Miracle-dz/UniFAR-FTUs huggingface dataset:
An Adaptive Approach to High-Throughput Inter-Cloud Data Transmission Based on Fast TCP

Cloud service is a trend of promising services on Internet. Data centers with high performance are the key to realize real-time services for worldwide users. For the users travelling in global, data mobility between cloud data centers is essential to offer quality-ensured cloud services. However, existing transmission protocols such as TCP, do not support high speed and high throughput transmission on long-distance networks. Legacy TCP lacks of the ability to efficiently transport data between distant data centers. In this paper, an adaptive Fast TCP is proposed to move data faster between data centers of cloud services. The proposed approach adapts the operational parameter of Fast TCP connections to improve the throughput and the rapidness of TCP connections. Numeric results show that the throughput is improved by 2.5 times and the rapid response of flow control eliminates packet loss. The better data mobility contributes the service quality of travelling users in clouds.
Specification and Implementation of a Light-Weight Internet Content Delivery Platform

The World Wide Web is the largest and most popular hypertext information system in the world. It is used by billions of people primarily to share information between themselves. As more and more features are added to it, modern Web has become a powerful general-purpose application platform. The cost of that complexity is the content itself being obscured behind all the layout, presentation and interaction. This thesis specifies a simple protocol and document format intended to solve the problem of exceeding complexity of using the Web to access content sources without using complicated monolithic applications that require powerful hardware to run. This provides an alternative to the current Web technologies for browsing pages focused on the content itself, while being significantly simpler to implement and use. By using the new technologies, accessing content sources becomes simple, while the current Web remains useful as an application platform. Foremost, this simplifies creation of new browser engines that are easier to implement and need less processing resources to run. At the same time, it enables programmatic access to content that used to be accessible only to human readers.
Research on Markov Logic Networks

Markov logic networks (MLNs) is a statistical relational learning (SRL) model, which combines Markov network and first order logic. It has been applied widely in nature language processing, complex networks, information extraction, etc. This paper addresses the theoretical model of Markov logic networks (MLNs), weight and structure learning of MLNs comprehensively, and finally presents future works of MLNs.
Design of a software quality decision system: a computational intelligence approach

This paper introduces an approximate reasoning system for assessing software quality and introduces the application of two computational intelligence methods in designing a software quality decision system, namely, granulation from fuzzy sets and rule-derivation from rough sets. This research is part of a computational intelligent systems approach to software quality evaluation, which includes a fuzzy-neural software quality factor-criteria selection model with learning and a rough-fuzzy-neural software quality decision system. Overall, computational intelligence results from a synergy of various combinations of genetic, fuzzy, rough and neural computing in designing engineering systems. Based on observations concerning software quality and the granulations of measurements in an extended form of the McCall software quality measurement framework, an approach to deriving rules about software quality is given. Quality decision rules express relationships between evaluations of software quality criteria measurements. A quality decision table is constructed relative to the degree of membership of each software quality measurement in particular granules. Decision-tables themselves are as a collection of sensors, which "sense" inputs and output conditions for rules. Rosetta is used to generate quality decision rules. The approach described in this paper illustrates the combined application of fuzzy sets and rough sets in developing a software quality decision system.
Increasing grammar coverage through fine-grained lexical distinctions

In this paper, I show how the development of Norsyg, an HPSG-inspired constructionalist grammar of Norwegian, benefits from the highly specific and precise implementation of NorGram, an LFG grammar for Norwegian. I focus on one aspect, NorGram’s fine-grained lexical categories. The aim of the paper is twofold: (i) to give a glimpse of the process of developing a computational grammar, and (ii) to illustrate how a constructionalist grammar benefits from the insights of NorGram, even though the grammatical models differ significantly.
PFC Cuk Converter Fed BLDC Motor Drive using Artificial Neural Network

—In this paper a Power Factor Correction Cuk converter fed Brushless DC Motor Drive using a Artificial Neural Network is used. The Speed of the Brushless dc motor is controlled by varying the output of the DC capacitor. A Diode Bridge Rectifier followed by a Cuk converter is fed into a Brushless DC Motor to attain the maximum Power Factor. Here we are evaluating the three modes of operation in discontinuous mode and choosing the best method to achieve maximum Power Factor and to minimize the Total Harmonic Distortion. We are comparing the conventional PWM scheme to the proposed Artificial neural network. Here simulation results reveal that the ANN controllers are very effective and efficient compared to the PI and Fuzzy controllers, because the steady state error in case of ANN control is less and the stabilization if the system is better in it. Also in the ANN methodology the time taken for computation is less since there is no mathematical model.The performance of the proposed system is simulated in a MATLAB/Simulink environment and a hardware prototype of the proposed drive is developed to validate its performance.
Body Image and Media

A portion of youthful females may acknowledge unpredictable dietary patterns because of shameful problems about their body shape or weight, others utilize sustenance to comfort themselves as far as unforgiving conditions in their social or instructive lives. Different components can bring about these issues. This is on the grounds that specific perspectives are solid in one's choice to eat certain foodstuffs. Such solid components incorporate companion weight, family standards, social practices, accessibility of various foodstuffs, and desires.
Hala ρ-VEX: Highly-Programmable Dynamically-Reconfigurable FPGA-based Streaming Platform for Image Processing

Image processing is found in many fields and in many domains. Advances in digital image capturing technology allows for faster video rates, of higher quality, than has been seen before and that trend continues. With greater resolution and increased data flow there is also a need for faster and better hardware for image processing. As the trend introduced in Moore's law is slowing down, and possibly reaching saturation in the coming years, there is an ongoing search for new and different solutions in processor architecture. The trend went from single core to multi core and many core and now we are looking into other designs like memory streaming architectures and runtime reconfigurable computers. This thesis designs, implements and evaluates a programming interface for a dynamically-reconfigurable memory-streaming platform for image processing with a focus on programmability, power consumption, reconfigurability and performance. An application programming interface (API) is created to aid with new code development for the platform. The API is a library of functions that are run on an ARM processor and are used to setup, and communicate with, a stream of ρ-VEX soft processors running on a field programmable gate array (FPGA). In this research we look at other state-of-the-art solutions, for comparison and inspiration, that focus on programmability, reconfiguration and performance. The platform is reconfigurable at runtime and experiments show that it takes under 200 ms to completely reconfigure the fabric and initialize a new configuration of ρ-VEX processors. The platform is tested on a Zynq-7000 chip from Xilinx. Comparison is made between streaming architecture and a many core setup using the same amount of ρ-VEX soft processors. The results show a speedup of factor of 2 by using a single processing stream of seven cores compared with seven cores individually running the same algorithm. The result is a working fully-programmable and open-source streaming platform for the image processing domain.
Forensic Examinations: Computational Analysis and Information Extraction

Complex interaction analysis, and information extraction from text and speech are an active resea rch field, based on linguistic theories and NLP techniques. In this paper we present a conceptual model that aims at generating a rich description of forensic examinations, exploiting –i n a novel way– forensic, psychological, and linguistic theories. Such description is then translated into profiles and a report. Profiles describe examiners and the person under examination, while the report evaluates the whole examination. Our main goal is to provide a didactical tool for improving forensic examination techniques. The model is based on a multi-layered set of HMMs, which leverage and combine speech (from audio recordings) and textual(from related transcriptions) features, classifying the examination at several granularity levels. Then, a rule-based expert system generates profiles and an evaluation of the examination. We also created a new audio/textual corpus based on real examinations collected from Italian trials. DIKE is the prototype we are currently implementing and that we plan to use for model validation.
Resolución automática de la ambigüedad léxica fundamentada en el modelo del espacio vectorial usando ventana contextual variable

The resolution of lexical ambiguity of polysemics words is a complex and useful task for many natural language processing applications. We present a new approach for word sense disambiguation based in the vector space model and a widely available training collection as linguistic resource. This approach uses a contextual windows (variable set of terms like local context). We have tested our disambiguator algorithm on a large documents collection, achieving high precision in the resolution of lexical ambiguity.
SIMULATION MODEL FOR THE EVOLUTION OF LANGUAGE WITH SPATIAL TOPOLOGY

In this paper, we present an agent-based simulation model for the evolution of language. This is based on a previous model proposed by the authors and inspired by Nowak’s simplest mathematical model. We extend our previous work with the introduction of a significant characteristic: a world where the languages live and evolve, and which influences interactions among individuals. The main goal of this research is to present a model which shows how the presence of a topological structure influences the communication among individuals and contributes to the emergence of clusters of different languages.
The effects of pre-processing strategies in sentiment analysis of online movie reviews

With the ever increasing of internet applications and social networking sites, people nowadays can easily express their feelings towards any products and services. These online reviews act as an important source for further analysis and improved decision making. These reviews are mostly unstructured by nature and thus, need processing like sentiment analysis and classification to provide a meaningful information for future uses. In text analysis tasks, the appropriate selection of words/features will have a huge impact on the effectiveness of the classifier. Thus, this paper explores the effect of the pre-processing strategies in the sentiment analysis of online movie reviews. In this paper, supervised machine learning method was used to classify the reviews. The support vector machine (SVM) with linear and non-linear kernel has been considered as classifier for the classification of the reviews. The performance of the classifier is critically examined based on the results of precision, recall, f-measure,.
Indoor detection of passive targets recast as an inverse scattering problem

The wireless local area networks represent an alternative to custom sensors and dedicated surveillance systems for target indoor detection. The availability of the channel state information has opened the exploitation of the spatial and frequency diversity given by the orthogonal frequency division multiplexing. Such a fine-grained information can be used to solve the detection problem as an inverse scattering problem. The goal of the detection is to reconstruct the properties of the investigation domain, namely to estimate if the domain is empty or occupied by targets, starting from the measurement of the electromagnetic perturbation of the wireless channel. An innovative inversion strategy exploiting both the frequency and the spatial diversity of the channel state information is proposed. The target-dependent features are identified combining the Kruskal-Wallis test and the principal component analysis. The experimental validation points out the detection performance of the proposed method when applied to an existing wireless link of a WiFi architecture deployed in a real indoor scenario. False detection rates lower than 2 [%] have been obtained.
Lighting quality and environmental satisfaction in open and enclosed offices

Using data from a national study of office buildings, this article tests and confirms previous research indicating that lighting is important to the overall quality of the workspace. The importance of lighting is demonstrated , even after taking into account other physical attributes subject to manipulation by designers . The research also demonstrates that , for people working in enclosed private offices, lighting quality is more important to their overall assessment of the workspace than it is for workers in open office systems . At the same time, privacy in open office systems influences assessments to a lesser degree than does lighting quality . These and other findings suggest that the design of future open offices needs to consider the ambient environment as well as privacy issues . Specific design considerations are outlined .
Proceedings of the 10th International Conference on Parsing Technologies

Welcome to the Tenth International Conference on Parsing Technologies, IWPT 2007, in the beautiful city of Prague. IWPT'07 continues the tradition of biennial workshops on parsing technology organized by SIGPARSE, the Special Interest Group on Parsing of the Association for Computational Linguistics (ACL). The first workshop, in Pittsburgh and Hidden Valley, was followed by workshops in Cancun (Mexico) in 1991; Tilburg (Netherlands) and Durbuy (Belgium) in 1993; Prague and Karlovy Vary (Czech Republic) in 1995; Boston/Cambridge (Massachusetts) in 1997; Trento (Italy) in 2000; Beijing (China) in 2001; Nancy (France) in 2003; and Vancouver (Canada) in 2005. Over the years the IWPT Workshops have become the major forum for researchers in natural language parsing. They have also given rise to four books on parsing technologies. For the first time this year, IWPT is organised as a co-located event with the main ACL conference and with EMNLP and many other workshops.
Differential Elimination and Biological Modelling

This paper describes applications of a computer algebra method, differential elimination, to applied mathematics problems mostly borrowed from biology. The two considered applications are related to the parameters estimation and the model reduction problems. In both cases, differential elimination can be viewed as a preparation to numerical treatments. Together with the applications, the paper introduces two implementations of the differential elimination algorithms: the diffalg package and the BLAD libraries.
Experimental evaluation of adaptive neurocontrollers for a prototype space robotic manipulator

The dynamics of robotic systems are often affected by poorly modeled internal and external forces. This paper presents an experimental evaluation of adaptive compensation for unmodeled dynamic effects on a prototype space robotic manipulator. Recent extensions to adaptive nonlinear control theory show that neural networks can be used to reliably compensate for these effects. In this paper, a newly developed neurocontrol algorithm is implemented on a prototype robotic manipulator with a single degree of freedom. The experimental results demonstrate that by adaptively compensating for friction torques in the motor joint and for hydrodynamic effects present during underwater operation of the arm, the neurocontroller greatly improves the tracking performance of the system, reducing tracking errors observed witli a simple PD controller by an order of magnitude. Since the neurocontroller is capable of compensating for unmodeled forces, it seems well suited for space robotic operations which occur in unfamiliar surroundings with poorly modeled environmental factors, as well as for neutral buoyancy simulation of space operations.
Classification of the EMG's Recruitment Pattern Using Neural Networks

In this work, we have developed an Artificial Neural Network (ANN) for the classification of the electromyogram (EMG) obtained with concentric needle electrodes during electromyography. The Neural Network is based on the back propagation algorithm and has been trained to distinguish and classify normal, myopathic and neurogenic EMG signals taken from Biceps * Author to whom correspondence should be addressed.
ROBUST DETECTION OF DYNAMICAL CHANGE IN SCALP EEG

We present a robust, model-independent technique for measuring changes in the dynamics underlying nonlinear time-serial data. We define indicators of dynamical change by comparing distribution functions on the attractor via L{sub 1}-distance and X{sup 2} statistics. We apply the measures to scalp EEG data with the objective of capturing the transition between non-seizure and epileptic brain activity in a timely, accurate, and non-invasive manner. We find a clear superiority of the new metrics in comparison to traditional nonlinear measures as discriminators of dynamical change.
Performance evaluation of wireless networks speed depending on the encryption

We can use a variety of encryption standards to encrypt data traffic to ensure the safety of wireless networks. The question is to what extent the security of the network affects network performance. For answering this question, experiments were performed without data encryption, and the use of various encryption standards. IEEE 802.11g and 802.11n wireless networking standards were used in the experiment. The answer of the question is that encryption should be used because it does not cause significantly slower speed.
Design and implementation of an untrimmed MOSFET-only 10-bit A/D converter with -79-dB THD

A MOSFET-only 10-bit A/D converter is described which achieves a total harmonic distortion of up to -79 dB without trimming or calibration. The maximum conversion rate is 200 ksample/s. Implemented in a 1-/spl mu/m single-poly technology, it occupies 5.12 mm/sup 2/ and consumes 12 mW from a single 5 V supply. The MOSFET-only R-2R ladder, which is the center of the successive approximation architecture, is analyzed, and design considerations, especially the device dimensions, are given. Measurements of the linear behavior of pure MOSFET ladders are presented. The offset sensitivity of the ladder is examined, and an alternative way of summing the ladder current is suggested. A fast and effective differential current comparator is described.
Integrity Coded Databases: Ensuring Correctness and Freshness of Outsourced Databases

In recent years, cloud storage has become an inexpensive and convenient option for individuals and businesses to store and retrieve information. The cloud releases the data owner from the financial burden of hiring professionals to create, update and maintain local databases. The advancements in the field of networking and the growing need for computing resources for various applications have made cloud computing more demanding. Its positive aspects make the cloud an attractive option for data storage, but this service comes with a cost that it requires the data owner to relinquish control of their information to the cloud service provider. So, there remains the possibility for malicious insider attacks on the data that may involve addition, omission, or manipulation of data. This paper presents a novel Integrity Coded Database (ICDB) approach for ensuring data correctness and freshness in the cloud. Various options for verifying the integrity of queried data in different granularities are provided, such as the coarse-grained integrity protection for the entire returned dataset or a more fine-grained integrity protection down to each tuple or even each attribute. ICDB allows data owners to insert integrity codes into a database, outsource the database to the cloud, run queries against the cloud database server, and verify that the queried information from the cloud is both correct and fresh. An ICDB prototype has been developed in order to benchmark several ICDB schemes to evaluate their performance.
An Evaluation of the Open Object-Oriented Database

The diversity of database designs has motivated standardization efforts. The Advanced Research Projects Agency (ARPA) sponsored Open Object-Oriented Database (Open OODB) project is the leading effort to develop an extensible, modular architecture for next-generation, object-oriented databases ( OODBs ). The Next-Generation Computer Resources (N GCR) Database Management Systems Interface Standards Working Group (DISWG) has published requirements that will help dictate how the Navy meets its future database needs. This thesis will evaluate Open OODB with respect to the DISWG requirements. Each DISWG requirement is evaluated from three distinct perspectives. First, we see if Open OODB has a matching requirement(s ). Second, we evaluate if Open OODB's proposed architecture would meet the requirement, and third, we evaluate if Open OODB's implementation meets the requirement. If a particular DISWG requirement is found to be unmet, we investigate the feasibility of extending Open OODB to meet the requirement.
Packaging Design for Implantable Microstimulator

Implantable biomicrosystems for restoring neuromuscular functions have gained more attention for studying the characteristics of various types of neural interfaces. In our previous study, we have developed a microprocessor-based microstimulation system by using the surface mount device (SMD) components on printed circuit board (PCB) and stimulating electrodes, prepared for implantation into animal on neuromodulation studies. The aim of this study is to investigate the feasibility of packaging design of an implantable microstimulator. In current study, Micro Electro Mechanical System (MEMS) fabrication process for microassembly and interconnection on flexible polyimide substrates was employed to integrate microstimulator circuitry and nerve cuff electrodes as an implantable biomicrosystem for peripheral nerve applications to achieve a module package. The flexible mechanical structure design of microstimulator is more suitable for module design and implantation purposes. Dam-and-fill process was applied to seal the module, which was later encapsulated with medical grade silicone rubber for biocompatible package. The implantable microstimulator measured at 4 cm in diameter and 8 mm in height with cuff electrode interconnected to it. Finally, in-vitro experiment in the normal saline has confirmed that it is feasible to employ dam-and-fill encapsulation and medical-grade silicone rubber to package the biomicrosystem for a period of 30 days. The microstimulator is undergoing in vivo tests through the implantation of implantable microstimulator for stimulating rabbit's sciatic nerve.