Miracle-dz/UniFAR-FTUs huggingface dataset:
DIAGNOSTIC ASSESSMENT SYSTEM FOR STRUCTURAL SEISMIC SAFETY-DAMAGE IDENTIFICATION BASED ON NEURAL NETWORKS AND TORSION -

Japan is subjected to frequent seismic activity due to its location within three major earthquake zones: the Pacific Ocean zone, Japan Sea zone, and inland zone. Structures in Japan are “older” than their actual age due to the poor quality of concrete used during Japan’s high-growth period (1960’s). Infrastructure constructed in the early 1900’s in the U.S. has also similarly aged. In recent years, many structures tend to be maintained or their performance managed due to environmental problems, such as waste of resources (e.g., tile, glass, wood) and increase in non-recycled products (e.g., columns, wallpaper, floor covering). Interest in applying a monitoring system to such structures has been strong in order to maintain and manage performance of a building to assure its safety and functionality. Although methods to detect damage sites and to determine the extent of the damage have been actively researched, no study has indicated the final application of their methods.
A Secure Method for Network Coding-based Reprogramming Protocols in Wireless Sensor Networks

Reprogramming protocols provide a convenient way to update program images via wireless communication. In hostile environments where there may be malicious attacks against wireless sensor networks, the process of reprogramming faces threats from potentially compromised nodes. While existing solutions can provide authentication services, they are insufficient for a new generation of network coding-based reprogramming protocols in wireless sensor networks. We present a security approach that is able to defend pollution attack against reprogramming protocols based on network coding. It employs a homomorphic hashing function and an identity-based aggregate signature to allow sensor nodes to check packets on-the-fly before they accept incoming encoded packets, and introduces an efficient mechanism to reduce the computation overhead at each node and to eliminate bad packets quickly. Castalia simulations show that when the 5% of the nodes in a network of 100 nodes are rogue, using our approach, the efficiency of the secure reprogramming protocol based on network coding improves almost ten-fold for a checking probability of 2%.
Efficient type-ahead search on relational data: a TASTIER approach

Existing keyword-search systems in relational databases require users to submit a complete query to compute answers. Often users feel "left in the dark" when they have limited knowledge about the data, and have to use a try-and-see approach for modifying queries and finding answers. In this paper we propose a novel approach to keyword search in the relational world, called Tastier. A Tastier system can bring instant gratification to users by supporting type-ahead search, which finds answers "on the fly" as the user types in query keywords. A main challenge is how to achieve a high interactive speed for large amounts of data in multiple tables, so that a query can be answered efficiently within milliseconds. We propose efficient index structures and algorithms for finding relevant answers on-the-fly by joining tuples in the database. We devise a partition-based method to improve query performance by grouping highly relevant tuples and pruning irrelevant tuples efficiently. We also develop a technique to answer a query efficiently by predicting the highly relevant complete queries for the user. We have conducted a thorough experimental evaluation of the proposed techniques on real data sets to demonstrate the efficiency and practicality of this new search paradigm.
BROAD BAND DIELECTRIC SPECTROSCOPY USING AN OPEN-ENDED LINE

In this work a method of broad band dielectric spectroscopy using an open-ended line is proposed. The mathematical development of this method leads to a transcendental equation on the complex plane that possesses infinite solutions. A numerical procedure is described which is capable of obtaining the solution required avoiding the problem of infinite solutions. The study of this equation suggests that even large errors in the experimental parameters induce only small uncertainties in the complex permittivity of the sample, and the thinner the sample the lower the uncertainty. An ad hoc sample holder with a characteristic impedance of 50 Ω was designed and built to implement the proposed method. It allows temperature control and can be connected to three different measuring devices: the precision LCR meters HP 4284A (20 Hz – 1 MHz) and HP4285A (75 kHz – 30 MHz) and the vectorial network analyzer HP8719D (50 MHz – 13 GHz). The work frequency is limited from above by the geometric characteristics of the sample holder and the sample permittivity. The acquisition and treatment of the data have been automatized. For that purpose an interface HPIB has been used and a code has been developed in HTBasic 8.3 for Windows designed in order that the measurements can be carried out by a laboratory technician without specific knowledge of dielectric characterization. The measurements of polar and non polar samples have established the appropriateness of all the different steps carried out for the implementation of the technique.
Uniform Parallel Machines Scheduling Using a Genetic Algorithm

Scheduling problems are very important for many (research) fields like management, industrial engineering, operations research and computer science. However many instances of scheduling problems were proven to be NP-hard, therefore the use of heuristics is the de-facto approach in order to cope in practice with its difficulty. In this paper we consider instance problems from the class of uniform parallel machines and present a genetic algorithm for this class of scheduling problems (GASP). We report some preliminary results and the performance of the presented approach are compared with other optimization techniques. Empirical results indicate that GASP approach is more efficient.
From Regulation to Free Market: How to Explain the Experience of the European Motor Insurance Market

In some European countries, the liberalization of the motor insurance market occurred in the 1990s led to increasing fares and claims with profits staying stable or decreasing. In this paper, we argue that these phenomena are due to the impact of liberalization on the companies' optimal choices. In particular, in the context of a spatial competition model, we show that in the short run price deregulation entails decreasing investments in monitoring and increasing indemnification costs, such that prices may increase while profits remain unaltered. In the long run, when the number of firms changes endogenously, premiums can be higher or lower than premiums prevailing under regulation, according to the dominance of a "competition effect" connected to entries or a "monitoring effect" raising marginal costs.
Strong interference conditions for Multiple Access-Cognitive Interference Channel

In this paper, we analyze the capacity region of a communication network where a Multiple Access Channel (MAC) and a point-to-point channel share a same medium and interfere with each other, where the transmitter of the point-to-point channel has cognitive capabilities. We introduce Multiple Access-Cognitive Interference Channel (MA-CIFC), with a two-user MAC as a primary network and a cognitive transmitter-receiver pair in which the cognitive transmitter knows the message being sent by all of the transmitters in a non-causal manner. We obtain an inner bound on the capacity region of MA-CIFC and derive two sets of strong interference conditions under which we establish the capacity regions. We also consider the Gaussian case and find capacity results for Gaussian MA-CIFC. Some numerical examples are also provided.
Limits and Loopholes: The Quest for Money, Free Speech, and Fair Elections

This title comes from the authors of "Legislative Labyrinth: Congress and Campaign Finance Reform". Elections, the basic mechanism of representative democracy, should be untainted by corruption and provide a platform for free speech. But running for office takes money - a lot of it, usually - which means campaign finance has become a pitched battle over the fundamental political values of free speech versus fair elections. With insiders' perspectives, Farrar-Myers and Dwyre tell the story of what it took to pass campaign finance legislation, provide analysis of the subsequent court action, and explore the regulatory and electoral outcomes of reform efforts. "Limits and Loopholes" is a story about incremental policymaking and inter-branch struggle, about institutional design and unintended consequences, about the influence of interest groups and the media, and about the health of our representative democracy. Bringing together discussions of core values and the policymaking process, this book serves as an excellent case study that traces an issue from inception, through legislation and litigation, and finally to implementation.
Fully-Automated Power Line Extraction from Airborne Laser Scanning Point Clouds in Forest Areas

High-voltage power lines can be quite easily mapped using laser scanning data, because vegetation close to high-voltage lines is typically removed and also because the power lines are located higher off the ground in contrast to regional networks and lower voltage networks. On the contrary, lower voltage power lines are located in the middle of dense forests, and it is difficult to classify power lines in such an environment. This paper proposes an automated power line detection method for forest environments. Our method was developed based on statistical analysis and 2D image-based processing technology. During the process of statistical analysis, a set of criteria (e.g., height criteria, density criteria and histogram thresholds) is applied for selecting the candidates for power lines. After transforming the candidates to a binary image, image-based processing technology is employed. Object geometric properties are considered as criteria for power line detection. This method was conducted in six sets of airborne laser scanning (ALS) data from different forest environments. By comparison with reference data, 93.26% of power line points were correctly classified. The advantages and disadvantages of the methods were analyzed and discussed.
An Online Dictionary Learning-Based Compressive Data Gathering Algorithm in Wireless Sensor Networks

To adapt to sense signals of enormous diversities and dynamics, and to decrease the reconstruction errors caused by ambient noise, a novel online dictionary learning method-based compressive data gathering (ODL-CDG) algorithm is proposed. The proposed dictionary is learned from a two-stage iterative procedure, alternately changing between a sparse coding step and a dictionary update step. The self-coherence of the learned dictionary is introduced as a penalty term during the dictionary update procedure. The dictionary is also constrained with sparse structure. It’s theoretically demonstrated that the sensing matrix satisfies the restricted isometry property (RIP) with high probability. In addition, the lower bound of necessary number of measurements for compressive sensing (CS) reconstruction is given. Simulation results show that the proposed ODL-CDG algorithm can enhance the recovery accuracy in the presence of noise, and reduce the energy consumption in comparison with other dictionary based data gathering methods.
What is the Impact of Imbalance on Software Defect Prediction Performance?

Software defect prediction performance varies over a large range. Menzies suggested there is a ceiling effect of 80% Recall [8]. Most of the data sets used are highly imbalanced. This paper asks, what is the empirical effect of using different datasets with varying levels of imbalance on predictive performance? We use data synthesised by a previous meta-analysis of 600 fault prediction models and their results. Four model evaluation measures (the Mathews Correlation Coefficient (MCC), F-Measure, Precision and Recall) are compared to the corresponding data imbalance ratio. When the data are imbalanced, the predictive performance of software defect prediction studies is low. As the data become more balanced, the predictive performance of prediction models increases, from an average MCC of 0.15, until the minority class makes up 20% of the instances in the dataset, where the MCC reaches an average value of about 0.34. As the proportion of the minority class increases above 20%, the predictive performance does not significantly increase. Using datasets with more than 20% of the instances being defective has not had a significant impact on the predictive performance when using MCC. We conclude that comparing the results of defect prediction studies should take into account the imbalance of the data.
The combined walkthrough: measuring behavioral, affective, and cognitive information in usability testing

This paper describes an experiment in studying users' behavior, emotions, and cognitive processes in single usability testing sessions using an experimental method called the combined walkthrough. The users' behavior was studied using task times and completion rates, and emotions were studied using bipolar scales for experienced valence and arousal. Cognition was studied after each task by revisiting detected usability problems together with the users and applying an interactive method based on cognitive walkthrough to each usability problem. An interactive media application was tested with 16 participants using these methods. The results of the experiment showed that the developed methods were efficient in identifying usability problems and measuring the different aspects of interaction, which enabled the researchers to obtain a more multifaceted view of the users' interaction with the system and the nature of the problems encountered.
Authoritarian Elections and Leadership Succession, 1975-2004

Why do non-democratic regimes hold elections they might lose? In this paper, I develop a model in which authoritarian rulers agree to positive levels of electoral risk primarily to gain information that reduces the risk of their violent removal from office via a coup d’etat or revolution. Using a comprehensive database documenting how the world’s leaders exited from office, I provide evidence that elections help authoritarian regimes regulate succession to their top posts. There is evidence of both regime effects (e.g., leaders of multi-party authoritarian regimes are more likely to exit electorally and less likely to exit violently) and electoral-cycle effects (violent and peaceful exits vary systematically across the electoral cycle in multi-party regimes).
Path prediction based on second-order Markov chain for the opportunistic networks

In the opportunistic networks, nodes carry and store the data and forward it until they encounter each other. How to choose an appropriate opportunity to forward data is pivotal for nodes' routing in this type of networks. Since nodes currently will keep a regular movement state in the scene of this paper discussed, forecasting a node's moving track in the near future would be very helpful. Through this way, the node can modify the forwarding strategy in time and increase the success rate of data routing. We proposed a path prediction model based on second-order Markov chain in this paper to analyze and predict node's next path choice at an intersection depending on its statistic of history tracks. Then we use the real data from Dartmouth College to verify the model and the result shows that it is more precise than normal one step Markov models and is more reasonable than some other models such as Manhattan model.
Performance Improvement of Routing Protocol in Ad-hoc Networks Using Smart Antenna with Balance Load

We have presented a balanced routing protocol for Mobile Ad-hoc Networks using the smart antenna in this paper. Multipath routing can be effectively used to maximize the utilization of network resources for real-time traffic. In mobile ad-hoc network, this approach can suffer from co-channel interference or route coupling due to simultaneous transmission of packets via multiple routes. We use zone-disjoint routes and define maximally zone disjointness as route selection criteria. An adaptive routing strategy is proposed that use the advantages of directional antennas in ad hoc networks through the selection of maximally zone disjoint routes. Zone-disjoint routes would reduce the route coupling effect in wireless media by selecting routes in such that it produce minimal interference among communication over multiple routes. The proposed routing protocol provide effective load balancing in wireless media and it is implemented for both single path and multipath routing on ad hoc networks with directional antennas. Simulation results show that zone-disjoint single path routing can produce better throughput compare to multipath and AODV (Ad-hoc on-demand distance vector) routing protocol for more number of simultaneous communications.
Limitations of concurrency in transaction processing

Given the pairwise probability of conflict p among transactions in a transaction processing system, together with the total number of concurrent transactions n, the effective level of concurrency E(n,p) is defined as the expected number of the n transactions that can run concurrently and actually do useful work. Using a random graph model of concurrency, we show for three general classes of concurrency control methods, examples of which are (1) standard locking, (2) strict priority scheduling, and (3) optimistic methods, that (1) E(n, p) ⩽ n(1 - p/2)n-1, (2) E(n, p) ⩽ (1 - (1 - p)n)/p, and (3) 1 + ((1 - p)/p)ln(p(n - 1) + 1) ⩽ E(n, p) ⩽ 1 + (1/p)ln(p(n - 1) + 1). Thus, for fixed p, as n ↣ ∞), (1) E ↣ 0 for standard locking methods, (2) E ⩽ 1/p for strict priority scheduling methods, and (3) E ↣ ∞ for optimistic methods. Also found are bounds on E in the case where conflicts are analyzed so as to maximize E. The predictions of the random graph model are confirmed by simulations of an abstract transaction processing system. In practice, though, there is a price to pay for the increased effective level of concurrency of methods (2) and (3): using these methods there is more wasted work (i.e., more steps executed by transactions that are later aborted). In response to this problem, three new concurrency control methods suggested by the random graph model analysis are developed. Two of these, called (a) running priority and (b) older or running priority, are shown by the simulation results to perform better than the previously known methods (l)-(3) for relatively large n or large p, in terms of achieving a high effective level of concurrency at a comparatively small cost in wasted work.
An evaluation of current ship wake detection algorithms en SAR images

SHORT ABSTRACT: Ship wakes are often used as the primary means to detect ships in SAR images since they can extend for kilometers. On radar images, they often take the appearance of bright and/or dark lines hidden in the sea clutter. For this reason, robust and efficient line detection algorithms are needed. Our first results tend to support the classical method relying on the Radon Transform and confirm the improvements brought the recently proposed stochastic matched filtering (proposed in 2005), but are somewhat mitigated about the wavelet correlator (proposed in 2003), the Hough Transform or the use of Wiener filtering to improve the Radon Transform thresholding.
A generalized network alignment for three-source three-destination multiple unicast networks with delays

The concept of interference alignment when extended to three-source three-destination instantaneous multiple unicast network for the case where, each source-destination pair has a min-cut of 1 and zero-interference conditions are not satisfied, is known to achieve a rate of half for every source-destination pair under certain conditions [6]. This was called network alignment. We generalize this concept of network alignment to three-source three-destination multiple unicast (3S-3D-MU) networks with delays, without making use of memory at the intermediate nodes (i.e., nodes other than the sources and destinations) and using time varying Local Encoding Kernels (LEKs). This achieves half the rate corresponding to the individual source-destination min-cut for some classes of 3S-3D-MU network with delays which do not satisfy the zero-interference conditions.
Adaptive Real-Time Compressive Tracking

The real-time compressive tracking algorithm, proposed by Kaihua Zhang etc. in 2012, is real-time and robust. But this algorithm may lead to object tracking losing in some complex environments, such as pose variation, illumination change, occlusion, and motion blur etc. This paper improves the compressive tracking algorithm in two aspects: (1) we propose a self-adaptive method for learning parameter of the compressive tracking algorithm to enhance the robustness; (2)To solve the problem of losing tracking object, we propose a method using cosine algorithm to judge whether the object is lost and retrieve the lost object again. A number of video object tracking experiments show that the improved algorithm is more effective and efficient.
Is Australian unemployment Keynesian or neo-classical?: a disequilibrium approach to unemployment

The basic aim of this thesis is to investigate unemployment in Australia using a disequilibrium framework. In particular, involuntary unemployment is examined from both a Keynesian and a Classical perspective. As a consequence, both Classical and Keynesian doctrines were interpreted as disequilibrium theories called Neo-Classical and (New) Keynesian respectively. Examined within a (New) Keynesian (disequilibrium) theory an unambiguous definition of involuntary unemployment emerges. The Neo-Classical (disequilibrium) theory, unlike the Classical theory, also allows for bouts of involuntary unemployment. Consequently, a distinction between Neo-Classical and (New) Keynesian involuntary unemployment is considered a matter of degree rather than principle; if wages adjust more rapidly than employment toward equilibrium, then unemployment would be Neo-Classical. Furthermore, since involuntary unemployment is a disequilibrium concept, the unemployment model was estimated using a disequilibrium procedure. After reviewing the econometrics and theory of disequilibrium a generalized partial adjustment equation, developed by Chow (1983), was adopted. This procedure has distinct advantages over other techniques. The unemployment model was estimated for Australia over two periods: 1964 to 1972 for the first period and from 1972 to 1986 for the second period. It was found that neither period could be classified as either pure (New) Keynesian or Neo-Classical; however, there is evidence of elements of both theories in each period. This thesis also examined structural and search unemployment. Finally, evidence of labour dishoarding in period two was also found.
Analytical comparison of various fiber-optic CDMA receiver structures

We study the performance of optical code-division multiple access (CDMA) systems using various receivers structures. Two general classes of receivers based on required electronic bandwidth are studied. Optical orthogonal codes (OOCs) are utilized as signature sequences and the performance studied in this paper takes into account the effect of all major noise sources, i.e., quantum shot-noise, dark current noise, and Gaussian circuit noise. Furthermore, this paper introduces a generalized method of analyzing the performance of various optical CDMA receiver structures. Required mean number of photon count per chip time for reliable transmission of data bits for various receiver structures is investigated. Finally, the advantages and disadvantages of various receiver structures are discussed.