The UNIX localization and Chinese Information Processing System

To facilitate the wider use of computers all over the world,it is necessary to provide National Language Support in the computer systems.This paper introduces some aspects of design and implementation of the UNIX-based Chinese Information Processing Systems (CIPS). Due to the special nature of the Oriental languages,and in order to be able to share resources and exchange in formation between different countries,it is necessary to create a standard of multilingual information exchange code.The unified Chinese/Japanese/Korean character code,Han Character Collection(HCC),was proposed to ISO/IEC JTC1/SC2/WG2 by China Computer and Information Processing Standardization Technical Committee.Based on this character set and the corresponding coding system,it is possible to create a true Internationalized UNIX System.     

ELM ∗ : distributed extreme learning machine with MapReduce

Extreme Learning Machine (ELM) has been widely used in many fields such as text classification, image recognition and bioinformatics, as it provides good generalization performance at a extremely fast learning speed. However, as the data volume in real-world applications becomes larger and larger, the traditional centralized ELM cannot learn such massive data efficiently. Therefore, in this paper, we propose a novel Distributed Extreme Learning Machine based on MapReduce framework, named ELM^???, which can cover the shortage of traditional ELM whose learning ability is weak to huge dataset. Firstly, after adequately analyzing the property of traditional ELM, it can be found out that the most expensive computation part of the matrix Moore-Penrose generalized inverse operator in the output weight vector calculation is the matrix multiplication operator. Then, as the matrix multiplication operator is decomposable, a Distributed Extreme Learning Machine (ELM^???) based on MapReduce framework can be developed, which can first calculate the matrix multiplication effectively with MapReduce in parallel, and then calculate the corresponding output weight vector with centralized computing. Therefore, the learning of massive data can be made effectively. Finally, we conduct extensive experiments on synthetic data to verify the effectiveness and efficiency of our proposed ELM^??? in learning massive data with various experimental settings.     

Design patterns percolating to parallel programming framework implementation

Structured parallel programming is recognised as a viable and effective means of tackling parallel programming problems. Recently, a set of simple and powerful parallel building blocks ( \(\mathsf{RISC\text{- }pb^2l}\) ) has been proposed to support modelling and implementation of parallel frameworks. In this work we demonstrate how that same parallel building block set may be used to model both general purpose parallel programming abstractions, not usually listed in classical skeleton sets, and more specialized domain specific parallel patterns. We show how an implementation of \(\mathsf{RISC\text{- }pb^2l}\) can be realised via the FastFlow framework and present experimental evidence of the feasibility and efficiency of the approach.     

An FAR-SW based approach for webpage information extraction

Automatically identifying and extracting the target information of a webpage, especially main text, is a critical task in many web content analysis applications, such as information retrieval and automated screen reading. However, compared with typical plain texts, the structures of information on the web are extremely complex and have no single fixed template or layout. On the other hand, the amount of presentation elements on web pages, such as dynamic navigational menus, flashing logos, and a multitude of ad blocks, has increased rapidly in the past decade. In this paper, we have proposed a statistics-based approach that integrates the concept of fuzzy association rules (FAR) with that of sliding window (SW) to efficiently extract the main text content from web pages. Our approach involves two separate stages. In Stage 1, the original HTML source is pre-processed and features are extracted for every line of text; then, a supervised learning is performed to detect fuzzy association rules in training web pages. In Stage 2, necessary HTML source preprocessing and text line feature extraction are conducted the same way as that of Stage 1, after which each text line is tested whether it belongs to the main text by extracted fuzzy association rules. Next, a sliding window is applied to segment the web page into several potential topical blocks. Finally, a simple selection algorithm is utilized to select those important blocks that are then united as the detected topical region (main texts). Experimental results on real world data show that the efficiency and accuracy of our approach are better than existing Document Object Model (DOM)-based and Vision-based approaches.     

Knowledge information processing language: ShapeUp

A new logic programming language, ShapeUp, is developed. ShapeUp is an expanded Prolog system with string matching facilities. The language has been developed to give programmers a new computer programming environment, especially for knowledge information processing. This area includes natural language comprehension and intelligent text processing systems with better man-machine interfaces. For this kind of application, character string data play a principal part rather than conventional numerical data. In ShapeUp, string patterns are introduced as Prolog ‘terms’. Their matching process is performed inside the unification. Thus, a program is far simpler and easier to write and read in ShapeUp, than in conventional Prolog systems, and program size is extremely reduced.     

Partial evaluation of metaprograms in a “multiple worlds” logic language

This paper describes a partial evaluation system specifically designed to be used as an automatic compilation tool for metaprograms in a KBMS (EPSILON) based on Prolog. EPSILON main underlying concepts are the extension of Prolog with theories (“multiple worlds”) and the use of metaprogramming as the basic technique to define new inference engines and tools. Our partial evaluator is oriented towards theories and metainterpreter specialization. Being designed to be used as an automatic compiler, it does not require declarations from the user to control the unfolding process. It handles full Prolog and provides also an elegant solution to the problem of the partial evaluation of incomplete and self-modifying programs, by exploiting the multiple worlds feature added to Prolog. EPSILON partial evaluation system turned out to be a very useful and powerful tool to combine the low cost and the flexibility of metaprogramming with the performance requirements of a practical knowledge based system.     

Real-time and robust hand tracking with a single depth camera

In this paper, we introduce a novel, real-time and robust hand tracking system, capable of tracking the articulated hand motion in full degrees of freedom (DOF) using a single depth camera. Unlike most previous systems, our system is able to initialize and recover from tracking loss automatically. This is achieved through an efficient two-stage k-nearest neighbor database searching method proposed in the paper. It is effective for searching from a pre-rendered database of small hand depth images, designed to provide good initial guesses for model based tracking. We also propose a robust objective function, and improve the Particle Swarm Optimization algorithm with a resampling based strategy in model based tracking. It provides continuous solutions in full DOF hand motion space more efficiently than previous methods. Our system runs at 40 fps on a GeForce GTX 580 GPU and experimental results show that the system outperforms the state-of-the-art model based hand tracking systems in terms of both speed and accuracy. The work result is of significance to various applications in the field of human–computer-interaction and virtual reality.     

Cryptanalysis and improvement of an efficient mutual authentication RFID scheme based on elliptic curve cryptography

Radio frequency identification (RFID) is a wireless technology for automatic identification and data capture. Security and privacy issues in the RFID systems have attracted much attention. Many approaches have been proposed to achieve the security and privacy goals. One of these approaches is RFID authentication protocols by which a server and tags can authorize each other through an intracity process. Recently, Chou proposed a RFID authentication protocol based on elliptic curve cryptography. However, this paper demonstrates that the Chou’s protocol does not satisfy tag privacy, forward privacy and authentication, and server authentication. Based on these security and privacy problems, we also show that Chou’s protocol is defenseless to impersonation attacks, tag cloning attacks and location tracking attacks. Therefore, we propose a more secure and efficient scheme, which does not only cover all the security flaws and weaknesses of related previous protocols, but also provides more functionality. We prove the security of the proposed improved protocol in the random oracle model.     

JackHare: a framework for SQL to NoSQL translation using MapReduce

As data exploration has increased rapidly in recent years, the datastore and data processing are getting more and more attention in extracting important information. To find a scalable solution to process the large-scale data is a critical issue in either the relational database system or the emerging NoSQL database. With the inherent scalability and fault tolerance of Hadoop, MapReduce is attractive to process the massive data in parallel. Most of previous researches focus on developing the SQL or SQL-like queries translator with the Hadoop distributed file system. However, it could be difficult to update data frequently in such file system. Therefore, we need a flexible datastore as HBase not only to place the data over a scale-out storage system, but also to manipulate the changeable data in a transparent way. However, the HBase interface is not friendly enough for most users. A GUI composed of SQL client application and database connection to HBase will ease the learning curve. In this paper, we propose the JackHare framework with SQL query compiler, JDBC driver and a systematical method using MapReduce framework for processing the unstructured data in HBase. After importing the JDBC driver to a SQL client GUI, we can exploit the HBase as the underlying datastore to execute the ANSI-SQL queries. Experimental results show that our approaches can perform well with efficiency and scalability.     

Making exhaustive search programs deterministic

This paper presents a technique for compiling a Horn-clause program intended for exhaustive search into a GHC (Guarded Horn Clauses) program. The technique can be viewed also as a transformation technique for Prolog programs which compiles away the ‘bagof’ primitive and non-determinate bindings. The class of programs to which our technique is applicable is shown with a static checking algorithm; it is nontrivial and could be extended. An experiment on a compiler-based Prolog system showed that our technique improved the efficiency of exhaustive search by 6 times for a permutation generator program. This compilation technique is important also in that it exploits the AND-parallelism of GHC for parallel search.     

Outline of the Personal Sequential Inference machine: PSI

PSI is a personal computer system being developed as a tool for providing researchers with an efficient programming environment. It directly supports logic programming language, KL0 (Fifth Generation Kernel Language, Version 0), with firmware and hardware. Its interpreter is implemented in the firmware and several hardware mechanisms are provided to attain almost the same level of performance as the DEC-10 Prolog on DEC2060. It also provides the user with a large memory space, 40 bits × 2 to 16 MW, which is essential for developing actual application programs like an expert system. To make efficient man-machine interaction possible, such input and output devices as bit-map display, pointing device and key-board are provided. A local area network is also being developed to build a distributed system.     

A built-in test pattern generator

Built-in testing is currently of more concern due to the difficulties in testing a VLSI byusing an external tester.In addition,Built-In Testing is also necessary for on-line testing and afault-tolerant computing system.Using a Linear Feedback Shift Register(LFSR)as a built-intest pattern generator(BITPG)is a realistic and simple approach.An LFSR with maximumlength can generate pseudo-random test patterns or all non-null vectors for exhaustive testing.This paper presents an LFSR design with non-maximum length to serve as a BITPG to generatea given test set T,which efficiently saves testing time.A search-verification process fordesigning this kind of LFSR is employed and implemented by the program SVBITPG.Thispaper presents the diagram of tire program and gives stone examples to illustrate the design ofthe BITPG.     

Temporal logic based hardware description and its verification with Prolog

Techniques of hierarchical specification and verification of hardware with temporal logic and Prolog are presented by example. Both hardware designs in gates and state-diagrams are translated into a relation between the present and the next state, which is represented in Prolog.¹⁾ Specifications are constructed by temporal logic that can express state sequences (e.g. timing diagrams) easily and also are translated into a relation between the present and the next state in Prolog. The verification method is based upon the temporal logic decision procedure in Ref. 2) and, referring to the relation tables between the present state and the next state, the verifier can reason in both directions—forward and backward in temporal sequences. Prolog has very powerful pattern matching, and its automatic backtracking capabilities facilitate easy-to-write verifier programs. It is concluded that a total verification system handling various design levels can be constructed with temporal logic and Prolog.     

Design and simulation of a sequential Prolog machine

Prolog-X is an implemented portable interactive sequential Prolog system in which clauses are incrementally compiled for a virtual machine called the ZIP Machine. At present, the ZIP Machine is emulated by software, but it has been designed to permit easy implementation in microcode or hardware. Prolog-X running on the software-based emulator provides performance comparable with existing Prolog interpreters. To demonstrate its efficiency, compatibility, and comprehensiveness of implementation, Prolog-X has been used to compile and run several large applications programs. Several novel techniques are used in the implementation, particularly in the areas of the representation of therecordx database, the selection of clauses, and the compilation of arithmetic expressions.     

The Aurora or-parallel Prolog system

Aurora is a prototype or-parallel implementation of the full Prolog language for shared-memory multiprocessors, developed as part of an informal research collaboration known as the “Gigalips Project”. It currently runs on Sequent and Encore machines. It has been constructed by adapting Sicstus Prolog, a fast, portable, sequential Prolog system. The techniques for constructing a portable multiprocessor version follow those pioneered in a predecessor system, ANL-WAM. The SRI model was adopted as the means to extend the Sicstus Prolog engine for or-parallel operation. We describe the design and main implementation features of the current Aurora system, and present some experimental results. For a range of benchmarks, Aurora on a 20-processor Sequent Symmetry is 4 to 7 times faster than Quintus Prolog on a Sun 3/75. Good performance is also reported on some large-scale Prolog applications.     

An energy-efficient storage for video surveillance

With the rapid growth of the video surveillance applications, the storage energy consumption of video surveillance is more noticeable, but existed energy-saving methods for massive storage system most concentrate on the data centers mainly with random accesses. The storage of video surveillance has inherent access pattern, and requires special energy-saving approach to save more energy. An energy-efficient data layout for video surveillance, Semi-RAID is proposed. It adopts partial-parallelism strategy, which partitions disk data into different groups, and implements parallel accesses in each group. Grouping benefits to realize only partial disks working and the rest ones idle, and inner-group parallelism provides the performance guarantee. In addition, greedy strategy for address allocation is adopted to effectively prolong the idle period of the disks; particular Cache strategies are used to filter the small amount of random accesses. The energy-saving efficiency of Semi-RAID is verified by a simulated video surveillance consisting of 32 cameras with D1 resolution. The experiment shows: Semi-RAID can save 45 % energy than Hibernator; 80 % energy than PARAID; 33 % energy than MAID; 79 % energy than eRAID-5, while providing single disk fault tolerance and meeting the performance requirement, such as throughput.     

The Prolog not-predicate and negation as failure rule

Clark’s query evaluation procedure for computing negative information in deductive databases using a “negation as failure” inference rule requires a safe computation rule which may only select negative literals if they are ground. This is a very restrictive condition, which weakens the usefulness of negation as failure in a query evaluation procedure. This paper studies the definition and properties of the “not” predicate defined in most Prolog systems which do not enforce the above mentioned condition of a safe computation rule. We show that the negation in clauses and the “not” Predicate of Prolog are not the same. In fact a Prolog program may not be in clause form. An extended query evaluation procedure with an extended safe computation rule is proposed to evaluate queries which involve the “not” predicate. The soundness and completeness of this extended query evaluation procedure with respect to a class of logic programs are proved. The implementation of such an extended query evaluation procedure in a Prolog system can be implemented by a preprocessor for executing range restricted programs and requires no modification to the interpreter/compiler of an existing Prolog system. We compare this proposed extended query evaluation procedure with the extended program proposed by Lloyd and Topor, and the negation constructs in NU-Prolog. The use of the “not” predicate for integrity constraint checking in deductive databases is also presented.