Miracle-dz/UniFAR-FTUs huggingface dataset:
A pivot-based index structure for combination of feature vectors

We present a novel indexing schema that provides efficient nearest-neighbor queries in multimedia databases consisting of objects described by multiple feature vectors. The benefits of the simultaneous usage of several (statically or dynamically) weighted feature vectors with respect to retrieval effectiveness have been previously demonstrated. Support for efficient multi-feature vector similarity queries is an open problem, as existing indexing methods do not support dynamically parameterized distance functions. We present a solution for this problem relying on a combination of several pivot-based metric indices. We define the index structure, present algorithms for performing nearest-neighbor queries on these structures, and demonstrate the feasibility by experiments conducted on two real-world image databases. The experimental results show a significant performance improvement over existing access methods.
Analysis of impacts of strategic human resource management innovation-oriented on enterprise performance

300 samples from 21 organizations in Meizhou were surveyed through questionnaire investigation(Effective ones are 208, accounting for 69.33%). The research carried on reliability analysis and validity analyses using the SPSS software. This research also executed regression analysis on the independent variable indexes and the extracted performance indexes. The result shows, strategic human resource management innovation-oriented is positively correlated with enterprise's both financial performance and non-financial performance.
Receptive field cooccurrence histograms for object detection

Object recognition is one of the major research topics in the field of computer vision. In robotics, there is often a need for a system that can locate certain objects in the environment - the capability which we denote as 'object detection'. In this paper, we present a new method for object detection. The method is especially suitable for detecting objects in natural scenes, as it is able to cope with problems such as complex background, varying illumination and object occlusion. The proposed method uses the receptive field representation where each pixel in the image is represented by a combination of its color and response to different filters. Thus, the cooccurrence of certain filter responses within a specific radius in the image serves as information basis for building the representation of the object. The specific goal in this paper is the development of an online learning scheme that is effective after just one training example but still has the ability to improve its performance with more time and new examples. We describe the details behind the algorithm and demonstrate its strength with an extensive experimental evaluation.
Towards a completeness result for model checking of security protocols

Model checking approaches to the analysis of security protocols have proved remarkably successful. The basic approach is to produce a model of a small system running the protocol, together with a model of the most general intruder who can interact with the protocol, and then to use a state exploration tool to search for attacks. This has led to a number of new attacks upon protocols being discovered. However if no attack is found, this only tells one that there is no attack upon the small system modelled; there may be an attack upon some larger system. This is the question considered in the paper: the author presents sufficient conditions on the protocol and its environment such that if there is no attack upon a particular small system (with one honest agent for each role of the protocol) leading to a breach of secrecy (using a fairly strong definition of secrecy), then there is no attack on any larger system leading to a breach of secrecy (using a more general definition of secrecy).
Health-Promoting Spatial Planning: Approaches for Strengthening Urban Policy Integration

Abstract Improving urban population health requires integrated spatial planning to create liveable communities, with affordable housing and daily living destinations accessible via walking, cycling and/or public transport. Integration must occur horizontally across transport, housing, employment, education and social infrastructure sectors, and vertically between levels of government. While horizontal integrated planning is a common urban policy aspiration, there is a lack of clarity on how it can be attained. Using a case study of Melbourne, Australia, this paper draws on interviews with state government policymakers and policy content analysis, to explore barriers and enablers of horizontal integrated planning for health. Key requirements for integrated planning are outlined, to assist policymakers in creating healthy, liveable communities.
Analysis of Social Networking Sites Using K- Mean Clustering Algorithm

Clustering is one of the very important technique used for classification of large dataset and widely applied to many applications including analysis of social networking sites, aircraft accidental, company performance etc. In recent days, Communication, advertising through social networking sites are most popular and interactive strategy among the users. This research attempts to find the large scale measurement study and analysis, effectiveness of communication strategy, analyzing the information about the usage, people's interest in social network sites in promoting and advertising their brand in social networking sites. The significance of the proposed work is determined with the help of various surveys, and from people who use these sites. Further a more specific pre-processing method is applied to clean data and perform the clustering method to generate patterns that will be work as heuristics for designing more effective social networking sites.
Determine the Hardware Choice to Improve HDFS Performance Deployed in a Commodity Cluster

The importance of storing and processing data eficiently is intensively highlighted in modern information technology infrastructures. Hadoop Distributed File System (HDFS) acts as the primary storage in modern cloud service environments and has been widely adopted for its portability and fault-tolerance. Current deployment of HDFS which runs on top of commodity hardware is unable to deliver desirable performance in terms of both latency and throughput. For data-intensive applications, I / O pressure becomes more exacerbated as the amount of data being stored and replicated to HDFS increases. In order to process extremely huge volume of data, investing in high-end hardware is one available practice. The primary contribution of this paper is to determine the I/O bottleneck for HDFS using both hardware and software approach and hence suggest corresponding solutions. Benchmarks and productivity tools are used to evaluate the proposed measure of improvement. The final conclusion about the crucial factor of the HDFS I/O performance is drawn based on experimental results.
Using Strategy Maps to Align Distributed Service Organizations

The paper introduces the importance of industrial services for manufacturers of capital goods and it analyzes the specific challenges in global service networks. It thereby emphasizes knowledge and information exchanges and the related coordination problem within the diversified organization. A strategy map framework is proposed to assess the interrelated dependencies between different organizational and functional units. It was found that the adapted Industrial Service Strategy Map facilitates the coordination and controlling of the service operations in distributed organizations by aligning the diversified goals with overall network performance objectives.
Electrical Model Simulation for a UHF RFID System

Radio Frequency IDentification (RFID) deployment is needed for efficient item identification. A simulation environment in HP-ADS (Advanced Design System of Agilent Technologies) of Ultra High Frequency RFID systems is constructed in this paper. This paper simulates the system through an electrical model. The tag is represented by a simple empirical model representing the antenna by an amplifier and the chip. The chip is modeled by its impedance which varies with the code. A wireless channel with path loss and variable distance factors establishes the reader-tag link. The reader has a mono-static architecture. Performance of the whole system can be evaluated by changing the operating distance. Modeling improvement can be obtained by modifying the parameters of the building blocks. Finally, some simulation results are also included in this paper where data recovery is achieved.
A pure Nash equilibrium guaranteeing game theoretical replica allocation method for reducing Web access time

This paper proposes a non-cooperative game theoretical replica allocation technique (NCOR) to reduce user perceived Web access delays. NCOR uses distributed agents that because of their local knowledge act in a self-interested manner in order to enhance the performance of the servers that they represent. This can lead to some performance gains for some servers but has the potential to negatively impact the overall system's performance. NCOR uses an effective cost model to guarantee the overall system performance gain despite the self-interested actions of these agents. With spontaneous and non-deterministic strategies, the system can exhibit Nash equilibrium. However, that may or may not guaranteed system-wide performance at a given time. Furthermore, their can be multiple Nash equilibria, making it difficult to decide which one is the best. Instead, we use the notion of pure Nash equilibrium, which if achieved is guaranteed to ensure stable optimal performance. Pure Nash equilibrium can be only achieved by deterministic strategies. In general, the existence of a pure Nash equilibrium is remarkably hard to achieve; however, we prove the existence of such an equilibrium in NCOR. Experimental comparisons with several non-game theoretical techniques reveal that NCOR maintains superior solution quality, in terms of lower communication cost and reduced execution time
Towards a Monitoring Middleware for Cloud Services

Cloud Computing represents a new trend in the development and use of software. Many organizations are currently adopting the use of services that are hosted in the cloud by employing the Software as a Service (SaaS) model. Services are typically accompanied by a Service Level Agreement (SLA), which defines the quality terms that a provider offers to its customers. Many monitoring tools have been proposed to report compliance with the SLA. However, they have some limitations when changes to monitoring requirements must be made and because of the complexity involved in capturing low-level raw data from services at runtime. In this paper, we propose the design of a platform-independent monitoring middleware for cloud services, which supports the monitoring of SLA compliance and provides a report containing SLA violations that may help stakeholders to make decisions regarding how to improve the quality of cloud services. Moreover, our middleware definition is based on the use of models@run.time, which allows the dynamic change of quality requirements and/or the dynamic selection of different metric operationalizations (i.e., Calculation formulas) with which to measure the quality of services. In order to demonstrate the feasibility of our approach, we show the instantiation of the proposed middleware that can be used to monitor services when deployed on the Microsoft Azure© platform.
A Robust Fitness Measure for Capturing Repetitions in Music Recordings With Applications to Audio Thumbnailing

The automatic extraction of structural information from music recordings constitutes a central research topic. In this paper, we deal with a subproblem of audio structure analysis called audio thumbnailing with the goal to determine the audio segment that best represents a given music recording. Typically, such a segment has many (approximate) repetitions covering large parts of the recording. As the main technical contribution, we introduce a novel fitness measure that assigns a fitness value to each segment that expresses how much and how well the segment “explains” the repetitive structure of the entire recording. The thumbnail is then defined to be the fitness-maximizing segment. To compute the fitness measure, we describe an optimization scheme that jointly performs two error-prone steps, path extraction and grouping, which are usually performed successively. As a result, our approach is even able to cope with strong musical and acoustic variations that may occur within and across related segments. As a further contribution, we introduce the concept of fitness scape plots that reveal global structural properties of an entire recording. Finally, to show the robustness and practicability of our thumbnailing approach, we present various experiments based on different audio collections that comprise popular music, classical music, and folk song field recordings.
Efficient provisioning of bursty scientific workloads on the cloud using adaptive elasticity control

Elasticity is the ability of a cloud infrastructure to dynamically change the amount of resources allocated to a running service as load changes. We build an autonomous elasticity controller that changes the number of virtual machines allocated to a service based on both monitored load changes and predictions of future load. The cloud infrastructure is modeled as a G/G/N queue. This model is used to construct a hybrid reactive-adaptive controller that quickly reacts to sudden load changes, prevents premature release of resources, takes into account the heterogeneity of the workload, and avoids oscillations. Using simulations with Web and cluster workload traces, we show that our proposed controller lowers the number of delayed requests by a factor of 70 for the Web traces and 3 for the cluster traces when compared to a reactive controller. Our controller also decreases the average number of queued requests by a factor of 3 for both traces, and reduces oscillations by a factor of 7 for the Web traces and 3 for the cluster traces. This comes at the expense of between 20% and 30% over-provisioning, as compared to a few percent for the reactive controller.
Iterative Hard Thresholding and L0 Regularisation

Sparse signal approximations are approximations that use only a small number of elementary waveforms to describe a signal. In this paper we proof the convergence of an iterative hard thresholding algorithm and show, that the fixed points of that algorithm are local minima of the sparse approximation cost function, which measures both, the reconstruction error and the number of elements in the representation. Simulation results suggest that the algorithm is comparable in performance to a commonly used alternative method.
A Novel Approach Based on Finite-State Machines with Fuzzy Transitions for Nonintrusive Home Appliance Monitoring

Recent studies have highlighted that a significant part of the electrical energy consumption in residential buildings is caused by an improper use of home appliances. The development of low-cost systems for profiling the consumption of electric appliances can play a key role in stimulating the users to adopt adequate policies for energy saving. In this paper, we describe a novel methodology for extracting the power consumption of each appliance deployed in a domestic environment from the aggregate measures collected by a single smart meter. In order to coarsely describe how each type of appliance works, we use finite-state machines (FSMs) based on fuzzy transitions. An ad-hoc disaggregation algorithm exploits a database of these FSMs for, at each meaningful variation in real and reactive aggregate powers, hypothesizing possible configurations of active appliances. This set of configurations is concurrently managed by the algorithm which, whenever requested, outputs the configuration with the highest confidence with respect to the sequence of detected events. We implemented a prototype of a monitoring system based on the proposed methodology and installed it in a real domestic scenario. We discuss an experiment in which 11 appliances were connected to the same circuit and the aggregate power consumption was measured by a smart meter for approximately 12 h. At the end of the experiment, only two possible configurations were outputs from the system, including the correct one.
Optimum sir balancing using extended 1-norm beamforming optimization

We address the problem of joint downlink beamforming and power control in a wireless cellular system, where several users share the same time slot and the same frequency band. In order to enable a fair sharing of resources among all users, the SIR levels should be balanced by minimizing the ∞-norm of a certain vector. To this end, Gerlach and Paulraj [1] proposed an iterative algorithm, which is based on a 1-norm cost function. It has been observed that this algorithm approximates the optimum ∞-norm solution. In this paper we characterize the case where this algorithm is optimal. The analytical results are used to develop a new algorithm, which always converges to the optimum ∞-norm solution, regardless of the chosen initialization. A proof of convergence is given.
Focusing crimes of honour through drama

This paper has been developed on the basis of research conducted in two projects. A special emphasis is however given to one of the projects concerning an evaluation of a drama pedagogical project. The evaluation is specifically aimed at the efficiency, intensity and depth of the educational drama input in mediating cultural messages from the play, The hat is Yours played by a professional Theatre group. The play was shown to all students of a junior high school during the autumn term of 2002. Data were gathered from 16 students (7 girls and 9 boys), 6 teachers, 5 performers, the director of the play and the playwright. Classroom observations were conducted during post play/performance sessions held at the specified school in classroom settings with all in all 60 students. The findings suggest that both the play and the project were viewed positively. All the students interviewed loved the performance and appreciated the efforts to instil drama as a discipline and broaden understandings of ‘cultural messages’ through imaginative learning and perspective taking and from the students’ responses and active engagement in the sessions it may be safely inferred that some form of emotional and intellectual processes are being triggered, sparked by the unique nature of the play itself. However, the pedagogical reconstructions of the play in classroom sessions also offer moments for reflection and the students’ voices are unanimously supportive of the educational drama efforts in the classroom. There were mixed opinions among the professional actors/actresses about moralising dramatic scenes and solving problems in a manner believed to be ‘right’ by one group of people or ‘civilisation. This is a thorny issue that should be debated further as should the number of issues that the play purposely left unsolved. We are also of the opinion that the effort should be further nurtured and extended to actively engage the whole school community on a regular basis. Our observation of several schools in Goteborg where the majority of the students are minority pupils and socially disadvantaged children testifies to the fact that these groups of students may genuinely benefit from drama not only as a form of aesthetic expression but also as a medium to interest them in other subjects. Key words: Honour crimes (murder), drama pedagogy, alienation, segregation, intercultural mediation
An incremental temporal partitioning method for real-time reconfigurable systems

In this paper, a temporal partitioning algorithm is presented which partitions data flow graphs in a real-time domain. Timing constraint is a critical factor in temporal partitioning of real-time reconfigurable design. An incremental algorithm is presented to partition data flow graphs while meeting the timing constraints by obtaining the target number of partitions. In addition, the proposed algorithm attempts to minimize the logic resources used for implementing the real-time application. In this algorithm, selecting the appropriate nodes and moving them between subsequent partitions results in more area balanced partitions and less number of partitions.
SonoSketch: Querying Sound Effect Databases through Painting

Numerous techniques support finding sounds that are acoustically similar to a given one. It is hard, however, to find a sound to start the similarity search with. Inspired by systems for image search that allow drawing the shape to be found, we address quick input for audio retrieval. In our system, the user literally sketches a sound effect, placing curved strokes on a canvas. Each of these represents one sound from a collection of basic sounds. The audio feedback is interactive, as is the continuous update of the list of retrieval results. The retrieval is based on symbol sequences formed from MFCC data compared with the help of a neural net using an editing distance to allow small temporal changes.
Other-Regarding Preferences in General Equilibrium

We study competitive market outcomes in economies where agents have other-regarding preferences. We identify a separability condition on monotone preferences that is necessary and sufficient for one’s own demand to be independent of the allocations and characteristics of other agents in the economy. Given separability, it is impossible to identify other-regarding preferences from market behavior: agents be- have as if they had classical preferences that depend only on own consumption in competitive equilibrium. If preferences, in addition, depend only on the final allocation of consumption in society, the Sec- ond Welfare Theorem holds as long as an increase in resources can be distributed such that all agents are better off. Nevertheless, the First Welfare Theorem generally does not hold. Allowing agents to care about their own consumption and the distribution of consump- tion possibilities in the economy, we provide a condition under which agents have no incentive to make direct transfers, and show that this condition implies that competitive equilibria are efficient given prices.
An algebraic description of programs with assertions, verification and simulation

A program in flow diagram form is described by a function from a free category to the category of sets and relations. Attaching assertions to it is described as a natural transformation and so is simulation of one program by another with the same shape of flow diagram. These notions are used to prove the theorems justifying Floyd's method of proving correctness by verification and Milner's method of proving simulation, restricted to programs of similar form. The treatment is novel but the results are not new, except that non-deterministic programs are dealt with throughout.