Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimizing Sparse Matrix-Vector Multiplication on GPUs

We are witnessing the emergence of Graphics Processor units (GPUs) as powerful massively parallel systems. Furthermore, the introduction of new APIs for general-purpose computations on GPUs, namely CUDA from NVIDIA, Stream SDK from AMD, and OpenCL, makes GPUs an attractive choice for high-performance numerical and scientific computing. Sparse Matrix-Vector multiplication (SpMV) is one of the most important and heavily used kernels in scientific computing. However with indirect and irregular memory accesses resulting in more memory accesses per floating point operation, optimization of SpMV kernel is a significant challenge in any architecture. In this paper, we evaluate the various challenges in developing a high-performance SpMV kernel on NVIDIA GPUs using the CUDA programming model and propose optimizations to effectively address them. The optimizations include: (1) exploiting synchronization-free parallelism, (2) optimized thread mapping based on the affinity towards optimal memory access pattern, (3) optimized off-chip memory access to tolerate the high access latency, and (4) exploiting data reuse. We evaluate our optimizations over two classes of NVIDIA GPU chips, namely, GeForce 8800 GTX and GeForce GTX 280, and we compare the performance of our approach with that of existing parallel SpMV implementations such as (1) the one from NVIDIA’s SpMV library, (2) the one from NVIDIA’s CUDPP library, and (3) the one implemented using optimal segmented scan primitive. Our approach outperforms the CUDPP and segmented scan implementations by a factor of 2 to 8. Our approach is either in par with NVIDIA’s SpMV library in performance or achieves up to 15% improvement over NVIDIA’s SpMV library.
Identity verification using complex representations of the handwritten signature

This paper is devoted to a handwritten signature verification using the cross-correlation approach (adopted by the authors from telecommunications) and dynamic time warping. The following invariants of the handwritten signature: net signature, instantaneous complex frequency and complex cepstrum, are analyzed. The problem of setting the threshold for deciding whether the current signature is authentic or forged is discussed. The database of 3400 signatures collected for the First International Signature Verification Competition (SVC) 2004 purposes is exploited. The obtained results are compared with those derived during the SVC 2004.
Effects of Harvest on the Sustainability and Leaf Productivity of Populations of Two Palm Species in Maya Homegardens

Traditional management practices are usually thought to be sustainable. The Maya manage Sabal (Arecaceae) palms in homegardens, using their leaves for thatching. The sustainability of such production systems depends on the long-term persistence of palm populations, whereas resource availability also depends on the number of leaves on individual palms. We examined how leaf harvest affects Sabal yapa and S. mexicana population growth rates (λ) and leaf production, comparing traditional and alternative harvest regimes in terms of sustainability and productivity. Demographic, harvest and leaf production data were recorded for three years in two homegardens. We used general integral projection models linked to leaf-production models to describe population dynamics and productivity. Harvest had no effect on S. yapa’s vital rates or on λ, but it changed the growth rate of individuals of S. mexicana, with a negligible impact on λ. Homegardens affected λ values, reflecting the species’ ecological affinities. S. mexicana, introduced from mesic forests, required watering and shade; therefore, its population declined rapidly in the homegarden that lacked both water and shade. The λ of the xerophilic S. yapa was slightly larger without watering than with watering. Palms usually compensated for leaf extraction, causing the number of leaves harvested per individual to increase with harvest intensity. Nevertheless, traditional management is relatively mild, allowing standing leaves to accumulate but reducing the homegarden’s yield. Apparently, the Maya do not seek to maximize annual production but to ensure the availability of large numbers of leaves in homegardens. These leaves may then be used when the entire roof of a hut needs to be replaced every few years.
Robust Class Similarity Measure for Traffic Sign Recognition

Traffic sign recognition is an example of a hard multiclass classification problem. The existing approaches to that problem typically associate with each sign class a real-valued likelihood function and assign such a label to the unknown image that maximizes the value of this function. These template-matching techniques are usually based on arbitrary similarity metrics, such as normalized cross correlation, which do not capture the characteristics of the sign imagery. In this paper, we study the concept of a robust sign similarity measure that can be inferred from the domain-specific data. Two novel machine-learning techniques are proposed as a framework for automatic construction of such a measure from the pairs of images representing either the same or different classes. One is called SimBoost, which is a variation of the AdaBoost algorithm, and the other is based on the fuzzy regression tree framework. Through the experiments with low-quality images, we show that the proposed method admits efficient road sign recognition and outperforms the existing approaches in terms of the classification accuracy.
Uniting a priori and a posteriori knowledge : A research framework

The ability to perform machine classification is a critical component of an intelligent system. We propose to unite the logical, a priori approach to this problem with the empirical, a posteriori approach. We describe in particular how the a priori knowledge encoded in Cyc can be merged with technology for probabilistic inference using Markov logic networks. We describe two problem domains – the Whodunit Problem and noun phrase understanding – and show that Cyc’s commonsense knowledge can be fruitfully combined with probabilistic reasoning.
Mitigating the cognitive overload of contemporary argumentation-based collaboration settings

We present CoPe_it! , an innovative web-based tool that complies with collaborative practices to provide members of diverse communities with the appropriate means to manage individual and collective knowledge during a complex sense-making and/or decision-making session. We discuss the rationale behind the tool's development and present its features and functionalities that aim to efficiently deal with cognitive overload issues.
Equivalent circuit of induction fed magnetic resonant WPT system

A procedure to calculate parameters of an equivalent circuit of the magnetic-coupled resonant wireless power transfer is discussed. Equivalent circuit parameters are calculated from the mechanical and material parameters of the wireless power transfer structure. Both direct-fed type and indirect-fed type structure are considered. MoM calculation shows that the equivalent circuit has capability to calculate S parameters and radiation power correctly.
Sensing task handover for indoor clustered wireless sensor network

This paper presents the proposal of implementing sensing task handover initiation control for wireless sensor network deployed in indoor environment. The structure of the wireless sensor network is based on indoor clustering so that sensor nodes are grouped in different clusters according to room partitions. For such a network, a simple and efficient multi-node handover initiation control method is proposed for the decision of handover initiation by comparing the combined received signal strengths and the number of effective nodes between two neighbouring clusters. Experiments were conducted to test the possibility and evaluate the performance of the proposed method. The results show that sensing task handover is possible to happen at accurate time while crossing boundary between two clusters by applying the proposed method.
Identification of Sumoylated Proteins in the Silkworm Bombyx mori

Small ubiquitin-like modifier (SUMO) modification (SUMOylation) is an important and widely used reversible modification system in eukaryotic cells. It regulates various cell processes, including protein targeting, transcriptional regulation, signal transduction, and cell division. To understand its role in the model lepidoptera insect Bombyx mori, a recombinant baculovirus was constructed to express an enhanced green fluorescent protein (eGFP)-SUMO fusion protein along with ubiquitin carrier protein 9 of Bombyx mori (BmUBC9). SUMOylation substrates from Bombyx mori cells infected with this baculovirus were isolated by immunoprecipitation and identified by LC–ESI-MS/MS. A total of 68 candidate SUMOylated proteins were identified, of which 59 proteins were functionally categorized to gene ontology (GO) terms. Analysis of kyoto encyclopedia of genes and genomes (KEGG) pathways showed that 46 of the identified proteins were involved in 76 pathways that mainly play a role in metabolism, spliceosome and ribosome functions, and in RNA transport. Furthermore, SUMOylation of four candidates (polyubiquitin-C-like isoform X1, 3-hydroxyacyl-CoA dehydrogenase, cyclin-related protein FAM58A-like and GTP-binding nuclear protein Ran) were verified by co-immunoprecipitation in Drosophila schneide 2 cells. In addition, 74% of the identified proteins were predicted to have at least one SUMOylation site. The data presented here shed light on the crucial process of protein sumoylation in Bombyx mori.
A Study of Sentiment and Trend Analysis Techniques for Social Media Content

The social media networks have evolved rapidly and people frequently use these services to communicate with others and express themselves by sharing opinions, views, ideas etc. on different topics. The social media trend analysis is generally carried out by sifting the corresponding or interlinked events discussed on social media websites such as Twitter, Facebook etc. The fundamental objective behind such analyses is to determine the level of criticality with respect to criticism or appreciation described in the comments, tweets or blogs. The trend analysis techniques can also be systematically exploited for opinion making among the masses at large. The results of such analyses show how people think, assess, orate and opine about different issues. This paper primarily focuses on the trend detection and sentiment analysis techniques and their efficacy in the contextual information. We further discuss these techniques which are used to analyze the sentiments expressed within a particular sentence, paragraph or document etc. The analysis based on sentiments can pave way for automatic trend analysis, topic recognition and opinion mining etc. Furthermore, we can fairly estimate the degree of positivity and negativity of the opinions and sentiments based on the content obtained from a particular social media.
Macromomentum: Evidence of Predictability in International Equity Markets

This study examines momentum and reversals in portfolios of international stock indices. The results indicate strong momentum up to a year following the portfolio formation date and significant reversals in the subsequent two years. While momentum is driven mostly by predictability within equity markets, reversals are at least partly due to a continuing decline in stock prices in response to past currency appreciation. These patterns seem to be related to misreaction to news about macroeconomic conditions, not corporate earnings. Overall, our results demonstrate the pervasiveness of momentum and reversals and provide support for behavioral theories.
Mouse models with human immunity and their application in biomedical research

• Introduction • Recipient mouse selection for engrafting xenogeneic human haematopoietic and immune cells • Pre‐conditioning regimens for establishing humanized mice ‐ Depletion of innate immune cells in recipient mice ‐ Implication of human growth factors ‐ Making ‘space’ for donor cells by irradiation or chemical agents • Transplantation strategies to establish humanized mice ‐ Humanized mice achieved by directly implanting mature human immune cells ‐ Humanized mice established by engrafting human HSCs ‐ Humanized mice achieved by engrafting human thymus and HSCs • A proposed ideal humanized mouse model • Applications of humanized mouse models in biomedical research ‐ Ontogeny of human HSCs and immunocell lineages ‐ Autoimmune diseases ‐ Virus infections ‐ Immune response or tolerance to allografts or xenografts ‐ Anti‐tumour immune response • Conclusions and perspectives
Should the Elements of Diagrams Be Rendered in 3D

To some extent the utility of a diagram depends on how effectively the information can be perceived. We have applied the structural object recognition theory of Biederman to the problem of constructing node-link diagrams. According to geon theory, as objects are perceived they are decomposed into 3D primitives called geons, together with the skeleton structure connecting them. This work evaluates diagrams using geon-like primitives. Results of two experiments are reported. These show that diagrams constructed of 3D components can be visually analyzed more rapidly, with fewer errors, and can be remembered better in comparison with equivalent 2D silhouette diagrams.
A Workbench for Anytime Reasoning by Ontology Approximation - With a case study on instance retrieval

Reasoning is computationally expensive. This is especially true for reasoning on the Web, where data sets are very large and often described by complex terminologies. One way to reduce this complexity is through the use of approximate reasoning methods which trade one computational property (eg. quality of answers) for others, such as time and memory. Previous research into approximation on the Semantic Web has been rather ad-hoc, and we propose a framework for systematically studying such methods. We developed a workbench which allows the structured combination of different algorithms for approximation, reasoning and measuring in one single framework. As a case-study we investigate an incremental method for instance retrieval through ontology approximation, and we use our workbench to study the computational behaviour of several approximation strategies.
Study on Heartbeat Information Acquired from Pressure Cushion Based on Body Sensor Network

Traditional Chinese medicine and Western medicine have proved that heartbeat information has a close relationship with human's health and emotion. The feasibility of acquisition heartbeat information associated with emotion and health states based on body sensor network is a hot research topic. This paper proposes a novel method to collect heartbeat information from pressure cushion. Heart rate, respiratory rate and respiratory heart rate can be extracted from the change of pressure with wavelet analysis in our proposed method. We are able to extract above mentioned three parameters more accurately through several experiments, including children, elderly people and women.
Regularized Channel Inversion for Multiple-Antenna users in Multiuser MIMO Downlink

Channel inversion is one of the simplest techniques for multiuser downlink systems with single-antenna users. In this paper, we extend the regularized channel inversion technique developed for the single-antenna user case to multiuser multiple- input multiple-output (MIMO) channels with multiple-antenna users. We first employ the multiuser preprocessing to project the multiuser signals near the null space of the unintended users based on the MMSE criterion, and then the single-user preprocessing is applied to the decomposed MIMO interference channels. In order to reduce the complexity, we focus on non- iterative solutions for the multiuser transmit beamforming and use a linear receiver based on an MMSE criterion. Simulation results show that the proposed scheme outperforms existing joint iterative algorithms in most multiuser configurations.
Living with an alcoholic partner: Problems faced and coping strategies used by wives of alcoholic clients

Background: Alcoholism is considered as a major health as well as a social problem. Often the family members of alcoholics suffer intense psychological, physical and social trauma due to the core drinking problem of the family member. Most deeply affected are the wives of alcoholics. Aim: The present descriptive study aimed to investigate the problems faced and coping strategies used by the wives of alcoholics. Methodology: A total of 30 wives of alcoholic clients seeking treatment in De-addiction Centre were interviewed for the same. The problems were identified using a non standardized 17 item structured questionnaire while coping in wives of alcoholics was assessed using standardized tool. Results: The findings revealed the problems faced by alcoholics wives were in multiple domains viz. physical, psychological and social. While most highly reported were the emotional problems and least reported were the problems of physical violence. Coping strategies used by wives of alcoholics were reported in three major styles: engaged, tolerant and withdrawal. Conclusion and Recommendations: The problems faced by alcoholics have often wedged the attention in society yet finding and applying effective interventions to reduce the pain and suffering of being a partner of alcoholic is still a challenge.
Interacting Agents with Memory in Virtual Ecosystems

An agent-based modeling of virtual ecosystems is presented. A virtual ecosystem develops by plant competition according to biologically inspired rules and tends to reach stability. Virtual agents enter the ecosystem and perform actions that favor certain plant species and cause system instabilities. Agents liberate space for some plant species by eliminating the others, they take out old plants if an area is overcrowded, they seed plants, water them, etc. Agents synchronize by message passing to cover the area efficiently and not to interpenetrate their areas of influence. Each agent has a local memory of pending tasks. When a memory overflow arises the agent divide the pending tasks among the nearest agents.
A composite material qualification Method that results in cost, time, and risk reduction

One of the largest single regulatory hurdles for an airframe manufacturer, i.e., user, of polymer based advanced composite materials in certified aircraft applications, is to generate design allowables that will satisfy Federal Aviation Regulations (FARs). Due to the lack of a regulatory mechanism that encourages materials users to share data, historically each user has independently executed coupon level test plans and design allowable programs for specific materials - a costly and time consuming process. Design allowables for similar or identical materials have often been generated consecutively by several users as a routine part of their certification efforts, which has resulted in redundant costs to users, materials manufacturers and regulators. A new composite materials qualification methodology has been developed by members the Advanced General Aviation Technology Experiments (AGATE) consortium. Based on Military Handbook 17 (MIL-HBK-17) 2 guidelines, the AGATE Method describes a standardized coupon level material qualification test plan and statistical technique that yields lamina design allowables for a specific material system, such that allowables can be shared among multiple users without each user having to repeat the full qualification procedure. Once the original qualification database is completed and its resultant design allowables are approved for use by the FAA, each user needs only to perform a limited equivalency test plan to verify that their process yields properties that are equivalent to the original database.
Fiscal Discipline and Exchange Rate Regimes

This paper explores the implications of a new theory of price determination (due to Leeper, Woodford and Sims) for the maintenance of various exchange rate systems – crawling pegs, fixed pegs, and common currency areas. It shows that deeper monetary integration requires more fiscal discipline, especially if price stability is an objective; these monetary arrangements cannot be achieved by monetary policy alone, as conventional wisdom would seem to suggest. A particularly striking result is that a currency peg is simply not sustainable if fiscal surpluses are determined by an exogenous political process; maintenance of a fixed currency peg requires the government to guarantee fiscal solvency for any equilibrium sequence of prices (which Woodford calls a Ricardian Regime). Interestingly, the debt and deficit constraints that were written into the Maastricht Treaty, and will continue in the Stability Pact after EMU, are examples of the fiscal discipline that is required.
A Multimodal System for Nonverbal Human Feature Recognition in Emotional Framework

A correct recognition of nonverbal expressions is currently one of the most important challenges of research in the field of human computer interaction. The ability to recognize human actions could change the way to interact with machines in several environments and contexts, or even the way to live. In this paper, we describe the advances of a previous study finalized to design, implement and validate an innovative recognition system already developed by some of the authors. It was aimed at recognizing two opposite emotional conditions (resonance and dissonance) of a candidate to a job position interacting with the recruiter during a job interview. Results in terms of the accuracy, resonance rate, and dissonance rate of the three new optimized neural network-based (NN) classifiers are discussed. Comparison with previous results of three NN classifiers is also presented based on three single domains: facial, vocal and gestural.
Education in the 'Virtual' Community: Can beating Malware Man teach users about Social Networking Security?

Social Networks have become part of daily life for millions of people and by their very nature they encourage information sharing. 2011 was a year that saw numerous targeted "Spear Phishing" attacks in which it was clear that attackers gained knowledge about victims prior to carrying out their attacks. There is evidence that social media has been utilised as the source for this information so therefore it is more important than ever that users are educated against the risks. This paper starts by looking at the current threats and awareness strategies. It then describes the design and evaluation of an online game to help educate users. The game has a central 'Malware Man' character and a firewall which burns him if the player answers correctly. The success of the game was evaluated using an experiment with a group of participants who had played the game, and a control group who had not. 101 users participated in the study. The results suggest that the game was successful in educating users as the average percentage of correct answers was 77% for those who had played the game, compared to 55% for those who had not.