Miracle-dz/UniFAR-FTUs huggingface dataset:
BEHAVIOURAL MODELLING UNDER OPTIMAL TRAJECTORY CONTROL OF SERIES RESONANT DC / DC CONVERTERS

The paper presents behavioural modelling of the control system of series resonant DC/DC converters operated above the resonant frequency under “optimal trajectory control” technique. This method predicts the fastest response possible with minimum energy surge in the resonant tank. The steady-state equations described the converter operation above the resonant frequency as a function of the diode trajectory radius and corresponding normalized load characteristics are proposed. They allow evaluating the behaviour of the considered converter when the load is changed strongly during the operation process. Simulation and experimental results are given.
Title Eigenvalue Problem of Anti-Wick ( Toeplitz ) Operators in Bargmann-Fock Space and Applications to Daubechies Operators ( Wavelet analysis and signal processing )

In this paper we will consider algebraic background of Gabor analysis and eingenvalue problem of anti‐ Wick (Toeplitz) operators in Bargmann‐ Fock space. We will clarify the relationship between anti‐ Wick (Toeplitz) operators and Daubechie (localization) operators. We apply our results to eingenvalue problem of Daubechie operators.
FISCAL POLICY INTERACTIONS AND IMBALANCES IN A MONETARY UNION

Are there important economic consequences from conducting fiscal policy at the national level within a monetary union? This paper investigates the consequences of strategic fiscal policy interactions in a two-country DSGE model of a monetary union with nominal rigidities and international financial frictions. I show that the fiscal policy makers in this framework face an incentive to set fiscal policy such as to switch the terms of trade in their favour. This incentive, the terms of trade externality, results in a Nash equilibrium where inflation differentials across countries and intra-union imbalances may be significantly larger than if the fiscal policy makers had cooperated. Indeed, the main results of the analysis is that strategic interactions between national fiscal policy makers can lead to excessive inflation differentials across countries as well as sub-optimally high current account imbalances within the monetary union. When this is the case, there are non-negligeable welfare losses associated with strategic national fiscal policy making in a monetary union.
Effect of Varieties and Sowing Dates on Forage Yield and its Components in Alfalfa (Medicago sativa L.)

This investigation was carried out to study the effect of temperature resulting from different sowing dates, varieties and their interaction on forage yield and its components of alfalfa. A set of seven varieties (Aswan, Balady, Dakhla, Ismailia-1, Nitrogen fixed, Genan, and Siwa) were sown on three sowing dates (20 of October, November and December) in randomized complete block design with three replicates in experimental farm of South Valley University during 2014/2015 and 2015/2016 seasons. Three cuts were taken after 80, 125 and 165 days from sowing. The results showed that the sowing dates and varieties had a significant effects on plant height, number of branches/plant, leaf/stem ratio, fresh and protein forage yields over the two seasons. Aswan population gave the tallest plant height, and highest forage yields over all sowing dates. Moreover, the tallest plant heightm highest number of branches/plant and seasonal fresh, dry and protein forage yields were obtained from the plants sown on 20 December over the two seasons. The sowing dates and varieties and their interactions were significant for plant height, number of branches/plant, and seasonal, fresh, dry and protein forage yields. Finally the stability analysis revealed that the average stability region involved Siwa, Balady, Dakhla and Nitrogen fixed populations for plant height and Genan and Ismailia populations for seasonal fresh forage yield. Moreover, all seven populations except Dakhla and Aswan populations were involved in stability region for seasonal protein forage yield.
Empirical Control Strategy for Learning Industrial Robot

Today’s industrial robot systems intensively include external sensors like cameras used for identification of objects in the working environment of industrial robot. Including cameras in the system of an industrial robot, the control problem of such learning industrial robot is set. Using empirical control strategy based on application of artificial neural networks system, the learning industrial robot can realize adaptive behaviour in the sense of flexible adjustment to changes in the working environment. Unlike natural systems which could learn on the basis of experience, artificial systems are thought to be unable to do so for a long time. However, the concept of empirical control realizes the ability of machine learning on the basis of experience. This paper aims to show that it is possible to realize the empirical control strategy for learning industrial robot using camera and system of artificial neural networks. Results obtained by the system of neural nets have shown that the robot can move the end-effector to the desired location of the object, even in the case where the location differs slightly from the learned patterns.
Pathfinding algorithms in graphs and applications

The aim of this work is to give a rigorous mathematical insight of the most popular pathfinding algorithms, focusing on A∗ and trying to understand how the heuristic it uses affects its correctness and performance. We complement this theoretical study of the algorithms with experimental results found by running two benchmarks of the algorithms using a simulator of the algorithms built for this project. 2010 Mathematics Subject Classification. 05C12, 05C38, 05C85, 68R10
Editorial for the Special ECIME Edition of EJISE – ECIME2014

COBIT, (Control Objectives for Information and Information related Technologies) as an IT governance framework is well-known in IS practitioners communities. It would impair the virtues of COBIT to present it only as an IT governance framework. COBIT analyses the complete IS function and offers descriptive and normative support to manage, govern and audit IT in organizations. Although the framework is well accepted in a broad range of IS communities, it is created by practitioners and therefore it holds only a minor amount of theoretical supported claims. Thus critic rises from the academic community. This work contains research focusing on the theoretical fundamentals of the ISACA framework, COBIT 5 released in 2012. We implemented a reverse engineering work and tried to elucidate as much as possible propositions from COBIT 5 as an empiricism. We followed a qualitative research method to develop inductively derived theoretical statements. However our approach differs from the original work on grounded theory by Glaser and Strauss (1967) since we started from a general idea where to begin and we made conceptual descriptions of the empirical statements. So our data was only restructured to reveal theoretical findings. We looked at three candidate theories: 1) Stakeholder Theory (SHT), 2) Principal Agent Theory (PAT), and 3) Technology Acceptance Model (TAM). These three theories are categorized and from each theory, several testable propositions were deduced. We considered the five COBIT 5 principles, five processes (APO13, BAI06, DSS05, MEA03 and EDM03) mainly situated in the area of IS security and four IT-related goals (IT01, IT07, IT10 and IT16). The choice of the processes and IT-related goals are based on an experienced knowledge of COBIT as well of the theories. We constructed a mapping table to find matching patterns. The mapping was done separately by several individuals to increase the internal validity. Our findings indicate that COBIT 5 holds theoretical supported claims. The lower theory types such as PAT and SHT contribute the most. The presence and contribution of a theory is significantly constituted by IT-related goals as compared to the processes. We also make some suggestions for further research. First of all, the work has to be extended to all COBIT 5 processes and IT-related goals. This effort is currently going on. Next we ponder the question what other theories could be considered as candidates for this theoretical reverse engineering labour? During our work we listed already some theories with good potential. Our used pattern matching process can also be refined by bringing in other assessment models. Finally an alternative and more theoretic framework could be designed by using design science research methods and starting with the most relevant IS theories. That could lead to a new IT artefact that eventually could be reconciled with COBIT 5.
Interactive comment on “ The influence of the vertical distribution of emissions on tropospheric chemistry ” by A . Pozzer et al

We did not describe any aircraft emissions in our model description section. However, we have certainly included this kind of emissions (see Jöckel et al., 2006) in the model simulation, and we did not change any emission heights for this emission type between simulation S1 and simulation F1. The aircraft emissions are based on Schmitt and Brunner (1997). Hence, no aircraft emissions were used from the EDGAR database.
DEMATEL method in ERP systems for TSL branch

Summary. The article introduces issues concerning the implementation of key performance indicators (KPIs) dedicated to the TSL (Transport-Shipping-Logistics) branch. The KPIs are used in different modules of the ERP (Enterprise resource planning) information systems, which support strategic decision making. Selected indicators have been used to create four perspectives of Balanced Scorecard in accordance with Balanced Scorecard methodology. Using the multi-factor method of DEMATEL (Decision Making Trial and Evaluation Laboratory) analysis, the evaluation of indicators and Balanced Scorecard’s perspectives has been performed. This article can be useful to persons interested in the implementation of modern solutions in ERP applications dedicated to the TSL branch. Presented article can be useful to persons from upper management of TSL companies who are interested in modern methods of supporting strategic management and for IT system developers who are considering expanding modules of ERP software solutions dedicated to TSL industry which support strategic management and decision making.
Implementation of a staggered trigger algorithm by velocity difference dealiasing rules

The staggered trigger technique consists of alternating between a long and a short Pulse Repetition Time (PRT) to mitigate the range-velocity ambiguity. Due to the two PRT, two different velocities can be estimated. The difference of these two velocities can be used to determine in which Nyquist interval is the real flow velocity. This method was originally proposed for Doppler weather radar where velocity folding factors are restricted to 2 times the conventional maximum velocity of the short PRT. In this work the staggered trigger method using the velocity difference for dealiasing purpose is further extended to a higher velocity folding factor. We show that emitting a 4-cycle ultrasound pulse this method can reach up to 5 times the conventional maximum velocity of the long PRT. The algorithm was tested using ultrasound simulation software Field II. The simulation consisted of a piston transducer emitting in a flow with a uniform velocity profile. The performance of the technique was also evaluated on several low SNR conditions.
Cascading of Compression Algorithm to Reduce Redundancy in FPGAs Configuration Bitstream-A Novel Technique

In recent times with increasing in capacity of FPGA, bitstream size of configuration file is increasing. This leads to need of more configuration memory. Also, reconfiguration time increases with increased in bitstream size. Redundant bitstream increases overheads in reconfiguration. Bitstream compression is technique to reduce redundancy in configuration bitstream. Various researchers have used existing and modified traditional lossless bitstream compression techniques. Existing studies in this field have focused on (i) small compression ratio with less decompression speed and (ii) more decompression speed compromising the compression ratio. We proposed an approach of cascading of bitstream compression algorithm to further reduce the bitstream. It is found that cascading of RLE with Arithmetic, LZW, Huffman and LZSS algorithm gives better compression ratio. Our approach of cascading of compression algorithm improves compression ration by an average of ≈ 23 %.
Do What I Mean, Not What I Say! Design Considerations for Supporting Intent and Context in Analytical Conversation

Natural language can be a useful modality for creating and interacting with visualizations but users often have unrealistic expectations about the intelligence of natural language systems. The gulf between user expectations and system capabilities may lead to a disappointing user experience. So — if we want to engineer a natural language system, what are the requirements around system intelligence? This work takes a retrospective look at how we answered this question in the design of Ask Data, a natural language interaction feature for Tableau. We examine two factors contributing to perceived system intelligence: the system's ability to understand the analytic intent behind an input utterance and the ability to interpret an utterance contextually (i.e. taking into account the current visualization state and recent actions). Our aim was to understand the ways in which a system would need to support these two aspects of intelligence to enable a positive user experience. We first describe a pre-design Wizard of Oz study that offered insight into this question and narrowed the space of designs under consideration. We then reflect on the impact of this study on system development, examining how design implications from the study played out in practice. Our work contributes insights for the design of natural language interaction in visual analytics as well as a reflection on the value of pre-design empirical studies in the development of visual analytic systems.
It’s Different When We’re Together: The Impact of Experiencing a Peak-Provoked Cigarette Craving State with a Smoking Friend

Cigarette craving predicts relapse to smoking, which remains the leading cause of preventable death in the United States. Understanding why individuals choose to smoke has important clinical implications and is a research priority. Ecological momentary assessment studies reveal that social factors, such as the presence of other people, affect the craving experience, yet laboratory smoking research has largely ignored these factors by testing participants in isolation. In this study, a shared reality framework aimed to broaden the set of responses related to craving, and in particular to evaluate social processes that may change when smokers experience craving while in the presence of a smoking friend compared to when smokers crave alone. Sixty pairs of smoking friends (n = 120) arrived together at the laboratory following a required a 5-hr of smoking abstinence. Participants then underwent an in vivo smoking cue-exposure craving induction either with their friend present or with the friend in the next room. Participants who were together with their smoking friend while craving experienced a greater sense of shared reality and felt closer to their friend than did those who were alone. Though social context did not influence their urge to smoke or craving-related affect, urge was associated with shared reality when participants were together, but not when they were alone. Further, for participants who were together, shared Duchenne smiles were associated with ratings of shared reality. Results highlight potential social motives for smoking (e.g., satisfying epistemic and relational goals), and highlight the need for increased laboratory research on smoking that includes a social context.
A Study on Intrusion Detection and Protection Techniques

Intrusion Detection Systems (IDS) plays a major role in computer security. In network environment IDS detect the activities that affect Confidentiality, Integrity and Availability on network data. There are two types of intruders External and Internal. External intruders are the outsiders from the network they are trying to attack the system with different techniques where as Internal Intruders are the authorized person to access the networks and they perform unauthorized or illegal activities. It is very difficult to detect the internal attacks. Most of the IDS and Firewalls detect the outsider attack only. Nowadays the numbers of cyber attacks and threats are increasing rapidly. Existing IDS are not efficient in detecting new threats and internal intrusions. Building efficient IDS for protecting information security system is a challenging task. The aim of this paper is to present a study on different techniques and algorithms used in IDS systems including insider attacks. The focus is on detection at System Call (SC) level using data mining and forensic techniques, genetic algorithms using the mechanism of natural selection and genetics and finally Fuzzy logic for an alert mechanism in IDS.
FUSION BASED VIDEO TEXT DETECTION APPROACH

Text extraction from pictures has forever been a challenge for the researchers since long. Lots of Techniques are developed and experimented for similar work. Text detection from the videos is incredibly necessary and in demand currently for pertinency in varied areas viz. video categorization, retrieval, content analysis, annotation. This paper presents a fusion based approach to find text within the video frames. The text thought of is particularly the news ticker, that typically appear at the lower 1/4th height of the (news) video as discovered. The approach uses Laplacian of Gaussian for edge detection and Otsu for foreground detection. Further the outcomes of those two algorithms are fussed into one image by using principal component analysis technique. This fusion based extraction of text can further is to be used further by us to develop a replacement algorithmic rule to find scrolling text in videos. In this paper we tend to demonstrate the results of text extraction by conducting experiments on quite a variety of frames of a news video. Keywords— Video image, frame extraction, text detection,
Switch reference in western South America DRAFT-DO NOT CITE WITHOUT PERMISSION

Switch-reference systems occur in a number of languages spoken in a contiguous area in western South America, across language families, and even across macro culture areas (Andes and Amazon). At first sight, this is suggestive of contact-induced diffusion, but the different systems show rather a lot of variation. This paper gives an overview of the switch-reference structures found in Western South America, taking a multi-variate approach to the phenomenon. In addition, it discusses the likelihood of horizontal transmission hypotheses to explain the current distribution of switch reference in South America.
Spatial and Temporal variation of seismic hazard parameter across the Circum Pacific Zone

Spatio-temporal distribution of earthquakes and variation of seismic b value in the circum pacific zone has been investigated with a view, to identify and understand the seismicity patterns associated with major earthquake in the zone. The earthquake catalogue of the zone from 1899 to 2009 has been analyzed and gridded into subzones. Events in each region were divided into constant time intervals and annular width of 100 km for the investigation of temporal and spatial distribution of the earthquakes respectively. The moment magnitude Mw was employed in this study and other magnitude types were converted to Mw. The b-values were determined from Gutenberg-Richter law using the linear curve fitting method. The result shows an increase in b values at some period while a decrease in b values were observed at other instance The long term variation employed in this research across the regions within the circum pacific zone reveals a pattern of b values that is repeatedly wavy or undulating but not periodic.
vGASNet: A PGAS Communication Library Supporting Out-of-Core Processing

[1] Chan and Igual, Runtime Data Flow Graph Scheduling of Matrix Computations with Multiple Hardware Accelerators, FW Note, 50 (1996) [2] Dahlin et al., Cooperative Caching: Using Remote Client Memory to Improve File System Performance, in Proc. of OSDI ’94 [3] AMD, AMD64 Architecture Programmer’s Manual Vol.2 System Programming. [4] Kanter, The Common System Interface: Intel’s Future Interconnect, Real World Tech 5. u SSD is much slower than DRAM. u Under vGASNet, each node has their own cache pool on DRAM. u Page-based cache u Reducing the amount of accesses to the SSDs, vGASNet adopts cooperative caching mechanism. u Using not only local caches but also remote caches. u Firstly implemented in a distributed file system [2]. Performance evaluation
A WAVELET BASED FLIGHT DATA PREPROCESSING METHOD FOR FLIGHT CHARACTERISTICS ESTIMATION AND FAULT DETECTION

This paper proposes a new flight data preprocessing method, which add time series data to flight phase indexes. In addition, the method outputs values representing correlation strength among different types of data. The generated information will greatly supports flight characteristics estimation and fault detection, whose performance quite depend on the quality of their input flight data. The effectiveness of the proposed method is demonstrated with these two applications by using the real flight data obtained with fixed-wing aircraft.
Anxiety detection and training task adaptation in robot-assisted active stroke rehabilitation

In the therapist-centered rehabilitation program, the experienced therapists can observe emotional changes of stroke patients and make corresponding decisions on their intervention strategies. Likewise, robotic-assisted stroke rehabilitation systems will be more appreciated if they can also perceive emotional states of the stroke patients and enhance their engagements by exploring emotion-based dynamic difficulty adjustments. Nevertheless, few research have addressed this issue. A two-phase pilot study with anxiety as the target emotion state was conducted in this article. In phase I, the motor performances and the physiological responses to the stroke subject’s anxiety with high, medium, and low intensities were statistically analyzed, and anxiety models with three intensities were offline developed using support vector machine–based classifiers. In phase II, anxiety-based closed-loop robot-aided training task adaptation and its impacts on patient–robot interaction engagements were explored. As a comparison, a performance-based robotic behavior adaptation was also implemented. Experimental results with 12 recruited stroke patients conducted on the Barrett WAMTM manipulator verified that the rehabilitation robot can implicitly recognize the anxiety intensities of the stroke survivors and the anxiety-based real-time robotic behavior adaptation shows more engagements in the human–robot interactions.
Exploit Prediction and Vulnerability Clustering Using Text Mining

Software vulnerabilities can lead to monetary and information losses. Moreover, detecting vulnerability is very resource intensive. Due to limited human and financial resources, prioritization of vulnerabilities is a crucial task. Very little attention has been paid to textual information hidden in vulnerabilities databases like CVE and OSVDB. This research explores how to use from the information hidden in these texts to vulnerability prediction and clustering.