Miracle-dz/UniFAR-FTUs huggingface dataset:
A NOVEL POWER MANAGEMENT TECHNIQUE FOR BI-DIRECTIONAL INVERTER INTEGRATED WITH BUCK-BOOST CONVERTER

A single-phase bi-directional inverter with two buck/boost maximum power point trackers (MPPTs) for dcdistribution applications. In a dc-distribution system, a bi-directional inverter is essential to control the power flow between dc bus and ac grid, and to regulate the dc bus to a certain range of voltages. Since the photovoltaic (PV) array voltage can vary from 0 to 600 V, especially with thin-film PV panels, the MPPT topology is formed with buck and boost converters to operate at the dc-bus voltage around 120 V, reducing the voltage stress of its followed inverter. In the proposed system battery back-up can be employed for PV for better stabilization. The system can be tested with the help of MATLAB software using Simulink. Keywords— Maximum Power Point Trackers (MPPT), BUCK/BOOST converter, Bi-directional inverter.
Queue reorganization for subscription congestion avoidance in publish/subscribe systems

Content-based publish/subscribe systems allow subscribers to specify interests based on event contents, rather than pre-assigned event topics. Since most of existing publish/subscribe systems use FIFO (First In First Out) as its queue management mechanism, it may face network congestion coming from suddenly burst of huge amount of subscription messages as well as event notifications. To promote the ability to handle congestion challenge, we present a new queue management mechanism called queue reorganization algorithm. By taking advantage of similarities among concurrent subscriptions, queue reorganization algorithm can make covering subscriptions as proxies and remove unnecessary subscriptions at each broker, which in turn greatly reduces pressure from congested input queue. Detailed evaluations under various workloads show significant benefits of the optimizations in terms of input queue size and message routing cost.
Draft Genome Sequence of Algoriphagus sp. Strain NH1, a Multidrug-Resistant Bacterium Isolated from Coastal Sediments of the Northern Yellow Sea in China

ABSTRACT Algoriphagus sp. NH1 is a multidrug-resistant bacterium isolated from coastal sediments of the northern Yellow Sea in China. Here, we report the draft genome sequence of NH1, with a size of 6,131,579 bp, average G+C content of 42.68%, and 5,746 predicted protein-coding sequences.
Pragmatics and word meaning

In this paper, we explore the interaction between lexical semantics and pragmatics. We argue that linguistic processing is informationally encapsulated and utilizes relatively simple ‘taxonomic’ lexical semantic knowledge. On this basis, defeasible lexical generalisations deliver defeasible parts of logical form. In contrast, pragmatic inference is open-ended and involves arbitrary real-world knowledge. Two axioms specify when pragmatic defaults override lexical ones. We demonstrate that modelling this interaction allows us to achieve a more refined interpretation of words in a discourse context than either the lexicon or pragmatics could do on their own.
Analysis on Intrusion Detection by Machine Learning Techniques: A Review

There are many risks of network attacks under the Internet environment, internet security is a vital issue and therefore, the intrusion detection is one major research problem for business and personal networks to resist external attacks. The goal of Intrusion detection systems (IDSs) is to provide a wall of defense to confront the attacks of computer systems on Internet where the conventional firewall do not succeeds. In this paper, comparison of most commonly used machine learning techniques based on genetic algorithm, support vector machines, artificial neural networks, etc. in intrusion detection domain, has been made. A comparative analysis of these techniques to detect intrusions in host and networks has also been made.
Retrieval Performance for USIM's Quranic Search Engine

The Quran covers every field of life namely medical, political, social, economic, and others. The extraction of quranic knowledge is a challenging task, as the Quran is rich in its linguistic and multi-layered meanings, difficult if done without the use of other resources such as the Hadith and Tafsir by Muslim Scholars. Several Quranic ontologies have been developed, however, most of these only focus on certain domains and language, rather than the content of the Quran. In many cases, the searching cannot retrieve the relevant fields. Discovering the fields of a keyword searched in the Quran can become a guidance to enhance knowledge in a particular domain. In this paper, we propose that the keyword searched in the Quranic ontology can be applied for extracting the relevant fields. For this purpose, exploratory search has been done. The sample domain ontology based on the medical and economic fields mentioned in the Quran has been developed in TopBraid Composer. Queries have been run to depict the proper role of ontology. Then, certain recommendation for the proposed Quranic ontology attaining semantic search from all domains and the result by searching from verse to domain, or domain to verse, has been proposed.
Enhancing the control and efficiency of the covering process [logic verification]

Coverage directed test generation (CDG) is a technique for providing feedback from the coverage domain back to a generator that produces new stimuli to the tested design. In this paper, we describe two algorithms that act in a CDG framework. The first algorithm controls the coverage events distribution using a "water-filling" approach. The second algorithm improves the efficiency of the covering process using clustering techniques.
Extreme compass and Dynamic Multi-Armed Bandits for Adaptive Operator Selection

The goal of Adaptive Operator Selection is the on-line control of the choice of variation operators within Evolutionary Algorithms. The control process is based on two main components, the credit assignment, that defines the reward that will be used to evaluate the quality of an operator after it has been applied, and the operator selection mechanism, that selects one operator based on some operators qualities. Two previously developed Adaptive Operator Selection methods are combined here: Compass evaluates the performance of operators by considering not only the fitness improvements from parent to offspring, but also the way they modify the diversity of the population, and their execution time; Dynamic Multi-Armed Bandit proposes a selection strategy based on the well-known UCB algorithm, achieving a compromise between exploitation and exploration, while nevertheless quickly adapting to changes. Tests with the proposed method, called ExCoDyMAB, are carried out using several hard instances of the Satisfiability problem (SAT). Results show the good synergetic effect of combining both approaches.
FPGA-implementation of Time-Multiplexed Multiple Constant Multiplication based on carry-save arithmetic

This paper proposes a method to implement time-multiplexed multiple constant multiplication (T-MMCM) based on carry-save adders on FPGA devices. Some basic cells have been defined. These cells are efficiently mapped on the FPGA devices and allow the designer to built T-MMCM circuits based on a tree topology. The performance of the proposed method has been validated by means of two designs: an n-point FFT butterfly with n=64, 128 and 256, and a 2-D DCT. Both designs have been implemented on a Virtex-5 device. The results show that the proposed method improves the throughput (up to 50%) and reduces the area in many cases compared to the implementation based on carry-propagate adders.
“We Have Closed Our Eyes and Sealed Our Lips”: Black Women’s Accounts of Discussing Suicide within the Black Community

ABSTRACT Conversing about suicide with an at-risk individual can be enough to save a life. Given the rise of suicidal behavior among African American subgroups (i.e., youth and male), advocates are urging blacks to have candid conversations about the issue. The current study highlights black women’s experiences discussing suicide. Findings suggest that widespread beliefs that suicide is an insignificant issue among blacks make conversing about suicide especially challenging. These findings reveal problematic implications for African Americans contemplating suicide in their communities. Suicide may be a phenomenon for which communal support is less prevalent.
Predicting SINR conditions in mobile MIMO-OFDM systems by interpolation techniques

Channel adaptive transmission in multi-user MIMO systems is seen as a promising concept to achieve high spectral efficiencies in future radio networks: Based on feedback on actual channel conditions, the base station allocates transmission resources to the user terminals where they can support high data rates. However, due to the delay between evaluation of the channels at the terminals and application of the resource allocation decision, the concept operates conveniently only under quasi-static channel conditions. In case user terminals are moving, the channel may vary and thus the adaptive concept may suffer strong performance degradations. For a channel-adaptive transmission concept based on evaluation of SINR conditions, we propose a solution to predict future SINR conditions based on channel interpolation techniques. For a limited prediction interval depending on the receive antenna spacing, the technique significantly diminishes potential SINR losses.
Everyone's a Critic: Memory Models and Uses for an Artificial Turing Judge

T he Turing test was originally conceived by Alan Turing [20] to determine if a machine had achieved human-level intelligence. Although no longer taken as a comprehensive measure of human intelligence, passing the Turing test remains an interesting challenge as evidenced by the still unclaimed Loebner prize[7], a high profile prize for the first AI to pass a Turing style test. In this paper, we sketch the development of an artificial “Turing judge” capable of critically evaluating the likelihood that a stream of discourse was generated by a human or a computer. The knowledge our judge uses to make the assessment comes from a model of human lexical semantic memory known as latent semantic analysis[9]. We provide empirical evidence that our implemented judge is capable of distinguishing between human and computer generated language from the Loebner Turing test competition with a degree of success similar to human judges.
Matching Configurator Attributes to Business Strategy

Product configurators are information system tools that allow automation of order taking process for customized products. They offer important enablers for attaining the efficiencies of mass customization and managing the sales interface for a broad product range. Previous research on the relationship between configurator characteristics and context is fragmented. There has been little focus on understanding how configurator systems appropriate to the application can be designed and selected. This paper examines empirical evidence of configurators and provides a comprehensive analysis of available configurators according to their attributes. It describes the development of a framework for matching configurator attributes to business strategy. The link between different types of customizable attributes and configurator functionality is analysed. Selecting configurator types for different operational modes for Mass Customization is discussed. Directions for further work are also noted.
Vortex Swarm Path Planning Algorithm

This paper presents an algorithm for trajectory planing using potential fields and swarms with vortex behavior. This algorithm is called Vortex Swarm Path Planning Algorithm (VSPP). There are several methods for trajectory planning in robotics, the most popular is the one based on artificial potential fields. However this method has the disadvantage of local minima which can make the robot fail when reaching the destination point. The proposed algorithm here presented employs a model of active Brownian particles with vortex behavior that allows the trajectory planning evading local minima.
Regulation of Caenorhabditis elegans Male Mate Searching Behavior by the Nuclear Receptor DAF-12

Coordination of animal behavior with reproductive status is often achieved through elaboration of hormones by the gonad. In the nematode Caenorhabditis elegans, adult males explore their environment to locate mates. Mate searching is regulated by presence of mates, nutritional status, and a signal from the gonad. Here we show that the gonadal signal acts via the nuclear receptor DAF-12, a protein known to regulate several C. elegans life-history traits. DAF-12 has both activational and organizational functions to stimulate exploratory behavior and acts downstream of the gonadal signal, outside of the gonad. DAF-12 acts upstream of sensory input from mating partners and physiological signals indicating nutritional status. Mate searching was rescued in germ-line ablated animals, but not if both germ line and somatic gonad were ablated, by a precursor of the DAF-12 ligand, dafachronic acid (DA). The results are interpreted to suggest that the germ line produces a DA precursor that is converted to DA outside of the germ line, possibly in the somatic gonad. As it does in other pathways in which it functions, in regulation of male mate searching behavior DAF-12 acts at a choice point between alternatives favoring reproduction (mate searching) vs. survival (remaining on food).
Political myth as a legitimation strategy

Golden age myths as an answer to political crises are a recurrent phenomenon. This article demonstrates how the idea of a past golden age as the answer to a crisis of society was employed in the discourses of the Third Way: At the turn of the 20th century, the Social Democrats (SPD) in Germany and New Labour in Britain employed a golden age myth to define their politics. Analysing a corpus of texts from the Labour Party and the SPD between 1990 and 2005, this article demonstrates how global ideological trends are locally legitimized differently through the use of local political myths. The major contribution to the field of political discourse analysis lies in the discussion of mythopoesis as a legitimatory strategy, as well as in the analysis of the local adaptation of the golden age myth, which draws on Laclau’s discourse theory and its idea of empty signifiers.
A new approach to computing two-dimensional manifolds

We propose an approach to computing two-dimensional unstable and stable manifolds of three-dimensional vector fields. The main idea is to estimate normal direction on each point around the boundary of current loop of manifold and normalize the normal growth rate during a settled time step to counter the disequilibrium in different directions. In order to enhance the reliability of our approach, linear and nonlinear conditions are considered. It is necessary to state that the time step should be appropriately small to meet the adjacent intervals of points on the boundary of manifold. As example we compute the two-dimensional stable manifold of the origin in Lorenz system. Both successes and shortcomings of our method are presented.
Understanding linked open data through keyword searching: the KEYRY approach

We introduce KEYRY, a tool for translating keyword queries over structured data sources into queries formulated in their native query language. Since it is not based on analysis of the data source contents, KEYRY finds application in scenarios where sources hold complex and huge schemas, apt to frequent changes, such as sources belonging to the linked open data cloud. KEYRY is based on a probabilistic approach that provides the top-k results that better approximate the intended meaning of the user query.
Detection, Modeling, and Classification of Moldings for Automated Reverse Engineering of Buildings from 3D Data

Laser scanner data is increasingly being used for the detailed reverse engineering of buildings. This process is currently primarily manual, but recent research has shown that basic structures, such as walls, ceilings, floors, doorways, and windows, can be detected and modeled automatically. Building on this previous research, we focus on the modeling of those linear moldings that typically surround doorways, windows, and divide ceilings from walls and walls from floors. These structures may be secondary and merely ornamental, but many projects nevertheless require that they be modeled. Moldings can be difficult to model manually owing to missing data caused by occlusions or to the ambiguity caused by low data density. Our molding modeling approach consists of two steps: 1) estimating the path of the molding; and 2) estimating the shape of the molding profile. In the first step, we iteratively update the molding’s line of extrusion by optimizing the similarity of cross-sections sampled along the path, thereby compensating for imperfections in the initial orientation estimate. In the second step, a unified profile is extracted using data from the entire length of the molding, which allows for partial missing data from occlusions. The profile is then characterized by a specific shape descriptor. Finally, a KNN algorithm classifies the molding into a database which has been constructed with profiles originating from various molding manufacturers. We demonstrate the method using real 3D laser scanner data of various types of moldings, both simple and complex.
PLUS: a distributed shared-memory system

PLUS is a multiprocessor architecture tailored to the fast execution of a single multithreaded process; its goal is to accelerate the execution of CPU-bound applications. PLUS supports shared memory and efficient synchronization. Memory access latency is reduced by nondemand replication of pages with hardware-supported coherence between replicated pages. The architecture has been simulated in detail, and some of the key measurements that have been used to substantiate the architectural decisions are presented. The current implementation of PLUS is also described. <<ETX>>
Author ' s personal copy Automatic Labeling of the Human Cerebral Cortex

Glossary 'fsaverage' Subject FreeSurfer subject (Figure 1b and 1c) obtained by averaging 40 subjects. This average subject forms the basis of the FreeSurfer surface coordinate system (Fischl, 2012). Graphical Models The different algorithms in this article can be summarized using graphical models. Graphical models provide a general framework for representing complex probabilistic models with explicit (conditional) independence assumptions. See Figure 2 and 'Summary' section for more details. Markov Random Field Markov Random Fields (MRFs) provides a principal approach to impose a prior on the spatial configuration of labels. One common prior is to favor adjacent spatial locations to have the same labels. See 'Spatially Dependent Priors: Markov Random Fields' section for more details. Mixture Models Registration-based labeling assumes the availability of pre-existing labels. By contrast, mixture modeling only requires that each label generate its own unique image features. Given observed image features, there are algorithms (e.g., Expectation-Maximization) that simultaneously estimate the labels and the probabilistic distribution of image features for each label. See 'Mixture Models' section for more details. MNI152 Template The International Consortium on Brain Mapping (ICBM) average brain obtained by aligning and averaging 152 subjects (Fonov et al., 2011). Registration-based Labeling Registration is the process of establishing spatial correspondences between images. The resulting deformation can be used to transfer pre-existing labels from an (single-subject or probabilistic) atlas to the target brain. See 'Registration-based Labeling' section for more details. The human cerebral cortex is a highly folded 2D sheet of neural tissue that possesses a mosaic of functionally distinct areas oriented parallel to its surface (Figure 1). Information processing proceeds via the transformation of neural signals across these areas (Felleman & Van Essen, 1991; Ungerleider & Desimone, 1986). Accurate labeling of areal locations is therefore an important problem in systems neuroscience. There are four main criteria for distinguishing cortical areas (Felleman & Van Essen, 1991; Kaas, 1987): function, architectonics, connectivity, and topography. Each of these criteria can be interrogated in the human cerebral cortex using a broad range of techniques (Figure 1). Because (1) cortical folds are visible to the naked eye and in anatomical Magnetic Resonance Imaging (MRI) and (2) some cortical folds are indicative of certain underlying cortical areas 2010b), cortical folds are often used as macroanatomical landmarks for comparison of results across brain imaging studies. Consequently, methods that can accurately label cor-tical folds across different subjects are important for studying the human brain (Figure 1). The …
Converging time synchronization algorithm for highly dynamic vehicular ad hoc networks (VANETs)

Vehicular ad hoc networks (VANETs), similar to other distributed systems, often require a scalable time synchronization service enabling data consistency and coordination. In this paper, we propose a new time synchronization protocol for VANETs, which provides excellent scalability, accuracy and robustness for high mobility traffic scenarios. The new protocol, Converging Time Synchronization (CTS), is simulated using a reliable simulation platform. The results are analyzed and compared with the well-known Reference Broadcast Synchronization (RBS) protocol. The results show that CTS has better performance than RBS in high traffic flow scenarios.
Incentive Based Ranking Mechanisms

We consider ranking and recommendation systems based on user feedback. We make a case for sharing the revenue generated by such systems with users as incentive to provide useful feedback. Our main contribution are mechanisms for ranking/recommendation which gives incentive for the users to provide useful feedback and is resistant to selfish/malicious behavior (click spam). The mechanisms are designed to give higher incentives for discovering high quality entities rather than for merely providing additional positive feedback for already established entities. A page whose rating/ranking is at variance with its real quality represents an arbitrage opportunity. The mechanisms are simple enough to be used with existing technology in ranking and recommendation systems, requiring little or no extra effort by the users.
The vision of bedfast nursing home residents of their quality of life and the contribution of technological innovations in and around the bed

Purpose Over 8 per cent of the Dutch nursing home population is bedfast, and this number is slowly increasing. The quality of life (QoL) of this population is lower than that of residents who are still mobile. Little research has been conducted on how to improve the QoL of this bedfast population, particularly through making technological adjustments to the bed and the direct surroundings. The purpose of this paper is to gain insight into the QoL of bedfast residents and how to improve this through technology. Design/methodology/approach A mixed-method multi-case study with thematic analysis was conducted in two nursing homes with seven participants based on semi-structured interviews and Short Form-12 questionnaire. Findings The major causes of the experienced low QoL were the limited opportunities for engaging in social contacts with others, and coping with the dependency on other people and having limited control. Participants suggested improvements of QoL through the application of modern communication technologies to engage in social contacts and to control the bed itself and environment around the bed. Practical implications The results may help improve the design of the bed and the direct environment in order to improve the QoL of bedfast nursing home residents. Originality/value The QoL of bedfast nursing home residents has not been studied before in relation to the bed itself and technological solutions that may help improve the QoL and level of control.