Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance analysis of channel coding in satellite communication based on VSAT Network and MC-CDMA scheme

Satellites are an essential part of our daily life, and they have a very large usage ranging from Search and Rescue Operations to Environmental Monitoring. The widest use of satellites is, however, in communication systems. Satellites can cover vast areas on the world; therefore, they are the nodes where all links pass through in a communications network. Many users can access such a network simultaneously while they are widely separated geographically. The purpose of this paper is to model and analyze a geostationary satellite communication system with VSATs networks in the uplink case, using Multicarrier CDMA system (MC-CDMA is a combination of multicarrier modulation scheme and CDMA concepts) and channel coding mechanisms “Turbo code and Convolutional code”. The envisaged system is examined in Ku band and over AWGN channel. The simulation results are obtained for each different case. The performance of the system is given in terms of Bit Error Rate (BER) and Signal to Noise Ratio (SNR). In this study the proposed system coded with Turbo code can achieve better error rate performance compared to coded VSAT MC-CDMA system with convolutional code. Keywords—VSAT Network, Turbo code, Convolutional code, MC-CDMA, Ku band, Satellite communication, Uplink.
Integrating case-based learning and cognitive biases for machine learning of natural language

This paper shows that psychological constraints on human information processing can be used effectively to guide feature set selection for case-based learning of linguistic knowledge. Given as input a baseline case representation for a natural language learning task, our algorithm selects the relevant cognitive biases for the task and then automatically modifies the representation in response to those biases by changing, deleting, and weighting features appropriately. We apply the cognitive bias approach to feature set selection to four natural language learning problems and show that performance of the casebased learning algorithm improves significantly when relevant cognitive biases are incorporated into the baseline instance representation. We argue that the cognitive bias approach offers new possibilities for case-based learning of natural language: it simplifies the process of instance representation design and, in theory, obviates the need for separate instance representations for each linguistic knowledge acquisition task. More importantly, the approach offers a mechanism for explicitly combining the frequency information available from corpus-based techniques with cognitively-based preferences employed in traditional linguistic and knowledge-based approaches to natural language processing.
Analysis of Adjacent Channel Power Ratio Performance in Two-Point Modulated Systems

In this study, the degradation of adjacent channel power ratio (ACPR) performance in personal mobile radio (PMR) systems, which use two-point modulation in their phase locked loops (PLLs) is investigated. First an expression for the widths of charge pump pulses, which arise due to imbalanced modulation are found by also taking into account the low pass filtering of the loop. Then the frequency domain representation of charge pump pulses is obtained by Fourier transform. Using this representation and the loop filter response, the spurious signals in the spectrum of the voltage controlled oscillator (VCO) is calculated by using narrowband FM assumption. Evaluating the power of the spectrum within the bandwidth of the adjacent channel, ACPR performance is obtained. A practical setup is constructed to validate the proposed method. Coherence is observed between the measurements of the test setup and expressions obtained in this study.
Drosophila Kelch Is an Oligomeric Ring Canal Actin Organizer

Drosophila kelch has four protein domains, two of which are found in kelch-family proteins and in numerous nonkelch proteins. In Drosophila, kelch is required to maintain ring canal organization during oogenesis. We have performed a structure–function analysis to study the function of Drosophila kelch. The amino-terminal region (NTR) regulates the timing of kelch localization to the ring canals. Without the NTR, the protein localizes precociously and destabilizes the ring canals and the germ cell membranes, leading to dominant sterility. The amino half of the protein including the BTB domain mediates dimerization. Oligomerization through the amino half of kelch might allow cross-linking of ring canal actin filaments, organizing the inner rim cytoskeleton. The kelch repeat domain is necessary and sufficient for ring canal localization and likely mediates an additional interaction, possibly with actin.
Dynamical and complex behaviors in human-machine co-adaptive systems

Abstract Human and computer subsystems should be structured and designed to work in mutually cooperating ways guaranteeing a user's usability. For this purpose, progressive system redesigns are needed with respect to human computer interactions to increase system reliability and transparency by increasing human-system interactions and especially a human user's proactive participation, rather than by eliminating the human out of the loop. Such a socially-centered view on the human-machine system design regards a human and an automated agent as equivalent partners, and through their mixed-initiative interactions some novel relations of mutual dependency and reciprocity would emerge as well as flexible changes of role-taking are expected. To realize such a kind of new style of human-machine relationships, we develop a new idea called co-adaptive design principle, which means that both a human user and a machine should be able to adapt to the other through experiencing the interactions occurring between them. We applied this idea to an artifacts design of a robot tele-operation systems.
Towards Optimal Broadcasting Policies for HARQ based on Fountain Codes in Underwater Networks

This paper explores hybrid ARQ policies based on fountain codes for the transmission of multicast messages in underwater channels. These rateless codes are considered because of two nice properties, namely, they are computationally lightweight and do not require to know the channel erasure probabilities at the receivers prior to transmission. In this paper, these codes are used together with a Stop and Wait ARQ to enhance the performance of broadcast communications. First, we present a dynamic programming model for the characterization of optimal broadcasting policies. The derived broadcasting rules are then compared against plain ARQ schemes via Monte-Carlo simulation. Our results show that digital fountain codes are a promising technique for the transmission over underwater channels as their performance, in terms of delay, reliability and energy efficiency, clearly dominates that of plain ARQ solutions. This paper is a preliminary study on the topic and encourages us towards the design of practical HARQ protocols for the underwater medium.
DAMAGE REDUCTION BY CULTURE BASED METHOD SUPPORTED BY SPATIAL TEMPORAL GIS-COLLABORATIVE RESEARCH WITH DUZCE MUNICIPALITY TURKEY

Spatial temporal GIS named DiMSIS (Disaster Management Spatial Information System) have been developed mainly focused on applying local government applications after the great HANSHIN earthquake of 1995 in Japan. This spatial temporal GIS which has been enhanced to have multi language support would be common core system to support Risk Adaptive Regional Management Information System (RARMIS) concept proposed after the experiences of emergency response of the HANSHIN Earthquake. Data structure to describe spatial temporal data is also enhanced to the one named KIWI+ (related to the data structure of Japanese Industry Standard for car navigation system). Disaster information and daily regional information can be described uniformly by connecting to spatial and temporal position which is universal. Emergency tasks of local government are composed of elements of daily tasks which are rational for each organization. Quickbird image data is used to detect changes and also integrate map database developed separately. DiMSIS with Quickbird data is also applied to Bam earthquake (Dec. 2003) for the case study. In this paper, we report this case study about the implementation process to the local government using spatial temporal GIS and satellite image data.
Semi-automatic Filtering of Translation Errors in Triangle Corpus

We are developing a multilingual machine translation system to provide foreign tourists with a multilingual speech translation service in the Winter Olympic Games that will be held in Korea in 2018. For a knowledge learning to make the multilingual expansibility possible, we needed large bilingual corpus. In Korea there were a lot of Korean-English bilingual corpus, but Korean-French bilingual corpus and Korean-Spanish bilingual corpus lacked absolutely. Korean-English-French and KoreanEnglish-Spanish triangle corpus were constructed by crowdsourcing translation using the existing large Korean-English corpus. But we found a lot of translation errors from the triangle corpora. This paper aims at filtering of translation errors in large triangle corpus constructed by crowdsourcing translation to reduce the translation loss of triangle corpus with English as a pivot language. Experiment shows that our method improves +0.34 BLEU points over the baseline system.
Improved foreground-background segmentation using Dempster-Shafer fusion

Popular foreground-background segmentation algorithms are based of background subtraction. In complex indoor environments, if an object in motion initially remains stationary for a certain period, it can be absorbed into the background, becoming invisible to the system. Aiming at solving this problem, this paper presents a flexible and robust foreground-background segmentation algorithm based on accurate moving objects classification. Our algorithm combines low level and high level information, i.e. the data belonging to single pixels and the result of accurate object classification respectively, to improve the background management. Accurate object classification is obtained by combining classification evidence from different object recognisers using the Dempster-Shafer rule. The proposed algorithm has been tested with a large amount of acquired images; moreover, real test cases are reported. Reported experimental results include object classification accuracies obtained with a proposed Basic Belief Assignments and measurements of the quality of the background image such as Recall-Precision and F-measure computed with different background management algorithms. The experimental results show the superiority of the proposed segmentation algorithm over popular algorithms.
Complex event processing over uncertain events: Techniques, challenges, and future directions

In the recent years, there is a massive surge in real-time data owing to the growing number of distributed software applications that continuously generates a large volume of data streams. These applications utilize new hardware technologies and data collection methods that inherently produce uncertain data. The Complex event processing (CEP) is a crucial software technology that manages highly dynamic event streams in a timely manner and determines the event patterns of interest. The CEP processes the massive data streams from different applications that depend on the reliability of data to produce accurate results. The business intelligence requires high-level of knowledge extracted from continuous streams. Ignoring uncertainty in event processing significantly degrades the performance and accuracy. Thus, efficient processing of uncertain data is vital to improving the efficiency and the accuracy of the CEP results for better decision making in business. This survey discusses the basics of uncertainty, explores models and query processing methods to deal with uncertainty. The primary contribution of this work is the survey of CEP regarding event query language and event query processing involved in identifying the complex event patterns over uncertain events. The challenges and the future directions for handling uncertain events in CEP are discussed in detail.
The Removal of EOG Artifacts From EEG Signals Using Independent Component Analysis and Multivariate Empirical Mode Decomposition

The recorded electroencephalography (EEG) signals are usually contaminated by electrooculography (EOG) artifacts. In this paper, by using independent component analysis (ICA) and multivariate empirical mode decomposition (MEMD), the ICA-based MEMD method was proposed to remove EOG artifacts (EOAs) from multichannel EEG signals. First, the EEG signals were decomposed by the MEMD into multiple multivariate intrinsic mode functions (MIMFs). The EOG-related components were then extracted by reconstructing the MIMFs corresponding to EOAs. After performing the ICA of EOG-related signals, the EOG-linked independent components were distinguished and rejected. Finally, the clean EEG signals were reconstructed by implementing the inverse transform of ICA and MEMD. The results of simulated and real data suggested that the proposed method could successfully eliminate EOAs from EEG signals and preserve useful EEG information with little loss. By comparing with other existing techniques, the proposed method achieved much improvement in terms of the increase of signal-to-noise and the decrease of mean square error after removing EOAs.
Setting up simulation experiments with SESSL

Setting up simulation experiments is hard, even more so as simulation systems usually offer only custom interfaces for this task (e.g., a graphical user interface or a programming interface). This steepens the learning curve for experimenters, who have to get accustomed with the idiosyncrasy of each simulation system they want to experiment with. It also makes cross-validation experiments between simulation systems cumbersome, since the same experiment needs to be set up for each system from scratch. In the following, we give a brief overview of SESSL, a domain-specific language for simulation experiments. SESSL addresses these issues by providing a common interface to set up simulation experiments in a more declarative manner, i.e., specifying what to do, not how to do it. Therefore, SESSL can also be used for documenting and reproducing simulation experiments.
A Near-Threshold Energy-Efficient ASK Transmitter for Biomedical Implants

A near-threshold amplitude shift keying (NT-ASK) transmitter for biomedical implants is presented in this paper. The ASK transmitter supports a 100-Mb/s baseband data rate with a carrier frequency of 2.4 GHz. The design incorporates an LC voltage-controlled oscillator (VCO), ASK modulator, and a class-E power amplifier. The carrier is generated by a low phase noise LC-VCO, and then directly modulated by an NT-ASK modulator. The modulated signal is amplified by a class-E power amplifier and transmitted through an inductive coil. The transmitter achieves a total power consumption of 1.65 mW at 0.5 V, an energy efficiency of 16.5 pJ/b, and a phase noise of -115.7 dBc/Hz at 1-MHz offset at a center frequency of 2.4 GHz. The output power level of the transmitter is -14 dBm. The ASK transmitter is implemented in a standard 0.13-μm CMOS process with a core area of 0.63 mm2.
Mining Software Repositories to Study Co-Evolution of Production & Test Code

Engineering software systems is a multidisciplinary activity, whereby a number of artifacts must be created - and maintained - synchronously. In this paper we investigate whether production code and the accompanying tests co- evolve by exploring a project's versioning system, code coverage reports and size-metrics. Our main aim for studying this co-evolution is to create awareness with developers and managers alike about the testing process that is followed. We explore the possibilities of our technique through two open source case studies and observe a number of different co-evolution scenarios. We evaluate our results both with the help of log-messages and the original developers of the software system.
Performance limits of coded diversity methods for transmitter antenna arrays

Several aspects of the design and optimization of coded multiple-antenna transmission diversity methods for slowly time-varying channels are explored from an information-theoretic perspective. Both optimized vector-coded systems, which can achieve the maximum possible performance, and suboptimal scalar-coded systems, which reduce complexity by exploiting suitably designed linear precoding, are investigated. The achievable rates and associated outage characteristics of these spatial diversity schemes are evaluated and compared, both for the case when temporal diversity is being jointly exploited and for the case when it is not. Complexity and implementation issues more generally are also discussed.
Preliminary validation of the Dark Triad questionnaires in a spanish juvenile justice sample

The interest in the Dark Triad (DT) constellation -machiavellianism (Mach), psychopathy (Psy), and narcissism (Narc)has significantly increased during last years. The Dirty Dozen Scale (DD) [1] and the Short Dark Triad Questionnaire (SD3) [2] are promising short measures of these constructs that have been adapted and validated to different languages and cultures. More recently, it has been proposed that sadism could be a fourth dark personality trait; however, the evidence up to now is inconclusive and more data is needed. The Varieties of Sadistic Tendencies Scale (VAST), was specifically developed for the assessment of this construct [3]. The study of “dark” personality traits could be useful to predict aggressive and antisocial behaviour in different kinds of populations and contexts.
SiAM - Situation-Adaptive Multimodal Interaction for Innovative Mobility Concepts of the Future

What does situation-adaptive technology mean for car drivers and how can it improve their lives? Why is multimodal interaction in the cockpit a critical ingredient? This contribution summarizes several important technological results of the three-year research project SiAM, which investigated these questions. Motivated by the story of an urban commuter, we illustrate three use cases for situation adaptivity: multimodal control of car functions, cognitive load aware interaction with the environment, and a persuasive intermodal travel assistant.
Adapting goal oriented approaches in requirement engineering of Inter-Organizational Information System

A collaborative information system is an Inter-Organizational Information System (IOIS) that can work beyond the typical borders of organizations. When partners want to work together, they already know the goal of the project through collaborative information system. Therefore, a collaborative network allows a goal to be met that cannot be completed by one partner. Due to the complexity of this type of systems, the requirements analysis stage is crucial; check the adequacy between expected objectives with the needs expressed by the all users of the several organizations in collaboration and the satisfaction of various goals generated by such collaboration. The aim of this research is to propose the most appropriate method by adapting goal oriented analysis. We indicate the added contributions and introduce efficiency by the use of goal oriented analysis approach in such environments.
Mixed-Initiative Cyber Security: Putting humans in the right loop

In recent years, organizations and their computer infrastructures have grown intertwined in complex relationships through mergers, acquisitions, reorganizations, and cooperative service delivery. Defensive actions and policy changes by one organization may have far-reaching negative consequences on its partner organizations. Human-only or machine-only approaches are insufficient. The former are slow but highly adaptable, while the latter are fast but highly specialized. In either case, humans retain the ultimate responsibility for the actions of their automated systems. Deploying automated defenses does not absolve humans of their inherent responsibility. We believe the solution lies in mixed-initiative defense unifying the complementary qualities of both human- and machine-based approaches. We describe the Cooperative Infrastructure Defense (CID), a new cyber-defense paradigm employing complex-adaptive swarm intelligence, logical rational agents, and human insight to enable collaborative cyber defense among cooperating organizations in an infrastructure setting. CID takes a mixed-initiative approach to infrastructure defense where teams of humans and software agents defend cooperating organizations in tandem, sharing insights and solutions without violating proprietary boundaries. CID will help create security policy via dialogue between humans and agents, foster a collaborative problem-solving environment, and increase human situational awareness and influence through visualization and shared control. CID will provide a foundation for more » building trust between humans and agents within and between organizations. « less
Influence of Self-Efficacy as a Mediator on Time Management and Students’ Performance Relationship in Malaysian Online Distance Learning Institutions

The main purpose of this study is to develop a mediating effect understanding of self-efficacy on time management and students’ performance relationship in Malaysian online distance learning institutions. A model was developed and later tested by adopting the partial Least Square (PLS) procedure on data collected from a survey that yielded 210 usable questionnaires. The findings showed that time management enhanced self-efficacy in Malaysian online distance learning institutions. It was also revealed that self-efficacy partially mediates the relationship between time management and students’ performance. In future, more research needs to be carried out to explore the role of self-efficacy in Malaysian online distance learning institutions. It is important to do the study utilizing experimental design by capturing longitudinal data in Malaysian online distance learning institutions using robust measures. The findings imply that the relationship between self-efficacy and attrition rate may reside in self-efficacy’s influence on students’ performance, and that self-efficacy plays a crucial function within the Malaysian online distance learning institutions. This study uses Smartpls 2.0 and SPSS 18.0 to test the hypothesis and analyze respondents’ profile respectively.
An intelligent system for detecting faults in photovoltaic fields

In this work, an intelligent system for automatic detection of fault in PV fields is proposed. This system is based on a Takagi-Sugeno-Kahn Fuzzy Rule-Based System (TSK-FRBS), which provides an estimation of the instant power production of the PV field in normal functioning, i.e, when no faults occur. Then, the estimated power is compared with the real power and an alarm signal is generated if the difference between powers overcomes a threshold. The TSK-FRBS has been trained using data collected from a PV plant simulator, during normal functioning. Preliminary tests were carried out in a simulated framework, by reproducing both normal and fault conditions. Results show that the system can recognize more than 90% of fault conditions, even when noisy data are introduced.