Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting User Movements in Heterogeneous Indoor Environments by Reservoir Computing

Anticipating user localization by making accurate predictions on its indoor movement patterns is a fundamental challenge for achieving higher degrees of personalization and reactivity in smarthome environments. We propose an approach to real-time movement forecasting founding on the efficient Reservoir Computing paradigm, predicting user movements based on streams of Received Signal Strengths collected by wireless motes distributed in the home environment. The ability of the system to generalize its predictive performance to unseen ambient configurations is experimentally assessed in challenging conditions, comprising external test scenarios collected in home environments that are not included in the training set. Experimental results suggest that the system can effectively generalize acquired knowledge to novel smart-home setups, thereby delivering an higher level of personalization while decreasing costs for installation and setup.
Pyomyositis: Are We Missing the Diagnosis?

BACKGROUND Pyomyositis (PY) is a primary infection of the skeletal muscles, leading to inflammation of the muscle fibers followed by pus formation and even necrosis in late stages. Because of overlap in presentation of intermuscular abscess (IM) and PY, the exact incidence and severity of PY is under-appreciated. PATIENTS AND METHODS We conducted a prospective analytical study in a tertiary care center in North India from October 2011 to January 2013, recruiting patients with abscesses involving the chest wall, abdomen (parietal wall including back), and extremities. Subcutaneous, hepatic, intra-abdominal abscess, and secondary abscesses were excluded. Primary PY was defined as a primary infection of skeletal muscle without any foci from adjacent skin, soft tissue, or bone. Clinical, radiologic, pathologic, and operative findings suggested diagnosis; loss of striations and lymphocytic infiltration in the muscle fibers was confirmatory. The chief outcome variables were death and length of hospital stay. RESULTS Thirty patients with a mean age of 29.5 y (IM: 29.7 ± 16.7, PY: 25.28 ± 17.6) were classified as IM (18/30, 60%) or PY (12/30, 40%). Most PY occurred in the lower limb (41.7% had multi-site involvement); most had a history of trauma or immunocompromised state. Fever, tachycardia, tachypnea, hypotension, pallor, and hyperesthesia were significantly higher (p < 0.05) in PY. Mean Sequential Organ Failure Assessment (SOFA) score was 0.33 for IM, 2.5 for PY. Staphylococcus aureus was predominant in both groups; however, all four patients with methicillin-resistant S. aureus (MRSA) were in the PY group. Both deaths also occurred in the PY group. The mean duration of hospital stay was 3.22 ± 1.11 d for IM and 10.27 ± 2.32 d for PY patients (p = 0.03). CONCLUSION PY is a specific and potentially fatal infection, which is common in our country and must be differentiated from IM. A high index of suspicion and early institution of specific antibiotics followed by operation is therapeutic.
Foundation for Object-Oriented Databases

The application of the object-oriented (0-0) para- digm in the database management field has gained much attention in recent years. Several experimental and commercial 0-0 data- base management systems have become available. However, the existing 0-0 DBMS's still lack a solid mathematical foundation for the manipulation of 0-0 databases, the optimization of queries, and the design and selection of storage structures for supporting 0-0 database manipulations. This paper presents an association algebra (A-algebra) to serve as a mathematical foundation for processing 0-0 databases, which is analogous to the relational algebra used for processing relational databases. In this algebra, objects and their associations in an 0-0 data- base are uniformly represented by association patterns which are manipulated by a number of operators to produce other association patterns. Different from the relational algebra, in which set operations operate on relations with union-compatible structures, the A-algebra operators can operate on association patterns of homogeneous and heterogeneous structures. Different from the traditional record-based relational processing, the A- algebra allows very complex patterns of object associations to be directly manipulated. In this paper, the pattern-based query formulation and the A-algebra operators are described. Some mathematical properties of the algebraic operators are presented together with their application in query decomposition and opti- mization. The completeness of the A-algebra is also defined and proven. The A-algebra has been used as the basis for the design and implementation of an object-oriented query language, OQL, which is the query language used in a prototype Knowledge Base Management System OSAM*. KBMS.
Information Visualization and Visual Data Mining

Never before in history has data been generated at such high volumes as it is today. Exploring and analyzing the vast volumes of data is becoming increasingly difficult. Information visualization and visual data mining can help to deal with the flood of information. The advantage of visual data exploration is that the user is directly involved in the data mining process. There are a large number of information visualization techniques which have been developed over the last decade to support the exploration of large data sets. In this paper, we propose a classification of information visualization and visual data mining techniques which is based on the data type to be visualized, the visualization technique, and the interaction and distortion technique. We exemplify the classification using a few examples, most of them referring to techniques and systems presented in this special section.
Use of the Multiple Lens Approach to Multiple Regression Findings with a National Dataset

University of North Texas University of North Texas Northern Illinois UniversityThis study builds upon the work of Nathans, Oswald, and Nimon (2012) to demonstrate how to apply variable importance metrics to an analysis of a national dataset. The paper (a) reviews the variable importance metrics; (b) details the strengths and weaknesses of national datasets as well as issues the analyst must confront when using them; (c) presents an integrated write-up of how to interpret variable importance metrics in analysis of fall of kindergarten math achievement from the Early Childhood Longitudinal Study – Kindergarten Cohort dataset; and (d) discusses how variable importance metrics inform the extant substantive literature on kindergarten math achievement. ultiple regression (MR) is a commonly employed statistical technique in social science research. Its purpose is to determine the “predictive power” of individual, as well as sets of independent variables (IVs), in explaining variance in a single dependent variable (DV) (Pedhazur, 1997). Researchers commonly rely upon beta weights when assessing the contributions of specific IVs to variance in the DV (Nimon, Gavrilova, & Roberts, 2010). As Nathans, Oswald, and Nimon (2012) and Zumbo (2012) pointed out, sole reliance on beta weights in interpreting MR findings provides limited, and potentially inaccurate, information regarding IVs’ contributions to regression models. Shared variance between variables, a statistical phenomenon referred to as multicollinearity, may distort or minimize the contribution of an IV to an MR equation as reflected in beta weight values (Courville & Thompson, 2001; Nunnally & Bernstein, 1994). Accordingly, researchers need to rely on other measures of IVs’ contributions to MR models to “yield the richest and most complete picture regarding the relationships between independent variables and the dependent variable” (Nathans et al., p. 2). Nathans et al. (2012) highlighted several measures of variable importance in their guidebook. They noted that variable importance must be operationalized in terms of a specific measure of a variable’s contribution to a regression equation, rather than employed as a “blanket term” (p. 2) that has general applicability when interpreting regression findings. As such, a brief outline of variable importance metrics utilized in said guidebook will be applied to the example in the current study.
Can Predictive Computation Reach the Level of Anticipatory Computing

Predictive computation is rapidly becoming the new focus of computer science and technological development. In some cases, under marketing pressure, it is characterised as ‘anticipatory computing. ’ In other cases, computation is expected to deliver predictive phenotyping, or new materials that will behave according to predefined expectations. Since dealing with the future is significant from the perspective of acknowledging and preparing for change, concepts pertinent to describing the future take on importance. There is a pragmatic necessity for establishing a common understanding of various aspects of prediction: forecasting, premonition, guessing, inference, foretelling, prolepsis, expectation, etc. Technology affords new possibilities, such as wearables and mobile computation. However, technology does not substitute for a sense of direction.
The phase vocoder: theory and practice

This article discusses the theoretical principles governing the short time Fourier transform (STFT) and its musical applications, using the CARL phase vocoder and the Composers' Desktop Project (CDP) spectral transformations. The former was originally developed by Dolson (1986, 1991) and ported to personal computer systems by Atkins, Bentley, Henderson, Orton and Wishart (Atkins, Bentley, Endrich, Fischman, Malham, Orton and Wishart 1987, Wishart 1994a). The latter was developed by Wishart (1994b). When possible, theoretical matters are presented in a qualitative way, keeping the number and complexity of mathematical expressions within the essential requirements for those interested in musical applications. The latter are accompanied by sound examples, including excerpts from pieces by the author.
Countermeasures for GPS Signal Spoofing

The strength of the GPS signal on the earth’s surface averages -160 dBw [5]. While many GPS receivers leave large space for signal dynamics, enough power space is left for the GPS signals to be overridden (spoofed). Spoofing is completely different from jamming. The objective of jamming is to simply interrupt the availability of the signal in space at the receiver. The effect is to cause the signal at the receiver to be corrupted so that no valid GPS signal can be decoded by the receiver. The goal of spoofing, on the other hand, is to provide the receiver with a misleading signal, fooling the receiver to use fake signals in space for positioning calculations. The receiver will produce a misleading position solution. While the GPS P-code is heavily encrypted and thus, is hard to spoof, the civilian GPS signal, the C/A code, is easy to spoof because the signal structure, the spread spectrum codes, and modulation methods are open to the public. The purpose of this paper is to analyze the vulnerability of the satellite signal and GPS system to spoof attacks, propose the anti-spoofing algorithms and illustrate the simulations of spoofing impact and anti-spoofing results. It is believed by the authors of this paper that GPS can be spoofed in theory and producing a spoofing satellite signal is possible. However, practical spoofing that provides misleading navigation results at the receiver is difficult to conduct due to the signal infrastructure, and by applying trivial anti-spoofing algorithms in GPS receivers, spoofing attack can be easily detected.
Modelo de gestión de listas de espera centrado en oportunidad y justicia

Waiting lists for elective surgery are considered a major health policy concern in most countries of the world. The most common reason to explain this phenomenon is that demand exceeds supply. Traditionally, the management of waiting lists has been focused on timeliness of medical attention. The objective of this paper is to present a waiting lists management model that includes the concepts of timeliness and justice simultaneously. We designed a prioritization method based solely on medical criteria. We developed a computer software to register patients, to prioritize and monitor the waiting lists. The system was implemented in 2013 and is currently used in all surgical specialties at a public hospital. The results show that timeliness does not suffice to manage the waiting lists for elective surgery, and therefore it should be complemented with an indicator of justice. Under this management model, hospitals should attempt to balance justice with timeliness of care and prioritize initiatives that improve both indicators at the same time. In addition, we propose using this model to manage the waiting lists of other hospital processes.
Evaluation of the Ghuman-Folstein Screen for Social Interaction (SSI)

ii Acknowledgements iv Vita v List of Tables viii List of Figures x Chapter 1: Introduction 1 Chapter 2: Methods 22 Chapter 3: Results 31 Chapter 4: Discussion 50 References 63 Appendix A: SSI Instrument Full Scale 70 Appendix B: Tables 76 Appendix C: Figures 105 Appendix D: SSI-T Instrument 119 Appendix E: SSI-PS Instrument 122
Impact of innovative and highly interactive online activities on energy efficiency education

: Energy Conservation and Environmental Protection (EGEE 102) course has been taught at Penn State since the fall of 2001. Over the past seven semesters the enrollment has increased from 69 to 760. This course was selected by the University under the “Courseware” initiative to be offered as an online course. To develop the online version of EGEE 102, the Energy and Geo-environmental Engineering Department, the Teaching and Learning with Technology Unit of the University’s Information Technology Services and the John A Dutton e-Education Institute have collaborated to generate highly interactive learning objects in an innovative manner. As a part of this endeavor, four home activities (simulations) using Macromedia Flash were developed. The goal of these simulations is to engage students through animations and enable students to calculate their energy consumption, analyze their energy consumption patterns and utility bills, understand the economics of insulation addition, and conduct an energy audit on a virtual home. Each of the students worked with a unique data set for each of these activities. The data sets for energy consumption of appliances or monthly energy bills for each student are generated using Perl scripts and are retained in the MySQL database. These student specific datasets are delivered through the Flash simulations. The students complete the required activity and submit their results via the Flash interface. The submitted values are automatically compared with the student-specific data sets and the correct numerical answers as calculated by the PHP script. This process minimizes the time required for the faculty to grade the reports, increased faculty efficiency, reduced grading errors, and counters plagiarism as duplicate submissions are ineffective. Informal student assessment indicated that the highly interactive Flash simulations were a motivational environment enabling comprehension of the cognitively challenging
Hardware Consolidation Of Systolic Algorithms On A Coarse Grained Runtime Reconfigurable Architecture

Application domains such as Bio-informatics, DSP, Structural Biology, Fluid Dynamics, high resolution direction finding, state estimation, adaptive noise cancellation etc. demand high performance computing solutions for their simulation environments. The core computations of these applications are in Numerical Linear Algebra (NLA) kernels. Direct solvers are predominantly required in the domains like DSP, estimation algorithms like Kalman Filter etc, where the matrices on which operations need to be performed are either small or medium sized, but dense. Faddeev’s Algorithm is often used for solving dense linear system of equations. Modified Faddeev’s algorithm (MFA) is a general algorithm on which LU decomposition, QR factorization or SVD of matrices can be realized. MFA has the good property of realizing a host of matrix operations by computing the Schur complements on four blocked matrices, thereby reducing the overall computation requirements. We will use MFA as a representative Direct Solver in this work. We further discuss Given’s rotation based QR algorithm for Decomposition of any matrix, often used to solve the linear least square problem. Systolic Array Architectures are widely accepted ASIC solutions for NLA algorithms. But the “can of worms” associated with this traditional solution spawns the need for alternative solutions. While popular custom hardware solution in form of systolic arrays can deliver high performance, but because of their rigid structure they are not scalable and reconfigurable, and hence not commercially viable. We show how a Reconfigurable computing platform can serve to contain the “can of worms”. REDEFINE, a coarse grained runtime reconfigurable architecture has been used for systolic actualization of NLA kernels. We elaborate upon streaming NLAspecific enhancements to REDEFINE in order to meet expected performance goals. We
An Extensive Comparison among DSDV, DSR and AODV Protocols in MANET

Mobile Ad-Hoc Network (MANET) routing protocols facilitate the creation of such networks without centralized infrastructure. Comprehensive analysis among Destination Sequence Distance Vector (DSDV), Dynamic Source Routing (DSR) and Ad-hoc on Demand Distance Vector (AODV) routing protocols of ad-hoc networks has been carried out using Network Simulator (NS-2). Some important performance metrics of MANET have been taken under consideration such as no. of Node Vs Throughput, no. of Node Vs Packet Drop, Packet Vs Propagation Delay and Throughput vs Time and it also investigates the best routing protocol with simulation environment.
A Message from the Immune System: A Vaccine Technology in Needs of Exploration!

Int J Vaccines Vaccin 2016, 2(4): 00039 Abbreviations: AAC: Antigen-antibody complex; Ab: Antibody; Ag: Antigen; APC: Antigen Presenting Cells; DC: Dendritic Cells; FDC: Follicular Dendritic Cells; FcR: Fc Receptors; GC: Germinal Centers; IBDV: Infectious Bursal Disease Virus; IC: Immune Complex; IFN-α: Interferon-Alpha; IFN-γ: InterferonGamma; IL: Interleukin; MHC: Major Histocompatibility Complex; RER: Rough Endoplasmic Reticulum
Human Detection in Compressed Images

Detecting human beings in images has gained prominence in the field of Computer Vision, with applications in the fields of surveillance, robotics and indexing of image databases, to name a few. With the growing need to transfer image data over the network and to store them in databases, image compression has also gained importance, and consequently, the need for detection systems to be resilient to compression. This paper proposes a method to solve the problem of human detection in images through the application of computer vision approaches to a machine learning framework. We attempt to find a robust descriptor for human detection in compressed images.
Practical interaction design

This paper describes a method for teaching interaction design in a school of computing setting. Practical Interaction Design is something of a hybrid incorporating elements of both 'pure' interaction design and human-computer interaction (HCI) to convey some of the flavour of the former with the tool-rich practicality of the latter. Practical Interaction Design is distinguished from (traditional) HCI in many ways, but it is with respect to what it does not address that their differences are most pronounced. Practical Interaction Design is not explicitly user centred, there is no place for cognitive psychology per se; nor for the modelling of tasks; nor for accounting for (that glaring category error) context. Instead there are roles for a Heideggerian treatment of familiarity; for ideation and for personae. The method itself incorporates a series of 'conversations' between designer and digital media and between designer and client.
PROCEEDINGS of the HUMAN FACTORS SOCIETY-29th ANNUAL MEETING-7985 THE STRUCTURE OF INFORNATION IN ONLINE AND PAPER TECHNICAL MANUALS

An experiment was conducted to compare online computer manuals to paper manuals. For each type of manual there were two different database structures -a linear (sequential) structure and a tree structure. The results showed that people using the paper manuals were faster at performing a switch setting task based on information in the manual than were people using the online manuals. No significant differences were found in speed of performance between the linear and tree structures. Nor were there any differences in the number of correct switch settings for the different types of manuals, The subjective evaluation data revealed that the online manuals were rated as better and judged to be more organized than the paper manuals.
Evaluation of spatially variable control parameters in a complex catchment modelling system : a genetic algorithm application

Successful implementation of a catchment modelling system requires careful consideration of the system calibration which involves evaluation of many spatially and temporally variable control parameters. Evaluation of spatially variable control parameters has been an issue of increasing concern arising from an increased awareness of the inappropriateness of assuming catchment averaged values. Presented herein is the application of a real-value coding genetic algorithm (GA) for evaluation of spatially variable control parameters for implementation with the Storm Water Management Model (SWMM). It was found that a real-value coding GA using multiple storms calibration was a robust search technique that was capable of identifying the most promising range of values for spatially variable control parameters. As the selection of appropriate GA operators is an important aspect of the GA efficiency, a comprehensive investigation of the GA operators in a high-dimensional search space was conducted. It was found that a uniform crossover operation was superior to both one-point and two-point crossover operations over the whole range of crossover probabilities, and the optimal uniform crossover and mutation probabilities for the complex system considered were in the range of 0.75–0.90 and 0.01–0.1, respectively.
THE EFFECT OF USING GRAMMAR-TRANSLATION METHOD ON ACQUIRING ENGLISH AS A FOREIGN LANGUAGE

The goal of this research is to investigate the effect of using Grammar-Translation method on acquiring English as a foreign language. This is an experimental research. The sample of this study comprises 20 students from Grade 10th in which all of them were females from Al-Mazar governmental school. The researcher used random sampling process to conduct this study. The finding of this research indicated that there is a positive effect of using Grammar-Translation method on English as a foreign language acquisition by female students. This research concluded that female students who were taught by using Grammar-Translation method progressed notably in grammar in which they achieved greater self confidence. This study recommends that further future research be conducted in this area to overcome problems with second language acquisition especially in grammar.
The semantic Web and its languages

The Web has drastically changed the availability of electronic information, but its success and exponential growth have made it increasingly difficult to find, access, present and maintain such information for a wide variety of users. In reaction to this bottleneck many new research initiatives and commercial enterprises have been set up to enrich available information with machine-processable semantics. The paper considers how the semantic Web will provide intelligent access to heterogeneous and distributed information, enabling software products (agents) to mediate between user needs and available information sources. The paper discusses the Resource Description Framework, XML and other languages.