. All empirical evaluations were assessed using four performance measures, including accuracy, precision, recall and F1-score, and were over the histological BreakHis public dataset with four magnification factors (40×, 100×, 200× and 400×). SK statistical test and Borda count were also used to cluster the designed techniques and rank the techniques belonging to the best SK cluster, respectively.

Results showed that the deep hybrid heterogenous ensembles outperformed both their singles and the deep stacked ensembles and reached the accuracy values of 96.3, 95.6, 96.3 and 94 per cent across the four magnification factors 40×, 100×, 200× and 400×, respectively.

The proposed deep hybrid heterogenous ensembles can be applied for the BC diagnosis to assist pathologists in reducing the missed diagnoses and proposing adequate treatments for the patients.

The purpose of this paper is to present a system for recognition of location names in ancient books written in languages, such as Chinese, in which proper names are not signaled by an initial capital letter.

Rule-based and statistical methods were combined to develop a set of rules for identification of product-related location names in the local chronicles of Guangdong. A name recognition system, with functions of document management, information extraction and storage, rule management, location name recognition, and inquiry and statistics, was developed using Microsoft's .NET framework, SQL Server 2005, ADO.NET and XML. The system was evaluated with precision ratio, recall ratio and the comprehensive index, F.

The system was quite successful at recognizing product-related location names (F was 71.8 percent), demonstrating the potential for application of automatic named entity recognition techniques in digital collation of ancient books such as local chronicles.

Results suffered from limitations in initial digitization of the text. Statistical methods, such as the hidden Markov model, should be combined with an extended set of recognition rules to improve recognition scores and system efficiency.

Electronic access to local chronicles by location name saves time for chorographers and provides researchers with new opportunities.

Named entity recognition brings previously isolated ancient documents together in a knowledge base of scholarly and cultural value.

Automatic name recognition can be implemented in information extraction from ancient books in languages other than English. The system described here can also be adapted to modern texts and other named entities.

“OF making many books there is no end,” said the Preacher, and since his day this fact has been reiterated successively by men all down the ages. Consequent upon the ever increasing number of books was the necessity of providing adequate storage for their preservation and use, and to meet this need libraries were founded. To facilitate reference to the books, catalogues were compiled and provided, but these were generally made by private individuals, who, though they would doubtless make a few rules for their guidance, had not the advantage of working upon any codified rules that had stood the test of experience.

Artificial Intelligence, Cybernetics, Production Describes the ELEKTRA reflective production rule interpreter, which differs from other interpreters by providing considerable support for meta‐level inference and reflection. Also describes the representations employed in the system, in which the control problem in production systems can be solved by increasing use of rules. Introduces the reflective properties of the system and gives examples. Shows that the interpreter on which the entire ELEKTRA system runs can be implemented as ELEKTRA rules.