Miracle-dz/UniFAR-FTUs huggingface dataset:
A Communication-Centric Embedded System Architecture (ACCESA)

In the era of application convergence, the embedded systems are required to support multiple applications with different traffic patterns and Quality of Service (QoS) requirements. But continual process technology's shrinking trend makes the communication network of the embedded system the performance bottleneck for its increased latency. To ameliorate this problem, a communication-centric embedded system architecture (ACCESA) is proposed in this paper which is modular and block based. The modular and block based architecture of ACCESA helps in performance improvement of the embedded system by means of flexible and efficient QoS provisions and power management. The pre-fabricated or preconfigured hybrid and hierarchical communication network of ACCESA saves on run-time reconfiguration time and on interconnect cost by preventing under utilization of communication resources without sacrificing on processing speed and throughput of the applications. This reduced and efficient resource usage in ACCESA in turn saves on power consumption of the chip.
On Improved MRI Segmentation Using Hierarchical Computational Intelligence Techniques and Textural Analysis of the Discrete Wavelet Transform Domain

This paper investigates a novel feature extraction approach to MRI segmentation based on identifying the critical image edges by using textural (cooccurrence matrices) analysis of the discrete wavelet transform (DWT) domain. Furthermore, the presented approach is based on formulating the problem as a two-stage unsupervised classification task using a modified Kohonen's self organizing feature map (SOFM) along with independent component analysis (ICA). The main goal of such a research effort is to better identify abrupt textural image changes without increasing the presence of noise in the resulting image. The suggested methodology is based on novel discrete wavelet descriptors involving the discrete k-level 2-D wavelet transform and cooccurrence matrices analysis applied to sliding windows raster scanning the original image. The proposed two-stage classification scheme applied to such textural wavelet descriptors and using a modified vector quantizing self-organizing feature map (SOFM) and ICA analysis is compared with a corresponding two-stage scheme involving PCA analysis and the widely used SOFM, trained with Kohonen's algorithm. The feasibility of this novel two-stage proposed approach is studied by applying it to the edge structure segmentation problem of brain slice MRI images. The promising results presented in the experimental study illustrate a performance favourably compared, also, to that of traditional Sobel edge detectors supported by usual contour tracing methods.
A MODEL AND GENETIC ALGORITHM TO SOLVE COMPLEX PS ( Project Scheduling ) PROBLEMS

This paper solves a complex PS problem by employing a reproduction mechanism which is closer to natural than the common GA methods. The PS problem consists of: operations sequence constraints, alternative modes per operation, multi renewable resources, resource setups, and other properties. The resulting model is very complex; hence, common GA methods produce unfeasible solutions very frequently. By mimicking the multilevel Chromosome’s structure in natural reproduction, we reduce the rate of unfeasibility produced by the crossover. The GA levels we consider are: DNA, Chromosome, Gene, and a Nucleic. The main idea is that crossover is conducted only between chromosomes, and mutations within genes. The proposed GA method is much more efficient, especially for large problems, and reaches its objective close to optimal versus a customized B&B algorithm. List of Terms: PS (Project Scheduling), GA (Genetic Algorithm), BB (Branch & Bound), MIP (Mixed Integer Programming), CPM (Critical Path Method).
Inter-transcriber reliability of toBI prosodic labeling

The goal of this study was to evaluate the reliability among transcribers of a standard prosodic labeling system under relatively optimal conditions of training, supervision, facili-ties, procedures, and extent of speaker familiarity. The ToBI (Tones and Break Indices) model for standard American English[7][1] was used in the study; break indices indicate thedegree of junction between words, pitchaccents designate word prominence, and edge tones mark phrase boundaries. The American English speech corpora were read by a female professional speaker and by a male professional speaker, and were composed of several typesof texts toensure prosodic variety. Eachof four experiencedtranscribers independentlyla-beled each corpus. For each corpus, word level agreement in break indices, pitch accents, and edge tones between all possible pairs of transcribers was analyzed, and various statistics were calculated. Agreement among labelers was generally higher than that reported in previous studies[6][3] of larger and more diverse groups of labelers. Agreement was high for some prosodic categories, but low for others. The extent of reliability for various prosodic distinctions has important implications for re(cid:12)ning the ToBI model and for limitations in the use of prosody in speech technologies.
Comparing farm and village-level determinants of millet diversity in marginal environments of India: the context of seed systems

"The purpose of the research paper is to characterize biological diversity related to millets in the semi-arid regions of India at various spatial scales of analysis (e.g., farm household versus community levels) and place that evidence in a broader seed systems (includes both formal and informal) context. An important finding of this research is that producer access to millet genetic resources is affected by the extent to which seed is traded via formal markets or through other social institutions, along with farm and household characteristics. Findings also underscore the need for an enhanced theoretical understanding of local seed markets in analyzing crop variety choices and the diversity of materials grown in less favored environments. " Authors' Abstract
A novel KNN join algorithms based on Hilbert R-tree in MapReduce

The kNN join (k nearest neighbor join) is a primitive operation widely adopted by many data mining applications. From a dataset S, it can find k nearest neighbors for every object in another dataset R. It is a combination of the k nearest neighbor query and the join operation. In this paper we perform kNN join in MapReduce. For kNN joins, the block nested loop methodology is the direct method. It is very efficient to load a R-tree and search kNN in R-tree. On the base, we build a Hilbert R-tree index for the local S block in a bucket. It can help us find kNNs in the same bucket. Extensive experiments demonstrate that our proposed methods are efficient.
Effective immobilisation of a metathesis catalyst bearing an ammonium-tagged NHC ligand on various solid supports

An ammonium-tagged ruthenium complex, 8, was deposited on several widely available commercial solid materials such as silica gel, alumina, cotton, filter paper, iron powder or palladium on carbon. The resulting catalysts were tested in toluene or ethyl acetate, and found to afford metathesis products in high yield and with extremely low ruthenium contamination. Depending on the support used, immobilised catalyst 8 shows also additional traits, such as the possibility of being magnetically separated or the use for metathesis and subsequent reduction of the obtained double bond in one pot.
THE APPROXIMATE AND EXACT SOLUTIONS OF THE SPACE- AND TIME-FRACTIONAL BURGERS EQUATIONS

In the paper, we extend the differential transform method to solve nonlinear fractional partial differential equations. The time- and space-fractional Burgers equations with initial conditions are chosen to illustrate our method. As a result, we successfully obtain some available approximate solutions of them. The results reveal that the proposed method is very effective and simple for obtaining approximate solutions of nonlinear fractional partial differential equations. The fractional derivatives are considered in the Caputo sense.
An LFG Chinese Grammar for Machine Use

This paper describes the Chinese grammar developed at PARC, including its three basic components: the tokenizer and tagger, lexicon and syntactic rules. Some of the challenges and issues that we have encountered in the process of development are discussed. In addition, we present our methods of handling these issues. We also illustrate how we evaluate our grammar, providing the evaluation results and some error analyses. 1 Background Introduction This paper describes a Chinese grammar developed at the Palo Alto Research Center (PARC). This grammar is designed for machine use and is implemented in the framework of Lexical Functional Grammar (LFG) (Kaplan and Bresnan, 1982; Dalrymple, 2001; Bresnan, 2001). LFG is characterized by its two parallel levels of syntactic representation: Constituent Structure (c-structure) and Functional Structure (f-structure). C-structure encodes information about phrasal structure and linear word order. F-structure encodes information about ‘the various functional relations between parts of sentences, information like what is the subject and what is the predicate’ (Sells, 1985). Both c-structure information and f-structure information are carried in syntactic rules such as (1). (1) S –> NP: (ˆ SUBJ) = ! ; VP: ˆ = ! The ˆ refers to the f-structure of the mother node and the ! refers to the f-structure of the node itself. (ˆSUBJ) = ! means that the SUBJ part of the mother’s f-structure (the f-structure of the S in (1)) is the f-structure of the node itself (the f-structure of the NP in (1)). ˆ= ! means that the f-structure of the node itself (the VP in (1)) goes into the f-structure of its mother node (the S in (1)); that is, VP is the functional head of S. (2) shows two additional phrase structure rules. Together with the rules in (1), these will derive the c-structure and f-structure in (4) and (5) for example (3). (2) NP –> N: ˆ = ! ; VP –> V: ˆ = ! †Fuji Xerox funded the initial research on the Chinese grammar described in this paper, and we are especially grateful to the support we have received from Tomoko Ohkuma and Hiroshi Masuichi of Fuji Xerox throughout the development. Professor Bing Swen and Professor Shiwen Yu of Beijing University have provided substantial support for the tokenizer and tagger used in this grammar. We also appreciate the feedback they provided during our conversations regarding ways to improve the tokenizer and tagger. We would also like to thank Yuqing Guo from DCU for her work in developing the gold analyses for the 200 gold sentences against which we evaluate our grammar. We also owe our thanks to Emily M. Bender for her helpful feedback and comments on this paper.
Performance of compressed inverted list caching in search engines

Due to the rapid growth in the size of the web, web search engines are facing enormous performance challenges. The larger engines in particular have to be able to process tens of thousands of queries per second on tens of billions of documents, making query throughput a critical issue. To satisfy this heavy workload, search engines use a variety of performance optimizations including index compression, caching, and early termination. We focus on two techniques, inverted index compression and index caching, which play a crucial rule in web search engines as well as other high-performance information retrieval systems. We perform a comparison and evaluation of several inverted list compression algorithms, including new variants of existing algorithms that have not been studied before. We then evaluate different inverted list caching policies on large query traces, and finally study the possible performance benefits of combining compression and caching. The overall goal of this paper is to provide an updated discussion and evaluation of these two techniques, and to show how to select the best set of approaches and settings depending on parameter such as disk speed and main memory cache size.
The role of attachment to God and spiritual self-awareness in predicting evangelical Christians’ appraisals of suffering

ABSTRACT The present study examined how attachment to God and spiritual self-awareness are related to evangelical Christians’ appraisals of suffering. Specifically, we were interested in whether attachment anxiety and attachment avoidance with God were related to the appraised meaning of stressful life experiences as transformational and whether spiritual self-awareness mediated this relationship. A national sample (N = 988) of students from Christian institutions completed an online survey. The results indicated that individuals with high levels of attachment anxiety or attachment avoidance with God were less likely to view suffering as a means of spiritual growth and connection with God. Mediation analyses also showed that higher levels of avoidant attachment to God were related to lower levels of spiritual self-awareness, which in turn were related to reduced ability to appraise suffering as transformational. Clinical implications and directions for future research are discussed.
An inconsistency measure of spatial data sets with respect to topological constraints

An inconsistency measure can be used to compare the quality of different data sets and to quantify the cost of data cleaning. In traditional relational databases, inconsistency is defined in terms of constraints that use comparison operators between attributes. Inconsistency measures for traditional databases cannot be applied to spatial data sets because spatial objects are complex and the constraints are typically defined using spatial relations. This paper proposes an inconsistency measure to evaluate how dirty a spatial data set is with respect to a set of integrity constraints that define the topological relations that should hold between objects in the data set. The paper starts by reviewing different approaches to quantify the degree of inconsistency and showing that they are not suitable for the problem. Then, the inconsistency measure of a data set is defined in terms of the degree in which each spatial object in the data set violates topological constraints, and the possible representations of spatial objects are points, curves, and surfaces. Finally, an experimental evaluation demonstrates the applicability of the proposed inconsistency measure and compares it with previously existing approaches.
Casuistic Reasoning in Expert Narratives on Healthy Eating

ABSTRACT Individualisation of healthy eating is a broad tendency in Western culture and is becoming a popular ideal in nutrition science. Public perception of dietary knowledge is central to this individualisation and many experts now aim to present dietary knowledge in a way which relates to individual experience, as well as a casuistic style in which particular cases are discussed in relation to general, universal principles. Analysis of casuistic narrative styles in the public communication about healthy eating by experts makes explicit their flexible use of both particular cases and universal claims, in which clinical and personal cases are narratively employed by the experts to invite readers to personally consider dietary knowledge. Such casuistic narration by experts relates human agency and particular bodies to universal concepts in a way that has generative and critical functions with respect to dietary knowledge and understanding. The public articulation of clinical narratives by experts make salient the intersubjective emergence and accumulation of dietary knowledge between expert reasoning and lay understanding. Personal narratives have an essential role in presenting casuistic reasoning through experts’ personal lives and making their own bodies relevant to public communication about healthy eating. This emphasises the experts’ personal agency in relationship to common norms and general knowledge. Furthermore, both clinical and personal narratives are used by experts in their assessment of the shortcomings in public health messages. Experts’ casuistic narration thus does not merely construct credibility but has epistemic functions in constructing dietary knowledge tangible with respect to actual eating practices.
Training and Displacement: is Employer Paid Training Firm-Specific?

This paper uses the natural experiment of displacement to test whether private sector training acts as a source of firm-specific human capital. If training reflects only firm-specific skills, workers with employer-paid training should have lower displacement rates than workers without. Training, however, should not alter the likelihood of post-displacement reemployment. The paper uses datasets constructed by linking together Current Population Survey Training and Displaced Worker Supplements from January 1983 & 1984, and 1991 & 1992. In the 1980s, employer-paid training acted as firm-specific human capital would. Training did not appear to provide firm-specific human capital for women in 1991-1992.
A cost-effective approach to software-in-the-loop simulation of pervasive systems and applications

In this paper we illustrate a cost-effective software-in-the-loop simulation methodology, which is particularly suitable for testing large-scale pervasive systems and applications. The main advantage of such an approach is that real code has to be deployed once, and a general-purpose simulation engine replicates it over virtual devices and environments as often as we wish. Our implementation of the proposed methodology is illustrated by means of the software-in-the-loop simulation of a peer-to-peer information sharing system, with real code running on simulated mobile nodes.
A pilot study on education for sustainable development in the Romanian economic higher education

This paper aims to emphasize how economics courses offered at higher education institutions can influence sustainable development, in general, and Romania’s sustainable development, in particular. ,The conclusions are based on a pilot questionnaire conducted by the authors on the level of Romanian students enrolled in public and private economic faculties. The results were based on a sample of 1,250 respondents – students, master and PhD – from the economic faculties of some prestigious Romanian universities. To identify differences between some groups, t-test analysis and ANOVA were conducted. ,Education is an important pillar for ensuring sustainable development because through education, people understand and learn how to become more responsible toward the environment. Studies conducted in the twenty-first century are showing a direct link between the investment in education and economic, social and human development. The present study revealed that the economic higher education system in Romania has started with small steps to adapt to the environmental requirements. Unfortunately, the efforts still required to be made are significant, since it is observed that all undergraduate, postgraduate and PhD require a change of attitude and mentality. Romanian public universities are more involved than private universities in the implementation of programs, projects, debates and courses on sustainable development and students’ reactions are positive. ,This paper provides useful insights, allowing a better understanding of the role of universities in fostering sustainable development. This research is useful to find solutions for developing education for sustainable development in Romania and it can be a starting point for ESD programs and policies.
Virtual set-top box in the cloud: Enabling interactive third party applications

The dramatic growth of mobile devices has led to a significant change in the TV industry. The trend to switch to the cloud is unstoppable, since it promises cost-savings and new ways of generating revenue. One big challenge is still to manage the virtualization of the full functionality of the set-top box in the cloud, so that it can be accessed from anywhere from any device. In this paper we present a platform-as-a-service media solution to addresses this challenge. The focus is to design and implement proper interfaces to enable interactive third-party applications to extend the capability of the virtual set-top box in the cloud. We validate the proposed APIs with some example applications and further discuss its theoretical and practical scalability. To the best of our knowledge, this is the first concrete work to discuss the design and implementation issues of application interfaces for virtual set-top box in the cloud.
Calibration, traceability and uncertainty issues in surface texture metrology.

Achieving consistent surface texture measurements is of vital importance to the performance of many components in well-established fields such as mechanical engineering and manufacturing, and is becoming increasingly important in the emerging field of nanotechnology. The route to traceability in surface texture measurements is still ill-defined and it is very uncommon to find a measured surface texture parameter presented with its associated uncertainty. This report summarises the methods used to calibrate surface texture measuring instruments and discusses the various ISO standards in the field. An uncertainty analysis of a fully traceable two-dimensional surface texture measuring instrument: NanoSurf IV, is undertaken and the uncertainties in measured surface texture parameters are analysed.
An improved algorithm for clustering gene expression data

MOTIVATION Recent advancements in microarray technology allows simultaneous monitoring of the expression levels of a large number of genes over different time points. Clustering is an important tool for analyzing such microarray data, typical properties of which are its inherent uncertainty, noise and imprecision. In this article, a two-stage clustering algorithm, which employs a recently proposed variable string length genetic scheme and a multiobjective genetic clustering algorithm, is proposed. It is based on the novel concept of points having significant membership to multiple classes. An iterated version of the well-known Fuzzy C-Means is also utilized for clustering. RESULTS The significant superiority of the proposed two-stage clustering algorithm as compared to the average linkage method, Self Organizing Map (SOM) and a recently developed weighted Chinese restaurant-based clustering method (CRC), widely used methods for clustering gene expression data, is established on a variety of artificial and publicly available real life data sets. The biological relevance of the clustering solutions are also analyzed.
The Existence of Pareto Equilibrium for Multiobjective Games in General Topological Spaces

The main purpose of this paper is to study the Pareto equilibrium for multiobjective games in general topological spaces without any linear and convexity structure. Following the method introduced by Nikaido and Isoda (1955), this paper defines an aggregate payoff function, and next then, determines some restrictions on the aggregate function which guarantee the existence of weighted Nash equilibrium for multiobjective games in general topological spaces without any linear and convexity structure. As consequences, two new Pareto equilibrium existence theorems for multiobjective games are obtained in general topological spaces without any linear and convexity structure.