Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Path Setup for a Photonic Network-on-Chip

Electrical Network-on-Chip (NoC) faces critical challenges in meeting the high performance and low power consumption requirements for future multicore processors interconnection. Recent tremendous advances in CMOS compatible optical components give the potential for photonics to deliver an efficient NoC performance at an acceptable energy cost. However, the lack of in ¿ight processing and buffering of optical data made the realization of a fully optical NoC complicated. A hybrid architecture which uses optical high bandwidth transfer and a tiny electrical control network can take advantage of both interconnection methods to offer an efficient performance-per-watt infrastructure to connect multicore processors and System-on-Chip (SoC). In this paper, we propose a hybrid photonic torus NoC (HPNoC) that uses a predictive switching to improve the performance of a hybrid architecture. By using prediction techniques, we can reduce the path set up latency for the electrical control network hence improving the overall end-to-end delay for communication in the HPNoC. Simulation results using a cycle accurate simulator under uniform, neighbor and bit reversal traffic patterns for 64 nodes show that predictive switching considerably improves the HPNoC overall performance.
A Transport Protocol for Real-time Applications

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Arabic complementary schools in England: language and Fundamental British Values

ABSTRACT Heritage language education is not included in the national curriculum in England, and therefore formal learning and teaching of heritage languages are primarily achieved through complementary schools, which are part-time, community-led and linked to various ethnic and national backgrounds. This study focuses on Arabic complementary schools and explores educational practices for teaching Arabic. The study also explores how pupils and teachers conceptualise, construct and manifest their linguistic and social identity, especially with regard to the context that is informed by the promotion of so-called Fundamental British Values (FBV). Observations are based on data from interviews with pupils, teachers and headteachers from three Arabic complementary schools across England. A qualitative analysis of the data reveals that the schools are strongly committed to tolerance and respect, which are part of the FBV; as well as to inclusivity and community cohesion. The analysis also shows that Arabic plays an important role in the construction of community and linguistic identities in the current political environment of suspicion.
Ricoeur's Theory of Interpretation: A Method for Understanding Text (Course Text)

2 Abstract: Hermeneutics, or the science of interpretation, is well accepted in the humanities. In the field of education, hermeneutics has played a relatively important role in understanding text. It is the task of this essay to introduce the theory and findings of Paul ricoeur's hermeneutics. Specifically, the essay interprets the usefulness of ricoeur's philosophy in understanding text (course text). With respect to the ricoeur's hermeneutic method, understanding test (course texts) accomplish in the three level: 1-explanation 2-understanding 3- appropriation, which ricoeur called it "hermeneutic arc. " In the first level, explanation, interpreter explores about this question which text (courses text) tells something? And examine the text inside nature. In the second level (understanding), interpreter explores about this question which text (course text) speaks about something? and do all the endeavors to restore text out ingredient at a relation to live and reach for deeper understanding. In the third level (appropriation), interpreter appropriate text (course text) world for themselves. Thus, expanded interpreter horizon (knowledge and perception).
Uncorrelated feature selection via intra-group competition and inter-group cooperation

Feature selection is an important topic in pattern recognition research, which is supposed to find the most informative subset of features and remove the redundant features as well. By doing this, feature selection not only reduces the size of data, but also improves the performance of pattern recognition algorithms. However, previous feature selection methods focus on identifying the most important features and ignore the redundancy in important features, i.e., the important features maybe very similar with each other. To address this problem, we propose a novel and efficient approach to find a subset of important and uncorrelated features. An example of the proposed approach can be summarized as follows: firstly, we evaluate the importance of each feature and, meanwhile, group the features based on their pair-wise similarity. Then, the features are ranked in each group and a new score for each feature is computed by referring to its ranks in the groups. Finally, the features are re-ranked altogether using their updated new scores. In this way, our method is able to select the important and uncorrelated features rather than the most important but similar features. Experimental results on benchmark image data sets and a UCI data set are demonstrated to show the effectiveness of the proposed method.
Virtual Machine Replication on Achieving Energy-Efficiency in a Cloud

The rapid growth in cloud service demand has led to the establishment of large-scale virtualized data centers in which virtual machines (VMs) are used to handle user requests for service. A user’s request cannot be completed if the VM fails. Replication mechanisms can be used to mitigate the impact of failures. Further, data centers consume a large amount of energy resulting in high operating costs and contributing to significant greenhouse gas (GHG) emissions. In this paper, we focus on Infrastructure as a Service (IaaS) cloud where user job requests are processed by VMs and analyze the effectiveness of VM replications in terms of job completion time performance as well as energy consumption. Three different schemes: cold, warm, and hot replications are considered. The trade-offs between job completion time and energy consumption in different replication schemes are characterized through comprehensive analytical models which capture VM state transitions and associated power consumption patterns. The effectiveness of replication schemes are demonstrated through experimental results. To verify the validity of the proposed analytical models, we extend the widely used cloud simulator CloudSim and compare the simulation results with analytical solutions.
Making Pretense Visible and Graspable: An augmented reality approach to promote pretend play

Children with autism are often found to lack facility for pretend play. It is believed that this deficit is linked to linguistic, social and creativity competencies in autism. We observe that both Augmented Reality (AR) and pretend play involve processing of information that is coupled with real scenes while not necessarily being directly perceived. This research therefore examines the potential of using AR technologies to promote pretend play behaviors in children with autism. As an initial outcome, we present the design and implementation of an AR system that aims to enhance the comprehension and flexibility of object substitution during pretend play.
Squibs: Towards a Catalogue of Linguistic Graph Banks

Graphs exceeding the formal complexity of rooted trees are of growing relevance to much NLP research. Although formally well understood in graph theory, there is substantial variation in the types of linguistic graphs, as well as in the interpretation of various structural properties. To provide a common terminology and transparent statistics across different collections of graphs in NLP, we propose to establish a shared community resource with an open-source reference implementation for common statistics.
Subcutaneous versus Intravenous Administration of Rituximab: Pharmacokinetics, CD20 Target Coverage and B-Cell Depletion in Cynomolgus Monkeys

The CD20-specific monoclonal antibody rituximab (MabThera®, Rituxan®) is widely used as the backbone of treatment for patients with hematologic disorders. Intravenous administration of rituximab is associated with infusion times of 4–6 hours, and can be associated with infusion-related reactions. Subcutaneous administration of rituximab may reduce this and facilitate administration without infusion-related reactions. We sought to determine the feasibility of achieving equivalent efficacy (measured by endogenous B-cell depletion) and long-term durability of CD20 target coverage for subcutaneously administered rituximab compared with intravenous dosing. In these preclinical studies, male cynomolgus monkeys were treated with either intravenous rituximab or novel subcutaneous formulation of rituximab containing human recombinant DNA-derived hyaluronidase enzyme. Peripheral blood samples were analyzed for serum rituximab concentrations, peripheral B-cell depletion, and CD20 target coverage, including subset analysis according to CD21+ status. Distal lymph node B-cell depletion and CD20 target coverage were also measured. Initial peak serum concentrations of rituximab were significantly higher following intravenous administration than subcutaneous. However, the mean serum rituximab trough concentrations were comparable at 2 and 7 days post-first dose and 9 and 14 days post-second dose. Efficacy of B-cell depletion in both peripheral blood and distal lymph nodes was comparable for both methods. In lymph nodes, 9 days after the second dose with subcutaneous and intravenous rituximab, B-cell levels were decreased by 57% and 42% respectively. Similarly, levels of peripheral blood B cells were depleted by >94% for both subcutaneous and intravenous dosing at all time points. Long-term recovery of free unbound surface CD20 levels was similar, and the duration of B-cell depletion was equally sustained over 2 months for both methods. These results demonstrate that, despite initial peak serum drug level differences, subcutaneous rituximab has similar durability, pharmacodynamics, and efficacy compared with intravenous rituximab.
FPT is characterized by useful obstruction sets: Connecting algorithms, kernels, and quasi-orders

Many graph problems were first shown to be fixed-parameter tractable using the results of Robertson and Seymour on graph minors. We show that the combination of finite, computable obstruction sets and efficient order tests is not just one way of obtaining strongly uniform FPT algorithms, but that all of FPT may be captured in this way. Our new characterization of FPT has a strong connection to the theory of kernelization, as we prove that problems with polynomial kernels can be characterized by obstruction sets whose elements have polynomial size. Consequently we investigate the interplay between the sizes of problem kernels and the sizes of the elements of such obstruction sets, obtaining several examples of how results in one area yield new insights in the other. We show how exponential-size minor-minimal obstructions for pathwidth k form the crucial ingredient in a novel or-cross-composition for k-Pathwidth, complementing the trivial and-composition that is known for this problem. In the other direction, we show that or-cross-compositions into a parameterized problem can be used to rule out the existence of efficiently generated quasi-orders on its instances that characterize the no-instances by polynomial-size obstructions.
On the Impact of the Mobility on Convergence Speed of Population Protocols

Population protocols provide theoretical foundations for mobile tiny device networks in which global behavior emerges from a set of simple interactions between anonymous agents. The works in this area mostly focus on studying the computational power of the model. Results hold as long as a fair scheduler, ensuring that all reachable system states are endlessly reached, governs the interactions between nodes. This assumption is crucial to ensure that the protocols eventually converge. This paper studies for the first time the impact of the agents? mobility model on the convergence speed of population protocols. We perform our study by considering several mobility models traditionally used in the ad-hoc network community. We propose an augmented population protocol model where each edge of the interaction graph is weighted, representing the probability of two agents to interact. This models the behaviour of the scheduler with respect to various mobility models. We empirically show that mobility models do have a significant impact on the convergence speed of the protocols. In fact, we observe that the uniform distribution always provides the best convergence time. Such a model is representative of the well-known random-way point model used to evaluate most of mobile ad-hoc network protocols. We then formally prove that a uniform distribution of weights provides the lowest bound of average convergence speed for any population protocol.
The intrapreneurial state: Singapore’s emergence in the smart and sustainable urban solutions field

ABSTRACT The East Asian developmental state model and the Anglo-American entrepreneurial state model profile varied ways in which the state continues to intervene in economic development. These models are developed by different disciplines and against diverse contexts to capture extrasocietal state responses to neoliberalism and globalization but leave the intrasocietal preconditions for state evolution little explored. We elaborate the concept of state intrapreneurialism as one way of understanding the interrelationship between economic and state transformation – one ingredient of the intrasocietal preconditions underpinning the responses to extrasocietal changes emphasized in the post-developmental state literature. Drawing on the case of Singapore's emergence in the field of smart/sustainable urban solutions, the subsidiary contributions of this paper are to suggest intrapreneurship as a specific and enduring advantage within the developmental state model, especially when set against its limitations signalled in the post-developmental state literature.
Systematic reverse genetic screening of T-DNA tagged genes in rice for functional genomic analyses: MADS-box genes as a test case.

We have generated 47 DNA pools and 235 subpools from 21,049 T-DNA insertion lines of rice. DNA pools of 500-1,000 lines were adequate for screening a T-DNA insertion within a 2-kb region. To examine the efficacy of the DNA pools, we selected MADS-box genes, which play an important role in controlling various aspects of plant development. A total of 34 MIKC-type MADS-box genes have now been identified from rice sequence databases. Our PCR screening for T-DNA insertions within 12 MADS-box genes resulted in the identification of five insertions in four different genes. These DNA pools will be valuable when isolating T-DNA insertional mutants in various rice genes. The DNA pool screening service and the mutant seeds are available upon request to genean@postech.ac. kr.
Using Reflection to Gain Insight into the Student Teaching Experience

NACTA Journal • March 2012 Abstract This study examined student teacher’ perceptions related to the student teaching experience. Using a focus group process, the student teachers were asked to reflect on their expectations of the experience, how they applied previous learning from university coursework to the experience, and what could be could be done to improve the preparation of students for the experience. Because of the importance of instruction, FFA, and Supervised Agricultural Experience in teaching agricultural education, the three components of a complete agricultural education program were used as the context for the reflective session. A semistructured set of questions were used in the focus group to gather participant responses. The session was audiotaped and transcribed. The transcription served as the primary data source. Secondary data consisted of field notes written by one member of the research team. Content analysis was used to interpret the data. The results indicated that the student teaching experience was not what the participants thought it would be in many ways, especially the time commitment involved in preparing for the teaching and learning process. The participants provided insights for improving the preparation of future student teachers and recommendations are included.
Document Style Recognition Using Shallow Statistical Analysis

Documents differ not only in topic but also in style. Style is a very broad and ambiguous term used in arts, fashion, literary criticism, and linguistics. In case of text documents we can accept an intuitive understanding that style is mainly related to the form (how) whereas topic – to the content (what) of a document. Although some topics determine strictly the style can be used, most topics allow their expression in various styles. Thus, style can be considered to be orthogonal to topic in a certain sense. Therefore style can be assumed to be a useful parameter in many text processing and information retrieval tasks.
The product life-cycle of online courses and student engagement

ABSTRACT With increased online course offerings at most higher education institutions, it is important to have a way to determine whether the courses continue to have value to students or outlived their usefulness. Courses are the central means of knowledge delivery for each institution and may be viewed through the lens of the product life-cycle, which is a common way for for-profit corporations to ensure they are aware of when it is time to make adjustments or completely overhaul what they provide to consumers. We leverage this concept to develop a conceptual mode of the life-span and cycle of curricular products; especially, those delivered online, which may have a shorter shelf life than in-classroom courses. To that end, we map a single course that has spanned nearly 20 years and shifted from face-to-face delivery, to a blended mode with learning technologies support, and then into a fully online format. This piece depicts the course life-cycle, which emerged from multi-strategy research analysis of that course. Understanding that online courses have a life-cycle can help department and university managers plan for the investment in the improvement of each as it comes to the end of its useful lifespan. This can ensure high-quality learning and a sustainable portfolio of programs and courses with which students are engaged.
Data mining based CIDS: Cloud intrusion detection system for masquerade attacks [DCIDSM]

Data mining has been gaining popularity in knowledge discovery field. In recent years, data mining based intrusion detection systems (IDSs) have demonstrated high accuracy, good generalization to novel types of intrusion, and robust behavior in a changing environment. Still, significant challenges exist in design and implementation of production quality IDSs. Masquerade attacks pose a serious threat for cloud system due to the massive amount of resource of these systems. This paper presents a Cloud Intrusion Detection System (CIDS) for CIDD dataset, which contains the complete audit parameters that help in detecting more than hundred instances of attacks and masquerades that exist in CIDD. It also offers numerous advantages in terms of alert infrastructure, security, scalability, reliability and also has data analysis tools.
A New Relay Based Dynamic Load Balancing Scheme in Cellular Networks

In cellular networks, mobile users in hot cells may suffer from low throughput due to the load imbalance problem. Different approaches such as channel borrowing and cell breathing have been proposed to accommodate this problem. Meanwhile, relay stations, which can extend cell coverage and enhance signal strength for boundary users, appear to be important components in next generation networks. In this paper, we propose a new relay-based load balancing scheme which utilizes relay stations to transfer over-loaded traffic from hot cells to neighboring cooler cells. The proposed algorithm dynamically controls the associations of relay stations to base stations, and the associations of mobile users to relay stations and base stations. Simulation results show that our scheme significantly improves the performance of boundary users without penalizing total system throughput.
Alignment of the cell nucleus from labeled proteins only for 4D in vivo imaging

Studies of protein dynamics by 4D (3D + time) confocal microscopy in vivo are hampered by global cell motion. The time between the acquisitions of the 3D images is in the order of minutes. Therefore, it is not to be expected that the cell as a whole remains fixed in the water basin on the stage. This superimposes a motion on the protein dynamics that has to be removed. We present a robust registration technique to align the cell images that does not require the a priori establishment of point‐to‐point correspondences. Instead, it uses the distribution of the labeled proteins. After correction for the translation, the 3D rotation of the cell is estimated. A robust intrinsic body coordinate system is constructed via the inertia tensor from the intensity distribution. By combining basis transformation to this intrinsic coordinate system, we can calculated the rotation matrix in a conceptual and computational straightforward manner. We have evaluated the performance of this approach in three experiments with human osteaosarcoma cells (U‐2 OS), where the nuclear proteins Histon H4 and PML were visualized. The PML is concentrated in several dozen nuclear spots. Expression of Histon H4 results in a total nuclear staining. The registration results for both channels computed independently are very similar. Practically, this means that only the labeled material needs to be observed and still registration of the cell as a whole can be achieved. Microsc. Res. Tech. 64:142–150, 2004. © 2004 Wiley‐Liss, Inc.
Personalized PageRank Solution Paths

Personalized PageRank vectors used for many community detection and graph diffusion problems have a subtle dependence on a parameter epsilon that controls their accuracy. This parameter governs the sparsity of the solution and can be interpreted as a regularization parameter. We study algorithms to estimate the solution path as a function of the sparsity and propose two methods for this task. The first computes a full solution path and we prove it remains localized in the graph for fast runtimes. Using this method, we propose a PageRank solution path plot to diagnose new aspects of the behavior of personalized PageRank. The second method is a faster approximation to the solution path on a grid of logarithmically-spaced values that uses an interesting application of bucket sort to make the process efficient. We demonstrate that both of these algorithms are fast and local on large networks.