Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional balance tests

Background and Aim: All activities of daily living need to balance control in static and dynamic movements. In recent years, a numerous increase can be seen in the functional balance assessment tools. Functional balance tests emphasize on static and dynamic balance, balance in weight transfer, the equilibrium response to the imbalances, and functional mobility. These standardized and available tests assess performance and require minimal or no equipment and short time to run. Functional balance is prerequisite for the most static and dynamic activities in daily life and needs sufficient interaction between sensory and motor systems. According to the critical role of balance in everyday life, and wide application of functional balance tests in the diagnosis and assessment of patients, a review of the functional balance tests was performed. Methods: The Google Scholar, PubMed, Science Direct, Scopus, Magiran, Iran Medex, and IranDoc databases were reviewed and the reliable and valid tests which were mostly used by Iranian researchers were assessed. Conclusion: It seems that Berg balance scale (BBS) have been studied by Iranian and foreign researches more than the other tests. This test has high reliability and validity in elderly and in the most neurological disorders.
Size Reduction and Bandwidth Enhancement of Microstrip Patch Antenna by Proper Positioning of Patch above the Defected Ground Plane

article, a single layer reduced size broadband microstrip antenna with properly positioned In this patch placed above defected ground plane has been successfully implemented. The size of the antenna is reduced with large enhancement in bandwidth by defecting the ground plane and proper positioning of the patch with respect to the defected ground plane. With theproposed design, a maximum size reduction of 75% in the antenna is obtained with respect to the conventional microstrip patch antenna on an infinite ground plane. The measuredresult shows -10dB return loss bandwidth of about 3.02 GHz (2.85-5.87GHz) and 1.4 GHz(7.10-8.5GHz) which are 69% and 18% respectively around their center frequencies. The overall dimensions of the proposed antenna (24x20x1.5875mm 3 ) can be easily applied for WLAN, HiPERLAN, HisWaNa and WiMAX applications
Studying the Effectiveness of Application Performance Management (APM) Tools for Detecting Performance Regressions for Web Applications: An Experience Report

Performance regressions, such as a higher CPU utilization than in the previous version of an application, are caused by software application updates that negatively affect the performance of an application.Although a plethora of mining software repository research has been done to detect such regressions, research tools are generally not readily available to practitioners. Application Performance Management (APM) tools are commonly used in practice for detecting performance issues in the field by mining operational data.In contrast to performance regression detection tools that assume a changing code base and a stable workload, APM tools mine operational data to detect performance anomalies caused by a changing workload in an otherwise stable code base.Although APM tools are widely used in practice, no research has been done to understand 1) whether APM tools can identify performance regressions caused by code changes and 2) how well these APM tools support diagnosing the root-cause of these regressions.In this paper, we explore if the readily accessible APM tools can help practitioners detect performance regressions. We perform a case study using three commercial (AppDynamics, New Relic and Dynatrace) and one open source (Pinpoint) APM tools. In particular, we examine the effectiveness of leveraging these APM tools in detecting and diagnosing injected performance regressions (excessive memory usage, high CPU utilization and inefficient database queries) in three open source applications. We find that APM tools can detect most of the injected performance regressions, making them good candidates to detect performance regressions in practice. However, there is a gap between mining approaches that are proposed in state-of-the-art performance regression detection research and the ones used by APM tools. In addition, APM tools lack the ability to be extended, which makes it hard to enhance them when exploring novel mining approaches for detecting performance regressions.
A new digital current sensing technique suitable for low power energy harvesting systems

Solar energy harvesting captures the greatest attention among the available self-powered systems recently. This paper presents a new control technique based on digital current sensing. The idea is based on sensing the output current through a series resistance, the current sensor is a simple analog circuit, and it generates a pulse of width that is directly proportional to the rate of change of current. A pulse-to-digital converter is designed to convert the input pulse to a thermometer code. The code is then used to control a low supply digital controlled oscillator, it generates a clock that control the charge pump that searches for the maximum power of the solar cell. This design features a hill climbing maximum power search embedded inside the pulse-to-digital converter. A low dropout regulator with resistive ladder is used to control the supply of the oscillator, the oscillator supply is used as control knob for the frequency of the charge pump. The proposed control unit exhibits low power consumption, since it works at lower supplies than the energy buffer. The design can reach a power efficiency of 58.2% up to SmW available photovoltaic power. The measured power consumption is 36.33/iW. The system is designed using Global Foundries (GF 65nm).
Phrasal or Lexical Constructions ?

Since the 1990s, more and more linguistic articles have been published in the framework of Construction Grammar. Although Kay and Fillmo re (1999, p. 19) make it clear that Constructions are not necessarily phrasa l, most of the authors suggest phrasal Constructions. This is especially apparen t in Construction Grammar-inspired studies in the HPSG framework. In what follows, I show that the difference between phrasal a pproaches and lexical approaches is not as great as is sometimes claimed, a lthough selecting one approach over the other may nevertheless have serious conse quences. This discussion focuses on resultative constructions, a phenomenon fo r which both phrasal and lexical analyses have been suggested. I show that a consi derable number of different Constructions must be postulated to account for a ll the patterns that may arise from the interaction of the resultative construction with both constituent reordering and valence changing processes. It is shown that ad juncts, predicate complexes, and derivational morphology pose considerable pro blems for the phrasal approach, while they are unproblematic for lexical rule-ba sed approaches. The discussion is relevant for all frameworks that do not use transformations to map phrasal configurations to other phrasal configuration s. ∗ ∗I thank Brian D. Joseph, the editor of Language, his Associat e Editor James McCloskey, and an anonymous reviewer of Language for detailed comments on an earlie r version of this paper. I thank Ann Copestake, Kerstin Fischer, Paul Kay, Laura Mich aelis, Detmar Meurers, Frank Richter, Ivan Sag, Anatol Stefanowitsch, and Arne Zeschel for discussion . I thank John Bateman, Dorothee Beermann, Gisbert Fanselow, Hans-Ulrich Krieger, Andrew McIntyre, a nd Shravan Vasishth for discussion and for comments on earlier versions of this paper. I gave presentations about phrasal and lexical analyses of t he resultative construction at the Institute for General and Applied Linguistics at the University of Bremen , at the Institute of Cognitive Science at the University of Osnabrück, at the Deutsches Seminar of the Uni versity of Tübingen, at the Linguistics Institute of the Ruhr University Bochum, at the workshop Foundations of Natural-Language Grammar at the ESSLLI 2005 in Edinburgh, and at HPSG 2005 in Lisbon. I thank the resp ective departments for the invitation, the reviewers of the conference and the workshop for comments, a d the audiences for comments and discussion. The resultative construction was also one of the topics that were discussed during the PhD school Languages and Theories in Contrast in Bergen in 2005. I enjoyed the discussion very much and want to thank the organizers Helge Dyvik and Torbjørn Nordgård, my coteac h rs Miriam Butt, Helge Dyvik, and Peter Svenonius and the audience again.
Dynamic Characteristics of k-ary n-cube Networks for Real-time Communication

Overlay topologies are now popular with many emerging peer-to-peer (P2P) systems, to efficiently locate and retrieve information. In contrast, the focus of this work is to use overlay topologies for transporting real-time streams on an Internet-scale. We aim to build an overlay communication system, for routing real-time data to potentially many thousands of subscribers with their own quality-of-service (QoS) requirements. In past work, we have analyzed the use of k-ary n-cube topologies for routing QoS-sensitive data. The basis for our work stems from the interconnection networks found in parallel communication architectures, such as the SGI Origin 2/3000. However, overlay networks addressed by our work are more scalable and dynamic than those found in traditional parallel computing platforms. We must address the issue of end-hosts joining and leaving the system at arbitrary times. While we have previously analyzed the optimal size and shape of an overlay, given the number of physical hosts in the system, this paper investigates the overheads of dynamically reconfiguring k-ary n-cubes to deal with system membership changes. Specifically, we study the control message exchanges needed to maintain a globally-consistent snapshot of the system configuration, given dynamic joins and departures of physical hosts. A cost model, capturing the lagged response in adapting the overlay to its optimal topology is derived.
Energy-Efficient Mobile P2P Communications Based on Context Awareness

Mobile Peer-to-peer (P2P) realizes communications between mobile nodes without any access points. In general, Mobile P2P utilizes IEEE 802.11 Wireless LANs. However, IEEE 802.11 Wireless LANs do not support intelligent energy management schemes. Therefore, nodes should appropriately switch on and off its WLAN interface for reducing energy consumptions. In this paper, we propose energy efficient mobile P2P communications based on context information of users. We propose two models: Server-based model and Client-based model. In both models, nodes collect their context information such as location acquired by GPS. Server-based model uses a server to handle users' context information. In Server-based model, mobile nodes transmit the acquired context information to the server periodically. The server determines if the user should wake up or sleep, and transmits the decision to the user. Client-based model does not use any server. In Client-based model, each node decides to wake up or sleep by itself. We evaluate the performance of the proposed models via Nexus S smartphone. As results, we confirm that the proposed models can reduce energy consumption compared with the conventional IEEE 802.11 WLANs without energy management. In addition, we implement an audio streaming application using the proposed mobile P2P communications.
Evaluating the performance of Gulf of Alaska walleye pollock (Theragra chalcogramma) recruitment forecasting models using a Monte Carlo resampling strategy

Multiple linear regressions (MLRs), generalized additive models (GAMs), and artificial neural networks (ANNs) were compared as methods to forecast recruitment of Gulf of Alaska walleye pollock (Theragra chalcogramma). Each model, based on a conceptual model, was applied to a 41-year time series of recruitment, spawner biomass, and environmental covariates. A subset of the available time series, an in-sample data set consisting of 35 of the 41 data points, was used to fit an environment-dependent recruitment model. Influential covariates were identified through statistical variable selection methods to build the best explanatory recruitment model. An out-of-sample set of six data points was retained for model validation. We tested each model’s ability to forecast recruitment by applying them to an out-of-sample data set. For a more robust evaluation of forecast accuracy, models were tested with Monte Carlo resampling trials. The ANNs outperformed the other techniques during the model fitting process. For f.
Bayesian Inference in Support Vector Regression

In the report, we apply popular Bayesian techniques on support vector regression. We describe a Bayesian framework in a function-space view with a Gaussian process prior probability over the functions. A unified non-quadratic loss function with the desirable characteristic of differentiability, called the soft insensitive loss function, is used in likelihood evaluation. In the framework, maximum a posteriori estimate of the functions results in an extended support vector regression problem. Bayesian methods are used to implement model adaptation, while keeping the merits of support vector regression, such as quadratic programming and sparseness. Moreover, we put forward confidence interval in making predictions. Experimental results on simulated and real-world datasets indicate that the approach works well even on large datasets.
State-dependent utility maximization in L\'evy markets

We revisit Merton's portfolio optimization problem under boun-ded state-dependent utility functions, in a market driven by a L\'evy process $Z$ extending results by Karatzas et. al. (1991) and Kunita (2003). The problem is solved using a dual variational problem as it is customarily done for non-Markovian models. One of the main features here is that the domain of the dual problem enjoys an explicit "parametrization", built on a multiplicative optional decomposition for nonnegative supermartingales due to F\"ollmer and Kramkov (1997). As a key step in obtaining the representation result we prove a closure property for integrals with respect to Poisson random measures, a result of interest on its own that extends the analog property for integrals with respect to a fixed semimartingale due to M\'emin (1980). In the case that (i) the L\'evy measure of $Z$ is atomic with a finite number of atoms or that (ii) $\Delta S_{t}/S_{t^{-}}=\zeta_{t} \vartheta(\Delta Z_{t})$ for a process $\zeta$ and a deterministic function $\vartheta$, we explicitly characterize the admissible trading strategies and show that the dual solution is a risk-neutral local martingale.
Performance evaluation of a self-excited induction generator for stand-alone wind energy conversion system

This paper presents the performance characteristics of a self-excited induction generator (SEIG) under various operating conditions. This also explains the modeling of parallel equivalent circuit to evaluate the reactive power required for SEIG. The variation of terminal voltage has been studied by varying the shaft speed, capacitance value and load. The simulations are carried through MATLAB/SIMULINK environment, and the validation of the simulation results are established through an experimental set-up.
Detecting & exploiting positive goal interaction in intelligent agents

Rational agents typically pursue multiple goals in parallel. However most existing agent systems do not have any infrastructure support for reasoning about either positive or negative interactions between goals. Negative interactions include such things as competition for resources, which if unrecognised can lead to unnecessary failure of both goals requiring the resource. Positive interactions include situations where there is potentially a common subgoal of two goals. This paper looks at mechanisms for identifying potential common subgoals, and attempting to schedule the actions of the agent to take advantage of this. Potential common subgoals are identified by maintaining summaries of definite and potential effects of goals and plans to achieve those goals. Template summaries for goal types are produced at compile time, while instance summaries are maintained and updated at execution time to allow the agent to choose and schedule its plans to take advantage of potential commonality where possible. This increases the ability of the agent to act in a rational manner, where rational is loosely defined as the sensible behaviour exhibited by humans.
Design of a low power charge pump circuit for phase-locked loops

In this paper, the design of a charge pump circuit suitable for lower power PLL-based frequency synthesizer is presented. The charge pump circuit was designed in 0. 18μm CMOS process. The proposed charge pump circuit improves current matching in a wide output voltage range by applying a wide input ranged operational amplifier. The percentage error of current mismatch for the output range from 0.3V to 1.7V is less than ±0.005%. The power consumption of the proposed charge pump circuit is around 0.56mW at a supply voltage of 1.8V.
Multi-feature combination for speaker recognition

Combination of different features has been proved to be a good method for improving performance in speech recognition. In speaker recognition (SRE), various features have also been developed to reflect complementary aspects of speaker's characteristics. This paper proposed an effective multi-feature combination in speaker recognition. In order to avoid the “dimensionality disaster” and to delimit the redundant information, linear discriminant analysis (LDA) is used to reduce the high dimensionality of combined feature to be lower. Then feature-domain channel compensation is applied to improve the performance. In experiments, we use the popular short-term spectral Mel-frequency cepstral coefficients (MFCC) and novel spectro-temporal time-frequency cepstrum (TFC) to do feature combination followed by LDA and feature-domain latent factor analysis (fLFA) for channel compensation respectively. The experimental results on the NIST SRE2008 short2 telephone-short3 telephone test set show that the proposed multi-feature combination is an effective method to outperform both raw features.
Optimal implementation of elliptic curve cryptography

The most time-consuming operation in the Elliptic Curve Cryptography (ECC) calculation is scalar multiplication. Scalar multiplication plays a major role in ECC. Currently, there are several optimization algorithms for point scalar multiplication which have either high computational complexity or additional storage requirement. They are all unsuitable for further applying. In this paper, we present a new compatible optimal algorithm which improves the efficiency by generating a special random number k as the scalar. The experimental results show that the processes of encryption and decryption have been speed up significantly in the same condition.
Greenland Temperatures and Solar Activity: A Computational Intelligence Approach

The complexity of the Earth's climate and its relationship with solar activity are here approached by means of two computational intelligence techniques: multivariate time series model mining (MVTSMM) and genetic programming (GP). They were applied to a temperature record (Delta 018/16), obtained from an ice core in central Greenland, representative of the climate variations in the North Atlantic regions, and the International Sunspot Number series, as a proxy of solar activity, both covering the period from 1721 to 1983. Several experiments were conducted using these records jointly and separately with the purpose of characterize and reveal their time dependencies. Preliminary results show this mining approach is a valid and promising research line. The time-lag spectra obtained with MVTSMM seem to point out to time stamps of some of the most important Earth-climate and solar variations, as well as the contribution of solar activity and sunspot solar cycles along time. The GP provided equations which approximate the relative contribution of particular solar time-lags. Although suggestive, this research is at an early stage and the results are preliminary, emphasizing methodological aspects.
Marching intersections: an efficient resampling algorithm for surface management

The paper presents a simple and efficient algorithm for the removal of small topological inconsistencies and high frequency details from surface models. The method, called marching intersections (MI), adopts a volumetric approach and acts as a resampling filter. All the intersection points between the input model and the lines of a user selected 3D reference grid are located and then, beginning from these intersections, an output surface is reconstructed. MI, which presents good characteristics in terms of efficiency, compactness, and quality of the output models, can be also used: for the conversion between different representation schemes; to perform logical operations on geometric models; for the topological simplification of surfaces; and for the simplification of huge meshes, i.e. meshes too large to be allocated in main memory during the simplification process. All these aspects are discussed in the paper and timing and graphic results are presented.
Security Measuring for Self-adaptive Security

Self-adaptive security is needed due to vast amount of changes in an execution environment and threat landscape, which all cannot be anticipated at software design-time. Self-adaptive security requires means for monitoring a security level and decision making capability to improve the current security level. In this paper, we describe how security metrics are able to support self-adaptive security. The paper analyses benefits and challenges of security measuring from the self-adaptive security perspective. Thus, five benefits and three challenges of security metrics in self-adaptive security are described. Furthermore, the paper derives requirements that measuring causes for self-adaptive security. Based on the derived requirements, extension components for the MAPE (Monitor, Analyse, Plan and Execute) reference model are proposed.
Map integration of human trajectory with sitting/standing position using LRF and Kinect sensor

This paper presents a service oriented map that includes a) environment shape, b) human walking trajectory, and c) human sitting/standing position. Such information is important for a robot that provides services to human beings. Environmental shape (a) and human walking trajectory (b) are obtained by LRF. Human sitting/standing position (c) is obtained from Microsoft Kinect sensor by actively positioning and orienting the sensor to confirm human posture. A combined algorithm to obtain an integrated map is described, and experimental results follow.
Research for underwater target tracking by using multi-sonar

Aim at the underwater target tracking by using multi-sonar, underwater target motion model and sonar observation model are proposed considering the measurement properties of different sonar and the target maneuvering characteristics. Adaptive Extended Kalman Filter (AEKF) based on current statistical model is proposed to improve the performance of underwater maneuvering target positioning and tracking. The AEKF approach is using new observational data to correct the signal model and noise statistics to maintain optimal filter and inhibit the filter divergence phenomenon. As to track fusion for multi-sonar, application of interacting multiple model (IMM) approach is presented. The IMM can be a self-adjusting variable bandwidth filter to estimate the state of a dynamic system. The simulation result presents that AEKF is good at maneuvering target tracking, meanwhile track fusion of Multi-Sonar is fit well for the real.