Miracle-dz/UniFAR-FTUs huggingface dataset:
A Universal Test Pattern Generator for DDR

Because the memory cores can be used to save the instructions/data, the memory cores are frequently used within the system-on-a-chips (SOCs). The quality of the SOCs is mainly determined by the memory cores. However, due to the complicated fabrication process, the fault models of the memories are more complicated than the fault models of the logical cores. So far, more than 40 march algorithms have been proposed; however; no any single march algorithm can be _________________________________________ *This work was supported in part by the National Science Council of R.O. C. under contract NSC 91-2215-E-230-003. used to detect all the faults. To test effectively the memories, at least two march algorithms are used, however increasing the hardware cost. The double data rate synchronous dynamic random access memory (DDR SDRAM) is one of the promising memory products of today. To meet the market requirements, various specifications of DDR SDRAMs are manufactured. In this paper, a universal test pattern generator has been proposed for testing the various DDR SDRAMs.
Active post-refined multimodality video semantic concept detection with tensor representation

In this paper, we resolve the problem of multi-modality video representation and semantic concept detection. Interaction and integration of multi-modality media types such as visual, audio and textual data in video are essential to video semantic analysis. Traditionally, videos are represented as vectors in the Euclidean space. Many learning algorithms are then taken to these vectors in a high dimensional space for dimension reduction, classification, clustering and so on. However, the multiple modalities in video not only have their own properties, but also have correlations among them; whereas the simple vector representation weakens the power of these relatively independent modalities and even ignores their relations to some extent. In this paper, we introduce a higher-order tensor framework for video analysis, in which we represent image, video and text three modalities in video shots as data points by the 3rd-order tensor called tensorshots. We propose a novel dimension reduction method that explicitly considers the manifold structure of the tensor space from multimodal media data which is temporal associated co-occurrence and then detect video semantic concepts through powerful classifiers which take tensor as input. Our algorithm preserves the intrinsic structure of the submanifold where tensorshots are sampled, and is also able to map out-of-sample data points directly. Moreover we apply an active learning based contextual and temporal post-refining strategy to enhance detection accuracy. Experiment results show that our method improves the performance of video semantic concept detection.
ComTouch : a vibrotactile mobile communication device

s of CHI'98: Conference on Human Factors in Computing Systems. ACM Press, 1998. (Johnson 1987) Johnson, M. The Body in the Mind. The University of Chicago Press, Chicago IL, 1987. (Katz 1989) Katz, D. The World of Touch. Lawrence Erlbaum Associates, Hillsdale, NJ, 1989. (Kaye 2001) Kaye, Joseph. The Olfactory Display of Abstract Information. Master's Thesis in the Department of Architecture, Program in Media Arts and Sciences, Massachusetts Institute of Technology, Cambridge, MA, 2001. (Krueger 1991) Krueger, M. K. Artificial Reality II. Addison Wesley Publishing, Reading MA, 1991. (Lederman 1987) Lederman, S. , and Klatzky, R. Hand Movements: A Window into Haptic Object Recognitions. Cognitive Psychology, Academic Press, Inc. 19, 342-368, 1987. (Macleod 2000) Macleod, D. The Rules of Work: A Practical Engineering Guide to Ergonomics, New York: Taylor & Francis,
Quantitative Proteomic Analysis of Gene Regulation by miR-34a and miR-34c

microRNAs (miRNAs) repress target genes by destabilizing mRNAs and/or by inhibiting translation. The best known factor for target recognition is the so called seed – a short continuous region of Watson-Crick base pairing between nucleotides 2–7 of the miRNA and complementary sequences in 3′ untranslated regions of target mRNAs. The miR-34 family consists of three conserved members with important tumor suppressor functions linked to the p53 pathway. The family members share the same seed, raising the question if they also have the same targets. Here, we analyse the effect of miR-34a and miR-34c on protein synthesis by pSILAC. Despite significant overlap, we observe that the impact of both family members on protein synthesis differs. The ability to identify specific targets of a family member is complicated by the occurrence of * strand mediated repression. Transfection of miR-34 chimeras indicates that the 3′end of the miRNA might be responsible for differential regulation in case of targets without a perfect seed site. Pathway analysis of regulated proteins indicates overlapping functions related to cell cycle and the p53 pathway and preferential targeting of several anti-apoptotic proteins by miR-34a. We used luciferase assays to confirm that Vcl and Fkbp8, an important anti-apoptotic protein, are specifically repressed by miR-34a. In summary, we find that miR-34a and miR-34c down-regulate distinct subsets of targets which might mediate different cellular outcomes. Our data provides a rich resource of miR-34 targets that might be relevant for clinical trials that want to implement the miR-34 family in cancer therapy.
Efficient temporal join processing using indices

We examine the problem of processing temporal joins in the presence of indexing schemes. Previous work on temporal joins has concentrated on non-indexed relations which were fully scanned. Given the large data volumes created by the ever increasing time dimension, sequential scanning is prohibitive. This is especially true when the temporal join involves only parts of the joining relations (e.g., a given time interval instead of the whole timeline). Utilizing an index becomes then beneficial as it directs the join to the data of interest. We consider temporal join algorithms for three representative indexing schemes, namely a B+-tree, an R*-tree and a temporal index, the Multiversion B+-tree (MVBT). Both the B+-tree and R*-tree result in simple but not efficient join algorithms because neither index achieves good temporal data clustering. Better clustering is maintained by the MVBT through record copying. Nevertheless, copies can greatly affect the correctness and effectiveness of the join algorithms. We identify these problems and propose efficient solutions and optimizations. An extensive comparison of all index based temporal joins, using a variety of datasets and query characteristics shows that the MVBT based join algorithms are consistently faster. In particular the link-based algorithm has the most robust behavior. In our experiments it showed a ten fold improvement over the R*-tree joins while it was between six and thirty times faster than the B+-tree joins.
Novel Data-Distribution Technique for Hadoop in Heterogeneous Cloud Environments

The Hadoop framework has been developed to effectively process data-intensive MapReduce applications. Hadoop users specify the application computation logic in terms of a map and a reduce function, which are often termed MapReduce applications. The Hadoop distributed file system is used to store the MapReduce application data on the Hadoop cluster nodes called Data nodes, whereas Name node is a control point for all Data nodes. While its resilience is increased, its current data-distribution methodologies are not necessarily efficient for heterogeneous distributed environments such as public clouds. This work contends that existing data distribution techniques are not necessarily suitable, since the performance of Hadoop typically degrades in heterogeneous environments whenever data-distribution is not determined as per the computing capability of the nodes. The concept of data-locality and its impact on the performance of Hadoop are key factors, since they affect the performance in the Map phase when scheduling tasks. The task scheduling techniques in Hadoop should arguably consider data locality to enhance performance. Various task scheduling techniques have been analysed to understand their data-locality awareness while scheduling applications. Other system factors also play a major role while achieving high performance in Hadoop data processing. The main contribution of this work is a novel methodology for data placement for Hadoop Data nodes based on their computing ratio. Two standard MapReduce applications, Word Count and Grep, have been executed and a significant performance improvement has been observed based on our proposed data distribution technique.
The Immigrant-Native Wage Gap in the United States

Immigrants to the United States earn lower wages than native workers, and this gap decreases with time spent working in the US labor market. In this paper, we study the determinants of the wage path of immigrants in order to understand this wage gap between natives and immigrants. We focus on two particular explanations: differing returns to experience in the US and search frictions when finding optimal occupations. Labor market experience in the US may be more valuable for jobs in the US than labor market experience in other countries. In addition, it can take time for new immigrants to be matched with their optimal occupation after moving to the US. Separating these factors is difficult due to potential self-selection of immigrants. To deal with this, we use data from the New Immigrant Survey which has detailed information on the occupations and wages of immigrants both before they enter the US as well as repeated observations after moving to the US. Reduced form evidence shows that both search frictions and work experience affect immigrant wages. We develop and estimate a simple model of on-the-job human capital accumulation and job search. Using the estimated model, we simulate counterfactuals to understand the importance of each factor. In the first simulation, we find that immigrant wages over a lifetime increase by 32% when returns to experience in the home country are the same as returns to experience in the US. In the second simulation, we match immigrants with their optimal occupation in their first US job, and find that this increases wages by 5%. JEL Codes: J31, J15, J62 ∗Tepper School of Business, Carnegie Mellon University. rlessem@andrew.cmu. edu †Department of Economics, Washington University in St. Louis and the Federal Reserve Bank of Saint Louis. carlsanders@wustl.edu ‡We thank Robert Miller for helpful comments. All errors are our own.
Object Boundary Detection For Ontology-Based Image Classification

Technology in the field of digital media generates huge amounts of non-textual information, audio, video, and images, along with more familiar textual information. The potential for exchange and retrieval of information is vast and daunting. The key problem in achieving efficient and user-friendly retrieval in the domain of image is the development of a search mechanism to guarantee delivery of minimal irrelevant information (high precision) while insuring that relevant information is not overlooked (high recall). The traditional solution to the problem of image retrieval employs content-based search techniques based on color, histogram, texture or shape features. The traditional solution works well in performing searches in which the user specifies images containing a sample object, or a sample textural pattern, in which the object or pattern is indexed. One can overcome this restriction by indexing images according to meanings rather than objects that appear in images, although this will entail a way of converting objects to meanings. We have solved this problem of creating a meaning based index structure through the design and implementation of a concept-based model using domain dependent ontologies. An ontology is a collection of concepts and their interrelationships which provide an abstract view of an application domain. With regard to converting objects to meaning the key issue is to identify appropriate concepts that both describe and identify images. For this, first we need to identify all object boundaries accurately that appear in images. We propose an automatic scalable object boundary detection algorithm based on edge detection and region growing techniques. We also propose an efficient merging algorithm to join adjacent regions using an adjacency graph to avoid the over-segmentation of regions. To illustrate the effectiveness of our algorithm in automatic image classification we implement a very basic system aimed at the classification of images in the sports domain. By identifying objects in images, we show that our approach works well when objects in images have less complex organization.
A Novel Stochastic Decoding of LDPC Codes with Quantitative Guarantees

Low-density parity-check codes, a class of capacity-approaching linear codes, are particularly recognized for their efficient decoding scheme. The decoding scheme, known as the sum-product, is an iterative algorithm consisting of passing messages between variable and check nodes of the factor graph. The sum-product algorithm is fully parallelizable, owing to the fact that all messages can be update concurrently. However, since it requires extensive number of highly interconnected wires, the fully-parallel implementation of the sum-product on chips is exceedingly challenging. Stochastic decoding algorithms, which exchange binary messages, are of great interest for mitigating this challenge and have been the focus of extensive research over the past decade. They significantly reduce the required wiring and computational complexity of the message-passing algorithm. Even though stochastic decoders have been shown extremely effective in practice, the theoretical aspect and understanding of such algorithms remains limited at large. Our main objective in this paper is to address this issue. We first propose a novel algorithm referred to as the Markov based stochastic decoding. Then, we provide concrete quantitative guarantees on its performance for tree-structured as well as general factor graphs. More specifically, we provide upper-bounds on the first and second moments of the error, illustrating that the proposed algorithm is an asymptotically consistent estimate of the sum-product algorithm. We also validate our theoretical predictions with experimental results, showing we achieve comparable performance to other practical stochastic decoders.
Compass-M1 Broadcast Codes and Their Application to Acquisition and Tracking

With the launch of the Compass-M1 satellite on 14 April 2007, China is set to become the latest entrant into global navigation satellite systems (GNSS). The satellite, sometimes referred to as Compass-2 or Beidou-2, is the first of the Compass navigation satellite system (CNSS) that will provide global satellite navigation coverage. While China has launched several other navigation satellites, these previous satellites, also termed Compass or Beidou (in Chinese), provided only regional coverage. The Compass-M1 differs significantly from these previous satellites in terms of signal structure, frequency, and coverage. Most significantly, unlike previous satellites, it has similar frequencies and signal structure to other GNSS, making the prospect of interoperation a tantalizing one. Understanding the interoperability and integration of CNSS with GPS, Galileo and GLONASS, requires knowing and understanding its signal structure, specifically its codes and code structure. The knowledge of the code is necessary for designing receivers capable of acquiring and tracking the satellite. These receivers are necessary for evaluating the performance and benefits of CNSS. Just as important is determining if the signal may degrade performance of GPS/Galileo in the form of interference. Interference with and degradation of GPS/Galileo performance are possibilities if interoperability was not a driving concern in the signal design. This is of concern to military users as well since Compass overlays GPS M-code and Galileo Public Regulated Service (PRS) on E1/E2. So our preliminary step in studying Compass is a determination and analysis of the Compass-M1 codes. Additionally, we will implement these codes within our software GNSS receiver to verify and validate our analysis. In this paper, we decode the PRN codes of the E2, E5b and E6 signals broadcast by the Compass-M1 satellite. The E2 and E5 codes are identical. They are 2046 bits long and are 11-stage Gold codes. The E6 PRN code is a 10230-bit concatenated Gold code. The head and tail parts are both 13-stage Gold codes. We then apply the codes for acquisition and tracking. By using our own software receiver, we are able to successfully acquire and track the Compass-M1 satellite. This is useful for evaluating the performance of the selected codes.
Mitochondrial Heat Shock Protein (Hsp) 70 and Hsp10 Cooperate in the Formation of Hsp60 Complexes*

Background: The formation of Hsp60 complexes is poorly understood. Results: The biogenesis of Hsp60 complexes depends on mitochondrial (mt) Hsp70 and Hsp10. Conclusion: MtHsp70 interacts with Hsp10 to promote Hsp60 biogenesis. Significance: Coupling to partner proteins like Hsp10 modifies the functional specificity of mtHsp70. Mitochondrial Hsp70 (mtHsp70) mediates essential functions for mitochondrial biogenesis, like import and folding of proteins. In these processes, the chaperone cooperates with cochaperones, the presequence translocase, and other chaperone systems. The chaperonin Hsp60, together with its cofactor Hsp10, catalyzes folding of a subset of mtHsp70 client proteins. Hsp60 forms heptameric ring structures that provide a cavity for protein folding. How the Hsp60 rings are assembled is poorly understood. In a comprehensive interaction study, we found that mtHsp70 associates with Hsp60 and Hsp10. Surprisingly, mtHsp70 interacts with Hsp10 independently of Hsp60. The mtHsp70-Hsp10 complex binds to the unassembled Hsp60 precursor to promote its assembly into mature Hsp60 complexes. We conclude that coupling to Hsp10 recruits mtHsp70 to mediate the biogenesis of the heptameric Hsp60 rings.
A 1 Customized individual promotions : Model , optimization , and prediction Appendix

For a retailer, running personalized promotions is a means to overcome the negative effects of promotions offered to all customers (e.g., stockpiling effects on the customer side). These customized promotions rely on the heterogeneous preferences of individuals for products within a category, and their different sensitivities to price discounts. We consider the problem of predicting individual customer responses to promotion decisions over a category of products, and based on the predictions, optimizing the portfolio of products to put on promotion for a particular individual. The data sources required by our methodology include historical purchase transactions data tagged by customer ID, information about the assortment available for the product category of interest at the moment of purchase, and the identification of the products that were on promotion by that time. In our model each customer is represented by a partial order or directed acyclic graph (DAG). The DAG is constructed from a set of rules that account for the revealed preferences of each customer through the history of past purchases. In a DAG, each node represents a product, and each arc represents a pairwise preference relation. While processing the data source in the DAG construction phase, a customer may exhibit an apparent inconsistency in her purchase behavior that may imply the creation of a cycle. Then, we run a de-cycling procedure based in a mixed-integer programming (MIP) formulation in order to keep a maximal number of arcs to describe consistent customer preferences. On the theoretical side, we provide tractable bounds to compute both the likelihood of partial orders (which in general is a #P-hard problem) and the purchase probabilities from these DAGs. Next, taking the collection of DAGs representing the customer basis as input, we calibrate a single class MNL model and a latent class MNL model. On the side, we also estimate two state-of-the-art parametric models: latent-class multinomial logit (LC-MNL), and random parameters logit (RPL) accounting for panel data, but without using the aforementioned DAG-based underlying structure. Finally, our DAG-based MNL variants and both benchmarks were tested for designing personalized promotions. Via a MIP formulation, we consider the problem where the offer set faced by the customers in each store visit is given and the decision variables are which products to promote in order to maximize expected revenues. Numerical experiments on real-world panel data for a grocery chain across 27 product categories. We observe that our approach allows more accurate, fine-grained predictions for individual purchase behavior compared to the state-ofthe-art benchmarks. For the performance score functions that we computed, our DAG-based models could outperform the benchmarks by more than 10%. Furthermore, our MIP for running personalized promotions can increase revenues by 26% (on average) over the current practice reflected in the dataset.
Impurities in High Molecular Weight Amine Products

The analysis of high molecular weight amines and of such products as the amine acetates is rather difficult, particularly when impurities are to be determined. There are three reasons for the difficulty. First, the amines are complex mixtures obtained from natural products, such as animal and vegetable fats. Thus, they will contain some of the sterols originally present in the fat. Second, the chemical properties of the constituent compounds are rather similar. The probable components can be deduced from a typical commercial method of synthesis (Armour, 1948). This consists of: hydrolysis of the fat, separation of the fatty acid, formation of the amide by reaction with ammonia, dehydration of the amide to form the nitrile, hydrogenation of the nitrile to the amine, and finally the reaction of the amine with acetic acid, if desired. The last step can lead to the formation of N-alkyl acetamides by dehydration of the amine acetate. Thus, in addition to primary, secondary and tertiary amines, we may expect to find nitriles, amides, N-alkylacetamides, and sterols. The third cause of difficulty in analysis is that the high molecular weight amines and their salts are surfactants, with the result that solutions foam to a great extent, and precipitates are frequently kept in suspension. For example, stearic acid will precipatate as lead stearate from 70 percent aqueous acetone upon the addition of lead acetate. However, no precipitate is obtained in the presence of large amounts of octadecylamine acetate. The obvious solution to the difficulty is the removal of the major portion of the amine, and to analyze for the impurities remaining in the residue. The following are chemical means of separation and analysis which are offered as a partial solution to the problem:
Use of Nutrition and Physical Activity Modules to Promote Continuing Professional Development: A Pilot Test

Background: The authors developed five online modules about physical activity and nutrition. Methods: Registered nurses completed surveys before and after each module. Results: Evaluations showed an increase in knowledge and skill, but the psychometric parameters of the evaluation tool were poor. The low participation rate was associated with module length and technological difficulties. Conclusions: Given busy schedules of health professionals, online education approaches need to be feasible and be easy to access and use.