Miracle-dz/UniFAR-FTUs huggingface dataset:
System-level analysis of a smart optoelectronic database filter for relational database applications

A challenging task facing the designers for the next generation of archival storage system is to provide storage capacities several orders of magnitude larger than existing systems while maintaining current data access times. To meet this challenge, we have developed a smart optoelectronic database filter suitable for large capacity relational database systems that use page-oriented optical storage devices. The photonic VLSI device technology based database filter monolithically integrates optical detectors, photoreceiver circuits, data manipulation logic, and filter control circuitry onto a single CMOS chip. This paper presents the design and system level analysis of the database filter system. Simulation data suggested that a 32 X 32-bit filter fabricated in a 1.5 micrometers CMOS process could have an optical page read rate of 87 Mpages/s and support 123 Mrecords/s transfer rate to a host computer. Queuing theory is used to show that even with the limitation of finite queue capacity, a database filter chip could be controlled to work at near optimal performance where database search time is limited by the data transfer rate going into the host computer. Since only valid search data is passed through to the host computer, the introduction of a database filter can dramatically reduce database search time.
System Integrity Monitoring System using Kernel-based Virtual Machine

The virtualization layer is executed in higher authority layer than kernel layer and suitable for monitoring operating systems. However, existing virtualization monitoring systems provide simple information about the usage rate of CPU or memory. In this paper, the monitoring system using full virtualization technique is proposed, which can monitor virtual machine`s dynamic kernel object as memory, register, GDT, IDT and system call table. To verify the monitoring system, the proposed system was implemented based on KVM(Kernel-based Virtual Machine) with full virtualization that is directly applied to linux kernel without any modification. The proposed system consists of KvmAccess module to access KVM`s internal object and API to provide other external modules with monitoring result. In experiments, the CPU utilization for monitoring operations in the proposed monitering system is 0.35% when the system is monitored with 1-second period. The proposed monitoring system has a little performance degradation.
Multi-object motion segmentation in image sequence based on cellular neural networks

In this paper, a new approach to multi-objects motion segmentation in image sequence based on cellular neural networks (CNN) is proposed. As the core ofthis approach, difference merged image algorithm is presented. In order to realize the algorithm, the reverse CNN template, the addition CNN template, the patch-filled CNN template and the composition CNN template are presented and designed. For based on CNN, this approach can improve the capability of real-time in motion segmentation. And on the other hand, because difference merged image algorithm we improved is directly used in gray-scale image processing instead of in binary image processing, it can get more information of motion and increase the accuracy of segmentation. Finally, we show the experiment results, which prove that this approach has a good capability in multi-objects motion segmentation.
CoLocScribe: A Media Space for Information Disclosure in Storytelling

Digital storytelling of remote social interaction, where the situation of a remote group distributed over two locations is captured and a story is generated for later retrieval, can provide valuable insight into the structure and processes in a group. Yet, capturing these situations is a challenge—both from a technical perspective, and from a social perspective. In this paper we present CoLocScribe: a concept and prototype of an advanced media space featuring ubiquitous computing technology for capturing remote social interaction as well as a study of its use providing valuable feedback for the captured persons as well as input for the authors.
Generalizing Database Access Methods

Efficient implementation of access methods is crucial for many database sys tems. Today, database systems are increasingly being employed to support new applications involving multi -dimensional data. A large variety of specialized access methods have been developed to solve specific problems. These specialized access methods are usually hand-coded from scratc h. The effort required to implement and maintain such data structures is high. As an alternative t o developing new data structures from scratch, some researchers have tried to simplify sea rch tree technology by generalization. This thesis generalizes access methods at multiple levels, starting wi h hierarchical search-tree access methods. The basic logic and commonalities among different database sea rch trees are explored. A generalized search tree is built and a generalized class libr ary is created including a small set of specialized components. Specific search trees can be built significantly faster than using the traditional approach, using the generalized model and selecting components f rom he library. This work attempts to start a taxonomy for secondary-memory data str uctures, which is used both to classify functionality and reuse implementation. It is simila r to the taxonomy provided by Leda/STL in C++ for primary-memory data structures. Example tree file s tructures are also developed and performance experiments on these file structures demonstrate the f easibility of the generalization approach to achieve efficient implementation of search-tr ee access methods.
Can neural pooling help insects see at night?

Neural pooling of signals generated in the photoreceptors of neighbouring ommatidia is investigated as a possible strategy for improving vision at low light levels in compound eyes. Theoretical calculations of the maximum spatial frequency detectable by an eye suggest that neural pooling greatly improves vision in dim light. This strategy is particularly useful for an insect such as the locust which is primarily day-active, has an eye design more suited to bright light (the apposition design), but often flies in the evening. Nevertheless, compound eyes primarily designed for nocturnal vision (superposition eyes) are found to out-perform neurally pooled apposition eyes in dim light, a situation which is most likely reversed in bright light when the apposition eye ceases to pool, thereby greatly improving spatial resolution. <<ETX>>
Becoming an Online Distance Learner: What can be learned from students’ experiences of induction to distance programmes?

This paper reports the findings of a qualitative study that investigated the experiences of distance learners beginning online Master of Education programmes. The research explored students’ induction (referred to as “orientation” in some contexts) to the programmes, and three key areas are given consideration in this paper. First, the opportunities and constraints provided by the technology in terms of introducing students to their online studies and the online environment are discussed. Second, some human elements are examined; namely, students’ needs, students’ relationships with fellow students, and the role of tutors. Third, there is a discussion on the development of online learning communities; their role and importance, and how students might be effectively integrated into them. Some implications for online teaching and learning are outlined and recommendations for online induction are provided. The paper concludes that a fundamental understanding of both students’ needs and their initial encounters with online distance education are important to ensure effective support is provided when students commence their studies.
Semantic Compositionality and Truth-Conditional Content

It is widely held that hearers grasp an utterance's truth conditions by assigning contents to the linguistic expressions used, and combining these contents according to semantic composition rules. To preserve compositionality of truth-conditional content while accounting for context-sensitivity that is not traceable to overt linguistic form, semanticists posit covert linguistic structure. The strongest justification for this approach is the allegedly unconstrained nature of the alternative, whereby a process of ‘free pragmatic enrichment’ supplies constituents of content that are not traceable to (overt or covert) encoded meaning. This paper argues that free enrichment is tightly constrained by purely pragmatic factors, thus undermining the motivation for semantic compositionality.
Advances in Bacteriology

Professor Houssay and his colleagues are all professors or directors of physiology, pharmacology, or biochemistry in institutes of research in Argentina. No one section is officially written by any one author; the team takes collective responsibility for every page. The translation is excellent and the illustrations are well chosen, most being taken from the original papers quoted. There are ample and complete references to the original literature, both as footnotes to the pages on the matter under discussion and also at the ends of chapters to the main reviews and monographs. This book is excellent in its approach to the subject. It is balanced, though it might be possible for a specialist to say that his aspect has not had justice done to it. It is to be compared with the standard textbooks of Starling and Halliburton in this country, and with Best and Taylor's in Canada, or Fulton-Howell's in the U.S.A. It has the great advantage of them all-that it is a first edition; it is new and therefore a comprehensive treatment of the application of physiology to the human subject in a framework and plan cast in the mould of physiology as it was in 1951 ; it is uninhibited by being written to a plan of earlier years and adapted as different aspects have grown or regressed in importance. The personalities and authority of the authors are visible throughout, and the book is to be recommended to all physiologists, physicians, and libraries. Its sole disadvantage in England is its price. A. Str. G. HuOOETT.
Construction and Influence Analysis of Co-Author Network Based on Network Science

In this paper, we are devoted to the construction and analysis of research network. Firstly, on the basis of data Erdos1, a co-author network is built and two novel measures are proposed to analyze properties of the co-author network. A data extraction method using string matching technique is developed and the network is visualized using UCINET. Then, the first-order and second-order entropy are defined to depict the complexity of the network, and the node’s invalidity probability and load-bearing capacity are defined to depict the robustness of the network.
A proof-of-concept experiment for the detection of occluded coronary arteries using array sensor technology

Describes measurement and signal processing techniques to identify energy transmission in a viscoelastic medium. The source of the energy is turbulent flow in an elastic tube which is embedded in a urethane solid. The flow field in the pipe is laminar until it reaches a blockage which makes the flow transition from laminar to turbulent. The resulting turbulent flow field transmits energy into the methane which is converted into propagating wave energy. This energy is measured on the surface of the solid using PVDF motion sensors at several locations. The resulting measurements are then processed in such a manner that the phase velocity and energy content of the wave can be identified. This test is intended as a proof-of-concept experiment to show that the energy conversion at blockages in flow fields can be detected.
Dr.LiTHO: a development and research lithography simulator

This paper introduces Dr.LiTHO, a research and development oriented lithography simulation environment developed at Fraunhofer IISB to flexibly integrate our simulation models into one coherent platform. We propose a light-weight approach to a lithography simulation environment: The use of a scripting (batch) language as an integration platform. Out of the great variety of different scripting languages, Python proved superior in many ways: It exhibits a good-natured learning-curve, it is efficient, available on virtually any platform, and provides sophisticated integration mechanisms for existing programs. In this paper, we will describe the steps, required to provide Python bindings for existing programs and to finally generate an integrated simulation environment. In addition, we will give a short introduction into selected software design demands associated with the development of such a framework. We will especially focus on testing and (both technical and user-oriented) documentation issues. Dr.LiTHO Python files contain not only all simulation parameter settings but also the simulation flow, providing maximum flexibility. In addition to relatively simple batch jobs, repetitive tasks can be pooled in libraries. And as Python is a full-blown programming language, users can add virtually any functionality, which is especially useful in the scope of simulation studies or optimization tasks, that often require masses of evaluations. Furthermore, we will give a short overview of the numerous existing Python packages. Several examples demonstrate the feasibility and productiveness of integrating Python packages into custom Dr.LiTHO scripts.
Hangul Password System for Preventing Shoulder-Surfing

Although conventional text-based passwords are used as the most common authentication method, they have significant drawbacks such as guess attacks, dictionary attacks, key loggers, and shoulder-surfing. To address the vulnerabilities of traditional text-based passwords, graphical password schemes have been developed as possible alternative solutions, but they have a potential drawback that they are more vulnerable to shoulder-surfing than conventional text-based passwords. In this paper, we present a new Hangul password input method to prevent shoulder-surfing attacks. Our approach uses Hangul as a password, and it requires the users to locate their password in the given wheeling password grid instead of entering the password. Our approach makes it difficult for attackers to observe a user`s password since the system shows the users` passwords with decoy characters as the noise on the screen. Also, we provide security analysis for random attacks, dictionary attacks, and shoulder-surfing attacks, and it shows that our password system is robust against these attacks.
Coded modulation to increase storage capacity of multilevel memories

Multilevel memory cells and analog memory cells have the capability of storing considerably more than one bit per cell. A multilevel or an analog memory cell is modelled as an additive white Gaussian noise channel. Thus storing a certain number of bits in one cell corresponds to storing a finite number of amplitude levels. Due to the additive noise in the memory cell, the bits read from the memory cell are affected by an output error probability. This paper proposes using a coded modulation technique to increase the storage capacity of multilevel and analog memory cells by one extra bit per cell. The technique can also be applied to improve the read-out bit-error probability and provide unequal error protection for the bits to be stored. One and two-dimensional coded modulation schemes as well as uncoded modulation schemes are presented in detail. Complexity issues are also considered.
Multivariate U‐statistics: a tutorial with applications

U‐statistics represent an important class of statistics arising from modeling quantities of interest defined by multi‐subject responses such as the classic Mann–Whitney–Wilcoxon rank tests. However, classic applications of U‐statistics are largely limited to univariate outcomes within a cross‐sectional data setting. As longitudinal study designs become increasingly popular in today's research, it is imperative to generalize the classic theory of U‐statistics to such a study setting to meet the challenges of modern clinical and translational research. In this article, we focus on applications of U‐statistics to longitudinal study data. We first give a brief overview of U‐statistics and then discuss how to apply this powerful class of statistics to model quantities of interest with a longitudinal data setting. In addition to generalizing U‐statistics and associated inference theory to longitudinal data analysis, we also discuss a class of function response models (FRM) to bring the power of U‐statistics to uncharted territory. We illustrate applications of generalized U‐statistics and FRM with data from some real longitudinal studies. WIREs Comp Stat 2011 3 457–471 DOI: 10.1002/wics.178
An Experiment in Productivity: The Use of Home Terminals

In recent years, the use of remote or home computer terminals has made a significant impact on the IS department and its clients ( users). In response to IS and user needs, including a desire to decentralize the workplace (i.e., IS department) and a belief that home terminals would have a positive effect on productivity and employee morale, IBM decided to implement several such home terminals as a means of determining their effectiveness. This article describes an experiment that measured the effects of implementing a home terminal program.
A new model of lexical choice for nouns 1

Natural language generation systems should choose nouns by searching for lexical units that (i) are known to the user; (ii) truthfully describe the object being lexicalised; (iii) convey sufficient information to fulfill the system's underlying communicative goals; and (iv) are maximal under a lexical preference function. This model of lexical choice allows a clean separation to be made between what the system knows about the object being lexicalized and what it wishes to communicate about this object. The model also allows lexical choice to be biased towards basic‐level and other preferred lexical units.
Path following control law for an industrial mobile robot

This paper presents a nonlinear control law based on partial state feedback linearization and Lyapunov method for the closed-loop path following problem of a nonholonomic mobile robot. The desired path is described by a reference mobile robot with the same kinematics constraints as the real robot. This method was successfully implemented on the autonomous mobile robot CHARLATTE in Automatic Systems Laboratory (LSA).
Wavelet-based ground vehicle recognition using acoustic signals

We present, in this paper, a wavelet-based acoustic signal analysis to remotely recognize military vehicles using their sound intercepted by acoustic sensors. Since expedited signal recognition is imperative in many military and industrial situations, we developed an algorithm that provides an automated, fast signal recognition once implemented in a real-time hardware system. This algorithm consists of wavelet preprocessing, feature extraction and compact signal representation, and a simple but effective statistical pattern matching. The current status of the algorithm does not require any training. The training is replaced by human selection of reference signals (e.g., squeak or engine exhaust sound) distinctive to each individual vehicle based on human perception. This allows a fast archiving of any new vehicle type in the database once the signal is collected. The wavelet preprocessing provides time-frequency multiresolution analysis using discrete wavelet transform (DWT). Within each resolution level, feature vectors are generated from statistical parameters and energy content of the wavelet coefficients. After applying our algorithm on the intercepted acoustic signals, the resultant feature vectors are compared with the reference vehicle feature vectors in the database using statistical pattern matching to determine the type of vehicle from where the signal originated. Certainly, statistical pattern matching can be replaced by an artificial neural network (ANN); however, the ANN would require training data sets and time to train the net. Unfortunately, this is not always possible for many real world situations, especially collecting data sets from unfriendly ground vehicles to train the ANN. Our methodology using wavelet preprocessing and statistical pattern matching provides robust acoustic signal recognition. We also present an example of vehicle recognition using acoustic signals collected from two different military ground vehicles. In this paper, we will not present the mathematics involved in this research. Instead, the focus of this paper is on the application of various techniques used to achieve our goal of successful recognition.
Teaching Managerial Finance Through Compressed Video: An Alternative for Distance Education

Abstract Compressed video is a means of delivering instruction that allows for two-way audio and video interaction between the instructor and students at remote sites. This article describes the teaching of the CBK managerial finance class using this delivery mode. A pretest/posttest comparison shows that students at both the send site and remote site do learn and have comparable learning experiences. Student feedback on the course and suggestions for improving the presentation and implementing the technology are presented.
Laser-based 3-D volumetric display system

In the past several years, the Display Systems Branch, Naval Ocean Systems Center (NOSC), has been involved in the development of laser based display systems with the goal of upgrading the image quality of shipboard displays. In this paper we report work on: (1) developing laser generated 3D volumetric images on a rotating double helix, (where the 3D displays are computer controlled for group viewing with the naked eye), and (2) system feasibility results along with the first and second generation component parameters.
Synthesis of isocyanate microcapsules as functional crosslinking agent for wood adhesive

ABSTRACT In this study, controlled-release isocyanate microcapsules were synthesized as functional crosslinking to slowdown the rate of cross-linking reactions. The isocyanate microcapsules were prepared by In-situ polymerization with polymethylene polyphenyl polyisocyanates (PAPI) as core and Urea formaldehyde resin as shell in oil-in-water emulsions. The particle size distribution, chemical structure, morphology, activity, and stability of the microcapsules were comprehensively characterized. Finally, the microcapsules were applied in a wood adhesive to prepare water-resistant plywood. The results showed that the size of the microcapsules was around 100 μm, the active content of NCO was about 23.5%, and the core content was approximately 80%. Compared with the stability of the bulk isocyanate, the stability of the isocyanate in microcapsules was significantly improved in the wood adhesive system. Furthermore, the isocyanate microcapsules showed highly efficient in plywood at different time, which indicated that isocyanate microcapsules could be controllable released in plywood applications.