bluuebunny/crossref_metadata_2025_split huggingface dataset:
Home Automation
Authors: Douligeris Christos 
Published: December 2007

Abstract
Home automation is expected to increase comfort and security around the house and provide economic benefits through energy conservation. An ideal home automation system would relieve the inhabitant of a house of any unwanted manual control of every appliance and electrical or gas equipment in the house and would provide for an automated environment that would be aware of specific user needs and habits and program the operation of these appliances accordingly. Given the recent advances and drop in costs in computers, fiber optics, and multimedia communications, the concept of home automation systems has been extended to include data, voice, and visual communications inside a home. The recent expansion of the Internet and the World Wide Web (WWW) coupled with efficient home automation systems may provide an additional added value to the concepts of telecommuting; home schooling; interaction between students, teachers, and parents; home entertainment; and remote efficient resource management of home appliances.
Logic Synthesis
Authors: Barriga Angel , Jimenez Carlos J. , Valencia Manuel 
Published: December 2007

AbstractThis article addresses logic synthesis, which involves the generation of a circuit at the logic level based on an RT level design specification. The article deals with aspects associated with logic design such as data types, system components, and modes of operation. The hardware description languages will be presented as tools to specify digital systems. Two standard languages (VHDL and Verilog) will be examined in detail, and the use of VHDL for automatic synthesis will be explained to illustrate specific aspects of logic synthesis descriptions. The article ends with an illustrative example of the principal concepts discussed.
Biologically Inspired Neural Computation
Authors: Leondopulos Stathis , Micheli‐Tzanakou Evangelia 
Published: December 2007

Abstract

The development of intelligent machines that are capable of robust sensory perception has been an elusive task for those involved in machine intelligence. Indeed, although machines have been developed for performing on the order of 10
12
floating‐point operations per second, they have not been able to outperform human infants at such simple tasks as face recognition. As a result, many researchers have turned their sights to the inner workings of the biological brain itself in the hope of finding clues to the development of more robust machine perception, thus spawning the field of biologically inspired computation.

It should be noted that biologically inspired computation includes many topics that are not directly related to the function of the nervous system, such as genetic algorithms and molecular or DNA computing. However, within the context of neural networks, biologically inspired computation can be described as the development and implementation of models and algorithms that imitate the behavior of individual nerve cells (or neurons) as well as groups or nuclei of synaptically interconnected neurons.
This article discusses the relationship between the biological neuron and popular artificial neural networks that have been used in the scientific literature. In addition, applications of neural networks that are exemplary of their biological origin will be presented.
Cognitive Systems and Cognitive Architectures
Authors: Sun Ron , Bringsjord Selmer 
Published: December 2007

Abstract
Cognitive systems refer to computational models and systems that are in some way inspired by human (or animal) cognition as we understand it. There is a variety of forms of cognitive systems. Among cognitive systems, cognitive architectures are generic models of cognition, inspired by psychological studies and aimed for capturing human cognition in a rather comprehensive fashion. Another common approach is specifying cognitive processes through logics and logic‐based systems. Many theoretical tools and perspectives have been developed along these lines. In this article, example cognitive systems will be described, and general issues in developing cognitive systems and cognitive architectures will also be discussed along the way.
Optimizing Compilers
Authors: Chapman Barbara M. , Leiss Ernst L. 
Published: December 2007

Abstract
Optimizing compilers are designed to modify (automatically and at compile time) the code of a given program in such a way that

The semantics of the program are maintained (i.e., the results of the original program and the modified program are identical), and

The new program is an improved one with respect to some predefined goal.

This goal is usually a reduction in execution time, but may be a reduction in memory or power consumption. Although these goals are distinct, and occasionally conflicting, programs that consume fewer resources tend to be a little faster and we do not consider other goals explicitly in the following.
Queueing Theory
Authors: Lee Ho Woo , Kumar Santosh 
Published: December 2007

Abstract
Waiting is pervasive in most computer systems—packets wait to be routed by a router, threads wait to be scheduled on a CPU, disk requests wait to be served by the disk subsystem, and so on. Queueing theory is used in to analyze the expected performance of all such systems. At design time, it is used to determine the optimal level of resources to provision. During operation, queueing theory is used to predict the performance expected of the system and to provide quality‐of‐service guarantees to the users of the system. Consequently, queueing theory is an indispensable tool for computer system designers and analysts. This article provides an introduction to queueing theory, key concepts, a summary of key results, and a discussion of current research issues in this area.
Relational Databases
Authors: Laurent Dominique 
Published: December 2007

Abstract
Database management systems (DBMSs) aim to provide users with an efficient tool for good modeling and for easy and efficient manipulation of data. The first DBMSs were based on a hierarchical and then network‐like conceptual data organization, which actually reflects the physical organization of the underlying files. These systems, although efficient, have some important drawbacks.
The relational model, proposed by Codd in 1970, avoids these drawbacks by distinguishing explicitly between the physical and the conceptual levels of data organization. This basic property of the relational model is a consequence of the fact that, in this model, users see the data as tables. The tables of a relational database are accessed and manipulated as a whole, contrary to languages based on hierarchical or network models, according to which data are manipulated on a record‐by‐record basis. As a consequence, data manipulation languages for relational databases are set‐oriented, and so, they fall into the category of declarative languages. On the other hand, because relations are a well‐known mathematical concept, the relational model stimulated a lot of theoretical research that led to successful implementations.
In this article, we focus on the theory of the relational model and on basic aspects of dependency theory. Then, we address problems related to updates and transaction management, and we briefly describe the structure of relational systems and the associated reference language called SQL. We conclude with a brief discussion on extensions of the relational model.
Software Architecture
Authors: Garlan David 
Published: December 2007

Abstract

As the size and complexity of software systems increase, the design, specification, and analysis of overall system structure becomes a critical issue. Structural issues include the organization of a system as a composition of components; global control structures, the protocols for communication, synchronization, and data access; the assignment of functionality to design elements; the composition of design elements; physical distribution; scaling and performance, and dimensions of evolution. This is the
software architecture
level of design.
CoXML: Cooperative XML Query Answering?
Authors: Chu Wesley W. , Liu Shaorong 
Published: December 2007

AbstractThe heterogeneity nature of XML data creates the need for approximate query answering. Approximate answers may be derived by relaxing query conditions to less restricted forms, i.e.,query relaxation. In this article, we first present an approach to XML query relaxation based on schema conversion, which leverages on the value relaxation techniques in the relational model. This approach, however, does not support structure relaxation. Also, information may be lost during schema conversion. To remedy these shortcomings, we then present a cooperative XML (CoXML) system provides user‐specific approximate query answers directly in the XML model. The key features of the system include:a query language that allows users to specify approximate query conditions and relaxation control requirements;a relaxation index structure, XTAH, that enables the system to provide user‐desired relaxations as specified in the queries; anda ranking model that incorporates both content and structure similarities in evaluating the relevancy of approximate answers.We also present a scalable and extensible architecture for the CoXML system based on mediators. Finally, we evaluate the system using the INEX test collections. The evaluation results demonstrate the effectiveness of the system in providing user‐specific relaxation.
Bioinformatic Databases
Authors: Herbert Katherine G. , Spirollari Junilda , Wang Jason T. L. , Wang Jason T. L. , Piel William H. , Westbrook John , Barker Winona C. , Hu Zhang‐Zhi , Wu Cathy H. 
Published: December 2007

AbstractBiological database research encompasses many topics, such as biological data management, curation, quality, integration, and mining. Biological databases can be classified in many different ways, from the topic they cover, to how heavily annotated they are or which annotation method they employ, to how heavily annotated they are or which annotation method they employ,. to how heavily annotated they are or which annotation method they employ, to how highly integrated the database is with other databases. Popularly, the first two categories of classification are used most frequently. For example, there are archival nucleic acid data repositories (GenBank, the EMBL Data Library, and the DNA Databank of Japan) as well as protein sequence motif/domain databases, like PROSITE, that are derived from primary source data.Modern biological databases comprise not only data, but also sophisticated query facities and bioinformatic data analysis tools; hence, the term “bioinformatic databases” is ofter used. This article presents information on some popular bioinformatic databased available online, including sequence, phylogenetic, structure and pathway, and microarray databases. It highlights features of these databases, discussing their unique charateristics, and focusing on types of data stored and query facilities available in the databaes. The concludes by summarizing important research and development challenges for these databases, namely knowledge discovery, large‐scale knowledge integration, and data providence problems.
Proofs of Correctness in Mathematics and Industry
Authors: Barendregt Henk 
Published: December 2007

Abstract
Quality of a product needs verification. If the product is complex, this verification cannot be done “by hand,” but one needs tools. The question then arises how those tools are being checked. Eventually quality comes from a careful specification and design methodology. Correctness is based on a mathematical proof that the design meets its specification. As mathematical proofs become long and complex themselves, we also need a tool to verify proofs. In order to prevent an infinite regress, this last tool must have a basic simplicity. Indeed, mathematical assistants that help users to develop and verify proofs are build on the current foundational logical systems that can be described in a couple of pages.
It is expected that within a couple of decades, the use of reliable mathematical assistants will be widespread and will help the human user to learn, develop, teach, communicate, referee, and apply mathematics. Computer‐verified correctness will probably become one of the most important applications of mathematics and computer science.
Run‐In Period
Authors: Berger Vance W. , Durkalski Valerie L. 
Published: December 2007

AbstractDefining the study population is a critical step in clinical trial design. Ideally, the goal should be to choose a population who best represent the target population in a clinical setting, which in turn should be that segment of the population most likely to derive benefit. Because prespecified criteria cannot always predict which patients will and will not derive benefit, run‐in periods, which may be used for other reasons as well, are often incorporated into the design to enrich the sample by detecting and excluding a subgroup of the study population that is less likely to respond to the intervention. We review the definition, objective, and impact of run‐in periods on clinical trial conduct and results.
Multinational (Global) Trial
Authors: Snapinn Steven M. 
Published: December 2007

Abstract
Multinational clinical trials are trials conducted in more than one country using a common protocol. They have become increasingly common and have many advantages, such as access to a large patient population and the potential to obtain a broadly generalizable conclusion. However, these trials also have a number of practical difficulties, such as differences among the countries in language, import/export procedures, and regulatory and legal requirements. In addition, country‐by‐treatment interactions have frequently been found in these trials, leading to difficulties in interpreting the results. For example, the MERIT‐HF trial, which evaluated metoprolol in patients with heart failure, found an overall hazard ratio for total mortality of 0.66, but a hazard ratio of 1.05 in the United States. There is particular concern that differences among countries hinder the ability to evaluate the cost effectiveness of an experimental treatment.
Optimizing Schedule of Administration in PhaseIClinical Trials
Authors: Braun Thomas M. , Thall Peter F. 
Published: December 2007

AbstractHistorically, phase I clinical trials of new agents have been designed to find a safe dose from a small set of possible doses. Typically, toxicity is defined based on one or possibly two cycles of chemotherapy so that it can be scored relatively quickly after the start of therapy. The study treats cohorts of patients according to an outcome‐adaptive statistical design or algorithm for choosing successive doses, and the resulting data are used to determine an acceptable or maximum tolerable dose (MTD). However, in most clinical settings, physicians administer multiple courses of an agent to a patient and monitor long‐term toxicity that may be related to the agent's cumulative effects. Furthermore, some patients may receive one or more modifications or delays of their planned treatment course due to low‐grade (non–dose limiting) toxicity from previous administrations. To address these situations, we have proposed a new paradigm for phase I clinical trials that determines a maximum tolerable schedule (MTS) of administration, rather than a conventional MTD (Braun, Yuan, and Thall, 14). The design is based on the time to toxicity of each patient rather than a binary indicator. The model and method account for the patient's entire sequence of administrations, with the overall hazard of toxicity modeled as the sum of a sequence of dose‐dependent hazards, each associated with one administration. As patients are enrolled, data monitoring and decision making are done continuously throughout the trial using an outcome‐adaptive Bayesian design that optimizes the schedule in terms of the overall risk of toxicity. We illustrate this new methodology with a clinical trial in allogeneic bone marrow transplantation.
Application of New Designs in PhaseITrials
Authors: Garrett‐Mayer Elizabeth 
Published: December 2007

AbstractIn recent years, novel designs have been introduced for dose‐finding studies in phase I clinical trials. Most of these are based on mathematical models of the relationship between dose and toxicity. Though these may appear more technical than more commonly used algorithmic designs, the novel designs tend be better for many reasons including smaller sample size, more precise and accurate estimate of the desired dose, fewer patients treated at unsafe levels, and more patients treated at efficacious doses. Several of these novel designs are discussed. The continual reassessment method is an adaptive approach that uses the information gathered on early patients in the trial to make decisions about the dose for patients treated later in the trial. Adaptive Bayesian designs behave in a similar way, but the framework in which they are developed differs. A design in which efficacy and toxicity are both used to determine an optimum dose is also discussed.
Vaccine
Authors: Chan Ivan S. F. 
Published: December 2007

Abstract
Vaccines are primarily developed to prevent infectious diseases. They have been given to millions of people worldwide and contributed significantly to the improvement in public health. This article provides an overview of the clinical development of vaccines in terms of efficacy, immunogenicity, and safety assessment. The high expectation for the benefit‐to‐risk ratio required for developing preventive vaccines generates some unique challenges in the design and analysis of vaccine clinical trials. We will briefly discuss these challenges and illustrate with real examples.
Dose Finding Studies
Authors: Bretz Frank , Pinheiro José C. 
Published: December 2007

AbstractDetermining an adequate dose level for a drug and, more broadly, characterizing its dose–response relationship are key objectives of clinical drug development. If the dose is set too high, safety and tolerability problems are likely to result, whereas selecting too low a dose makes it difficult to establish adequate efficacy in the confirmatory phase, possibly leading to a failed program. It is well known that many potentially useful drugs have been discarded, and much time and resources have been wasted by pharmaceutical companies because of incorrect dosing. In addition, many marketed drugs have needed to have their label changed due to inappropriate, generally excessive, initial dose recommendations. A variety of issues must be considered when planning and analyzing a dose‐finding study so as to ensure it produces useful information for decision making. We describe key statistical methodologies for designing and analyzing clinical dose‐finding studies. These methodologies can be classified into different categories: multiple comparison procedures (including trend tests), modeling techniques, hybrid methods combining the previous two approaches, and adaptive dose‐finding strategies.
Computer‐Assisted Data Collection
Authors: Gabel Tim J. , Pedrazzani Susan D. , Day Orin A. 
Published: December 2007

Abstract
Computer‐assisted data collection methods have been widely used in the government survey and market research industries but have not been as prominent in the clinical research setting, which relies heavily on the use of paper‐based case report forms. In many clinical studies, respondents typically use paper forms to provide self‐reported data for the study. These forms are then converted to electronic format by data‐entry or clinical data management systems suitable for electronic data capture. Methods such as audio computer‐assisted self‐interviewing (A‐CASI) and telephone audio computer‐assisted self‐interviewing (T‐ACASI) may be particularly helpful in collecting high‐quality patient‐reported data, especially in Phase IV and postmarketing surveillance studies. This article introduces the primary considerations for using A‐CASI or T‐ACASI and provides insights into the management of data collected with these methods. It describes some of the advantages and data management efficiencies inherent in computer‐assisted interviewing systems and concludes with specific examples of successful use of these approaches in clinical studies.
Aligned Rank Test
Authors: McNeil Rebecca B. , Woolson Robert F. 
Published: December 2007

AbstractAligned rank tests are an intuitive rank‐based approach to the evaluation of an experimental treatment effect in blocked or stratified data. Their interblock ranking foundation yields an efficiency advantage relative to comparable tests constructed from intrablock rankings such as Friedman's test. Both exact and asymptotic tests of the null hypothesis are available with this approach. We present a general overview of the history and construction of aligned rank tests, and provide an example in selected data from a clinical trial of high‐dose vitamin D supplementation.
Characterization of Organic Solar Cells: the Importance of Device Layout
Authors: Cravino A. , Schilinsky P. , Brabec C. J. 
Published: December 2007

AbstractEasily adjustable parameters such as area and design can affect the determination of the efficiency of donor–acceptor organic solar cells. Devices with crossing electrodes and unpatterned (semi)conducting organic layers can collect a non‐negligible current from regions usually not considered as part of the photovoltaic element, a fact that might lead to an overestimation of the power conversion efficiency.
Pulsed Laser Deposition and Electrochemical Characterization of LiFePO4–Ag Composite Thin Films
Authors: Lu Z. G. , Cheng H. , Lo M. F. , Chung C. Y. 
Published: December 2007

AbstractA simple approach is proposed to enhance the electrical conductivity of olivine‐structured LiFePO4 thin films by uniformly dispersing small fractions of highly conductive silver (ca. 1.37 wt %) throughout the LiFePO4 film. In this approach, a highly densified (>85 %) LiFePO4–Ag target was first fabricated by coating conductive silver nanoparticles onto the surfaces of hydrothermally synthesized LiFePO4 ultrafine particles by a soft chemical route. Pulsed laser deposition (PLD) was then employed to deposit LiFePO4–Ag composite thin films on the Si/SiO2/Ti/Pt substrates. The PLD experimental parameters were optimized to obtain well‐crystallized and olivine‐phase pure LiFePO4–Ag composite thin films with smooth surfaces and homogeneous thicknesses. X‐ray diffraction (XRD), scanning electron microscopy (SEM), Raman spectrometry (Raman), X‐ray photoelectron spectroscopy (XPS), DC conductivity measurements, cyclic voltammetry(CV), as well as galvanostatic measurements were employed to characterize the as‐obtained LiFePO4–Ag composite films. The results revealed that after silver incorporation, the olivine LiFePO4 film cathode shows a superior electrochemical performance with a good combination of moderate specific capacity, stable cycling, and most importantly, a remarkable tolerance against high rates and over‐charging and ‐discharging.