Miracle-dz/UniFAR-FTUs huggingface dataset:
Generating Realistic Node Mobility and Placement for Wireless Multi-Hop Network Simulation

SUMMARY There exists a considerable number of node placement models and algorithms for simulation of wireless multihop networks. How-ever, the topologies created with the existing algorithms do not have prop- erties of real networks. We have developed NPART (Node Placement Algorithm for Realistic Topologies) in order to resolve this fundamental issue in simulation methodology. We compare topologies generated by NPART with open wireless multihop network in Berlin. The NPART generated topologies have almost identical node degree distribution, number of cut-edges and vertices as the real network. Unlike them, topologies gener- ated with the common node placement models have their own characteristics which are considerably di ﬀ erent both from NPART and from reality. NPART algorithm has been developed into a tool. We propose a method and present a tool for integration of NPART with various realistic node mobility algorithms and tools, such as Citymob [1] and MOVE [2]. This integrated tool allows easy and time-e ﬃ cient generation of highly complex, realistic simulation scenarios. We use the tool to evaluate e ﬀ ects of integration between existing open community wireless multi-hop networks and vehicular ad-hoc networks (VANETs). The evaluation shows that despite partial coverage and peculiar topological properties of open networks, they o ﬀ er high levels of performance and network availability to the mobile end users, virtually identical to performance and availability of planned, dedi- catedly deployed networks. Our results indicate that the integration of these networks may bring considerable beneﬁts to all parties involved.
Stackelberg-Game-Based Demand Response for At-Home Electric Vehicle Charging

Consumer electricity consumption can be controlled through electricity prices, which is called demand response. Under demand response, retailers determine their electricity prices, and customers respond accordingly with their electricity consumption levels. In particular, the demands of customers who own electric vehicles (EVs) are elastic with respect to price. The interaction between retailers and customers can be seen as a game because both attempt to maximize their own payoffs. This study models an at-home EV charging scenario as a Stackelberg game and proves that this game reaches an equilibrium point at which the EV charging requirements are satisfied, and retailer profits are maximized when customers use our proposed utility function. The equilibrium of our game can vary according to the weighting factor for the utility function of each customer, resulting in various strategic choices. Our numerical results confirm that the equilibrium of the proposed game lies somewhere between the minimum-generation-cost solution and the result of the equal-charging scheme.
A pattern-based technique for ground-roll and multiple attenuation

We present a pattern-based method that separates coherent noise from signal. This method finds its mathematical foundation in the work conducted by Nemeth (1996) on coherent noise attenuation by least-squares migration. We show that a similar inverse problem can be formulated to attenuate coherent noise in seismic data. In this paper, we use deconvolution with prediction error filters to model the signal and noise vectors in a least-squares sense. This new formulation of the noise separation problem has been tested on 2-D real data for ground-roll and multiple attenuations. So far, it achieves similar results to the approach used by Brown and Clapp (2000) and Clapp and Brown (2000). However, we show that the main strength of this new method is its ability to incorporate regularization in the inverse problem in order to decrease the correlation effects between noise and signal.
tBurton: A Divide and Conquer Temporal Planner

Planning for and controlling a network of interacting devices requires a planner that accounts for the automatic timed transitions of devices, while meeting deadlines and achieving durative goals. Consider a planner for an imaging satellite with a camera that cannot tolerate exhaust. The planner would need to determine that opening a valve causes a chain reaction that ignites the engine, and thus needs to shield the camera. While planners exist that support deadlines and durative goals, currently, no planners can handle automatic timed transitions. We present tBurton, a temporal planner that supports these features, while additionally producing a temporally least-commitment plan. tBurton uses a divide and conquer approach: dividing the problem using causal-graph decomposition and conquering each factor with heuristic forward search. The `sub-plans' from each factor are then unified in a conflict directed search, guided by the causal graph structure. We describe why this approach is fast and efficient, and demonstrate its ability to improve the performance of existing planners on factorable problems through benchmarks from the International Planning Competition.
Bag of features with dense sampling for visual tracking

The bag-of-feature model has become a state-of-the-art method of visual classiﬁcation. Visual codebooks can be used to capture image statistical information for object detection and classiﬁcation, which is extracted from local image patches and based on the quantization of robust appearance descriptors. In this paper, more information of target objects can be captured by dense sampling rather than sparsely sampling. Then a robust visual tracking method is proposed based on dense sampling and bag of features. Firstly, local image patches are densely extracted by sliding windows and represented as invariant descriptors. Secondly, visual codebooks are generated by fast clustering algorithms such as hierarchical k-means. Therefore, the object region and candidate regions are represented by the bag-of-feature model with the learnt codebooks. After that, tracking can operate in a Bayesian inference framework. The bag-of-feature tracking method with dense sampling is adaptive and ﬂexible. It works independently in many situations without the complement of existed tracking algorithms. The experiments on various challenging videos demonstrate that the proposed tracker outperforms several state-of-art algorithms.
Optimization of Percentage Cube Queries

OLAP cubes are a powerful database technology to join tables and aggregate data to discover interesting trends. However, OLAP cubes exhibit limitations to uncover fractional relationships on a measure aggregated at multiple granularity levels. One prominent example is the percentage, an intuitive probablistic metric, used in practically every analytic application. With such motivation in mind, we introduce the percentage cube, a generalized data cube that takes percentages as the target aggregated measure. Specifically, the percentage cube shows the fractional relationship on a measure in every cuboid between fact table rows grouped by a set of columns (detail individual groups) and their rolled-up aggregation by a subset of those grouping columns (total group). We inroduce minimal query syntax and we carefully study query optimization to compute percentage cubes. It turns out that percentage cubes are significantly more difficult to evaluate than standard data cubes because, in addition to the exponential number of cuboids, there exists a doubly exponential number of grouping column pairs (grouping columns at the individual level and at the total level) on which percentages are computed. Fortunately, it is feasible to prune the search space with a threshold similar to iceberg queries. Experiments on a DBMS compare our novel query optimizations against existing SQL OLAP window functions. Our benchmark results show that our proposed SQL extension is more abstract, more intuitive and faster than existing SQL functions to compute percentages on the cube.
Journal of Internet Banking and Commerce a Framework for Evaluating the Effectiveness of Information Systems at Jordan Banks: an Empirical Study

Dr. Ahmad Mashhour is an associate professor of Information Systems at the University of Bahrain since last academic year 2005/2006. Formerly, he has taught many information systems courses for graduate and undergraduate levels at Jordan institutes. Abstract Banks and other financial institutions in Jordan are one of the largest investors in the fields of information systems (IS), and there are many indications that these trends to continue in the future. However, there is a concern among CEOs and top managers that the IS investments are not yielding the anticipated outcomes. This paper investigates the investment of information systems at Jordan banks and reports the results of an empirical study that evaluates the contribution of IS in the effectiveness of banks operations. The paper measures the factors which determine information systems effectiveness at Jordan main banks. These variables are presumably system decision performance, system usage and user satisfaction among others that are considered the
The Generalized TP Model Transformation for T–S Fuzzy Model Manipulation and Generalized Stability Verification

This paper integrates various ideas about the tensor product (TP) model transformation into one conceptual framework and formulates it in terms of the Takagi-Sugeno (T-S) fuzzy model manipulation and control design framework. Several new extensions of the TP model transformation are proposed, such as the quasi and “full,” compact and rank-reduced higher order singular-value-decomposition-based canonical form of T-S fuzzy models, and the bilinear-, multi, pseudo-, convex-, partial TP model transformations. All of these extensions together form the generalized TP model transformation, which provides an effective tool to freely and readily manipulate the antecedent sets and rules of T-S fuzzy models and also provides main fuzzy rule component analysis, as well as a means for complexity and accuracy tradeoffs. It is demonstrated in this paper that the proposed manipulation forms a new, effective, and necessary optimization step of T-S fuzzy or polytopic models and linear-matrix-inequality-based control design, and can also decrease conservativeness. Identification techniques are typically constructed according to the available data and measurement set, as well as the type of system to be identified. As a result, they may not always provide good representations for control design frameworks. This paper demonstrates that the proposed TP model transformation is unique in that it bridges between various soft-computing-based identification techniques and T-S fuzzy model-based approaches. Finally, this paper proposes the multi-TP model transformation, which is a tractable and nonheuristic framework to verify the stability of the result of fuzzy or various soft-computing-based control designs. The multi-TP model transformation could provide an answer to the frequently emerging criticisms regarding the lack of mathematical stability verification techniques in the soft-computing-based control design. Control examples are provided in this paper.
Motivations, Consumption Emotions, and Temporal Orientations in Social Media Use: A Strategic Approach to Engaging Stakeholders Across Platforms

ABSTRACT How to engage stakeholders effectively with different social media platforms is an important topic in strategic communication research. Grounded in uses and gratifications theory, consumption emotion theory, and temporal orientation framework, this study conducted an online survey among social media users in the United States (N = 940) to examine how individuals’ motivations, emotions, and temporal orientations in social media use might differ by multi-platform usage groups (i.e., Facebook+Instagram users vs. Facebook+Pinterset users). Our findings indicate that Facebook+Instagram users focus more on self-status seeking and entertainment, while Facebook+Pinterest users are more information-seeking driven and future-oriented. In addition, more optimism is detected among Facebook+Pinterest users. Implications for strategic communication theory development as well as insights for organization-stakeholder engagement on social media are discussed.
1 3 0 Se p 20 01 Les Houches Lectures on De Sitter Space ∗

These lectures present an elementary discussion of some background material relevant to the problem of de Sitter quantum gravity. The first two lectures discuss the classical geometry of de Sitter space and properties of quantum field theory on de Sitter space, especially the temperature and entropy of de Sitter space. The final lecture contains a pedagogical discussion of the appearance of the conformal group as an asymptotic symmetry group, which is central to the dS/CFT correspondence. A (previously lacking) derivation of asymptotically de Sitter boundary conditions is also given. Based on lectures by A. S. at the LXXVI Les Houches school “Unity from Duality: Gravity, Gauge Theory and Strings”, August 2001. On leave from the L. D. Landau Institute for Theoretical Physics, Moscow, Russia.
On The Trail of Epidemics in Distributed Systems

Epidemic algorithms have recently been rediscovered, and have been implemented in many applications which require high scalability and robustness to random failures in process and/or network links. In this paper we look into some implementations of these algorithms from a historical perspective highlighting on successful implementations over diverse applications. The common thread that connects these implementations is that all of them require fast and efficient dissemination of a particular information over a large scale distributed system which is connected not as a central – node relationship, rather, as many peers cooperating over the execution of some common task or set of tasks.
Temporary Absences From Prison in Canada Reduce Unemployment and Reoffending: Evidence for Dosage Effects From an Exploratory Study

Temporary absences (TAs) from prison are intended to assist gradual reintegration. TAs can be either escorted (ETA) or unescorted (UTA). This exploratory study examined who received TAs, ETAs, and UTAs in Canadian federal prisons and the impact of these absences on community outcomes. The sample included 27,098 offenders released to the community between April 1, 2005 and March 31, 2011. Propensity scores for receiving TAs were used to control for group differences in outcome analyses. Participation rates were 22% for ETAs and 4% for UTAs. The strongest predictor was sentence length: Offenders with longer prison sentences were more likely to receive TAs. Other key predictors included moderate risk, higher motivation level, and fewer problems with institutional adjustment and on prior periods of community supervision. Participation was related to significantly lower levels of unemployment, returns to custody for any reason, and returns to custody for a new offense. Furthermore, a significant dosage effect was found for all TAs and ETAs: The more TAs the offender received, the less likely they were to return a custody. Absences from prison play an important role in gradual reintegration to the community, and the more the offenders participate in, the better the outcomes.
Asset Pricing with Regime Shifts in Consumption and Dividend Growth PRELIMINARY - DO NOT CIRCULATE

We present an asset pricing model with two regimes, where the conditional mean of the aggregate consumption growth rate reverts to its unconditional mean with a process that diers across regimes. The representative consumer, endowed with recursive preferences, observes the conditional mean but not the regime. He forms a posterior probability of being in the …rst regime based on his current information set. The two state variables, the conditional mean and the posterior probability, are latent to the econometrician. We show that, in equilibrium, the market-wide log price-dividend ratio and risk free rate and, hence, the pricing kernel are a¢ ne functions of the two state variables and their product. Therefore, these two equations may be inverted to extract the two latent state variables as known functions of the observable log price-dividend ratio and risk free rate. The two-regime model produces signi…cantly lower pricing errors in the market portfolio, the risk free rate, and the cross-section of returns over 1930-2006 than the single-regime model does. The …rst regime, characterized by a short (less than 3 years) half-life and higher volatility of the conditional mean of the consumption growth rate, corresponds to NBER-registered recessions while the second regime, characterized by a half-life longer than 8 years corresponds to business cycle expansions.
Deadlock Resolution in Self-Assembly of Modular Structure Systems

In self-assembly of modular structure systems, decentralized planning of module movements has deadlock problems since it uses only local information. Mechanisms of deadlock occurrence are considered, and it is pointed out that simple rules of module movements based on local information sometimes set the module not to move entirely or to repeat same movements infinitely. To solve deadlock problems, the method, which is to control randomness of module movements, is proposed. Through computer simulations using the proposed method, deadlock resolution is clearly demonstrated, and considerable reduction of assembly time is also shown
A pattern recognition system for environmental sound classification based on MFCCs and neural networks

The paper proposes a study of a background noise classifier based on a pattern recognition approach using a neural network. The signals submitted to the neural network are characterised by means of a set of 12 MFCC (Mel frequency cepstral coefficient) parameters typically present in the front end of a mobile terminal. The performance of the classifier, evaluated in terms of percent misclassification, indicate an accuracy ranging between 73% and 95% depending on the duration of the decision window.
Flexible Marker-based Augmented Reality Based on Estimation of Object Pose With RGB-D Sensor

Augmented Reality (AR) is one of the important technologies in the field of computer graphics and is utilized for many applications. When marker-based AR systems are utilized for applications in maintenance of plants, markers need to be allowed to be placed at any points on the target objects because of a lot of occlusions by the complicated piping network in plants. Therefore, we propose a method to overlay the virtual graphic models exactly onto the corresponded physical objects in an RGB image, by the extension of the marker-based AR. In our proposed method, the camera pose is tracked by the detection of the marker on the target object from the RGB image. It is also possible to recognize the object by using the information included in the marker. On the other hand, the 3D pose of the objects is estimated based on the alignment of 3D point clouds instead of markerbased AR method. We present the validity of the proposed method by conducting experiments with an RGB-D sensor and physical objects on which a marker is installed.
Memory Acquisition: A 2-Take Approach

When more and more people recognize the value of volatile data, live forensics gains more weight in digital forensics. It is often used in parallel with traditional pull-the-plug forensics to provide a more reliable result in forensic examination. One of the core components in live forensics is the collection and analysis of memory volatile data, during which the memory content is acquired for searching of relevant evidential data or investigating various computer processes to unveil the activities being performed by a user. However, this conventional method may have weaknesses because of the volatile nature of memory data and the absence of original data for validation. This may cause implication to the admissibility of memory data at the court of law which requires strict authenticity and reliability of evidence. In this paper, we discuss the impact of various memory acquisition methods and suggest a 2-Take approach which aims to enhance the confidence level of the acquired memory data for legal proceedings.
Clusters versus GPUs for Parallel Target and Anomaly Detection in Hyperspectral Images

Remotely sensed hyperspectral sensors provide image data containing rich information in both the spatial and the spectral domain, and this information can be used to address detection tasks in many applications. In many surveillance applications, the size of the objects (targets) searched for constitutes a very small fraction of the total search area and the spectral signatures associated to the targets are generally different from those of the background, hence the targets can be seen as anomalies. In hyperspectral imaging, many algorithms have been proposed for automatic target and anomaly detection. Given the dimensionality of hyperspectral scenes, these techniques can be time-consuming and difficult to apply in applications requiring real-time performance. In this paper, we develop several new parallel implementations of automatic target and anomaly detection algorithms. The proposed parallel algorithms are quantitatively evaluated using hyperspectral data collected by the NASA's Airborne Visible Infra-Red Imaging Spectrometer (AVIRIS) system over theWorld Trade Center (WTC) in New York, five days after the terrorist attacks that collapsed the two main towers in theWTC complex.
Neuropsychiatric reaction induced by clarithromycin in a patient on highly active antiretroviral therapy (HAART)

A 58 year old man, diagnosed HIV-1 antibody positive 3 years previously, presented with a 24 hour history of hyperactivity. This culminated in the development of suicidal and homicidal ideation. For fear of injury to himself and others he was admitted to hospital. He had commenced a course of clarithromycin by mouth 500 mg twice daily 10 days previously, for a bacterial chest infection. Two months before this, HAART had been commenced with zidovudine by mouth 250 mg twice daily, didanosine by mouth 200 mg twice daily, and nevirapine by mouth 200 mg twice daily. This was in addition to long term treatment with simvastatin by mouth 20 mg once daily for hypercholesterolaemia. There was no other medical history of note. He also had no previous history of mental ill health, alcohol, or drug misuse. On physical examination, he was afebrile with oxygen saturations of 100% on air. His pulse was regular at 80 beats/minute and blood pressure 110/60 mm Hg. Examination of his respiratory and …
Position control using adaptive backlash compensation for bowden cable transmission in soft wearable exoskeleton

In recent years, bowden-cable transmissions have been developed and utilized widely in many robotic applications due to advantages in durability, lightweight, safety, and flexibility. Especially, over the last decade, a substantial number of soft wearable exoskeletons using bowden cables for motion transmission have been designed for human assistance, empowerment and rehabilitation. The major advantage of soft assistive devices driven by bowden-cable transmissions is to allow decentralizing the actuation stages proximally such that their mass has the least effect on the end-effector. Besides the advantage, the main drawback of the bowden cable-driven system comes from the presence of nonlinearities such as friction and backlash hysteresis that affects their control accuracy. Hence, in this paper, we introduce a mathematical model for backlash hysteresis and propose a solution based on the nonlinear adaptive control to compensate for the backlash effect. The backlash hysteresis model and control scheme are validated first on a custom-designed test bench and then applied to control a soft exoskeleton in a preliminary human trial.