Miracle-dz/UniFAR-FTUs huggingface dataset:
Indigenous languages and the informal economy in Africa: A qualitative analysis of the economics of language dynamics in rural Kenya

Abstract There is a dearth of research on the economics of language of Africa’s official and national languages, not to mention non-official, non-national indigenous languages. The article seeks to fill this hiatus using qualitative data from rural Kenya. A key finding is the discovery and characterisation of reciprocal/symbiotic relationships between indigenous languages and informal economic activities which are amplified by adaptive broker-agent relationships at the indigenous languages/informal economy interface and three-dimensional resilient networks of linkages between non-official, non-national indigenous languages and the informal economy that largely defy the asymmetries that define and characterise the relationships between these languages and the formal economy in much of Africa. On the basis of these insights, the article argues that the linkages between non-official, non-national indigenous languages and the informal economy in Africa hold promise for discourses, processes and interventions that seek to engender the viability, vitality and resilience of indigenous languages on the continent.
A Scalable Projective Bundle Adjustment Algorithm using the L infinity Norm

The traditional bundle adjustment algorithm for structure from motion problem has a computational complexity of O((m+n)3) per iteration and memory requirement of O(mn(m+n)), where m is the number of cameras and n is the number of structure points. The sparse version of bundle adjustment has a computational complexity of O(m3+mn) per iteration and memory requirement of O(mn). Here we propose an algorithm that has a computational complexity of O(mn(radicm+radicn)) per iteration and memory requirement of O(max(m,n)). The proposed algorithm is based on minimizing the Linfin norm of reprojection error. It alternately estimates the camera and structure parameters, thus reducing the potentially large scale optimization problem to many small scale subproblems each of which is a quasi-convex optimization problem and hence can be solved globally. Experiments using synthetic and real data show that the proposed algorithm gives good performance in terms of minimizing the reprojection error and also has a good convergence rate.
Identification and Functional Analysis of microRNAs Involved in the Anther Development in Cotton Genic Male Sterile Line Yu98-8A

Hybrid vigor contributes in a large way to the yield and quality of cotton (Gossypium hirsutum) fiber. Although microRNAs play essential regulatory roles in flower induction and development, it is still unclear if microRNAs are involved in male sterility, as the regulatory molecular mechanisms of male sterility in cotton need to be better defined. In this study, two independent small RNA libraries were constructed and sequenced from the young buds collected from the sporogenous cell formation to the meiosis stage of the male sterile line Yu98-8A and the near-isogenic line. Sequencing revealed 1588 and 1536 known microRNAs and 347 and 351 novel miRNAs from male sterile and male fertile libraries, respectively. MicroRNA expression profiles revealed that 49 conserved and 51 novel miRNAs were differentially expressed. Bioinformatic and degradome analysis indicated the regulatory complexity of microRNAs during flower induction and development. Further RT-qPCR and physiological analysis indicated that, among the different Kyoto Encyclopedia Gene and Genomes pathways, indole-3-acetic acid and gibberellic acid signaling transduction pathways may play pivotal regulatory functions in male sterility.
Using variable DC sources in order to improve the voltage quality of a multilevel STATCOM with low frequency modulation

In this paper, a Selective Harmonic Elimination Pulse Width Modulation (SHE-PWM) method, which utilizes adjustable dc links, is presented for a Static Synchronous Compensator (STATCOM) based on Cascaded H-Bridge (CHB) multilevel converter. The proposed switching algorithm is able to fix the capacitors voltages at optimum and unequal values, while injecting the desired reactive power, in order to eliminate more low order harmonics. An indirect current control method is combined with a loss estimation block to control the dc link voltages that might have different losses. Moreover, by using unequal dc link voltages more levels at the output is achievable compared to the symmetrical multilevel converters that could be used in enhancing the power quality, while keeping the switching frequency near the fundamental (the maximum switching frequency can be kept below 150 Hz). The validity of the proposed method is verified by simulations in Matlab/Simulink environment.
Multi-source Automatic Annotation for Deep Web

A large number of Web pages returned by filling in search forms are not indexed by most search engines today. The set of such Web pages is referred to as the deep Web. Since results returned by Web databases seldom have proper annotations, it is necessary to assign meaningful labels to the results. This paper presents a framework of automatic annotation which uses multi-annotator to annotate results from different aspects. Especially, search engine-based annotator extends question-answering techniques commonly used in the AI community, constructing validate queries and posing to the search engine. It finds the most appropriate terms to annotate the data units by calculate the similarities between terms and instances. Information for annotating can be acquired automatically without the support of domain ontology. Experiments over four real world domains indicate that the proposed approach is highly effective.
Redundant Network Traffic Elimination Techniques : A comprehensive Survey

a large amount of popular content is transformed across the network for different purposes. This transformed content comprises large amount of duplication that consume bandwidth inefficiently and degrade network performance. Redundant Traffic Elimination (RTE) also known as data deduplication detects and removes repeated chunks of data across network flows, protocols, and applications, with the purpose of reducing bandwidth usage. In this paper we survey state of the art RTE techniques (WAN optimization, protocol independent, PACK, SMART-RE, EndTo-End elimination etc.) implemented in various types of networks. We categorize the techniques based on the problem solution perspective, critically analyze the techniques, and find gaps that need consideration in future. Results show that already implemented RTE techniques considerably remove the repeated content and improve network performance. However, still there are gaps especially in mobile networks, wireless and cloud computing area that needs consideration in future.
Symmetry in Security Protocol Cryptographic Messages -- A Serious Weakness Exploitable by Parallel Session Attacks

This paper is concerned with detection and prevention of weaknesses in the design of security protocols. These weaknesses can be exploited by an attacker mounting attacks that compromise the security of the protocol. A novel theory defining weaknesses caused by the symmetry of cryptographic messages in protocols is introduced. This theory incorporates new rules describing the cases when the symmetry of messages has a structural weakness that is exploitable by parallel session attacks. Further, the rationale behind the Symmetry rules is presented and the structures of detected generic attacks for each rule are provided. Additionally, the Symmetry rules are applied to a protocol that is vulnerable to a parallel session attack. It is demonstrated that the proposed theory successfully detects the weaknesses caused by the symmetry of protocol messages, which lead to parallel session attacks.
Frequent Changes in Expression Profile and Accelerated Sequence Evolution of Duplicated Imprinted Genes in Arabidopsis

Eukaryotic genomes have large numbers of duplicated genes that can evolve new functions or expression patterns by changes in coding and regulatory sequences, referred to as neofunctionalization. In flowering plants, some duplicated genes are imprinted in the endosperm, where only one allele is expressed depending on its parental origin. We found that 125 imprinted genes in Arabidopsis arose from gene duplication events during the evolution of the Brassicales. Analyses of 46 gene pairs duplicated by an ancient whole-genome duplication (alpha WGD) indicated that many imprinted genes show an accelerated rate of amino acid changes compared with their paralogs. Analyses of microarray expression data from 63 organ types and developmental stages indicated that many imprinted genes have expression patterns restricted to flowers and/or seeds in contrast to their broadly expressed paralogs. Assays of expression in orthologs from outgroup species revealed that some imprinted genes have acquired an organ-specific expression pattern restricted to flowers and/or seeds. The changes in expression pattern and the accelerated sequence evolution in the imprinted genes suggest that some of them may have undergone neofunctionalization. The imprinted genes MPC, HOMEODOMAIN GLABROUS6 (HDG6), and HDG3 are particularly interesting cases that have different functions from their paralogs. This study indicates that a large number of imprinted genes in Arabidopsis are evolutionarily recent duplicates and that many of them show changes in expression profiles and accelerated sequence evolution. Acquisition of imprinting is a mode of duplicate gene divergence in plants that is more common than previously thought.
Sentence clustering in text document using fuzzy clustering algorithm

The paper proposes FRECCA algorithm to find out the clusters of sentences having the inter relation among them. The system uses the fuzzy clustering algorithm that compares the sentences and find out the similarity value and forms a cluster. The fuzzy clustering algorithm checks the possibility of the sentence to which cluster it belongs to. In this paper a Genetic algorithm approach is also suggested that checks the highest similarity value between the sentences and grouped to form a cluster in a more sophisticated manner, there by forming n number of clusters from n sentences.
Parameter Estimation and Capacity Fade Analysis of Lithium-Ion Batteries Using Reformulated Models

Many researchers have worked to develop methods to analyze and characterize capacity fade in lithium-ion batteries. As a complement to approaches to mathematically model capacity fade that require detailed understanding of each mechanism, capacity fade was accurately and efficiently predicted for future cycles using a discrete approach by extrapolating the change in effective transport and kinetic parameters with cycle number (N) for a battery tested under controlled experimental conditions. The effective parameters and their uncertainties are estimated using a mathematical reformulation of a porous electrode model, whose computational efficiency enables the integration of the proposed approach into an inexpensive microprocessor for estimating the remaining lifetime of a battery based on past charge-discharge curves. The approach may also provide some guidance for designers as to which battery components to focus on for redesign to reduce capacity fade. V C 2011 The Electrochemical Society. [DOI: 10.1149/1.3609926] All rights reserved.
ADC clock jitter requirements for software radio receivers

The effective number of bits of an analogue-to-digital converter (ADC) is limited not only by the quantisation step inaccuracy, but also by sampling time uncertainty. According to a commonly used model, timing jitter errors should not introduce a sampling error bigger than 1 quantisation level for full swing input signals at a frequency equal to half the sample rate. This results in unfeasible phase noise requirements for the sampling clock in software radio receivers with direct RF sampling. The paper explores the clock jitter requirements for a software radio application, using a more realistic model found in the literature and taking into account both the power spectrum of the input signal and the spectrum of the sampling clock jitter. Using this model, we show that the clock jitter is not the limiting factor in the feasibility of software radio receivers.
Enhancing sentiment extraction from text by means of arguments

Sentiment Analysis is concerned with (1) differentiating opinionated text from factual text and, in the case of opinionated text, (2) determine its polarity. With this paper, we address problem (1) and present A-SVM (Argument enhanced Support Vector Machines), a multimodal system that focuses on the discrimination of opinionated text from non-opinionated text with the help of (i) Support Vector Machines (SVM) and (ii) arguments, acquired by means of a user feedback mechanism, and used to improve the SVM classifications. We have used a prototype to investigate the validity of approaching Sentiment Analysis in this multi faceted manner by comparing straightforward Machine Learning techniques with our multimodal system architecture. All evaluations were executed using a purpose-built corpus of annotated text and A-SVM's classification performance was compared to that of SVM. The classification of a test set of approximately 4,500 n-grams yielded an increase in classification precision of 5.6%.
A Novel Cross-Layer Routing Algorithm in Wireless Mesh Network

Routing in wireless mesh network (WMN) is challenging because of the unpredictable variations of the wireless environment. Traditional mechanisms have been proved that the routing performance would get deteriorated and ideal metrics must be explored. Cross-layer approach for routing has been paid more attention to in the recent. Its objective is to provide the network layer with an overall view of information from underlying layers when routing. So a path with reasonable delay, throughput and reliability can be selected timely. This paper introduces a new cross-layer metric for ad hoc on-demand distance vector (AODV) routing in WMN based on the information obtained from wireless channel conditions from physical layer, link quality and congestion from MAC layer. Simulation results have demonstrated that this new metric can greatly improve AODV routing performance in terms of end-to-end delay and throughput in contrast to the traditional metric of minimum hop.
An algorithm for extracting subgraph of specific species from metabolic pathway

A large number of metabolic pathway databases are currently available, such as KEGG, EcoCys, and BioPath. For a better use of the KEGG databases, studying the KEGG data structure and rebuilding it into a convenient form become crucial tasks to our research, such as functional modularity detection, conserved pathway analysis, phylogenetic analysis. This paper presents an algorithm for extracting the metabolic pathways from KEGG database to the form of enzyme-enzyme interactions (EEI) and compound-compound ones. Using the algorithm EMP (Extract Metabolic Pathway), we can transform a specific species metabolic pathway in KEGG into a subgraph which consists of EEI edges. Additionally, we provide a tool named ExtKEGG to extract compound-based metabolic pathways. Furthermore, the experimental results show that our algorithm causes no information loss.
An ensemble of replication and erasure codes for cloud file systems

Geographically distributed storage is an important method of ensuring high data availability in cloud computing and storage systems. With the increasing demand for moving file systems to the cloud, current methods of providing such enterprise-grade resiliency are very inefficient. For example, replication based methods incur large storage cost though they provide low access latencies. While erasure coded schemes reduce storage cost, they are associated with large access latencies and high bandwidth cost. In this paper, we propose a novel scheme named CAROM, an ensemble of replication and erasure codes, to provide resiliency in cloud file systems with high efficiency. While maintaining the same consistency semantics seen in today's cloud file systems, CAROM provides the benefit of low bandwidth cost, low storage cost, and low access latencies. We perform a large-scale evaluation using real-world file system traces and demonstrate that CAROM outperforms replication based schemes in storage cost by up to 60% and erasure coded schemes in bandwidth cost by up to 43%, while maintaining low access latencies close to those in replication based schemes.
Computing The Kullback-Leibler Divergence Between Probabilistic Automata Using Rational Kernels

Kullback-Leibler divergence is a natural distance measure between two probabilistic finite-state automata. Computing this distance is difficult, since it requires a summation over a countably infinite number of strings. Nederhof and Satta (2004) recently provided a solution in the course of solving the more general problem of finding the cross-entropy between a probabilistic context-free grammar and an unambiguous probabilistic automaton. We propose a novel solution for two unambiguous probabilistic automata, by showing that Kullback-Leibler divergence can be defined as a rational kernel (Cortes et al., 2004) over the expectation semiring (Eisner, 2002). Using this definition, the computation is performed using the general algorithm for rational kernels, yielding an elegant and efficient solution.
Spatial Correlation between Type of Mountain Area and Land Use Degree in Guizhou Province, China

A scientific definition of the type of mountain area and an exploration of the spatial correlation between different types of mountain areas and regional land use at the county level are important for reasonable land resource utilization and regional sustainable development. Here, a geographic information system was used to analyze digital elevation model data and to define the extent of mountainous land and types of mountain areas in Guizhou province. Exploratory spatial data analysis was used to study the spatial coupling relation between the type of mountain area and land use degree in Guizhou province at the county level. The results were as follows: (1) Guizhou province has a high proportion of mountainous land, with a ratio of mountainous land to non-mountainous land of 88:11. The county-level administrative units in Guizhou province were exclusively mountainous, consisting of eight semi mountainous counties, nine quasi mountainous counties, 35 apparently mountainous counties, 13 type I completely mountainous counties, and 23 type II completely mountainous counties; (2) The land use degree at the county level in Guizhou province have remarkable spatial differentiation characteristics. Counties with a high cultivation coefficient are mainly located in the western area along the line between Yinjiang county and Anlong county in west Guizhou province. Counties with a large proportion of construction land or a high integrated index of land use degree are mainly distributed in the economically developed area of central Guizhou province, including parts of the counties (districts/cities) administrated by Guiyang, Zunyi, Liupanshui, Anshun, Duyun, and Kaili; (3) County-level administrative units with relatively flat topography and a low proportion of mountainous land have a large proportion of construction land and a large degree of regional land exploitation. However, the extent of cultivation of county-level administrative units under similar topography differs considerably; (4) The increase in urban land intensity and the decrease in cultivated land intensity are distinctive features of land system change in mountain areas, which is conducive to the sustainable development of mountain.
Defining interfaces at a high level of abstraction

One of the newest user-interface management systems, the User-Interface Development Environment, is described by its creators. UIDE is built around a knowledge-based representation of the conceptual design of a user interface. UIDE supports design at a high-level specification of the interface from information provided by the designer. By using the same knowledge base, the interface developer can generate a new interface design with the same functionality as the original design. This lets users try many functionally equivalent interfaces for the same application. <<ETX>>
Human cutaneous T cell lymphoma and leukemia cell lines produce and respond to T cell growth factor

Three cell lines of mature T cell origin derived from patients with cutaneous T cell lymphoma-leukemias (CTCL) were found to be constitutive producers of T cell growth factor (L-TCGF). These are the first reported human cell lines which constitutively produce TCGF. Biologically active TCGF could also be eluted from the surface of these cells using an acid glycine buffer under conditions that maintained cell viability, and subcellular fractionation showed that almost all the TCGF activity was associated with the plasma membrane. Over 30 other human hematopoietic cell lines derived from other disorders were unable to produce TCGF even after induction, and their acid eluates did not contain TCGF activity. L-TCGF from CTCL lines had the same biological activity as TCGF obtained from normal leukocytes (N-TCGF) in that they both supported the long-term growth of normal T cells only after the cells were previously activated by antigen or lectin. Both L-TCGF and N-TCGF increased the rate of proliferation of TCGF-independent and TCGF-dependent CTCL cell lines. The same three factor-independent cell lines that released TCGF adsorbed TCGF in a cell-concentration, time-, and temperature-dependent manner. Since the CTCL cell lines produce TCGF, adsorb TCGF, and increase their proliferative rate in response to TCGF or a related molecule, it is suggested that this endogenously produced factor plays a role in maintaining the abnormal proliferation of these cells in culture as permanently growing cell lines independent of exogenous TCGF. However, this does not mean that this is an essential aspect of neoplastic transformation. Since it is unusual to develop these cell lines in the absence of the continuous need for added TCGF, “autostimulation” may be one of the many unusual variant phenotypic properties sometimes associated with neoplastic cells that gives them a selective advantage for in vitro growth.
Unsupervised Learning of Basic Object Affordances from Object Properties

Affordance learning has, in recent years, been generating heightened interest in both the cognitive vision and developmental robotics communities. In this paper we describe the development of a system that uses a robotic arm to interact with household objects on a table surface while observing the interactions using camera systems. Various computer vision methods are used to derive, firstly, object property features from intensity images and range data gathered before interaction and, subsequently, result features derived from video sequences gathered during and after interaction. We propose a novel affordance learning algorithm that automatically discretizes the result feature space in an unsupervised manner to form affordance classes that are then used as labels to train a supervised classifier in the object property feature space. This classifier may then be used to predict affordance classes, grounded in the result space, of novel objects based on object property observations.