Miracle-dz/UniFAR-FTUs huggingface dataset:
A practical approach for image quality assesment

Image quality assessment is a research field that becomes more and more important in the mobile devices market. In practice, estimation of the image quality has applications in several fields such as mobile printing, user assistance and memory management, to mention a few. In this paper we propose a novel practical approach for image quality assessment. More specifically, we introduce an iterative algorithm able to estimate the amount of blur from the input image. The proposed approach is well suited to be used in mobile implementations.
The Complete Genome Sequence of Roseobacter denitrificans Reveals a Mixotrophic Rather than Photosynthetic Metabolism

ABSTRACT Purple aerobic anoxygenic phototrophs (AAPs) are the only organisms known to capture light energy to enhance growth only in the presence of oxygen but do not produce oxygen. The highly adaptive AAPs compose more than 10% of the microbial community in some euphotic upper ocean waters and are potentially major contributors to the fixation of the greenhouse gas CO2. We present the complete genomic sequence and feature analysis of the AAP Roseobacter denitrificans, which reveal clues to its physiology. The genome lacks genes that code for known photosynthetic carbon fixation pathways, and most notably missing are genes for the Calvin cycle enzymes ribulose bisphosphate carboxylase (RuBisCO) and phosphoribulokinase. Phylogenetic evidence implies that this absence could be due to a gene loss from a RuBisCO-containing α-proteobacterial ancestor. We describe the potential importance of mixotrophic rather than autotrophic CO2 fixation pathways in these organisms and suggest that these pathways function to fix CO2 for the formation of cellular components but do not permit autotrophic growth. While some genes that code for the redox-dependent regulation of photosynthetic machinery are present, many light sensors and transcriptional regulatory motifs found in purple photosynthetic bacteria are absent.
Service based Personalized Learning System in Cloud Computing Environment

Cloud computing is a new paradigm of IT. It can provide all resources such as software (SaaS), platform (PaaS) and infrastructure (IaaS) as a service over the internet. It also offers the opportunity to store a huge amount of data relatively cheaply. In cloud computing, user can access the services regardless of their location or computing device/platform they use. In these advantages, many researchers of e-learning area attempt to apply their process to cloud computing. In this research, we propose service based e-learning system in cloud computing. In order to provide personalized learning process considering user’s characteristics, we use the user profile data. Also, in our system architecture, we consider virtualization technique for hardware and software resources for controlling and managing their services in cloud computing.
A wirelessly powered injection-locked oscillator with on-chip antennas in 180nm SOI CMOS

This paper presents a battery-less mm-sized wirelessly powered injection-locked oscillator with on-chip antennas in 180nm SOI CMOS. The chip harvests electromagnetic radiation from a continuous-wave source in the X-band using an on-chip antenna. In addition, the chip is equipped with a broadband injection-locking oscillator that locks to the frequency of the input and produces a synchronized signal at the half frequency of the input. The new signal is then radiated back using an on-chip dipole antenna. This architecture resolves the conventional self-interference issue in RFID sensors by separating the received and transmitted frequencies. In addition, the locking mechanism improves the phase-noise of the on-chip oscillator to -93dBc/Hz at 100Hz offset.
Safety of Botulinum Toxin Type A for Children With Nonambulatory Cerebral Palsy

OBJECTIVE: To determine safety of intramuscular botulinum toxin A (BoNT-A) injections to reduce spasticity and improve care and comfort of nonambulatory children with cerebral palsy (CP). METHODS: Nonambulatory children with CP were randomly allocated to receive either BoNT-A (n = 23) or sham procedure (n = 18) in Cycle 1. In Cycle 2, the BoNT-A group received a second episode of BoNT-A (n = 20) and sham group received their first episode of BoNT-A (n = 17). A pediatric rehabilitation specialist masked to group allocation graded each adverse event (AE) according to system, severity (mild, moderate, serious, sentinel) and causality (unlikely/unrelated; possible; probable/definite). RESULTS: There was no difference for all moderate/serious AEs between the BoNT-A and sham/control groups in either Cycle 1 (incident rate ratio = 1.30, 95% confidence interval = 0.43–4.00; P = .64) or Cycle 2 (incident rate ratio = 0.72, 95% confidence interval = 0.30–1.75; P = .47). In Cycle 2, 1 serious, 3 moderate (single-episode group), and 24 mild (single-episode group n = 10; 2 episode group n = 14) AEs were probably/definitely related to BoNT-A. CONCLUSIONS: Children receiving BoNT-A were at no greater risk of moderate/serious AEs compared with a sham control procedure. There was no increased risk of moderate/serious AEs between one and two episodes of BoNT-A.
Block Cipher Involving Key Based Random Interlacing and Key Based Random Decomposition

Problem statement: The strength of the block ciphers depend on the degree of confusion and diffusion induced in the cipher. Most of the transformations used for this purpose are well known to every one and can be broken by a crypt analyzer. Therefore, in order to counter attack the crypt analyzer, there is a need for better transformations in addition to the existing one. Approach: We tried to use key based random interlacing and key based random decomposition for this purpose. So that, a crypt analyzer cannot understand how interlacing and decomposition is done in every round unless the key is known. Results: The strength of the cipher is assessed by avalanche effect which is proved to be satisfactory. Conclusion/Recommendations: Key based random interlacing and decomposition can be used for introducing confusion and diffusion in block ciphers. The cryptanalysis carried out in this regard shows that the cipher cannot be broken by any cryptanalytic attack.
Moving engagement research to a higher level: The impact of unit-level engagement on business metric outcomes

MOVING ENGAGEMENT RESEARCH TO A HIGHER LEVEL: THE IMPACT OF UNIT-LEVEL ENGAGEMENT ON BUSINESS METRIC OUTCOMES by TARA K. McCLURE August 2013 Advisor: Dr. Boris Baltes Major: Psychology (Industrial-Organizational) Degree: Doctor of Philosophy Although engagement has been slow to take hold within the academic literature, it has quickly become a hot topic within the applied and business environments. Because of the rapid growth within these areas, there has been a great deal of conceptual confusion and mystery surrounding the engagement construct. Recent research within the literature has sought to define engagement, differentiate it from existing job attitude constructs, and link it with both personal and organizational outcomes. To date, a majority of the research demonstrating the impact of engagement has been conducted at the individual-level. While individual-level outcomes are of use to organizations, the success of a company is usually measured at higher levels of analysis. The purpose of the current study was to explore the factor structure of a new engagement index, investigate its discriminant validity with two common job attitude measures (job satisfaction and organizational commitment), look at various composition models for aggregating individual-level engagement to the unit level, and determine the relationship between work unit engagement and business metric outcomes (voluntary turnover, operating costs, and earnings). Results of the
Local primitive code mining for fast and accurate face recognition

This paper proposes a new feature descriptor named as Local Primitive Code (LPC), which exhibits impressively discriminative capability on various face datasets. Essentially, LPC descriptors are somewhat like filter banks of Gaussian derivatives to capture multi-scale and multi-orientation image local textures but meanwhile enables faster feature extraction. It employs a framework composed of two stages: Firstly facial images are preprocessed by the pool of differential and quotient filters to generate numerous filtered images with various textures, and then directional binary encoding (DBE) operates on filtered images for primitive code mining. With such stages, feature maps with complementary discriminative information will be generated, and the fusion of them can greatly improve face recognition performance. Experimental results verify its performance even on some challenging databases. The algorithm is transplanted into mobile platform and achieves real-time performance on Nokia N82.
Adaptive Parallel Iterative Deepening Search

Many of the artificial intelligence techniques developed to date rely on heuristic search through large spaces. Unfortunately, the size of these spaces and the corresponding computational effort reduce the applicability of otherwise novel and effective algorithms. A number of parallel and distributed approaches to search have considerably improved the performance of the search process. Our goal is to develop an architecture that automatically selects parallel search strategies for optimal performance on a variety of search problems. In this paper we describe one such architecture realized in the EUREKA system, which combines the benefits of many different approaches to parallel heuristic search. Through empirical and theoretical analyses we observe that features of the problem space directly affect the choice of optimal parallel search strategy. We then employ machine learning techniques to select the optimal parallel search strategy for a given problem space. When a new search task is input to the system, EUREKA uses features describing the search space and the chosen architecture to automatically select the appropriate search strategy. EUREKA has been tested on a MIMD parallel processor, a distributed network of workstations, and a single workstation using multithreading. Results generated from fifteen puzzle problems, robot arm motion problems, artificial search spaces, and planning problems indicate that EUREKA outperforms any of the tested strategies used exclusively for all problem instances and is able to greatly reduce the search time for these applications.
A Single Image Super-Resolution Algorithm Using Non-Local-Mean Self-Similarity and Noise-Robust Saliency Map

This paper presents a single image super-resolution (SR) algorithm based on self-similarity using non-local-mean (NLM) metric. In order to accurately find the best self-example even under noisy environment, NLM weight is employed as a self-similarity metric. Also, a pixelwise soft-switching is presented to overcome an inherent drawback of conventional self-example-based SR that it seldom works for texture areas. For the pixel-wise soft-switching, an edge-oriented saliency map is generated for each input image. Here, we derived the saliency map which can be robust against noises by using a specific training. The proposed algorithm works as follows: First, auxiliary images for an input low-resolution (LR) image are generated. Second, self-examples for each LR patch are found from the auxiliary images on a block basis, and the best match in terms of self-similarity is found as the best self-example. Third, a preliminary high-resolution (HR) image is synthesized using all the self-examples. Next, an edge map and a saliency map are generated from the input LR image, and pixel-wise weights for soft-switching of the next step are computed from those maps. Finally, a super-resolved HR image is produced by soft-switching between the preliminary HR image for edges and a linearly interpolated image for non-edges. Experimental results show that the proposed algorithm outperforms state-of-the-art SR algorithms qualitatively and quantitatively. key words: self-similarity, super-resolution, self-example, NLM, softswitching
Dense Labeling with User Interaction: an Example for Depth-Of-Field Simulation

This work presents a method to achieve dense labeling in a very simple and efficient way, faster and with more flexibility than related approaches. We use an initial superpixel graph and reformulate its constraints as a sparse linear system of equations, which is efficiently solved as a linear least squares problem. We demonstrate our approach with an interactive application for depth-of-field simulated effects based on dense depth estimation from a single image. This kind of interactive application requires to continuously obtain a dense labeling estimation, therefore it is necessary to solve the task with high efficiency. Our experiments show our method obtains comparable results for a dense depth estimation against related approaches, while providing a more generic and powerful representation of the problem. The proposed dense labeling system opens new opportunities to design interactive applications that require dense labeling estimation of any other image property.
Low Complexity UWB Radios for Precise Wireless Sensor Network Synchronization

Wireless sensor networks are becoming widely diffused because of the flexibility and scalability they offer. However, distributed measurements are significant only if the readout is coupled to time information. For this reason, network-wide time synchronization is the main concern. The objective of this paper is to exploit a very simple hardware implementation of an IR-UWB radio for realizing an accurate synchronization system for wireless sensors. The proposed solution relies on commercial-off-the-shelf discrete electronic components (rather than on specialized transceivers). It is designed for providing accurate timestamping of the packet time of arrival (TOA) to an adder-based tunable clock, which tracks the network time reference. The comprehensive set of experimental results based on prototypes, shows a TOA detection error with a standard deviation well below 1 ns. On the other hand, in the FPGA-based prototype, the synchronization performance reaches an overall synchronization error of few nanoseconds. Finally, in order to highlight the tradeoff between timestamping accuracy, clock stability, and synchronization performance, some additional simulations have been carried out: a synchronization error in the order of 1 ns is possible, if good local oscillator sources are available in the nodes and if the adjustable clock has a sufficient resolution.
Involvement of Girdin in the Determination of Cell Polarity during Cell Migration

Cell migration is a critical cellular process that determines embryonic development and the progression of human diseases. Therefore, cell- or context-specific mechanisms by which multiple promigratory proteins differentially regulate cell migration must be analyzed in detail. Girdin (girders of actin filaments) (also termed GIV, Gα-interacting vesicle associated protein) is an actin-binding protein that regulates migration of various cells such as endothelial cells, smooth muscle cells, neuroblasts, and cancer cells. Here we show that Girdin regulates the establishment of cell polarity, the deregulation of which may result in the disruption of directional cell migration. We found that Girdin interacts with Par-3, a scaffolding protein that is a component of the Par protein complex that has an established role in determining cell polarity. RNA interference-mediated depletion of Girdin leads to impaired polarization of fibroblasts and mammary epithelial cells in a way similar to that observed in Par-3-depleted cells. Accordingly, the expression of Par-3 mutants unable to interact with Girdin abrogates cell polarization in fibroblasts. Further biochemical analysis suggests that Girdin is present in the Par protein complex that includes Par-3, Par-6, and atypical protein kinase C. Considering previous reports showing the role of Girdin in the directional migration of neuroblasts, network formation of endothelial cells, and cancer invasion, these data may provide a specific mechanism by which Girdin regulates cell movement in biological contexts that require directional cell movement.
Effects of the MDM2 promoter SNP285 and SNP309 on Sp1 transcription factor binding and cancer risk

The proto-oncogene MDM2 inhibits p53 and plays a key role in cell growth control and apoptosis. Identification of two antagonizing MDM2 polymorphisms, SNP285 and SNP309, affecting cancer risk through modulation of Sp1 transcription factor binding, shed new light on the biological activity and phylogeny of this gene.
Estimating vegetation fractional Coverage of Steppe based on Multi-spatial Resolution Remotely Sensed images

In this study, vegetation fractional coverage (VFC) of steppe was taken as the study object. Based on the Bottom-up method, we established the two-stage experiential model for estimating vegetation fractional coverage. In addition, this newly-established model is compared with sub-pixel model and common model that is acquired by simply regressing field data and remotely sensed data with moderate spatial resolution. The result suggests the two-stage experiential model for estimating vegetation fractional coverage successfully realize the aim of extending field data to local region, thereby making the spatial scale transformation of data true.
The Quest to Retain Teachers: One School System's Story of Teacher Movement

THE QUEST TO RETAIN TEACHERS: ONE URBAN-SUBURBAN SCHOOL SYSTEM’S STORY OF TEACHER MOVEMENT by Karen Smits Recent data on teacher attrition indicate that approximately 15 percent of teachers either leave the profession or move from one school to another each year. The attrition rate is highest for teachers new to the profession with 30-50 percent leaving within five years. High rates of attrition are a contributing cause of various educational problems including reduced student achievement, teacher shortages, declining teacher morale, and organizational discontinuity. The purpose of this study was to examine the reasons why teachers choose to leave the profession or move to another school from one year to the next. A qualitative case study was conducted to explore the reasons teachers from one urban-suburban school system voluntarily resigned at the end of one school year and what changes could have been made to keep them from leaving. The study answers three questions: Why do teachers leave? Why do some move to other schools while other teachers leave the profession? What could keep teachers from leaving? Data were collected using exit questionnaires, exit interviews, and semi-structured interviews of teachers leaving after the 2006-2007 school year. Data were analyzed using both deductive and inductive methods. Teachers who participated in this study made the decisions to move or leave for two primary reasons: administrative support and new opportunities. Administrative support took many forms and was described in a variety of ways including the following: administrative visibility, communication, use of time, support with student behavior, workload, implementation of new initiatives, and school climate. Teachers who left for new prospects were seeking different teaching opportunities or a better chance of moving into administration. The greatest difference between the teachers who moved and those who left the profession was hope. Teachers who moved to another school system believed the situation would be better elsewhere. Teachers who left the profession saw the struggles they endured as likely to occur in any teaching situation. Teachers indicated that they may have considered staying if they had received more administrative support, experienced better working conditions, had more supportive mentors, or had a teacher advocate who could have intervened on their behalf. THE QUEST TO RETAIN TEACHERS: ONE URBAN-SUBURBAN SCHOOL SYSTEM’S STORY OF TEACHER MOVEMENT by Karen Smits
On Planning an Evaluation of the Impact of Identifier Names on the Readability and Maintainability of Programs

—One of the long running debates between programmers is whether camelCaseIdentifiers are better than underscore_identifiers . This is ultimately a matter of programming language culture and personal taste, and to our best knowledge none of the camps has won the argument yet. It is our intuition that a solution exists which is superior to both the previous ones from the point of view of usability: the solution we name sentence case identiﬁers allows phrases as nams for program entities such as classes or methods. In this paper we propose a study in which to evaluate the impact of sentence case identiﬁers in practice.
The Role of Volume Inversion on the Intrinsic RF Performance of Double-Gate FinFETs

Quantum interactions between the inversion channels of multigate devices and their resulting effects on charge distribution and carrier mobility are analyzed in this paper. Results of this analysis are then used to assess the role of volume inversion on the intrinsic RF performance of double-gate FinFETs. Thin-fin devices are beneficial to low-operating and high-performance powers, and wideband RF blocks, while they are detrimental to low-power cross coupled pair-based RF oscillators, and are more power hungry for high-performance oscillators. Also, we highlight that the intrinsic capacitance variation induced by the fin volume inversion dominates the power and wideband RF performance of FinFETs over the variation in carrier mobility. Accurate definition of fin below 8-10 nm will enable extreme RF performance devices
Numerical modeling and Computational simulation of the SDE using C + + & FOTRAN 90 : Application in Fisheries management

In the present paper an attempt is made for the solution of SDE (Stochastic differential equation ) using different numerical simulation . Here the four different technique has been adopt for the two test problem for the verification process . Main emphasis is given on the RKM (Runge kutta Method) in which the solution has minimum number of absolute error . i.e more accurate then other. some of the solution has been given in the literature which adopt directly. The RKM (Runge kutta Method) code for the generalized IVP problem in C++ and FORAN 90 is also presented given for the sake of convince to understand the simulation process. The comparative study is also shows the accuracy of the RKM (Runge kutta Method) simulation process. The application of the specific problem is also found in the field of Fisheries Management