Miracle-dz/UniFAR-FTUs huggingface dataset:
Adaptive FEC based diffserv model for real-time media streaming

Media streaming applications over networks are often disturbed by data packet loss and errors as well as the limited network bandwidth,which degrades the video quality on the receiving side.Based on cross-layer design,an adaptive forward error correction algorithm at the application layer,in the hope that the media could be played on receivers with high quality.On the other hand,a diffserv model used for the data link layer is proposed,so that high-priority data streams(such as media streaming data streams) can be assigned more bandwidth.The simulation results and mathematical analysis demonstrate that the proposed mechanism achieves better quality of media streaming,in terms of playable frame rate,reliability and real-time performance on the receiving side.
Game Theoretical Framework for Distributed Dynamic Control in Smart Grids

In the emerging smart grids, production increasingly relies on a greater number of decentralized generation sites based on renewable energy sources. The variable nature of the new renewable energy sources will require a certain form of distributed energy storage, such as batteries, flywheels, compressed air and so on to help maintain supply security. Moreover, integration of demand response programs in conjunction with distrusted generation makes an economic and environmental advantage by altering end-users’ normal consumption patterns in response to changes in the electricity price. These new techniques change the way we consume and produce energy also enable the possibility to reduce the greenhouse effect and improve grid stability by optimizing energy streams. In order to accommodate these technologies, solid mathematical tools are essential to ensure robust operation of heterogeneous and distributed nature of smart grids. In this context, game theory could constitute a robust framework that can address relevant and timely open problems in the emerging smart grid networks. In this dissertation, three dynamic game-theoretical approaches are proposed for distributed control of generation and storage units and demand response applications in smart grid networks. We first study the competitive interactions between an autonomous pumped-storage hydropower plant and a thermal power plant in order to optimize power generation and storage. Each type of power plant individually tries to maximize its own profit by adjusting its strategy: both types of plants can sell their power to the market; or alternatively, the thermal-power plant can sell its power at a fixed price to the pumped-storage hydropower plant by storing the energy in the reservoir. A stochastic differential game is formulated to characterize this competition. The solutions are derived using the stochastic HamiltonJacobi-Bellman equations. Based on the effect of real-time pricing on users’ daily demand profile, the simulation results demonstrate the properties of the proposed game and show
Self-perception of Social Isolation and Loneliness in Older Adults

There are a large group of older individuals suffering from social isolation and loneliness; in fact, the number of older adults affected is increasing due to the large aging population worldwide. Within the United States, the baby boomers are or will be potentially facing social isolation and loneliness in great numbers. The current research literature in this area is difficult to interpret because the variable used to define social isolation and loneliness varies across disciplines when looking at this problem. Intervention research has also produced mixed findings. This article looks at this public health issue by reviewing some of the research in this area and discussing potential interventions.
Suicide, unemployment and other socioeconomic factors: evidence from the economic crisis in Greece

Background and Objectives: Economic adverse conditions are acknowledged as having a major impact on the exacerbation of mental disorders and suicides. The severity of current European crisis and the local unrelenting spending is affecting largely the economy of Greece. METHODS: The aim of this study was to explore changes in suicides and their possible association with macroeconomic and behavioural factors. Data for the period 1990-2011 were drawn mainly from the Hellenic Statistical Authority and Eurostat. Suicide mortality rates were correlated with economic and behavioural factors. RESULTS: Suicide mortality rates were increased by 55.8% between 2007 and 2011 while the total mortality was increased by 1.1% only. Significantly increasing trends in public debt, unemployment rates, consumption of daily units of antidepressants as well as divorces per 1000, homicides per 100,000 and persons with HIV per 100,000 were also observed. Suicides have been found to bear strong correlation with unemployment (r. 0.64). Significant associations were also found between suicide mortality and the percentage of public debt as percentage of GDP, the incidence of infections from HIV and homicides. CONCLUSIONS: People suffering from income and job losses, living in a demoralized social state caused by severe austerity measures and restrictive health policies, are exposed to risks for developing depression or commit suicide. KEYWORDS: Suicide; Unemployment; Public debt; Antidepressants; Economic factors. Language: en
Alcohol Intake by Workers in a Health Care Institution in Bucaramanga, Colombia

The harmful alcohol intake represents a global problem. Its high consumption has been associated with cardio metabolic risk factors. Evaluating their consumption in health workers is important for the formulation of strategies to promote healthy lifestyles. The objective of this study was to determine the consumption of alcohol and establish the differences of this intake in terms of socio-demographic and cardiovascular characteristics of interest in hospital workers of Bucaramanga, Colombia. An analytical cross sectional was made (baseline of an intervention study to reduce cardiovascular risk factors). Sociodemographic, anthropometric, biochemical, physical activity, and lifestyles characteristics, as well as alcohol consumption (g / week) were evaluated using a previously validated Frequency Alcohol Questionnaire. Multiple linear regression models were used, adjusting for sex, age, socio-economic level, schooling and marital status. 77.4% (95% CI: 71.2% to 82.8%) of the study participants consumed some type of alcoholic beverage during the month prior to the survey, with an average of 70.0 grams of alcohol per week of 70.0 g. We found a statistically significant difference (p = 0.012) of 40.4 grams of alcohol per week (95% CI: 8.9 to 71.8 g / week) consumed among those who have hypertriglyceridemia and those who do not. In conclusion, the high consumption of grams of alcohol per week is related to a triglyceride level above the normal ranges.
Data Security in Cloud Computing Based on Advanced Secret Sharing Key Management Scheme

Cloud computing is a globalised concept and there are no borders within the cloud. Computers used to process and store user data can be located anywhere on the globe, depending on where the capacities that are required are available in the global computer networks used for cloud computing. Because of the attaractive features of cloud computing many organizations are using cloud storage for storing their critical information. The data can be stored remotely in the cloud by the users and can be accessed using thin clients as and when required.One of the major issue in cloud today is data security in cloud computing.Storage of data in the cloud can be risky because of use of Internet by cloud based services which means less control over the stored data. One of the major concern in cloud is how do we grab all the benefits of the cloud while maintaining security controls over the organizations assets. Our aim is to propose a more reliable, decentralized light weight key management technique for cloud systems which provides more effecient data security and key management in cloud systems. Our proposed technique provides better security against byzantine failure, server colluding and data modification attacks.
Degrees of freedom of optical systems and signals with applications to sampling and system simulation

Based on space-frequency analysis, we show how to quantify the degrees of freedom of first-order optical systems with apertures, and give conditions for lossless transfer. Secondly, we focus on the degrees of freedom of signals and provide a sub-Nyquist sampling approach for signals with arbitrary space-frequency support. Implications for simulating optical systems are also discussed.
Adaptive Memory Controller for High-performance Multi-channel Memory

—As the number of CPU/GPU cores and IPs in SOC increases and applications require explosive memory bandwidth, simultaneously achieving good throughput and fairness in the memory system among interfering applications is very challenging. Recent works proposed priority-based thread scheduling and channel partitioning to improve throughput and fairness. However, combining these different approaches leads to performance and fairness degradation. In this paper, we analyze the problems incurred when combining priority-based scheduling and channel partitioning and propose dynamic priority thread scheduling and adaptive channel partitioning method. In addition, we propose dynamic address mapping to further optimize the proposed scheme. Combining proposed methods could enhance weighted speedup and fairness for memory intensive applications by 4.2% and 10.2% over TCM or by 19.7% and 19.9% over FR-FCFS on average whereas the proposed scheme requires space less than TCM by 8%.
Written feedback in Japanese EFL classrooms: A focus on content and organization

The exact nature of written feedback to L2 learners of English is often vague to both the teachers who provide it and the learners who receive it. However, this does not have to be the case. This paper describes a study carried out with 16 Japanese and 14 native English speaker EFL teachers in Japan who provided feedback on one L2 learners’ academic essay. After analyzing and coding the feedback, the researchers found that the most common form of feedback given on the essay was in relation to the content and organization of the essay. Five of these teachers were subsequently interviewed in order to elicit their beliefs about the nature of feedback they gave on the learners’ essay. The findings suggest a need for EFL teachers in Japan to specifically focus on teaching how learners can attend to the content and organization of an essay, all the while providing a rubric or checklist that allows for a transparent and easy to understand method of decoding the feedback process for our learners. Normal 0 false false false EN-US JA AR-SA /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:. 0001pt; mso-pagination:widow-orphan; font-size:10.5pt; mso-bidi-font-size:11.0pt; font-family:"Century","serif"; mso-ascii-font-family:Century; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Century; mso-hansi-theme-font:minor-latin; mso-font-kerning:1.0pt;}
Factitious Disorder By Proxy: The Role of Child Mental Health Professionals

Factitious Disorder By Proxy (FDBP) has been gaining increasing amounts of media attention and is being diagnosed more commonly. Here we propose a wider definition to include seven other, related clinical presentations. We then go on to review ‘classic’ FDBP and the role of mental health professionals. FDBP often has grave consequences both physically and psychologically, and may result in extensive misuse of health care resources. The literature concerning FDBP has largely been written by paediatricians, but this review pays particular attention to aspects of FDBP that concern child mental health professionals. The presentation, investigation, diagnosis, and management of FDBP are discussed with reference to the role of child mental health professionals, particularly psychiatrists. What little is known of the prognostic factors is reviewed and suggestions are made for further research.
THE RELATIONSHIP BETWEEN THE CRIMINAL OFFENCE AND SELF SERVING COGNITIVE DISTORTIONS

Literature in the field of aggressive and violent behavior indicated a strong link between anti-social behavior and self-serving cognitive distortions. The concept of self-serving is represented by a series of distorted cognitive processes, which can take shape due to the generally oversized tendency of self-perception. The purpose of this study was to investigate the possible positive relationships between different levels of offences/ crimes and self-serving cognitive distortions in a sample of juvenile delinquents and young individuals from Romania. The assessment of the self-serving cognitive distortions was measured with the How I Think Questionnaire and the type of the criminal offence was taken from the Institutional evaluation sheet. Data was gathered from 55 juvenile delinquents, ages between 15 and 19, the average age being 17.13 (SD = .92). Positive correlations were found between the different levels of offences/ crimes and self-serving cognitive distortions, except for Self-Centered, Minimizing/Mislabeling, Physical Aggression and Stealing. These results suggest that as the level of offence gets higher so does the level of self-serving cognitive distortions and anti-social tendencies.
The IRAF Mosaic Data Reduction Package

The IRAF Mosaic Data Reduction Package, mscred ,p ro- cesses data from mosaics of CCDs such as the NOAO CCD Mosaic Camera 2 . A brief design of the package was presented earlier by Valdes (1997a). Since then a rst implementation of the software has been completed. This paper summarizes the current status of the software and our plans for future developments.
Optimal Commutation Law for Three-Phase Surface-Mounted Permanent Magnet Linear Synchronous Motors

Sinusoidal commutation of phase currents leads to force ripple, if the motor back-EMFs differ from ideal case. Force ripple reduces the tracking performance significantly, if no compensation methods are applied. This paper presents a method to optimize the commutation in order to prevent force ripple. No assumptions of periodicity, symmetry, shape or balance of the motor back-EMFs are made. The proposed commutation law considers nonidealities of motor and amplifier. It is based on non-parametric force functions, which are identified in a proposed procedure. The optimal commutated currents produce minimal winding losses and therefore maximize imize motor efficiency. The commutation law is valid for any velocity and any desired thrust force. In this research, three-phase synchronous motors with surface-mounted magnets are considered. Experiments are performed with a linear motor, but the results are also valid for rotating motors.
Research on Robot Navigation Based on Multi-data Fusion using Bayesian Model

Navigation and localization is one of the key technologies to mobile robots, as human beings, mobile robot need sensors to detect the surrounding environment and plan its path to implement various tasks. Single sensor has limitation and insufficiency, so it is effective to use multiple sensors data to get the reliable navigating. This paper proposed a method of multiple sensors data fusion based on Bayesian theory, the experimental results demonstrates the effectiveness and validity of the method.
Nosocomial infection modeling and simulation using fine-grained healthcare data

Simulation has long been used in healthcare settings to study a range of problems, such as determining ideal staffing levels, allocating patient beds, and assisting with medical decision making. Some of this work naturally focuses on the spread of infection within hospitals, where the importance of hospitals as loci and amplifiers of infection was demonstrated during the 2002-2003 SARS outbreak. Increasingly, fine-grained healthcare data is being collected (e.g., patient care data stored in electronic medical record systems, and healthcare worker data from sources including nurse locator badges), presenting an opportunity to develop models that can drive more realistic simulations. We seek to build a realistic hospital simulator that can be used to answer a wide variety of questions about infection prevention, the allocation and placement of expensive resources, and issues surrounding patient care. Our simulation framework requires three primary inputs: architectural, healthcare worker, and patient data. We used data from the University of Iowa Hospitals and Clinics to build our virtual hospital. We manually constructed a weighted, directed, 19,000 node graph-theoretic representation of the facility based on printed architectural drawings. Using timestamped location information from electronic medical record system logins and algorithms inspired by prior work on location-aware search, each healthcare worker is modeled by one or more “centers” of activity. Centers are determined using a maximum likelihood approach to fit a location and appropriate decay parameters that best describe the observed data. Finally, we developed
Staging with delimited control

It is often hard to write programs that are efficient yet reusable. For example, an efficient implementation of Gaussian elimination should be specialized to the structure and known static properties of the input matrix. The most profitable optimizations, such as choosing the best pivoting or memoization, cannot be expected of even an advanced compiler because they are specific to the domain, but expressing these optimizations directly makes for ungainly source code. Instead, a promising and popular way to reconcile efficiency with reusability is for a domain expert to write code generators. Two pillars of this approach are types and effects. Typed multilevel languages such as MetaOCaml ensure safety and early error reporting: a well-typed code generator neither goes wrong nor generates code that goes wrong. Side effects such as state and control ease correctness and expressivity: An effectful generator can resemble the textbook presentation of an algorithm, as is familiar to domain experts, yet insert let for memoization and if for bounds checking, as is necessary for efficiency. Together, types and effects enable structuring code generators as compositions of modules with well-defined interfaces, and hence scaling to large programs. However, blindly adding effects renders multilevel types unsound. We introduce the first multilevel calculus with control effects and a sound type system. We give small-step operational semantics as well as a one-pass continuation-passing-style translation. For soundness, our calculus restricts the code generator’s effects to the scope of generated binders. Even with this restriction, we can finally write efficient code generators for dynamic programming and numerical methods in direct style, like in algorithm textbooks, rather than in continuation-passing or monadic style.
Walk detection and step counting on unconstrained smartphones

Smartphone pedometry offers the possibility of ubiquitous health monitoring, context awareness and indoor location tracking through Pedestrian Dead Reckoning (PDR) systems. However, there is currently no detailed understanding of how well pedometry works when applied to smartphones in typical, unconstrained use. This paper evaluates common walk detection (WD) and step counting (SC) algorithms applied to smartphone sensor data. Using a large dataset (27 people, 130 walks, 6 smartphone placements) optimal algorithm parameters are provided and applied to the data. The results favour the use of standard deviation thresholding (WD) and windowed peak detection (SC) with error rates of less than 3%. Of the six different placements, only the back trouser pocket is found to degrade the step counting performance significantly, resulting in undercounting for many algorithms.
A Location-Aware Middleware Framework for Collaborative Visual Information Discovery and Retrieval

This work addresses the problem of scalable location-aware distributed indexing to enable the leveraging of collaborative effort for the construction and maintenance of world-scale visual maps and models. These maps and models support numerous activities including navigation, visual localization, persistent surveillance, and hazard or disaster detection. Due to the physical scale of the world, the problem of constructing and maintaining relevant world-scale visual models generally requires significant effort to be spent on visual mapping. The dynamic nature of physical environments also causes visual records to lose relevance, requiring that mapping be re-accomplished periodically in order to account for both natural and man-made environmental changes. While physical scale and environmental dynamism pose the most obvious challenges to solutions for this problem, the underlying computational and data storage infrastructures required are non-trivial. The infrastructure must be capable of providing for the storage, indexing, and retrieval of published images as well as the expiry of images which are not relevant or representative of the physical environment. A solution to the problem of constructing and maintaining surface level visual world models is presented in the form of a peer-to-peer middleware framework named PeerAppear. The system architecture for PeerAppear is developed including descriptive use-cases, indexing methods, geospatial addressing, and a protocol specification. Computational methods are presented which support the framework by providing for efficient visual search, cell-based geospatial representation for position and viewshed, and a search-based scoring of visual landmarks based on area of visibility. Finally, an evaluation of PeerAppear’s indexing performance, scalability, and visual search