Miracle-dz/UniFAR-FTUs huggingface dataset:
Tetrahedral framework registration algorithm for the robot-assisted surgical navigation system

The accuracy of registration is one of the key issues in surgical navigation, which directly affects the result of operation. In this paper, we proposed a new registration algorithm, Tetrahedral Framework (TF), to improve precision and computing speed and conducted a calibration experiment by using the wax model with markers. The image data are obtained by Micro-CT scanning and loaded in VTK to gain the coordinate of the markers, while the tracking data in real space are collected from NDI equipment. The proposed TF algorithm can be described as follow. Firstly, the two point-sets are respectively divided into a tetrahedral framework part and a few of particles; secondly, the scale coefficient is calculated for mapping the image data into the real space; finally, the particle swarm optimization (PSO) is used to adjust the positions and attitude of image framework to acquire a maximal projection on the tracking framework planes. In order to improve the precision of registration, we combined the particles information in an optimization process. Besides, the experimental results show that the algorithm can satisfy the requirement in surgical navigation.
DPLM: a novel application-layer routing scheme for low delay VoIP

In order to achieve low delay services in VoIP, we can use application-layer routing scheme, which is to find proper relay nodes to intermediate voice packets from the source peer to the destination peer. The difficulty of the scheme is how to find the proper relay nodes, which we call relay problem. This paper presents a new application-layer routing scheme, called DPLM, to resolve relay problem. We introduced the mechanism in detail, and evaluated our mechanism in NS2 network simulation environment and got a high relay node hit ratio result, which confirms the feasibility of a real system. Also we make a comparison with traditional schemes, and the results show that DPLM scheme has good performances.
GA-Based Job Scheduling Strategies for Fault Tolerant Grid Systems

This work mainly aims at the designs of the genetic algorithm based scheduling strategies by considering four different fault tolerance techniques in the grid environment, including retry, migration, checkpoint, replication. We also take into account the risk relationship between jobs and nodes to improve the system reliability in the scheduling algorithm. According to the simulation results, we can find out that the performance of fault tolerant algorithms is better than risky algorithm whether in makespan, average turnaround time, or the job failure rate. Checkpoint algorithm has the best performance in all algorithms. On the other hand, retry algorithm is recommended for the system where the job sizes are usually smaller because of its simplicity. Finally, replicated algorithm is not suitable for the grid since it imposes too much overhead.
Directional antennas for wireless sensor networks

Directional antennas provide angle-of-arrival information, which can be used for localization and routing algorithms in wireless sensor networks. We briefly describe three classical, major types of antennas: 1) the Adcock-pair antenna, 2) the pseudo-Doppler antenna, and 3) the electronically switched parasitic element antenna. We have found the last type to be the most suitable for wireless sensor networks, and we present here the early design details and beam pattern measurements of a prototype antenna for the 2.4-GHz ISM band, the SPIDA: SICS Parasitic Interference Directional Antenna.
The Genomic Architecture of Interactions Between Natural Genetic Polymorphisms and Environments in Yeast Growth

Gene-environment interaction (G×E) refers to the phenomenon that the same mutation has different phenotypic effects in different environments. Although quantitative trait loci (QTLs) exhibiting G×E have been reported, little is known about the general properties of G×E, and those of its underlying QTLs. Here, we use the genotypes of 1005 segregants from a cross between two Saccharomyces cerevisiae strains, and the growth rates of these segregants in 47 environments, to identify growth rate QTLs (gQTLs) in each environment, and QTLs that have different growth effects in each pair of environments (g×eQTLs) . The average number of g×eQTLs identified between two environments is 0.58 times the number of unique gQTLs identified in these environments, revealing a high abundance of G×E. Eighty-seven percent of g×eQTLs belong to gQTLs, supporting the practice of identifying g×eQTLs from gQTLs. Most g×eQTLs identified from gQTLs have concordant effects between environments, but, as the effect size of a mutation in one environment enlarges, the probability of antagonism in the other environment increases. Antagonistic g×eQTLs are enriched in dissimilar environments. Relative to gQTLs, g×eQTLs tend to occur at intronic and synonymous sites. The gene ontology (GO) distributions of gQTLs and g×eQTLs are significantly different, as are those of antagonistic and concordant g×eQTLs. Simulations based on the yeast data showed that ignoring G×E causes substantial missing heritability. Together, our findings reveal the genomic architecture of G×E in yeast growth, and demonstrate the importance of G×E in explaining phenotypic variation and missing heritability.
Face Detection , Extraction , and Swapping on Mobile Devices

The Face Swap algorithm uses Viola-Jones face detection, Active Shape Model fitting, and Laplacian Pyramids among other methods to locate faces in an image and swap them while maintaining a natural and realistic look. The main application of this this software is preventing unwanted online identification of people in photos, such as those on Google and Bing Maps.
Interconnect simulation using FDTD method with variable mesh size technique

This paper describes the electromagnetic field simulation using FDTD method with the variable mesh size technique. In this technique, the mesh size is changed dynamically during the simulation. In this method, the mesh size and the time step size are controlled according to the electromagnetic field intensity. The proposed technique can reduce the simulation cost without degradation of accuracy, even if the simulation is done for the input signal including the high frequency factors. Finally, the validity and efficiency of the proposed method are verified by some electromagnetic field simulations for the example boards.
Implementeringen af motion og bevægelse i skolen – et review af hæmmende og fremmende faktorer set i et lærerperspektiv

Implementeringen af den ny skolereform inkluderer 45 minutters daglig motion og bevaegelse for alle elever. Formalet med artiklen er at praesentere en oversigt over eksisterende videnskabelige studier, der har undersogt faktorer, som pavirker laereres oplevelse af og villighed til at implementere motion og bevaegelse. Vi har sogt i 6 databaser (2000-2016) og inkluderet 24 studier. Vi har brugt en socio-okologisk model i praesentationen af resultaterne og Rogers’ diffusion of innovation teori i diskussionen af haemmende og fremmende faktorer. Mangel pa tid som folge af akademisk pres, og mangel pa viden, kompetencer og support er blandt de haemmende faktorer.
Toward a Theory of Socialization in Open Source Software Communities: A Symbolic Interactionist Perspective

Recent literature reviews highlight a gap in our understanding of how members socialize into virtual communities. Motivated by this shortcoming, we seek to understand how members socialize into open source software (OSS) communities, which are both virtual and normative in nature. Using the symbolic interactionist perspective, we define socialization and explicate the socialization process in OSS communities. Specifically, we define socialization as the extent of correspondence between the personal meanings of individual members and the shared meanings of the community, which emerge from the negotiated experiences of members. In addition, we posit that the socialization process consists of the interplay between individuals’ meaning-making process, consisting of both action and personal meaning, and the negotiated shared meanings within the community.
KUKA youBot - a mobile manipulator for research and education

Establishing mobile manipulation as a powerful key technology for the cognitive factory requires mobile manipulation platforms, which at the same time pay attention to industrial requirements, meet requirements of education and research and last, but not least, come with a decent price tag. KUKA has recently launched a major research and development effort towards designing a mobile manipulation platform that meets these requirements and can serve as a reference platform for industry, research and education at the same time. Although the initiative has just left the starting blocks, a first off-spring, the KUKA youBot, an omni-directional mobile manipulator has just seen the light of day. In this paper we report on the development of the first prototypes.
A Sparse Representation-Based Binary Hypothesis Model for Target Detection in Hyperspectral Images

In this paper, a new sparse representation-based binary hypothesis (SRBBH) model for hyperspectral target detection is proposed. The proposed approach relies on the binary hypothesis model of an unknown sample induced by sparse representation. The sample can be sparsely represented by the training samples from the background-only dictionary under the null hypothesis and the training samples from the target and background dictionary under the alternative hypothesis. The sparse vectors in the model can be recovered by a greedy algorithm, and the same sparsity levels are employed for both hypotheses. Thus, the recovery process leads to a competition between the background-only subspace and the target and background subspace, which are directly represented by the different hypotheses. The detection decision can be made by comparing the reconstruction residuals under the different hypotheses. Extensive experiments were carried out on hyperspectral images, which reveal that the SRBBH model shows an outstanding detection performance.
Development of a High-Resolution Melting Analysis Method for CYP2C19*17 Genotyping in Healthy Volunteers

Background: Genetic polymorphisms of drug metabolisms by cytochrome P450 (P450s) could affect drug response, attracting particular interest in the pharmacogenetics. Due to the importance of CYP2C19* 17 allele and its capability of super- fast metabolism and also lack of information about distribution of the alleles in Iranian population, this research aimed to use High Resolution Melting (HRM) method compared to PCR-RFLP for genotyping healthy Iranian population. Methods: Blood samples were collected from 100 healthy Iranian volunteers. DNA was extracted by salting out method. Real-time PCR was used for amplification of the CYP2C19 gene and the alleles were identified by HRM. Sequencing was used to confirm the amplified DNA fragments and data were analyzed using SPSS software ver.18. Results: The frequency of alleles CYP2C19*1/*1, CYP2C19*1/*17 and CYP2C19*17/*17 were estimated as 58.33, 29.1 and 11.1%, respectively. Specificity and sensitivity of HRM method were 90% and 100%, with respect to PCR-RFLP. Also, HRM analysis has been evaluated as a faster and more effective approach. Conclusion: Comparison of our results based on HRM analysis with PCR-RFLP showed that our developed method is rapid, accurate, fast and economic to study the CYP2C19*17 allele and it is appropriate for other similar population genetic studies.
COMPLESSITÀ LINGUISTICA E VARIAZIONE SINTATTICA

In this paper I analyse the notion of linguistic complexity. It has been recently applied by linguists, above all in cross-linguistic analysis, in order to discuss on language change or on patterns in language acquisition which recur both in languages that do not belong to the same linguistic family and in languages that belong to different types. In the second part of the paper I apply the notion of linguistic complexity in order to describe and to explain some aspects of syntactic variability in Italian.
Researching and communicating the complexity of IT image management

Today, the process of image management is extremely time-consuming for IT administrators. Until now, this complicated process has not been extensively explored by design researchers. During a recent research study at Citrix, we interviewed 17 IT professionals. We used a process we call "adaptive interviewing," a flexible methodology that could accommodate the various infrastructures of IT organizations and the diversity of ways that administrators handle image management. While conducting our interviews, we worked with our information designer to create several visualizations of our data. Ultimately, we found that supplementing interviews with information visualizations is a powerful way to explore, understand, and explain the complex system of IT image management.
Bits extraction for palmprint template protection with Gabor magnitude and multi-bit quantization

In this paper, we propose a method of fixed-length binary string extraction (denoted by LogGM_DROBA) from low-resolution palmprint image for developing palmprint template protection technology. In order to extract reliable (stable and discriminative) bits, multi-bit equal-probability-interval quantization and detection rate optimized bit allocation (DROBA) are operated on the real-valued features, which are resulted from representing the palmprint image by simple statistics on logarithmic transform of Gabor magnitude (LogGM). Assuming the Helper Data Scheme with a BCH error correction coding is adopted for template protection, the performance is evaluated on the Hong Kong PolyU palmprint database. The experimental results show that our method can achieve low Bit Error Rate (BER) resulted from genuine binary strings so that a long secret key (around 100 bits) is allowed to be combined for security, and low False Rejection Rate and low False Acceptance Rate (FRR/FAR) when the key retrial process is considered as a Hamming distance classifier, which verify the high stability and strong distinctive ability of our extracted palmprint binary string.
Implementing graph coloring heuristic in construction phase of curriculum-based course timetabling problem

Curriculum-based course timetabling problem (CB-CTP) is a classical problem that is still being researched on nowadays. There are two phases in solving CB-CTP. The first phase is the construction phase where a population of initial solutions is generated. The second phase is the optimization phase where the final optimal solution is produced. While most papers concentrate on the optimization phase, this paper focuses on the construction phase due to the importance of initial solutions to the optimization phase. The initial solutions are generated by implementing graph coloring heuristic to the CB-CTP. The graph coloring heuristics used in this paper are largest degree and largest weighted degree. Result from computational experiment shows that both methods are able to produce population of initial solutions for almost every data instance.
The Role of Cognitive and Metacognitive Tool Use in Narrative-Centered Learning Environments.

SHORES, LUCY R. The Role of Cognitive and Metacognitive Tool Use in NarrativeCentered Learning Environments. (Under the direction of James C. Lester). Inquiry-based learning has shown to afford several opportunities for domain knowledge acquisition while also developing inquiry and self-regulatory skills obligatory for lifelong learning. However, several challenges create an impasse for the execution of such instruction including creating self-sustaining, engaging environments and providing requisite individualized guidance and support as students often lack the necessary skills for successful inquiry-based learning. Advancements in intelligent technologies provide a platform for investigating the potential for computer-based learning environments as a means for creating inquiry-based learning environments equipped with cognitive and metacognitive tools that automatically generate personalized guidance. This thesis presents a specific cognitive and metacognitive tool for assisting students during inquiry-based learning within a narrative-centered learning environment. A 137subject experiment revealed the tool, an organized virtual space designed to assist students with organizing and reasoning about collected information, if used correctly, is indicative of significant domain learning gains. Domain learning gains were especially prevalent for students coming into the experiment with relatively low levels of prior knowledge. Because of the advantageous nature of the tool, machine learning modeling techniques were employed in order to predict student tool use as early as possible. Identification of students prone to inadequately use the space can be incorporated within more robust student models to generate personalized feedback to promote the use of the space; therefore, identifying such students as early as possible allows more time for the system to guide the student to utilize the tool as much as possible. The results of the modeling indicated students can be identified as either good or poor users of the tool by the first ten minutes of interaction. This finding suggests machine learning classifiers are sufficient for generating informative models, which can be used to produce influential guidance for the use of this compensatory space. The Role of Cognitive and Metacognitive Tool Use in Narrative-Centered Learning Environments
Implicit Prime Cover Computation : An OverviewOlivier

A set of products is a prime cover of a Boolean function f if it is made of prime implicants of f, and if the sum of its products covers f. Finding a prime cover, an irredundant prime cover, or a minimal prime cover of a function f is a problem that arises in several elds of computer science, for instance in logic synthesis, automated reasoning, realiability analysis, and some optimization problems. This paper shows how the three prime cover computation problems mentioned above can be eeciently solved using implicit manipulations of sets of products.
Mindfulness and the ethics of intercultural knowledge-work

ABSTRACT Mindfulness, or 念 (niàn) in Chinese, is a concept and set of related practices which have both ancient Eastern roots and current popularity (especially in the West). It provides a fascinating example of intercultural knowledge-work involving a complex set of conceptual migrations through time and space, across languages and cultures, and within domains and disciplines. We first review the vitality of the concept as used in Western disciplines (chiefly intercultural communication and psychotherapy), noting how the Eastern origins are mentioned but not fully discussed. We then review the ancient origins in Eastern religious and philosophical thinking concluding with an account of the development of the term in the East until recent times. As we discuss next, when these differing arenas of use and development interact, understandings become contested and issues of privilege vis-á-vis knowledge sources can be seen. These complexities raise questions about authenticity versus translation with regard to the differing uses made of the concept in the different arenas. Learning from the reviews of the differing understandings of this concept and the sometimes fraught interactions between them, we propose that scholars and practitioners working in our highly interconnected era, adopt an intercultural ethic to regulate and guide such knowledge-work.
High (≥6.5) Spontaneous and Persistent Urinary pH Is Protective of Renal Function at Baseline and during Disease Course in Idiopathic Membranous Nephropathy

Metabolic acidosis correction in advanced renal failure slows renal function decline attributed to tubulointerstitial damage (TID) reduction. No study evaluated if spontaneous baseline high urinary pH (UpH) is renoprotective in patients with normal renal function and without metabolic acidosis. The study tested this hypothesis in idiopathic membranous nephropathy (IMN). Eighty-five patients (follow-up 81 ± 54 months) measured UpH, serum creatinine, eGFR, protein/creatinine ratio, fractional excretion of albumin, IgG, α1-microglobulin, and urinary N-acetyl-β-D-glucosaminidase (β-NAG)/creatinine ratio. Twenty-eight patients (33%) had UpH ≥ 6.5 and 57 (67%) pH < 6.5; high versus low UpH patients had significantly lower values of the tubulointerstitial damage (TID) markers FE α1m and β-NAG and significantly better baseline renal function. These differences persisted over time in a subset of 38 patients with 5 measurements along 53 ± 26 months. In 29 patients with nephrotic syndrome (NS) treated with supportive therapy (follow-up: 80 ± 52 months) renal function was stable in 10 high and significantly worse in 19 low UpH patients. Steroids + cyclophosphamide treatment in 35 NS patients masks the renoprotection of high UpH. Conclusions. In IMN high and persistent UpH is associated with reduction of the proteinuric markers of tubulointerstitial damage and baseline better renal function in all patients and in NS patients treated only with supportive therapy during disease course. The factors associated with high pH-dependent renoprotection were lower values of TID markers, eGFR ≥ 60 mL/min, BP < 140/90 mmHg, and age < 55 years.
Liquid surface tracking with error compensation

Our work concerns the combination of an Eulerian liquid simulation with a high-resolution surface tracker (e.g. the level set method or a Lagrangian triangle mesh). The naive application of a high-resolution surface tracker to a low-resolution velocity field can produce many visually disturbing physical and topological artifacts that limit their use in practice. We address these problems by defining an error function which compares the current state of the surface tracker to the set of physically valid surface states. By reducing this error with a gradient descent technique, we introduce a novel physics-based surface fairing method. Similarly, by treating this error function as a potential energy, we derive a new surface correction force that mimics the vortex sheet equations. We demonstrate our results with both level set and mesh-based surface trackers.
Hybrid LS-LMMSE Channel Estimation Technique for LTE Downlink Systems

In this paper, we propose to improve the performance of the channel estimation for LTE Downlink systems under the effect of the channel length. As LTE Downlink system is a MIMO-OFDMA based system, a cyclic prefix (CP) is inserted at the beginning of each transmitted OFDM symbol in order to mitigate both intercarrier interference (ICI) and inter-symbol interference (ISI). The inserted CP is usually equal to or longer than the channel length. However, the cyclic prefix can be shorter because of some unforeseen channel behaviour. Previous works have shown that in the case where the cyclic prefix is equal to or longer than the channel length, LMMSE performs better than LSE but at the cost of computational complexity . In the other case, LMMSE performs also better than LS only for low SNR values. However, LS shows better performance for LTE Downlink systems for high SNR values. Therefore, we propose a hybrid LS-LMMSE channel estimation technique robust to the channel length effect. MATLAB Monte –Carlo simulations are used to evaluate the performance of the proposed estimator in terms of Mean Square Error (MSE) and Bit Error Rate (BER) for 2x2 LTE Downlink systems.