Miracle-dz/UniFAR-FTUs huggingface dataset:
WLS Design of Sparse FIR Digital Filters

In this paper, we propose a novel algorithm for sparse finite impulse response (FIR) filter designs. The objective of the sparse digital filter design problem considered in this paper is to reduce the number of nonzero-valued filter coefficients, subject to a weighted least-squares (WLS) approximation error constraint imposed on the frequency domain. The proposed design method is inspired by the iterative shrinkage/thresholding (IST) algorithms, which are used in sparse and redundant representation for signals. The basic idea of the proposed design algorithm is to successively transform the original nonconvex problem to a series of constrained subproblems in a simpler form. Despite of their nonconvexity, these subproblems can be efficiently and reliably solved in each iterative step by a numerical approach developed in this paper. Furthermore, it can be demonstrated that the obtained solutions are essentially optimal to their respective subproblems. Since its major part only involves scalar operations, the proposed algorithm is computationally efficient. Three sets of numerical examples are presented in this paper to illustrate the effectiveness of the proposed design algorithm.
Supporting Self-Reflection through Presenting Visual Feedback of Adaptive Assessment and Self-Evaluation Tools

Two tools for skill assessment are presented in this paper. First the Adaptive Assessment Tool provides an efficient way for testing the learner's knowledge by posing questions. Second the Self-Evaluation Tool provides a method to assess the learner's knowledge by defining skills based on a controlled vocabulary. In both cases the result is a set of skills which is visualised by the Learner Knowledge Presenter Tool by rendering acquired skills on a skill map. These tools are supposed not only to test the learner's knowledge but also to stimulate self-reflection on what a learner has learned. The presented approach advances traditional testing, since it stimulates selfreflection during the assessment process.
Mitigating Economic Denial of Sustainability (EDoS) in Cloud Computing Using In-cloud Scrubber Service

Cloud computing is not a new technology, it is a new way of delivering computing resources. Elastic cloud computing enables services to be deployed and accessed globally on demand with little maintenance by providing QoS as per service level agreement (SLA) of customer. The Cloud-based DDoS attacks or outside DDoS attacks can make ostensibly legitimate requests for a service to generate an economic Distributed Denial of Service (eDDoS) - where the elastic nature of the cloud allows scaling of service beyond the economic means of the purveyor to pay their cloud-based service bills which leads to Economic Denial of Sustainability (EDoS). Attacks mimicking legitimate users are on the climb. For cloud computing to remain attractive, the DDoS threat is to be addressed before it triggers the billing mechanism. This problem can be addressed by using reactive/on-demand in-cloud eDDoS mitigation service (scrubber Service) for mitigating the application-layer and network-layer DDOS attacks with the help of an efficient client-puzzle approach.
Mercury Toxicity and Treatment: A Review of the Literature

Mercury is a toxic heavy metal which is widely dispersed in nature. Most human exposure results from fish consumption or dental amalgam. Mercury occurs in several chemical forms, with complex pharmacokinetics. Mercury is capable of inducing a wide range of clinical presentations. Diagnosis of mercury toxicity can be challenging but can be obtained with reasonable reliability. Effective therapies for clinical toxicity have been described.
Differences in Anthropometric Characteristics among Junior Basketball and Volleyball Players

Introduction Understanding the morphological characteristics is considered as an essential part of the total management process (Popovic, Bjelica, Jaksic, & Hadzic, 2014; Bjelica i Fratric, 2011). Th e need to investigate the anthropometrical characteristics numbers of basketball and volleyball players is important, because among other factors, contribute to optimal exercise routines and performance (Spaic, Vukasevic, & Masanovic, 2018). It is widely known in the scientifi c literature that adequate profi les are primarily important in various sports, mostly due to the reason that absolute size contributes a signifi cant percentage of total variance associated with athletic success (Rađa, Erceg, & Grgantov, 2016; Vukotic, 2018). According to previous studies, successful participation in both basketball and volleyball games, requires not only a high level of technical and tactical skills, but also suitable anthropometrical characteristics and body composition from each athlete (Monson, Brasil, & Hlusko, 2018; Hurst et al., 2017; Pojskic, Separovic, Muratovic, & Uzicanin, 2014; Masanovic, Spaic, & Vukasevic, 2018). In sports like basketball and volleyball, players tend to be tall because they handle a ball above their heads (Popovic et al., 2013; Popovic et al., 2014). Muscle-skeletal mass is an indicator of sports performance, because it contributes to the energy production during high-intensity activities and provides absolute strength to athletes. On the contrary, excessive fat mass compromises the physical performance, acts as a dead body mass in activities where the body must be repeatedly lift ed during motion and jumping, decreasing performance and increasing energy demands (Ramos-Campo et al., 2014; Bjelica, Popovic, & Gardasevic, 2016; Masanovic, Milosevic, & Corluka, 2018). Mentioned facts acknowledge that profesionaly engaging with basketball and volleyball beside high level of tehnical and tactical skills and high level of atletic abilities it is necessary to have certain anthropomtric characteristics. Basketball is considered an acyclic sports game, with extremely complex movements, specifi c and functional characteristics, defi ning it as anaerobic-glycotic activity, characterized with a large number of repetitive explosive-velocity moving structures, of extremely high intensity. Due to the constant changes in the intensity of movement, which is manifested through diff erent off ensive and defensive situations, the average intensity of basketball players during the compeAbstract
Mortar : Towards Million-Node Data Stream Management

Compute federations represent a global pool of wellprovisioned sensors, continuously emitting system and application-specific data streams, that can be queried for distributed debugging, application control, anomaly detection, measurement and data sampling. Such queries may involve thousands of stream sources distributed across the wide area, implying that node and network failures will be common. This has recently been referred to as the “Internet-Scale Sensing” problem [1].
INTELLIGENT AGENT FOR INFORMATION EXTRACTION BASED ON PATTERN DISCOVERY AND ONTOLOGY

In recent years, several approaches have been proposed to extract information from web pages on the internet. In this research, a key technique focused on crawling and ontology used to discover knowledge from web. In this paper, we present intelligent crawling system that uses pattern and ontology to extract particular information from WEB sites. The system developed as an efficient tool to construct researcher’s profile automatically from web pages. Moreover, some searching and indexing methods, text mining and computational linguistics for underlying this problem are exploited. We evaluated the performance of our system on an information extraction task from different real academic web sites. Experimental results show that with the extraction rules based on pattern discovery and ontology, our system achieves 84.90 % average of overall precision.
Sequential Blind Identification of Underdetermined Mixtures Using a Novel Deflation Scheme

In this brief, we consider the problem of blind identification in underdetermined instantaneous mixture cases, where there are more sources than sensors. A new blind identification algorithm, which estimates the mixing matrix in a sequential fashion, is proposed. By using the rank-1 detecting device, blind identification is reformulated as a constrained optimization problem. The identification of one column of the mixing matrix hence reduces to an optimization task for which an efficient iterative algorithm is proposed. The identification of the other columns of the mixing matrix is then carried out by a generalized eigenvalue decomposition-based deflation method. The key merit of the proposed deflation method is that it does not suffer from error accumulation. The proposed sequential blind identification algorithm provides more flexibility and better robustness than its simultaneous counterpart. Comparative simulation results demonstrate the superior performance of the proposed algorithm over the simultaneous blind identification algorithm.
The Condensin Complex Governs Chromosome Condensation and Mitotic Transmission of Rdna

We have characterized five genes encoding condensin components in Saccharomyces cerevisiae. All genes are essential for cell viability and encode proteins that form a complex in vivo. We characterized new mutant alleles of the genes encoding the core subunits of this complex, smc2-8 and smc4-1. Both SMC2 and SMC4 are essential for chromosome transmission in anaphase. Mutations in these genes cause defects in establishing condensation of unique (chromosome VIII arm) and repetitive (rDNA) regions of the genome but do not impair sister chromatid cohesion. In vivo localization of Smc4p fused to green fluorescent protein showed that, unexpectedly, in S. cerevisiae the condensin complex concentrates in the rDNA region at the G2/M phase of the cell cycle. rDNA segregation in mitosis is delayed and/or stalled in smc2 and smc4 mutants, compared with separation of pericentromeric and distal arm regions. Mitotic transmission of chromosome III carrying the rDNA translocation is impaired in smc2 and smc4 mutants. Thus, the condensin complex in S. cerevisiae has a specialized function in mitotic segregation of the rDNA locus. Chromatin immunoprecipitation (ChIP) analysis revealed that condensin is physically associated with rDNA in vivo. Thus, the rDNA array is the first identified set of DNA sequences specifically bound by condensin in vivo. The biological role of higher-order chromosome structure in S. cerevisiae is discussed.
On the Strong Universal Consistency of Nearest Neighbor Regression Function Estimates

Two results are presented concerning the consistency of the k-nearest neighbor regression estimate. We show that all modes of convergence in L 1 (in probability, almost sure, complete) are equivalent if the regression variable is bounded. Under the additional condition k/log n → ∞ we also obtain the strong universal consistency of the estimate
Optimal decay rates of the energy of a hyperbolic-parabolic system coupled by an interface

This work is dedicated to the study of a linear model arising in fluid-structure interaction and introduced by Rauch, Zhang and Zuazua. The system is formed of a heat and a wave equation, taking place in two distinct domains, and coupled by transmission conditions at the interface of the domains. Two different transmission conditions are considered. In both cases, when the interface geometrically controls the wave domain, we show the quick polynomial decay of the energy for solutions with smooth initial data, improving the rate of decay obtained by the previous authors. The polynomial stability is deduced from an optimal observability inequality conjectured in their work. The proof of this estimate mainly relies on a known generalized trace lemma for solutions of partial differential equations and the results of Bardos, Lebeau and Rauch on the control of the wave equation. Without the geometric condition, we show, using a Carleman inequality of Lebeau and Robbiano and an abstract theorem of N. Burq, a logarithmic decay for solution of the system with one of the two transmission conditions. This result improves the speed of decay obtained by Zhang and Zuazua, and is also optimal in some geometries.
A NARRATIVE PERSPECTIVE ON ORGANIZATIONAL LEARNING FROM UNUSUAL EXPERIENCES *

We explain how organizational experiences that fall outside already known experience categories pose a challenge to traditional notions of learning. We suggest that one way to learn about and from such unusual experiences is through the use of narratives. Not only do narratives help individuals make sense of unusual experiences, but, at the same time, they facilitate a process whereby others can learn from them too. We explore how the use of narratives to learn from unusual experiences can be a generative process, i.e., every instance of learning from an unusual experience can potentially inform how other unusual experiences can be addressed. We illustrate how this learning process unfolds and then consider the differences between a narrative approach and the traditional logico-scientific approach to learning.
EXAMINING THE CONCEPTUAL FRAMEWORK, PERCEPTIONS, AND PRACTICES OF TEACHERS IN THE EASTERN CARIBBEAN

This paper examines the conceptual framework of social studies as held by a sample of primary school teachers, as well as their perceptions and classroom practices. A modified Social Studies Perception Scale (SSPS) was employed with a sample of 98 primary school teachers in seven islands of the Eastern Caribbean. Using percentages, means, and t-tests, it was found that: 1) while the majority of the teachers indicated a clear preference for the reflective inquiry approach to the teaching of social studies, their actual classroom practices appear to be at odds with their perceptions of the subject; 2) while younger teachers are initially reflective in their approach and practice, over time they increasingly become didactic knowledge transmitters; and 3) male teachers are far more likely to exhibit a reflective approach and practices than female teachers. The t-tests also reveal some significant differences between male and female teachers, and between younger and older teachers. These findings may have implications both for the selection of social studies teachers and for teacher preparation programmes in the Caribbean.
Introduction: Applying Critical Theory to the Study of ICT

As three academics located in the domain of information systems (IS), we are delighted to act as guest editors and to highlight scholarship that applies a critical lens to the examination of information and communication technologies (ICT). In this editorial, we briefly present how reference disciplines—particularly sociology—have addressed issues of technology in society, placing this discussion in the context of the comparatively new disciplinary field of IS and its paradigmatic roots. We argue that IS has been dominated by inquiry adopting the philosophical approach of positivism but stress that there is a small and growing body of theoretical and empirical research from a critical perspective. We discuss this broadening field of critical research and critical research in IS in particular. Finally, we are pleased to introduce the articles we have chosen for this special issue that apply critical theories and methods to a number of ICT applications. Looking back at the entirety of sociology as a discipline, studying the role of technology in society has been marginal at best. Although never central to their doctrine, Marx, Weber, and Parsons all noted that technology played an instrumental role in society, subordinate to economic action, effectively a means to an economic end (Shields, 1997). With the arrival of the Frankfurt School in the mid-20th century, the study of the role of technology in society merged with the burgeoning field of critical theory, in which technology was part of a critique of modernity and the developments and institutions associated with modern society. For sociologists, critical theory allied technology with modernity and again viewed it instrumentally, as a tool of the modern state used for more perfect subjugation of the masses and the individual. In the later half of the 20th century, sociologists have drawn on authors such as Habermas, Offe, Bourdieu, Foucault, Calhoun, and Kellner to develop a more sophisticated critique of domination with an emancipatory interest, the fusion of social or cultural analysis, and the role of technology in society. Critical theorists of technology are typically seen by sociologists as mild technological determinists who have focused on the coevolution of modernity and technology and their joint limitations, pathologies, and destructive effects (Kellner, 1989).
Probabilistic Query Expansion Method Based on a Query Recommendation Algorithm

Query Expansion Methods are proposed to solve many problems of information retrieval systems, but most of these methods do not use the information of interactions between the users and the system. In our approach, we applied a Query Recommendation Algorithm on a list of past user queries, to extract the most associated queries to the input query, and used it in a Probabilistic Query Expansion method, that is constructed as a language model to search in set of candidate terms for the most relevant terms for the initial query that we have to expand. The output of this approach is a table of terms that are candidates for the expansion of the user query, and their values of correlation with the whole query. We did our experiments using the database CISI of the standard collection of test SMART. The results show that the best values are reached by adding fifteen terms to the input queries, using the five most relevant documents of the input query and the five most relevant documents for each of the recommended queries used, for short and long queries. Our experiments shows also, that for short queries we need to use just the best recommended query in the process of expansion to have a very high value of the Interpolated Average Precision (IAP), but concerning long queries we need to employ also the second best recommended query to have the highest value of IAP. The final experiment was a comparison between our approach and the Rocchio Algorithm, and it shows that our approach gives best results except in the case of using four Recommended Queries (RQs) for short input queries.
MEASURING FOREST CANOPY HEIGHT USING A COMBINATION OF LIDAR AND AERIAL PHOTOGRAPHY DATA

It has been demonstrated that the height of forest canopies can be measured with a good accuracy using small footprint lidars. This is essentially accomplished by subtracting the last return altitude (ground) from the corresponding first return altitude (canopy surface). The technique is considered superior to photogrammetric methods mainly because the ground level, which is difficult to see on aerial photos of densely forested areas, can be well identified using small footprint lidars. However, lidar cannot be used to characterized past forest states, while these can be assessed, and photogrammetically measured, in the wealth of historical aerial photographs most developed countries possess. Our goal is to replace the first return lidar data by altitude models derived from aerial photos in order to map forest canopy height changes of the past decades. This paper presents the first methodological steps which consist in comparing canopy heights obtained from lidar data only to a combination of lidar and photogrammetry data. The lidar data was acquired over an area of the boreal forest in Quebec, Canada, in 1998, using Optech’s ALTM1020 flying at an altitude of 700 m. Two stereo-pairs of aerial black and white photographs were used: 1) a pair of 1:15,000 photos taken in 1994, and 2) a pair of 1:40,000 photos taken in 1998. A lidar canopy height model (CHM) was created by subtracting ground altitudes from canopy altitudes. Aerial photo altitude models were derived using the image correlation methods of Virtuozo 3.2 software. The ground level altitudinal fit between the aerial photo altitude model and the lidar data was checked on rock outcrops. A photo CHM was created by subtracting the lidar ground altitude model from the aerial photo altitude model. The photo CHM and the lidar CHM show a good degree of correlation.
Determinates of Throughput Times in the Emergency Department

This article studies factors that affect throughput times in a level 1 inner city emergency department (ED) in Chicago, USA. Previous research has shown increased throughput times are related to non-urgent patient use of the ED and lack of coordination of auxiliary hospital departments. Knowledge of these factors will allow for an improvement in patient flow and a reduction in wait times. This is a retrospective study of all factors that contribute to throughput times. Data was collected on a monthly basis for a four-year period that included presenting illness, triage level, wait times, time taken for laboratory results, radiology, bed availability, admitted or sent home, Fast Track availability, age, gender and race. The results show that factors affecting throughput are influenced by numerous determinants often beyond the ED itself. The two most influential are: the numbers of presenting illnesses that require in-patient beds, and the ability of the hospital's auxiliary departments, such as the lab, to meet the needs of the ED in a timely fashion. Based on these findings, the way to reduce throughput times is to focus on auxiliary hospital systems, such as laboratory, psychiatry and medicine, which support the ED.
A Production Rule System for Message Summarization

In summarizing a message, it is necessary to access knowledge about linguistic relations, subject matter knowledge about the domain of discourse, and knowledge about the user's goals for the summary. This paper investigates the feasibility of integrating these knowledge sources by using computational linguistic and expert system techniques to generate one-line summaries from the narrative content of a class of Navy messages. For deriving a knowledge representation of the narrative content, we have adapted an approach developed by Sager et al. at New York University. This approach, called information formatting, uses an explicit grammar of English and a classification of the semantic relationships within the domain to derive a tabular representation of the information in a message narrative. A production system, written in OPS5, then interprets the information in the table and automatically generates a summary line. The use of a production rule system provides insight into the mechanisms of summarization. A comparison of computer-generated summaries with those obtained manually showed good agreement, indicating that it is possible to automatically process message narrative and generate appropriate, and ultimately useful, summaries.
PERM: A Collaborative System for Residential Internet Access

802.11 networks have spread rapidly in residential areas, and it is common for neighbors to receive the signals from each other’s home wireless routers. Residents can leverage such an opportunity to improve their Internet connectivity, at no additional cost, by pooling their individual Internet connections together. In this paper we present our design, implementation, and evaluation of PERM, a system that enables collaborative Internet access in residential areas. Compared with related work, PERM is practical in that it does not rely on support from the network infrastructure in terms of advanced naming or proxy, or from the remote host in terms of new transport protocols. Instead, PERM employs automated on-line analysis of the user’s networking behaviors, and exploits the recognized patterns to achieve highperformance scheduling at the flow level. PERM is also highly usable for normal residential users. It mitigates the free-riding problem, and preserves a user’s privacy and security. We have implemented PERM in the open-source LinkSys wireless router and Linux client. Our evaluation in a dual-homed residential host shows that PERM significantly improves perceived last-mile Internet connectivity at homes.