Miracle-dz/UniFAR-FTUs huggingface dataset:
A Combined De-correlation Method for Acoustic Feedback Cancellation in Hearing Aids

Acoustic Feedback is a common problem in most hearing aids, it reduces the maximum useable gain and even causes "howling" while large forward gain is required, which is quite annoying for patient with severe hearing losses. This paper gives a new combination of de-correlation LMS adaptive algorithm and fixed forward delay to better de-correlate input and output signals of hearing aids as well as input signals to adaptive filters in consecutive time. Simulations in MATLAB showed that more than 20 dB additional gain could be obtained with new method
Robust actuator placement in flexible plates subject to worst-case spatial distribution of disturbances

In this study, we consider the problem of actuator placement in the vibration control of flexible plates. Unlike earlier approaches based on enhanced controllability and/or improved performance measures, we consider the case of actuator placement based on robustness-with-respect to spatial variability of disturbances. As predicted from our extensive numerical investigation, when the spatial distribution of disturbances is known, then the resulting optimal location differs from the one predicted from controllability/LQR approaches. When the distribution is not known, then one may introduce an element of spatial robustness by considering the worst-case spatial distribution. Extensive numerical results are reported here which provide an insight on the judicious actuator placement when spatial distributions of disturbances are taken into consideration for actuator placement and controller design.
Navigation Leads Selection Considering Navigational Value of Keywords

Searching a vast information space such as the Web presents a challenging task and even more so, if the domain is unknown and the character of the task is thus exploratory in its nature. We have proposed a method of exploratory navigation based on navigation leads, i.e. terms that help users to filter the information space of a digital library. In this paper, we focus on the selection of the leads considering their navigational value. We employ clustering based on topic modeling using LDA (Latent Dirichlet Allocation). We present results of a preliminary evaluation on the Annota dataset containing more than 50,000 research papers.
ON-LINE MINIMUM MUTUAL INFORMATION METHOD FOR TIME-VARYING BLIND SOURCE SEPARATION

The MeRMaId (Minimum Renyi’s Mutual Information) algorithm for BSS (blind source separation) has previously been shown to outperform several popular algorithms in terms of data efficiency. The algorithms it compared favorably with include Hyvarinen’s FastICA, Bell and Sejnowski’s Infomax, and Comon’s MMI (Minimum Mutual Information) methods. The drawback is that the MeRMaId algorithm has a computational complexity of O(L2), as compared to O(L) for the other three. However, a new advancement referred to as SIG (Stochastic Information Gradient), can be used to modify the MeRMaId criterion such that the complexity is reduced to O(L). The modified criterion is then applied to the separation of instantaneously mixed sources using an on-line implementation. Simulations demonstrate that the new algorithm preserves the separation performance of the original algorithm and, in fact, compares quite favorably with several published methods.
A Generic Log-Service-The key architectural element to support efficient recovery from node crashes

In distributed systems, computations run the risk of failing completel y if ven one processor should fail. For applications without hard real-time requirements, backw ard error recovery can be a cost-efficient method of providing fault tolerance. Following this approach, the adequate use of logs is most important. They allow to reliably stor e information needed to maintain a consistent system state, especially after the fa iling of individual computing nodes in the system. Implementors of a log like to point out that the log know s everything that is going on in a distributed system. During normal execution, state inform ation about each process is saved on the log so that the process is later able to be restor d to certain earlier states of its execution. After a failure, if a consistent sys em state can be formed from these individual process states, the computation as a whole can be resumed and completed successfully. Dependent on the used communication paradigm, incoming messa ges or current data states are logged in order to maintain the informati on necessary to recover from such a failure. For reasons of simplicity and without restricting generality we assume that the distributed system clearly separates data objects which carry st te from computations which carry on system activity by changing the state of data objects via the execution of some operations. Thus, only data objects are the target of any recovery ac tion nd we are able to describe our logging approach independent from a specific communication and data model, respectively.
Evaluating Video Streaming in Network Architectures for the Internet of Things

In this paper we discuss the experimentation results we obtained from performing video streaming in Internet of Things (IoT) scenarios built on top of Content Centric Networking (CCN) architecture. More precisely, we used the Dynamic Adaptive Streaming over HTTP (DASH) mechanism to split videos into multiple pieces, also offering multiple bit-rates. Such pieces are then streamed by a DASH client from a typical HTTP server through a CCN network. HTTP/CCN adapters are used to translate the HTTP requests to CCN interests and HTTP responses to CCN content objects. The results are promising, the experiment demonstrated that CCN can fit into IoT environments and that its integrated caching mechanisms will highly reduce the necessary time to retrieve content, specifically streamed video, therefore increasing network efficiency.
Evaluating Unstructured Information Management: A Case Study Driven Approach

Many organizations have recognized the potential of managing unstructured information alongside structured information as a way to increase their business value and improve their competitive advantage. The evaluation of a UIM process is a challenging research area that has received little attention up to now. Thus, it is important to provide information officers with appropriate techniques to help them evaluate how UIM technologies should be deployed and how to maximise the benefits to the organisation. The proposed UIM evaluation scheme is a comprehensive set of criteria for the UIM process and it is generic in that it could be used to evaluate any applications and technologies that follow this process. In addition, parts of the evaluation scheme could be used in the evaluation of a different UIM process. It follows that the proposed evaluation scheme could assist information officers that use such applications and designers that develop such applications in evaluating and deploying UIM systems that increase business value and improve competitive advantage. Finally, the proposed framework provides a common language for communication between designers and information officers because the majority of its evaluation criteria focus on the usability and functionality of UIM applications and technologies.
Modeling Social Networking Privacy

In this paper we propose to use a formal language, called Secure UML, to model social networking privacy. Secure UML is a language for specifying role-based static and dynamic access control policies, the latter being policies that depend on the run-time satisfaction of specific constraints (e.g., the privacy settings in social networking sites). By using a formal language for modeling social networking privacy, we provide a rigorous, unambiguous description of the policies, and a solid, much-needed formal foundations for tools to validate them and to perform change impact analysis. To illustrate our proposal, as well as its benefits, we use Facebook as a case study, in particular, the latest two versions of Facebook's policy for posting and tagging.
D-LAROD: A Density Based LAROD for Geographical Routing in Intermittently Connected MANETs

Most Routing Protocols of Mobile Ad-Hoc Networks (MANETs) were studied using open space models where nodes were able to move throughout the entire simulation area. However, a more realistic topology should account for restricted mobility of nodes, such as in an urban city setting where there may be concentrations of nodes within specific areas (such as within buildings) and low density of nodes in other areas (such as in parks and roadways). Consequently, the simulation area should be partitioned into smaller sub-areas with varying densities to model such areas, called dense/ sparse areas. Routing the packets in fully connected Mobile AdHoc Networks (MANETs) has been studied to great extent, but the assumption on full connectivity is generally not valid in a real system. The challenge here is to design a routing protocol to handle intermittently connectivity and dense/sparse topologies. This study characterized the effect of dense/sparse topologies on MANET routing performance and proposes an extension for an existing LAROD-LoDiS, routing protocol to work in such topologies called D-LAROD. The proposed protocol improved the performance of MANETs by reducing the communication overhead incurred during the routing processes by implementing a new density based geographical routing algorithm. The proposed routing algorithm was based on the density and connectivity of the nodes and not just the number of nodes.
Genetic Algorithm based Human Face Recognition

This paper proposes a novel algorithm for recognizing human faces using Genetic Algorithms. This proposed method consists of three major phase namely, face representation, face detection and face detection. In Addition, a comparative study is made using Principle Component Analysis and Linear Discriminant Analysis using the commonly used face databases such as Essex Face Database-Face94, Indian Face Database [16], Yale Database, FACE 1999 [18] and UMIST Face Database [19]. The proposed method produces better results than PCA and LDA for one sample per person. For Face 1999, which contained images with different background, the recognition rate is not quite good. But for all the other databases the test produces more than 90% recognition accuracy rate. From the result obtained it is observed that the proposed system does not need more number of images per person. Here the same recognition rate is achieved in around 5 images per person instead of around 10 images per person in basic PCA and LDA.
Traffic engineering with MPLS in the Internet

This article discusses traffic engineering with multiprotocol label switching (MPLS) in an Internet service provider's network. We first review MPLS, constraint-based routing, and enhanced link state interior gateway protocols to provide a background for traffic engineering. We then discuss the general issues of designing an MPLS system for traffic engineering. The design of GlobalCenter's MPLS system is presented. Based on our experiences, a generic procedure for deploying an MPLS system is proposed. We also discuss how to provide QoS in a network with MPLS. Putting these together, we present to readers the practical issues of traffic engineering and a working solution for traffic engineering with MPLS in the Internet.
Finding parameters which influence the performance of Java for streaming video over the network

Java has been growing tremendously as a language and as a platform over the past few years. Multimedia applications written in Java are gaining popularity because of the platform independence of Java. Basically, the write once - run anywhere nature of Java applications is what makes Java a potential contender for developing software compared to other high level languages. However, there is still a lot of work that needs to be done to determine how multimedia performance is affected in Java using its various features such as Garbage collection, Just in Time (JIT) compilation. In this paper, we present experiments that measure the multimedia performance of an MPEG-1 client in Java, considering the frame rate and jitter. We find that Just in Time compilation, different MPEG files, local media access as well as access to media over a network, have implications on multimedia performance. Local media access shows less jitter than the network access and different MPEG files show different jitter amounts. Although, overall Java lags behind C++, as far as multimedia performance is concerned, we believe that improvement in performance can be achieved in Java through the use of its inherent features like JIT.
Hiding sensitive association rules using central tendency

Privacy Preserving in Data Mining (PPDM) is a process by which certain sensitive information is hidden during data mining without precise access to original dataset. Majority of the techniques proposed in the literature for hiding sensitive information are based on using Support and Confidence measures in the association rules, which suffer from limitations. In this paper we propose a novel architecture which acquired other standard statistical measures instead of conventional framework of Support and Confidence to generate association rules. Specifically a weighing mechanism based on central tendency is introduced. The proposed architecture is tested with UCI datasets to hide the sensitive association rules as experimental evaluation. A performance comparison is made between the new technique and the existing one. The new architecture generates no ghost rules with complete avoidance of failure in hiding sensitive association rules. We demonstrate that Support and Confidence are not the only measures in hiding sensitive association rules. This research is aimed to contribute to data mining areas where privacy preservation is a concern.
Reorder notifying TCP (RN‐TCP) with explicit packet drop notification (EPDN)

Numerous studies have shown that packet reordering is common, especially in networks where there is high degree of parallelism and different link speeds. Reordering of packets decrease the TCP performance of a network, mainly because it leads to overestimation of the congestion in the network. In this paper, we analyse the performance of networks when reordering of packets occur. We propose a proactive solution that could significantly improve the performance of the network when reordering of packets occurs. We report results of our simulation experiments, which support this claim. Our solution is based on enabling the senders to distinguish between dropped packets and reordered packets. Copyright © 2005 John Wiley & Sons, Ltd.
Examination of Agression of University Students by the Level of Playing Sports

The aim of this research is to examine aggression of university students by the level of playing sports. 215 students constituted the sample of this study. Personal information form and “Aggression Scale” were used as a data collection tool. Mann-Whitney U Test and Anova Test were performed for difference between groups and Cronbach’s Alfa (,898) was performed in order to measure reliability of data concerning scale (p<0.05). As a conclusion; it was determined that sport is effective on the aggression level of university students. It was stated that the average aggression level of people who play sports is lower than people who don’t play sports. As there is no difference between ways of playing sports, there is a difference between departments. Males have higher aggression level than females. It is possible to say that sport has aggression reducing effect besides health and entertainment benefits in the direction of these findings.
Precise Measurement of the e

Citation Lees, J. et al. " Precise measurement of the e[superscript +]e[superscript-][superscript +][superscript-]() cross section with the initial-state radiation method at BABAR. " Physical Review D 86.3 (2012). Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Impact of Famagusta Port Effi ciency on North Cyprus Economic Development

This study aims at evaluating the performance of the Famagusta Port in order to find out its impact on the economy of NC. It is critical to analyze the economic impact of the Famagusta port in particular. The performance of the economy is correlated to the productivity and the efficiency of the port over a given period of time. The more the port performs the higher the efficiency and productivity. With Famagusta Port’s low growth rate, the question of port efficiency is necessary in a country like NC. Data envelopment analysis (DEA) is used to conduct this research. The results obtained determine the efficiency of the port.
Nonparametric Poisson Factorization Machine

Factorization Machine (FM) provides a generic framework that combines the prediction quality of factorization models with the flexibility of feature engineering that discriminative models like SVM offer. The Bayesian Factorization Machine [11], with its impressive predictive performance and the convenience of automatic tuning of parameters, has been one of the most successful and efficient approaches within this framework. However, this model has two major drawbacks. Firstly, it assumes that the data is generated from Gaussian distributions that may not be the best assumption for count data such as integer-valued ratings. Secondly, to get the best performance, one needs to cross-validate over the number of latent factors used for modeling the pairwise interaction in FM, a process that is computationally intensive. This paper introduces the Nonparametric Poisson Factorization Machine (NPFM), which models count data using the Poisson distribution, which provides both modeling and computational advantages for sparse data. The ideal number of latent factors is estimated from the data itself, thereby addressing a key limitation of existing approaches to FM. Additionally, NPFM has linear time complexity with respect to the number of non-zero observations.
Cognitive channel selection for opportunistic spectrum access: a reinforcement-learning approach

Cognitive Radio has been proposed to address the problem of spectrum scarcity by exploiting under-utilized frequency bands (FBs). With opportunistic spectrum access, cognitive secondary users (SUs) may access vacant FBs originally assigned to Primary Users (PUs). Considering autonomous cognitive radio networks, where no central entity can share environment information, SUs have to operate as independent agents. Such agents are confronted with PU traffic which may follow either deterministic patterns, as in TV transmission, or stochastic patterns, as in packet-switched or circuit-switched networks. However, the traffic stochastic patterns cannot, in general, reflect the dynamic changes in the FBs, especially when these channels are accessed by not registered users as the SUs. Addressing this issue, a novel reinforcement-learning (R-L) scheme is proposed, based on Q-learning with two alternatives. The proposed scheme enables SUs to use information acquired solely by own sensing and evaluate the available FBs accordingly in order to set an optimal channel selection and sensing order. The evaluation of FBs is based on (i) the occupancy probability and (ii) the mean duration of the time that the PUs are idle. The effectiveness of both alternatives is examined in different environment characteristics. Simulations show that the proposed scheme succeeds in setting the FBs in the optimal sensing order in both static and dynamic cases providing SUs with self-awareness and efficient channel utilization.
The Role of her4 in Inner Ear Development and Its Relationship with Proneural Genes and Notch Signalling

The generation of sensory neurons and hair cells of the inner ear is under tight control. Different members of the Hairy and Enhancer of Split genes (HES) are expressed in the inner ear, their full array of functions still not being disclosed. We have previously shown that zebrafish her9 acts as a patterning gene to restrict otic neurogenesis to an anterior domain. Here, we disclose the role of another her gene, her4, a zebrafish ortholog of Hes5 that is expressed in the neurogenic and sensory domains of the inner ear. The expression of her4 is highly dynamic and spatiotemporally regulated. We demonstrate by loss of function experiments that in the neurogenic domain her4 expression is under the regulation of neurogenin1 (neurog1) and the Notch pathway. Moreover, her4 participates in lateral inhibition during otic neurogenesis since her4 knockdown results in overproduction of the number of neurog1 and deltaB-positive otic neurons. In contrast, during sensorigenesis her4 is initially Notch-independent and induced by atoh1b in a broad prosensory domain. At later stages her4 expression becomes Notch-dependent in the future sensory domains but loss of her4 does not result in hair cell overproduction, suggesting that there other her genes can compensate its function.
A high-order model looking beyond the first-order harmonic superposition assumption

In this paper, a hybrid high-order behavioural model is proposed to mimic the response of strongly nonlinear unmatched RF transistors. In this model, a high-order Multi-Harmonic Volterra (MHV) behavioural model is used to predict the DC and fundamental frequency components of the output signal, while higher harmonic components are predicted by the Poly-Harmonic Distortion (PHD) model. The added coefficients of the MHV model augment the first-order expansion (harmonic superposition) of the PHD model to improve the model accuracy where it is needed. The hybrid MHV-PHD model improves the DC drain current prediction by 5dB and fundamental frequency output-power by 2dB in terms of Normalized Mean Squared Error (NMSE), while improving overall time-domain prediction by 1dB.
Safety Strategies employed when responding to Intimate Partner Violence:: A systematic review

The research report sets out to provide evidence-based safety strategies adopted by those affected by Intimate Partner Violence (IPV). Where appropriate, other forms of interpersonal violence are considered in order to add breath to the evidence that supports practice offered to those affected by IPV. Globally, IPV is public health and human rights issue crossing over into the justice system and while the outcomes of IPV victimisation are well documented, it is less clear how victims who experience violence or abuse manage their experiences. The systematic review presented in this report initially scoped 3,540 papers moving through screen and quality assessment procedures. As a consequence the review yields 5 themes that centre on evidence for safety strategies adopted by those affected by IPV: Victims of Interpersonal Violence are likely to seek help from personal sources; Significant barriers for victims of interpersonal violence in seeking help; Victims use of an array of strategies to prevent or reduce harm from inter-personal violence; Victims of interpersonal violence engage in a variety of behaviours to manage their emotions; Type and severity of interpersonal violence affecting type of help sought by victims. While the implications of the study presented in this report are two-fold: research and clinical.