Miracle-dz/UniFAR-FTUs huggingface dataset:
Transmission Range Adjustment in WSNs Based on Dynamic Programming Algorithm

Recent studies show much energy can be saved and the capacity of wireless sensor networks (WSNs) can be significantly increased when route nodes can have variable transmission ranges. However, this will result some problems difficult to be dealt with. It is well known that in WSNs, energy can be saved by setting the redundancy nodes in sleeping mode along the multi-hop routes. In this paper, we consider the energy efficient route schemes in a linear network with the sensors uniformly distributed and the candidate route nodes randomly deployed. To find an optimal energy efficient route, a dynamic programming algorithm (DPA) is presented to select the optimal route nodes and their transmission ranges. Simulation results show the efficiency of the algorithm
CCN1/Cyr61-PI3K/AKT signaling promotes retinal neovascularization in oxygen-induced retinopathy

Retinal neovascularization (RNV) is a characteristic pathological finding of retinopathy of prematurity (ROP). Cysteine-rich 61 [Cyr61, also known as CCN family member 1 (CCN1)] has been reported to mediate angiogenesis. The aim of the present study was to investigate the mechanisms of CCN1/Cyr61-phosphoinositide 3-kinase (PI3K)/AKT signaling in ROP. The contribution of CCN1 to human umbilical vein endothelial cell (HUVEC) proliferation and apoptosis under hypoxic conditions was determined using a cell counting kit-8 (CCK-8) and Annexin V/propidium iodide (PI) staining, respectively, as well as using siRNA targeting CCN1 (CCN1 siRNA). The cells exposed to hypoxia were also treated with the PI3K/AKT inhibitor, LY294002. In addition, mouse pups with oxygen-induced retinopathy (OIR) were administered an intravitreal injection of CCN1 siRNA. RNV was assessed by magnesium-activated adenosine diphosphatease (ADPase) staining. RT-qPCR, western blot analysis, immunofluorescence staining and immunohistochemistry were used to detect the distribution and expression of CCN1, PI3K and AKT. Exposure to hypoxia increased the neovascularization clock hour scores (from 1.23±0.49 to 5.60±0.73, P<0.05) and the number of preretinal neovascular cells, as well as the mRNA and protein expression levels of CCN1, PI3K and AKT (all P<0.05). The injection of CCN1 siRNA decreased the neovascularization clock hour scores and the number of preretinal neovascular cells (1.53±0.72 vs. 4.76±1.04; 12.0±2.8 vs. 31.4±2.6, respectively, both P<0.05), as well as the mRNA and protein expression levels of CCN1, PI3K and AKT (protein, −45.3, −22.5 and −28.4%; mRNA, −43.7, −58.7 and −42.9%, respectively, all P<0.05) compared to the administration of scrambled siRNA under hypoxic conditions. Treatment with LY294002 decreased the mRNA and protein expression levels of CCN1 in the cells exposed to hypoxia (both P<0.05). The administration of CCN1 siRNA resulted in less severe neovascularization in the eyes of the the mouse pups with OIR. Thus, out data suggest that CCN1 plays an important role in RNV in ROP, and may thus be a potential target for the prevention and treatment of ROP.
Recognizing facial expressions based on Gabor filter selection

Recognition of human emotional state is an important component for efficient human-computer interaction. In this paper a method of Gabor filter selection for facial expression recognition is investigated. We first preprocess facial images based on affine transform to normalize the faces. Then the using of a separability judgment is proposed to evaluate the separability of different Gabor filters, and only use those filters that can better separate different expressions. In the recognition process a PCA and FLDA multiclassifier scheme is used. The experiment result shows that the introducing of Gabor filter selection can not only reduce the dimension of feature space but also reduce the computation complexity significantly, while retaining high recognition rate of above 93%.
Computer-assisted spherical osteotomy with a curved-bladed Tuke Saw®

Techniques for spherical osteotomy, such as rotational acetabular osteotomy, can help orthopaedic surgeons correct bony deformities and remove spherical acetabular components. Curved chisels are used during a spherical osteotomy, but they require skill and have a potential risk of damaging blood vessels or nerves. In order to perform a precise, quick and safe spherical osteotomy, we have developed a novel computer-assisted surgical tool using a vibrating bone saw, the Tuke Saw®, with a curved blade that operates under the guidance of an optical navigation system. In this study, the accuracy and ease of use of this curved-bladed Tuke Saw® in spherical osteotomy were examined in comparison with the conventional curved chisel. Using these surgical tools, hemispherical osteotomies were performed on rectangular parallelepiped Sawbones® blocks and rotational acetabular osteotomies were performed on cadaveric pelves. The distance error with the curved-bladed Tuke Saw® was significantly smaller than that with the curved chisel, and the procedure time with the Tuke Saw® was approximately half that with the chisel. It can thus be concluded that the curved-bladed Tuke Saw® is more accurate and easier to use than the conventional curved chisel.
Design of robust control and monitoring system for microgrid stabilization

This paper proposes a design of the robust control and monitoring system (RCMS) for stabilization of microgrid (MG) system. The power sources in MG consists of wind power (WP), photovoltaic (PV), micro-turbine (MT) and fuel cell (FC). Due to intermittent powers from WP, PV and load fluctuations, the MG stabilization of RCMS is performed by controlling the power outputs of MT and electrolyzer system (ES) in both islanding and interconnected utility grid operations. The structure of MT and ES controllers is the proportional integral (PI). By taking system uncertainties into account, control parameters of MT and ES are simultaneously optimized based on the particle swarm optimization (PSO) based fixed-structure H∞ loop shaping control. Simulation results show the robustness and effectiveness of the proposed RCMS against the variation of system parameters and operating conditions.
Preliminary Version Encryption as an abstract datatype : An extended abstract

At the Dolev-Yao level of abstraction, security protocols can be specified using multisets rewriting. Such rewriting can be modeled naturally using proof search in linear logic. The linear logic setting also provides a simple mechanism for generating nonces and session and encryption keys via eigenvariables. We illustrate several additional aspects of this direct encoding of protocols into logic. In particular, encrypted data can be seen naturally as an abstract data-type. Entailments between security protocols as linear logic theories can be surprisingly strong. We also illustrate how the well-known connection in linear logic between bipolar formulas and general formulas can be used to show that the asynchronous model of communication given by multiset rewriting rules can be understood, more naturally as asynchronous process calculus (also represented directly as linear logic formulas). The familiar proof theoretic notion of interpolants can also serve to characterize communication between a role and its environment.
CAN COMPUTERS LEARN FASTER ?

Ever since computers were invented, mankind wondered whether they might be made to learn. In the field known as data mining, text categorization has been extensively studied by the machine learning community, as it is a classic example of supervised learning by machines. In supervised learning, computers learn from a categorization function which is calculated using the information from the labeled training data provided by the supervisor. Then, it can classify any unlabeled document into predefined categories. It is known that the learner’s approximation of the function will improve with the amount of training data supplied to it. However supplying training data to the learning machine is expensive in terms of time and money since it is generally done by humans. In this paper, our motivation is to decrease the number of training data needed by the computers in order to decrease the human intervention as much as possible. This paper talks about a very efficient method to select the training data from the unlabeled data pool to train the classifier machines. We present experimental results showing that with carefully selected training data, the need for labeled data can be significantly reduced, and the learner’s classification performance is preserved, even increased in some cases.
Generating fluent tubes in video synopsis

Video synopsis is one of the effective techniques to build a short video representation preserving the essential activities for a long video. Existing methods usually have the problem that a continuous activity (tube) from a single moving object is separated to a few small pieces. In this paper, two schemes are proposed to generate fluent tubes for video synopsis. The Gaussian mixture model and a texture method are combined to detect more compact foreground with shadow removed. The foreground constitutes a set of initial trajectories. A particle filter tracker is used to concatenate two trajectories if they belong to the same foreground activity, which generates more fluent tubes for video synopsis. Experimental results on 4 videos show that our method produces better accuracies and visual effects in video synopsis.
Cyclostationary detection of 5G GFDM waveform in cognitive radio transmission

Generalized frequency division multiplexing (GFDM) is a new flexible multicarrier waveform. With the flexibility of pulse shaping techniques and a tail-biting cyclic prefix, it has very low out of band leakage. This makes this potential 5G waveform suitable for cognitive radio opportunistic access with lower interference to the adjacent legacy/primary users. Because of the per-subcarrier pulse shaping technique, the cyclostationary autocorrelation properties of GFDM produces extra correlation peaks at particular cyclic frequencies. Cyclostationary detection based on these side peaks improve the spectrum sensing of GFDM over traditional OFDM. The GFDM receiver with ICI cancellation unit mitigates the ICI for any values of the roll-off factor, and hence, increasing the roll-off factor does not impact the BER performance of the GFDM system. This paper highlights the innovative cyclostationary properties of GFDM and studies the effect of pulse shaping roll-off factors on detection performance.
Hybrid color filter array demosaicking for effective artifact suppression

Color filter array (CFA) demosaicking is an essential process for restoring full-color images from incomplete color samples acquired by single-sensor digital cameras. We present two main contributions to CFA demosaicking. First, we analyze the causes of two main types of CFA demosaicking artifacts and examine the schemes that are effective in suppressing them, respectively. Second, by combining and extending the core merits of the schemes examined, we compose a new CFA demosaicking algorithm to suppress as many demosaicking artifacts as possible and obtain full-color images of high quality. Experiments using a large variety of test images have been conducted, and the results show that the proposed method outperforms the existing state-of-the-art methods both visually and in terms of peak signal-to-noise ratio.
A succinct physical storage scheme for efficient evaluation of path queries in XML

Path expressions are ubiquitous in XML processing languages. Existing approaches evaluate a path expression by selecting nodes that satisfies the tag-name and value constraints and then joining them according to the structural constraints. We propose a novel approach, next-of-kin (NoK) pattern matching, to speed up the node-selection step, and to reduce the join size significantly in the second step. To efficiently perform NoK pattern matching, we also propose a succinct XML physical storage scheme that is adaptive to updates and streaming XML as well. Our performance results demonstrate that the proposed storage scheme and path evaluation algorithm is highly efficient and outperforms the other tested systems in most cases.
Comparative In Vitro Study of Contact-and Image-Based Rigid Registration for Computer-Aided Surgery

We present an in vitro study of rigid registration methods for computer-aided surgery. The goals of the study were to obtain accuracy measures empirically under optimal laboratory conditions, and to identify the weak links in the registration chain. Specifically, we investigated two common registration methods (contact-based registration and image-based landmark registration) and established a framework for comparing the accuracy of both methods. The phantoms, protocols, and algorithms for tool tip calibration, contact-based registration with an optical tracker, fluoroscopic X-ray camera calibration, and fluoroscopic X-ray image-based landmark registration are described. Average accuracies of 0.5 mm (1.5 mm maximum) and 2.75 mm (3.4 mm maximum) were found for contact-based and image-based landmark registration, respectively. Based on these findings, the camera calibration was identified as being the main source of error in image-based landmark registration. Protocol improvements and algorithmic refinements to improve the accuracy of image-based landmark registration are proposed.
HIGH SPEED AND LOWER HARDWARE COMPLEXITY VLSI ARCHITECTURE FOR LIFTING BASED DISCRETE WAVELET TRANSFORM

—A high speed and lower hardware complexity 2-D discrete wavelet transform architecture has been proposed. Previous DWT architectures are based on the modified lifting scheme or the flipping structure. Folded architecture method has been adopted. In the proposed architecture, modifications are made to the lifting scheme, and the intermediate results are combined to form the lifting elements. So as the number of registers can be reduced without extending the critical path. , the two-input/two-output parallel scanning architecture is adopted in our design. For a 2-D DWT with the size of N × N, the proposed architecture requires three registers as data memory, and a higher efficiency can be achieved.
Enterprise Architecture for Addressing Business Transformation Challenges: The Case of Embedded Mobile Provisioning Process in the Telecommunications Industry

The present is a report of an exploratory case study about using an Enterprise Architecture method for addressing the business transformation challenges of embedded mobile provisioning in the telecommunications industry. The study focused on the analysis of the provisioning process for gathering transformation requirements, translating them into business objectives and deriving a set of strategic initiatives. In addition, it explored the construction and usefulness of visual representations of the vision and strategy. The results show that such formal method is perceived useful for defining the transformation strategy.
The transition between tonic spiking and bursting in a six-transistor neuromorphic device

We introduce a novel methodology to implement the physiological transition between tonic spiking and bursting in electronic circuits composed of resistors, capacitors and transistors. The result is a six-transistor neuromorphic device organized by the same geometry of high-dimensional electrophysiological neuron models and therefore exhibiting the same qualitative behavior.
Social Network Analysis Layout Algorithm under Ontology Model

Social network analysis and visualization is an active area of study but good organizations of social network information are lacking. This paper proposes a domain ontologies model focusing on social network information, which abstracts the impersonal existences in social network information domain into some primary ontologies. The model is suitable for describing a wide variety of social network analysis and visualization methods. For overcoming the disadvantage of transitional force directed layout algorithms in social network structure analysis, we propose a Social Network Analysis Layout (SNAL) algorithm based on domain ontologies model. SNAL algorithm analyses the subgroups, the roles and the key attributes in social network. Then the results are used to improve the force directed layout algorithm, in both 2D and 3D visualization. Results with the case of terrorist information demonstrate its advantages in analyzing and displaying the structure of social network.
Modulation of gut mucosal biofilms

Non-digestible inulin-type fructans, such as oligofructose and high-molecular-weight inulin, have been shown to have the ability to alter the intestinal microbiota composition in such a way that members of the microbial community, generally considered as health-promoting, are stimulated. Bifidobacteria and lactobacilli are the most frequently targeted organisms. Less information exists on effects of inulin-type fructans on the composition, metabolism and healthrelated significance of bacteria at or near the mucosa surface or in the mucus layer forming mucosa-associated biofilms. Using rats inoculated with a human faecal flora as an experimental model we have found that inulin-type fructans in the diet modulated the gut microbiota by stimulation of mucosa-associated bifidobacteria as well as by partial reduction of pathogenic Salmonella enterica subsp. enterica serovar Typhimurium and thereby benefit health. In addition to changes in mucosal biofilms, inulin-type fructans also induced changes in the colonic mucosa stimulating proliferation in the crypts, increasing the release of mucins, and altering the profile of mucin components in the goblet cells and epithelial mucus layer. These results indicate that inulin-type fructans may stabilise the gut mucosal barrier. Dietary supplementation with these prebiotics could offer a new approach to supporting the barrier function of the mucosa.
Måleegenskaper ved den norske foreldreversjonen av Behavior Rating Inventory of Executive Function (BRIEF)

Description. The Behavior Rating Inventory of Executive Function (BRIEF) is a parent report questionnaire for children and youth aged 5-18 years. The questionnaire assesses executive functions in everyday life. BRIEF was developed by Gioia, Isquith, Guy and Kenworthy (2000) and was translated into Norwegian by Nicholas and Hermansen (2004), and later revised by Fallmyr, Ekerholt and Nicholas (2007). A license by the copyright holder PAR, Inc. is needed to buy and use
The role of networking and social media tools during job search: an information behaviour perspective.

The paper presents a critical analysis of the extant literature pertaining to the networking behaviours of young jobseekers in both offline and online environments. A framework derived from information behaviour theory is proposed as a basis for conducting further research in this area. Method. Relevant material for the review was sourced from key research domains such as library and information science, job search research, and organisational research. Analysis. Three key research themes emerged from the analysis of the literature: (1) social networks, and the use of informal channels of information during job search, (2) the role of networking behaviours in job search, and (3) the adoption of social media tools. Tom Wilson’s general model of information behaviour was also identified as a suitable framework to conduct further research. Results. Social networks have a crucial informational utility during the job search process. However, the processes whereby young jobseekers engage in networking behaviours, both offline and online, remain largely unexplored. Conclusion. Identification and analysis of the key research themes reveal opportunities to acquire further knowledge regarding the networking behaviours of young jobseekers. Wilson’s model can be used as a framework to provide a holistic understanding of the networking process, from an information behaviour perspective.
Control of a thrust‐vectored flying wing: a receding horizon—LPV approach

This paper deals with the application of receding horizon methods to hover and forward flight models of an experimental tethered flying wing developed at Caltech. The dynamics of the system are representative of a vertical landing and take off aircraft, such as a Harrier around hover, or a thrust‐vectored aircraft such as F18‐HARV or X‐31 in forward flight. The adopted control methodology is a hybrid of receding horizon techniques and control Lyapunov function (CLF)‐based ideas.
Sports video categorizing method using camera motion parameters

In this paper, we propose a content based video categorizing method focusing broadcasted sports videos using camera motion parameters. We define two new features in the proposed method; "camera motion extraction ratio" and "camera motion transition". Camera motion parameters in the video sequence contain very significant information for categorization of broadcasted sports video, because in most of sports video, camera motions are closely related to the actions taken in the sports, which are mostly based on a certain rule depending on types of sports. Based on the characteristics, we design a sports video categorization algorithm for identifying 6 major different sports types. In our algorithm, the features automatically extracted from videos are analyzed in a statistical manner. The experimental results show a clear tendency the applicability of the proposed method for sports genre identification.
Updating Wireless Signal Map with Bayesian Compressive Sensing

In a wireless system, a signal map shows the signal strength at different locations termed reference points (RPs). As access points (APs) and their transmission power may change over time, keeping an updated signal map is important for applications such as Wi-Fi optimization and indoor localization. Traditionally, the signal map is obtained by a full site survey, which is time-consuming and costly. We address in this paper how to efficiently update a signal map given sparse samples randomly crowdsourced in the space (e.g., by signal monitors, explicit human input, or implicit user participation). We propose Compressive Signal Reconstruction (CSR), a novel learning system employing Bayesian compressive sensing (BCS) for online signal map update. CSR does not rely on any path loss model or line of sight, and is generic enough to serve as a plug-in of any wireless system. Besides signal map update, CSR also computes the estimation error of signals in terms of confidence interval. CSR models the signal correlation with a kernel function. Using it, CSR constructs a sensing matrix based on the newly sampled signals. The sensing matrix is then used to compute the signal change at all the RPs with any BCS algorithm. We have conducted extensive experiments on CSR in our university campus. Our results show that CSR outperforms other state-of-the-art algorithms by a wide margin (reducing signal error by about 30% and sampling points by 20%).