Miracle-dz/UniFAR-FTUs huggingface dataset:
SHAKTI-F: A Fault Tolerant Microprocessor Architecture

Deeply scaled CMOS circuits are vulnerable to soft and hard errors. These errors pose reliability concerns, especially for systems used in radiation-prone environments like space and nuclear applications. This paper presents SHAKTI-F, a RISC-V based SEE-tolerant micro-processor architecture that provides a solution to the reliability issues mentioned above. The proposed architecture uses error correcting codes (ECC) to tolerate errors in registers and memories, while it employs a combination of space and time redundancy based techniques to tolerate errors in the ALU. Two novel re-computation techniques for detecting errors for the addition/subtraction and multiplication modules are proposed. The scheme also identifies parts of the circuitry that need to be radiation hardened thus providing a total protection to SEEs. The proposed scheme provides fine-grain error detection capability that help in localization of the error to a specific functional unit and isolating the same, rather than the entire processor or a large module within a processor. This provides a graceful degradation and/or fail-safe shutdown capability to the processor. The HDL model of the processor was validated by simulating it with randomly induced SEEs. The proposed scheme adds an extra penalty of only 20% on the core area and 25% penalty on the performance when compared with conventional systems. This is very less when compared to the penalty incurred by employing schemes including double modular and triple modular redundancy. Interestingly, there is a 45% reduction in power consumption due to introduction of fault tolerance. The resulting system runs at 330 MHz on a 55nm technology node, which is sufficient for the class of applications these cores are utilized for.
Psychological approach to indexing: effects of the operator's expertise upon indexing behaviour

Studies of indexing have shown significant variation in the indexing terms chosen by several indexers to represent the same document. In our opinion, this variability depends on various indexing strategies used by the indexers with different expertise. Professional and novice indexers were asked to index eight books; they had to express the topics and to choose the indexing terms from an indexing language. The factors which influenced the indexing were: expertise in the indexing task, expertise in the use of an indexing language and familiarity with the subject domain. The criteria were: the number of indexing terms chosen, the rate of the intra-indexer consistency, the types of transformation made on the concepts, the indexing procedures and the objectives pursued during the task. The findings identified three indexing strategies which depend on indexers' exper tise. The first is characterised by a search for indexing terms from the document analysis stage. The second consists of identifying the generic terms in the document that allow them to quickly access the indexing language. The third strategy is characterised by a precise analysis. These results raise questions about the compatibility between knowledge representation produced by the indexing languages and the operators' representation produced by the text in order to specify assistance to indexing work.
The Role of Responsive Choreography in Alternative Assessment: Sequencing Writing Tasks To Support Concept Assimilation.

In an attempt to understand, holistically, how teachers make sense of their classrooms and how they use assessment to facilitate learning, this paper explores the use of a metaphor, "responsive choreography," to examine instruction in one classroom. "Responsive choreography" describes the subtle interplay or "dance" between the learner and the teacher in the role of enabling each other. How alternative assessment strategies were used to inform instructional practice and how the teacher's responsiveness made sense of assessment were studied through the analysis of writing tasks for a seventh grade social studies class. Observation of the social studies teacher and student writings indicate that the teacher seldom reached the ideal of responsive choreography. The focus of this teacher appeared to be on what she wanted students to know rather than on student learning and student response. Over the course of the research, the teacher saw the value of being responsive in her instructional choreography, but sustaining this approach would require the re-examination of her instructional practice overall. (Contains 27 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document. The Role of Responsive Choreography in Alternative Assessment: Sequencing writing tasks to support concept assimilation Kathryn A. Noel, PhD Nova Scotia Department of Education Halifax, Nova Scotia, Canada Paper presented at the 2000 American Educational Research Association New Orleans, Louisiana April 24 28, 2000 CO U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) LoTh<s document has been reproduced as received from the person or organization originating it. Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. 1 PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY
A compact 3D VLSI classifier using bagging threshold network ensembles

A bagging ensemble consists of a set of classifiers trained independently and combined by a majority vote. Such a combination improves generalization performance but can require large amounts of memory and computation, a serious drawback for addressing portable real-time pattern recognition applications. We report here a compact three-dimensional (3D) multiprecision very large-scale integration (VLSI) implementation of a bagging ensemble. In our circuit, individual classifiers are decision trees implemented as threshold networks - one layer of threshold logic units (TLUs) followed by combinatorial logic functions. The hardware was fabricated using 0.7-/spl mu/m CMOS technology and packaged using MCM-V micro-packaging technology. The 3D chip implements up to 192 TLUs operating at a speed of up to 48 GCPPS and implemented in a volume of (/spl omega/ /spl times/ L /spl times/ h) = (2 /spl times/ 2 /spl times/ 0.7) cm/sup 3/. The 3D circuit features a high level of programmability and flexibility offering the possibility to make an efficient use of the hardware resources in order to reduce the power consumption. Successful operation of the 3D chip for various precisions and ensemble sizes is demonstrated through an electronic nose application.
Multimedia Tools and Applications Manuscript No. Everyday Concept Detection in Visual Lifelogs: Validation, Relationships and Trends

The Microsoft SenseCam is a small lightweight wearable camera used to passively capture photos and other sensor readings from a user's day-today activities. It captures on average 3,000 images in a typical day, equating to almost 1 million images per year. It can be used to aid memory by creating a personal multimedia lifelog, or visual recording of the wearer's life. However the sheer volume of image data captured within a visual lifelog creates a number of challenges, particularly for locating relevant content. Within this work, we explore the applicability of semantic concept detection, a method often used within video retrieval, on the domain of visual lifelogs. Our concept detector models the correspondence between low-level visual features and high-level semantic concepts (such as indoors, outdoors, people, buildings, etc.) using supervised machine learning. By doing so it determines the probability of a concept's presence. We apply detection of 27 everyday semantic concepts on a lifelog collection composed of 257,518 SenseCam images from 5 users. The results were evaluated on a subset of 95,907 images, to determine the accuracy for detection of each semantic concept. We conducted further analysis on the temporal consistency, co-occurance and relationships 2 within the detected concepts to more extensively investigate the robustness of the detectors within this domain.
Expression of a Synthesized Gene Encoding Cationic Peptide Cecropin B in Transgenic Tomato Plants Protects against Bacterial Diseases

ABSTRACT The cationic lytic peptide cecropin B (CB), isolated from the giant silk moth (Hyalophora cecropia), has been shown to effectively eliminate Gram-negative and some Gram-positive bacteria. In this study, the effects of chemically synthesized CB on plant pathogens were investigated. The S50s (the peptide concentrations causing 50% survival of a pathogenic bacterium) of CB against two major pathogens of the tomato, Ralstonia solanacearum and Xanthomonas campestris pv. vesicatoria, were 529.6 μg/ml and 0.29 μg/ml, respectively. The CB gene was then fused to the secretory signal peptide (sp) sequence from the barley α-amylase gene, and the new construct, pBI121-spCB, was used for the transformation of tomato plants. Integration of the CB gene into the tomato genome was confirmed by PCR, and its expression was confirmed by Western blot analyses. In vivo studies of the transgenic tomato plant demonstrated significant resistance to bacterial wilt and bacterial spot. The levels of CB expressed in transgenic tomato plants (∼0.05 μg in 50 mg of leaves) were far lower than the S50 determined in vitro. CB transgenic tomatoes could therefore be a new mode of bioprotection against these two plant diseases with significant agricultural applications.
A Comparison of C-Store and Row-Store in a Common Framework

Recently, a “column store” system called CStore has shown significant performance benefits by utilizing storage optimizations for a read-mostly query workload. The authors of the C-Store paper compared their optimized column store to a commercial row store RDBMS that is optimized for a mixture of reads and writes, which obscures the relative benefits of row and column stores. In this paper, we describe two storage optimizations for a row store architecture given a read-mostly query workload ‐ “super tuples” and “column
PCR-Based Method for Isolation of Full-Length Clones and Splice Variants from cDNA Libraries

Most cDNA library screening procedures do not distinguish between full-length and incomplete clones and therefore may yield incomplete cDNA fragments. Thus, there is a widespread need for a method allowing the efficient selection of full-length clones. I present a rapid, PCR-based method that allows the simultaneous screening of >106 cDNAs. The longest cDNA is identified in the first step so that incomplete clones may be eliminated from study at this stage to save time. The method also facilitates the identification and isolation of rare splice variants from a background of a more
An experimental evaluation of quality guidelines on the maintainability of object-oriented design documents

This paperpresents a controlled experimentfocusing on the impact of applying quality design principles such as the ones provided by Coad and Yourdon on the maintainability of object-oriented design documents. Results, which repeat thefindings of a previous study; strongly suggest that such design principles have a benejicial eflect on the maintainability of object-oriented design documents. It is argued that object-oriented design documents are sensitive to poor design practices because the cognitive complexity introduced becomes increasingly unmanageable. However; as our ability to generalise these results is limited, they should be considered as preliminaq\ i.e., it is very likely that they can only be generalised to programmers with little object-oriented training and programming experience. Such programmers can, however; be commonly found on maintenance projects. As well as additional research, external replications of this study are required to confirm the results and achieve conjdence in these findings.
Report on Experiments and Clinical Cases ― Experience with Direct Kugel Patch Method for Repair of Adult Inguinal Hernia

The direct Kugel Patch method is a minimally invasive but nonlaparoscopic preperitoneal method of hernia repair which has various ideal characteristics including all the benefits of laparoscopic hernia repair without the risks of complications. In this retrospective study, we report our experience with this method for adult inguinal hernia repair. Forty-four hernias, including 35 indirect, 7 direct inguinal hernias, and 1 recurrent indirect inguinal hernia, in 41 patients were surgically repaired using the direct Kugel patch method. The average operation time was 45.6 ± 11.3 min, and the average hospitalization time was 6.2 ± 5.0 days. There were 5 complications of seroma and only 1 recurrence of hernia which were successfully managed. We concluded that the direct Kugel patch method provides an ideal approach to adult inguinal hernia repair with short operation time and hospital stay and a very low risk of complications or recurrence. (J Nippon Med Sch 2008; 75: 28―31)
Path planning on grid maps with unknown goal poses

Path planning for robots typically consists of finding a path from a given start state to one or multiple given goal states. However, there are situations in which the pose of the goal state is not explicitly known, e.g. in sensor-based autonomous driving in unknown environments. This paper presents a path planner that is capable of planning feasible paths in the absence of goal poses. The approach combines the advantages of both the focused search of A* and the uniformly-exploring search of Rapidly Exploring Random Trees. With this approach, it is possible to quickly find potential goal states and their corresponding paths and to continue the exploration as processing time allows. Furthermore, it is shown how to cluster paths to extract the main possible directions. Results on simulation and real data are given to demonstrate the utility and efficiency of the proposed approach.
Beamformer With Constant-Gm Vector Modulators and Its Spatial Intermodulation Distortion

Spatial interference rejection in analog adaptive beamforming receivers can improve the distortion performance of the circuits following the beamforming network, but is susceptible to the nonlinearity of the beamforming network itself. This paper presents an analysis of intermodulation product cancellation in analog active phased array receivers and verifies the distortion improvement in a four-element adaptive beamforming receiver for low-power applications in the 1.0–2.5-GHz frequency band. In this architecture, a constant-Gm vector modulator is proposed that produces an accurate equidistance square constellation, leading to a sliced frontend design that is duplicated for each antenna element. By moving the transconductances to RF, a fourfold reduction in power is achieved, while simultaneously providing input impedance matching. The 65-nm implementation consumes between 6.5 and 9 mW per antenna element and shows a +1 to +20 dBm in-band and out-of-beam third-order intercept point due to intermodulation distortion reduction.
CANVAS: computer-assisted narrative animation synthesis

Despite the maturity in solutions for animating expressive virtual characters, innovations realizing the creative intent of story writers have yet to make the same strides. The key challenge is to provide an accessible, yet expressive interface for story authoring that enables the rapid prototyping, iteration, and deployment of narrative concepts. We present CANVAS, a computer-assisted visual authoring tool for synthesizing multi-character animations from sparsely-specified narrative events. In a process akin to storyboarding, authors lay out the key plot points in a story, and our system automatically fills in the missing details to synthesize a 3D animation that meets author constraints. CANVAS can be used by artists and directors to pre-visualize storyboards in an iterative fashion, and casual users may provide arbitrarily sparse specifications and harness automation to rapidly generate diverse narratives. CANVAS provides an accessible interface for rapidly authoring and pre-visualizing complex narratives. Automation reduces the authoring effort further without undermining creative control or interfering with the storytelling process.
Co-regularized kernel k-means for multi-view clustering

In clustering applications, multiple views of the data are often available. Although clustering could be done within each view independently, exploiting information across views is promising to gain clustering accuracy improvement. A common assumption in the field of multi-view learning is that the clustering results from multiple views should be consistent with a latent clustering. However, the potential noise among some views would make this assumption difficult to be satisfied, which finally hurts the clustering performance. To address this issue, we propose a novel clustering algorithm where the intrinsic clustering is found by maximizing the sum of weighted similarities between clusterings of different views. Weights that indicate the qualities of views are learned simultaneously along with the latent clustering and clusterings of different views. A three-step alternative algorithm is designed to solve the problem efficiently. Empirical comparisons with a number of baselines on various datasets confirm the efficacy of our approach.
The Power of Linear Programming for Valued CSPs

A class of valued constraint satisfaction problems (VCSPs) is characterised by a valued constraint language, a fixed set of cost functions on a finite domain. An instance of the problem is specified by a sum of cost functions from the language with the goal to minimise the sum. This framework includes and generalises well-studied constraint satisfaction problems (CSPs) and maximum constraint satisfaction problems (Max-CSPs). Our main result is a precise algebraic characterisation of valued constraint languages whose instances can be solved exactly by the basic linear programming relaxation. Using this result, we obtain tractability of several novel and previously widely-open classes of VCSPs, including problems over valued constraint languages that are: (1) sub modular on arbitrary lattices, (2) bisubmodular (also known as k-sub modular) on arbitrary finite domains, (3) weakly (and hence strongly) tree-sub modular on arbitrary trees.
Supervised rank aggregation approach for link prediction in complex networks

In this paper we propose a new topological approach for link prediction in dynamic complex networks. The proposed approach applies a supervised rank aggregation method. This functions as follows: first we rank the list of unlinked nodes in a network at instant t according to different topological measures (nodes characteristics aggregation, nodes neighborhood based measures, distance based measures, etc). Each measure provides its own rank. Observing the network at instant t+1 where some new links appear, we weight each topological measure according to its performances in predicting these observed new links. These learned weights are then used in a modified version of classical computational social choice algorithms (such as Borda, Kemeny, etc) in order to have a model for predicting new links. We show the effectiveness of this approach through different experimentations applied to co-authorship networks extracted from the DBLP bibliographical database. Results we obtain, are also compared with the outcome of classical supervised machine learning based link prediction approaches applied to the same datasets.
Expression and functional analysis of the plant-specific histone deacetylase HDT701 in rice

Reversible histone acetylation and deacetylation at the N-terminus of histone tails play a crucial role in regulating eukaryotic gene activity. Acetylation of core histones is associated with gene activation, whereas deacetylation of histone is often correlated with gene repression. The level of histone acetylation is antagonistically catalyzed by histone acetyltransferases citation(HATs) and histone deacetylases (HDACs). In this work, we examined the subcellular localization, expression pattern and function of HDT701, a member of the plant-specific HD2-type histone deacetylase in rice. HDT701 is localized at the subcellular level in the nucleus. Histochemical GUS-staining analysis revealed that HDT701 is constitutively expressed throughout the life cycle of rice. Overexpression of HDT701 in rice decreases ABA, salt and osmotic stress resistance during seed germination. Delayed seed germination of HDT701 overexpression lines is associated with decreased histone H4 acetylation and down-regulated expression of GA biosynthetic genes. Moreover, overexpression of HDT701 in rice enhances salt and osmotic stress resistance during the seedling stage. Taken together, our findings suggested that HDT701 may play an important role in regulating seed germination in response to abiotic stresses in rice.
Can Youth Health Care Scans at the Age of Five Discriminate between Adolescent Psychiatric Inpatients with Severe Disruptive Behavior and a Non-Treatment Group?

The aim of the study was to examine whether adolescent psychiatric inpatients (n = 24) with severe disruptive behavior could be discriminated from a control sample (n = 41) based on information about disruptive behavior recorded early in their lives. Remarks by teachers and health professionals made in youth health care files when the respondents were five years of age were used. Both teachers and professionals made significantly more remarks regarding disruptive behavior in the files of the future patients. The files of the patients also contained more remarks about other behavior. The sensitivity and specificity of behavior at the age of five to predict future treatment was satisfactory. The majority of the inpatients belonged to the prototypical life-course-persistent group that is known from epidemiological studies.
Incremental Localization Algorithm Based on Multivariate Analysis

In view of the traditional increment localization method, only the heteroscedasticity caused by the error accumulation is considered unilaterally a kind of incremental localization algorithm based on multivariate analysis is proposed. The algorithm combines the feasible weighted least squares (FWLS) in the multianalysis with the canonical correlation regression (CCR) and utilizes the FWLS to solve the heteroscedasticity caused by the error accumulation in the process of incremental localization; in the process of estimation, the CCR is used to solve the topology problems between the original beacon nodes and new beacon nodes. The simulation results show that the method can not only effectively restrain the influence caused by the accumulative errors but also can adapt to the different node topological shapes, so as to improve the positioning accuracy of the nodes.