Miracle-dz/UniFAR-FTUs huggingface dataset:
The Hand Mouse: GMM hand-color classification and mean shift tracking

This paper describes an algorithm to detect and track a hand in each image taken by a wearable camera. We primarily use color information, however, instead of pre-defined skin-color models, we dynamically construct hand- and background-color models by using a Gaussian mixture model (GMM) to approximate the color histogram. Not only to obtain the estimated mean of hand color necessary for the restricted EM algorithm that estimates the GMM but also to classify hand pixels based on the Bayes decision theory, we use a spatial probability distribution of hand pixels. Since the static distribution is inadequate for the hand-tracking stage, we translate the distribution with the hand motion based on the mean shift algorithm. Using the proposed method, we implemented the Hand Mouse that uses the wearer's hand as a pointing device, on our wearable vision system.
Culturally Responsive Evaluation Meets Systems-Oriented Evaluation

The authors of this article each bring a different theoretical background to their evaluation practice. The first author has a background of attention to culturally responsive evaluation (CRE), while the second author has a background of attention to systems theories and their application to evaluation. Both have had their own evolution of thinking and application of their respective conceptual traditions over the last 20+ years, influenced considerably by their involvement in the American Evaluation Association. They recently worked together to build evaluation capacity among evaluators of science, technology, engineering, and mathematics (STEM) education programs, in which they explored how these two conceptual and theoretical paths connect. In this article, the authors present their current thinking about the relationship between CRE and systems-oriented evaluation. In a case example, they illustrate the value of integrating the two perspectives to determine the guiding questions for an evaluation of a STEM education project.
On the Use of Binary Programming for Sensor Scheduling

In this paper, we propose two myopic sensor scheduling algorithms for target tracking scenarios in which there is a tradeoff between tracking performance and sensor-usage costs. Specifically, we consider the problem of activating the lowest cost combination of at most L sensors that maintains a desired squared-error accuracy in the target's position estimate. For sensors that provide position information only, we develop a binary (0-1) mixed integer programming formulation for the scheduling problem and solve it using a linear programming relaxation-based branch-and-bound technique. For sensors that provide both position and velocity information, we pose the scheduling problem as a binary convex programming problem and solve it using the outer approximation algorithm. We apply our scheduling procedures in a network of sensors where the sensor-usage costs correspond to network energy consumption. Our simulation results demonstrate that scheduling using binary programming allows us to obtain optimal solutions to scheduling involving up to 50-70 sensors typically in the order of seconds
A New Jpeg Image Scaling Algorithm Based on the Area Pixel Model

--------------------------------------------------ABSTRACT-------------------------------------------------------- Image scaling is a very important technique and has been widely used in many image processing applications. In this paper, we present an edge-oriented area-pixel scaling processor. To achieve the goal of low cost, the area-pixel scaling technique is implemented with a low-complexity VLSI architecture in our design. A simple edge catching technique is adopted to preserve the image edge features effectively so as to achieve better image quality. Compared with the previous low-complexity techniques, our method performs better in terms of both quantitative evaluation and visual quality. The seven-stage VLSI architecture of our image scaling processor contains 10.4-K gate counts and yield a processing rate of about 200 MHz by using TSMC 0.18-m technology. --------------------------------------------------------------------------------------------------------------------------------------
Antecedents and consequences of trust in supply chain: the role of information technology

Trust has been a central construct in studies of inter-firm relationships. Many operational, organizational, social, and cultural factors have been identified to have significant impact on inter-firm trust. In this study, we investigate the role of information technology in generating inter-firm trust and the consequences of this trust in the context of supply networks. Using structural equation modeling techniques, our data show that the level of information systems integration among the partner firms in a supply network significantly impacts the trust among the firms which, together with the integrated information systems, explains more than half of the variances in information sharing and business process coupling in the network. Given the substantial evidence in the literature on the impact of information sharing and process coupling on supply chain performance, we conclude that information systems integration among the partners is critical to supply network performance. We also confirm that information systems flexibility and use of standards in information systems significantly contribute to the level of systems integration among the partners in supply networks as suggested in prior studies. Our findings extend the current literature on inter-firm trust by considering the role of information technology in addition to other important factors already identified.
Gabor Noise for Coherent

Stylized rendering algorithms, which aim at depicting 3D animated scenes with a pattern (i.e., watercolor pigments, strokes, paper grain, etc.), are facing the temporal coherence problem. To achieve successful temporal coherent stylization three constraints must be fulfilled: flatness (2D impression of the style), coherent motion (high correlation between the 3D motion field and the pattern motion) and temporal continuity (minimal changes from frame to frame). The conflicting nature of these goals implies that any solution to this problem is necessarily a compromise.
The Bang for the Birr: Public Expenditures and Rural Welfare in Ethiopia

Abstract This article explores the impact of different types of public spending on rural household welfare in Ethiopia. The analysis reveals that public spending on road infrastructure is characterised by relatively high, but regionally strongly concentrated, returns in terms of rural household welfare. This is quite in contrast to the returns to public expenditures in education, which have attributes of much wider reach but less intensity. Public investments in agriculture show results that are low in magnitude and in statistical significance, mostly due to a poor link between public expenditures in agriculture and productivity in the sector.
DCT-like Transform for Image Compression Requires 14 Additions Only

A low-complexity 8-point orthogonal approximate discrete cosine transform (DCT) is introduced. The proposed transform requires no multiplications or bit-shift operations. The derived fast algorithm requires only 14 additions, less than any existing DCT approximation. Moreover, in several image compression scenarios, the proposed transform could outperform the well-known signed DCT, as well as state-of-the-art algorithms.
Sparse PDF Volumes for Consistent Multi-Resolution Volume Rendering

This paper presents a new multi-resolution volume representation called sparse pdf volumes, which enables consistent multi-resolution volume rendering based on probability density functions (pdfs) of voxel neighborhoods. These pdfs are defined in the 4D domain jointly comprising the 3D volume and its 1D intensity range. Crucially, the computation of sparse pdf volumes exploits data coherence in 4D, resulting in a sparse representation with surprisingly low storage requirements. At run time, we dynamically apply transfer functions to the pdfs using simple and fast convolutions. Whereas standard low-pass filtering and down-sampling incur visible differences between resolution levels, the use of pdfs facilitates consistent results independent of the resolution level used. We describe the efficient out-of-core computation of large-scale sparse pdf volumes, using a novel iterative simplification procedure of a mixture of 4D Gaussians. Finally, our data structure is optimized to facilitate interactive multi-resolution volume rendering on GPUs.
Streamlining object-oriented software for deeply embedded applications

Most of today's computer systems are embedded and a substantial amount of them are deeply embedded systems with very limited resources. Object-oriented software is rarely to be found in those systems. We discuss reasons why object orientation is seldom used in this area. We also propose a set of design and implementation techniques based on modern object-oriented methods, which reconcile the reusability and flexibility of object-oriented software with the required efficiency of deeply embedded systems.
BER Analysis of Space Shift Keying in Cooperative Multi-Hop Multi-Branch DF Relaying

Space shift keying (SSK) is an attractive modulation technique for multi-antenna communications. In SSK, only one among the available transmit antennas is activated during one channel use, and the index of the chosen transmit antenna conveys information. In this paper, we analyze the performance of SSK in multi-hop, multi-branch cooperative relaying systems. We consider the decode-and-forward relaying protocol, where a relay forwards the decoded symbol if it decodes the symbol correctly from the received signal. We derive closed-form expressions for the end-to-end bit error rate of SSK in this system. Analytical and simulation results match very well.
2 . BACKGROUND 2 . 1 Support Vector Machines ( SVM ’ s )

Support Vector Machine (SVM) training is equivalent to solving a large constrained optimization problem. Much work has been spent on decompositional optimization methods for this problem, but non-decompositional approaches have only recently regained attention. Notably, Sentelle’s work in applying Rusin’s revised simplex method to SVM training demonstrated a significantly shorter training time for complex problems, but requires much more memory than the competing decompositional methods. We propose a revision to Sentelle’s approach, replacing his direct inner solver with an iterative solver: the preconditioned conjugate residual method. Results show an unexpected performance penalty, due to extreme ill-conditioning of the inner problems; avoiding this may require the creation of a specialized functional preconditioner.
Automatic detection of traffic lights using support vector machine

Many traffic accidents occurred at intersections are caused by drivers who miss or ignore the traffic signals. In this paper, we present a new method for automatic detection of traffic lights that integrates both image processing and support vector machine techniques. An experimental dataset with 21299 samples is built from the captured original videos while driving on the streets. When compared to the traditional object detection and existing methods, the proposed system provides significantly better performance with 96.97% precision and 99.43% recall. The system framework is extensible that users can introduce additional parameters to further improve the detection performance.
Selective self-adaptive approach to ant system for solving unit commitment problem

This paper presents a novel approach to solve the constrained unit commitment problem using Selective Self-Adaptive Ant System (SSAS) for improving search performance by automatically adapting ant populations and their transition probability parameters, which cooperates with Candidate Path Management Module (CPMM) and Effective Repairing Heuristic Module (ERHM) in reducing search space and recovering a feasible optimality region so that a high quality solution can be acquired in a very early iterative. The proposed SSAS algorithm not only enhances the convergence of search process, but also provides a suitable number of the population sharing which conducts a good guidance for trading-off between the importance of the visibility and the pheromone trail intensity. The proposed method has been performed on a test system up to 100 generating units with a scheduling time horizon of 24 hours. The numerical results show the most economical saving in the total operating cost when compared to the previous literature results. Moreover, the proposed SSAS topology can remarkably speed up the computation time of ant system algorithms, which is favorable for a large-scale unit commitment problem implementation.
Kalman filter based channel estimation in OFDM multi-user single-input-multi-output system

The linear MMSE receiver, which utilizes Kalman filter channel estimation, gives excellent performance in a highly time-varying environment. The use of this receiver design in an OFDM based multi-user single-input-multi-output (MU-SIMO) system is investigated. The complex nature and behaviour of the channel and noise are taken into consideration during this performance analysis. From simulation results, the symbol error rate (SER) performance of this system is found to be quite satisfactory with the use of channel estimation through a Kalman filter based linear MMSE receiver. By accurately tracking the phase of the time-varying channel, this receiver can effectively counter the 'carrier frequency offset' (CFO) problem.
Does mass customization pay? An economic approach to evaluate customer integration

The paper provides an integrated view of value creation in mass customization-based production models. While flexible manufacturing technologies are often seen as the main enabler of mass customization, we argue that modern information technologies play a similar important role. Their significance is based on enabling a distinctive principle of mass customization efficiently: customer integration into the production processes. The customer is integrated into value creation during the course of configuration, product specification and co-design. Customer integration is often seen as a necessity and source of additional costs of customization. However, we argue in this paper that customer integration may also be an important asset to increase efficiency and could pave the way for a new set of cost-saving potentials. We coin the term ‘economies of integration’ to sum up these saving potentials. Economies of integration arise from three sources: (1) from postponing some activities until an order is placed, (2) from more precise information about market demands and (3) from the ability to increase loyalty by directly interacting with each customer. By examining and structuring the economic principles of mass customization the paper will give insights into the benefits, but also the constraints of a mass customization strategy.
Optimization of some parameters in the speech-processing module developed for the speaker independent ASR system

This paper deals with looking for an optimum parameterization in automatic speech recognition systems working with the speech transferred over a telephone channel. The performed experiments were supported by a large collection of training data provided from telephone calls of at least one thousand speakers. MFCC and PLP cepstral parameterizations were tested with the aim to find the optimal number of filters and coefficients. Temporal patterns describing several adjacent frames of a given frame were verified in connection with techniques ensuring feature extraction and decorelation of pattern space.
Sequence recognition with scanning N-tuple ensembles

The scanning N-tuple classifier (SNT) is a fast and accurate method for classifying sequences. Applications include both on-line and off-line hand-written character recognition. SNTs have conventionally been trained using maximum likelihood parameter estimation. This paper describes a discriminative training rule that can be applied to ensembles of SNTs. Results demonstrate a significant improvement for the discriminative ensemble method. For comparison purposes we also implemented a support vector machine (SVM) operating in the sequence domain. We tested each method on a chain-coded version of the MNIST hand-written digit dataset. The SNT is not quite as accurate as the SVM, but is much faster both in training and recognition.
Analysis and Characteristic at the Chat Session Level in Instant Message Traffic

Instant messaging (IM) has become increasingly popular due to its social functionality. Despite its popularity and large user base, little has been done to the analysis and characteristic of the IM traffic, especially at the chat session level. In this paper, we analyze the traffic of two popular instant messaging systems, Yahoo messenger and MSN/Windows Live Messenger. We mainly consider the distribution of chat session level traffic between end users, and find the distribution in many cases follows a power law, as shown in recent work. This power law finding was previously used to support the hypothesis that chat interval time has a power law tail. We further show the scale property by V-T plot and R/S estimation. That is, the interval time is characterized by a strong self-similarity for larger time scales. And the packet arrival times are independent explaining the weak correlation of the data. Our analysis sheds light on instant messaging system design and optimization and provides a scientific basis for instant messaging traffic generation.
A restarted iterative homotopy analysis method for three-dimensional image segmentation

Total variational segmentation models provide effective tools for identifying all features and their boundaries in two and three dimensional images and have been proven to be useful and successful. Speeding up a simulation is one of the remaining challenges. In this paper we propose a restarted homotopy analysis method to improve the computational efficiency in three-dimensional image segmentation. The algorithm replaces the nonlinear variational problem by a sequence of linear approximations by working with linear equations instead of nonlinear ones which lead to efficient energy minimization while maintaining the segmentation quality. Experimental results will show that the computational efficiency is significantly improved.
Incentive compatible mechanism for coordinated temperature control in multi-occupant buildings

Minimizing the total energy consumption (cost) and maximizing the aggregate comfort across all building occupants, are two major objectives that must be balanced for effective environmental control in multi-occupant buildings and other shared spaces. Energy cost function for a given building is generally available (or can be measured/estimated) but information on the comfort ranges/functions are held privately by the occupants. In this work we present a game-theoretic (auction) mechanism, that requires occupants to “purchase” their individualized comfort levels beyond what is provided by default by the building operator. The comfort pricing policy is incentive-compatible in the sense that it elicits truthful comfort feedback from rational occupants acting only in self-interest. The declared (or estimated) occupant comfort ranges (functions) are then utilized by the building operator (HVAC system operator) - along with the energy cost information - to set the environment controls to optimally balance the aggregate discomfort of the occupants and the energy cost of the building operator. We use realistic building model and parameters based on our test facility to demonstrate the convergence of the actual temperatures in different zones to the desired temperatures, and provide insight to the pricing structure necessary for truthful comfort feedback from the occupants.
Does the “Project Manager” Still Exist in Agile Software Development Projects?

The project manager has been a ubiquitous feature of traditional software development projects. However, agile software development (ASD) methods which emphasize selforganizing teams and rapid response to change have done away with the project manager's title. New job titles such as the scrum master and product owner have been introduced instead. It is unclear as to what extent the "project manager" is still encountered in the agile software industry. An online survey was posted out to agile special interest groups on popular social media platforms to discover the frequency of the job title "project manager" in agile projects. Analysis of the 97 responses from 31 countries around the world revealed that: a) the title of project manager is still widely used (67%); b) there is a correlation between the team size and presence of project manager such that there is a higher probability the project manager will be present in teams of 5-10 members and those over 25 members; and c) there is an inverse correlation between the co-location of a team and presence of project manager. Further research is needed to better understand why the project manager continues to be present on ASD projects and how their role may have changed.
Using semijoin programs to solve traversal queries in graph databases

Graph data processing is gaining popularity and new solutions are appearing to analyze graphs efficiently. In this paper, we present the prototype for the new query engine of the Sparksee graph database, which is based on an algebra of operations on sets of key-value pairs. The new engine combines some regular relational database operations with some extensions oriented to collection processing and complex graph queries. We study the query plans of graph queries expressed in the new algebra, and find that most graph operations can be efficiently expressed as semijoin programs.
Hypoxia Inducible Factor-1α Directly Regulates Nuclear Clusterin Transcription by Interacting with Hypoxia Response Elements in the Clusterin Promoter

Differential transcription of the clusterin (CLU) gene yields two CLU isoforms, a nuclear form (nCLU) and a secretory form (sCLU), which play crucial roles in prostate tumorigenesis. Pro-apoptotic nCLU and anti-apoptotic sCLU have opposite effects and are differentially expressed in normal and cancer cells; however, their regulatory mechanisms at the transcriptional level are not yet known. Here, we examined the transcriptional regulation of nCLU in response to hypoxia. We identified three putative hypoxia response elements (HREs) in the human CLU promoter between positions −806 and +51 bp. Using a luciferase reporter, electrophoretic gel mobility shift, and chromatin immunoprecipitation assays, we further showed that hypoxia-inducible factor-1α (HIF-1α) bound directly to these sites and activated transcription. Exposure to the hypoxiamimetic compound CoCl2, incubation under 1% O2 conditions, or overexpression of HIF-1α enhanced nCLU expression and induced apoptosis in human prostate cancer PC3M cells. However, LNCaP prostate cancer cells were resistant to hypoxia-induced cell death. Methylation-specific PCR analysis revealed that the CLU promoter in PC3M cells was not methylated; in contrast, the CLU promoter in LNCap cells was methylated. Co-treatment of LNCaP cells with CoCl2 and a demethylating agent promoted apoptotic cell death through the induction of nCLU. We conclude that nCLU expression is regulated by direct binding of HIF-1α to HRE sites and is epigenetically controlled by methylation of its promoter region.