Software for Wearable Devices: Challenges and Opportunities

Wearable devices are a new form of mobile computer system that provides exclusive and user-personalized services. Wearable devices bring new issues and challenges to computer science and technology. This paper summarizes the development process and the categories of wearable devices. In addition, we present new key issues arising in aspects of wearable devices, including operating systems, database management system, network communication protocol, application development platform, privacy and security, energy consumption, human-computer interaction, software engineering, and big data.Comment: 6 pages, 1 figure, for Compsac 201

Output regulation of nonlinear singularly perturbed systems

AbstractIn this paper, the state feedback regulator problem of nonlinear singularly perturbed systems is discussed. It is shown that, under standard assumptions, this problem is solvable if and only if a certain nonlinear partial differential equation is solvable. Once this equation is solvable, a feedback law which solves the problem can easily be constructed. The developed control law is applied to a nonlinear chemical process

AntFuzzer: A Grey-Box Fuzzing Framework for EOSIO Smart Contracts

In the past few years, several attacks against the vulnerabilities of EOSIO smart contracts have caused severe financial losses to this prevalent blockchain platform. As a lightweight test-generation approach, grey-box fuzzing can open up the possibility of improving the security of EOSIO smart contracts. However, developing a practical grey-box fuzzer for EOSIO smart contracts from scratch is time-consuming and requires a deep understanding of EOSIO internals. In this work, we proposed AntFuzzer, the first highly extensible grey-box fuzzing framework for EOSIO smart contracts. AntFuzzer implements a novel approach that interfaces AFL to conduct AFL-style grey-box fuzzing on EOSIO smart contracts. Compared to black-box fuzzing tools, AntFuzzer can effectively trigger those hard-to-cover branches. It achieved an improvement in code coverage on 37.5% of smart contracts in our benchmark dataset. AntFuzzer provides unified interfaces for users to easily develop new detection plugins for continually emerging vulnerabilities. We have implemented 6 detection plugins on AntFuzzer to detect major vulnerabilities of EOSIO smart contracts. In our large-scale fuzzing experiments on 4,616 real-world smart contracts, AntFuzzer successfully detected 741 vulnerabilities. The results demonstrate the effectiveness and efficiency of AntFuzzer and our detection p

THE CHARACTERISTICS OF STRIDE LEG GROUND REACTION FORCE BETWEEN DIFFERENT STRIDE TVPES BASEBALL PITCHERS WHILE PITCHING

The purpose of current study was to compare the ground reaction forms (GRF) of the stride leg in baseball pitchers using two different pitching stride techniques. Fourteen college pitchers volunteered as participants and made maximum effort pitches on an indoor mound toward a 8 m away target. The ball velocity were measured by a radar gun, the GRF were measured by a forceplate, and the trajectory of pelvis center were measured by a motion analysis system to classify pitcher's strides as tall-and-fall (TF) or dip-and-drive (DD). There were no significant difference between two groups in ball velocity and stride leg GRF during pitching, and the ball velocity were significantly correlated with the vertical GRF of stride leg at ball release in TF group. It suggested that the different pitching technique might be used for different stride types

Generation of novel high quality HMW-GS genes in two introgression lines of Triticum aestivum/Agropyron elongatum

<p>Abstract</p> <p>Background</p> <p>High molecular weight glutenin subunits (HMW-GS) have been proved to be mostly correlated with the processing quality of common wheat (<it>Triticum aestivum</it>). But wheat cultivars have limited number of high quality HMW-GS. However, novel HMW-GS were found to be present in many wheat asymmetric somatic hybrid introgression lines of common wheat/<it>Agropyron elongatum</it>.</p> <p>Results</p> <p>To exploit how these new subunits were generated, we isolated HMW-GS genes from two sib hybrid lines (II-12 and 11-4-6) and compared them with those from their parents. The result shows that two genes of hybrid (<it>H11-3-3 </it>and <it>H11-4-3</it>) are directly introgressed from the donor parent <it>Agropyron elongatum</it>; one hybrid gene (<it>H1Dx5</it>) comes from point mutation of a parental wheat gene (<it>1Dx2.1</it>); two other hybrid genes (<it>H1By8 </it>and <it>H1By16</it>) are likely resulting from unequal crossover or slippage of a parental wheat gene (<it>1By9.1</it>); and the sixth novel hybrid gene (<it>H1Dy12</it>) may come from recombination between two parental genes.</p> <p>Conclusion</p> <p>Therefore, we demonstrate that novel HMW-GS genes can be rapidly created through asymmetric somatic hybridization in a manner similar with the evolution mechanism of these genes supposed before. We also described gene shuffling as a new mechanism of novel HMW-GS gene formation in hybrids. The results suggest that asymmetric somatic hybridization is an important approach for widening HMW-GS genebank of wheat quality improvement.</p

Improving WalkSAT for Random 3-SAT Problems

Stochastic local search (SLS) algorithms are well known for their ability to efficiently find models of random instances of the Boolean satisfiability (SAT) problems. One of the most famous SLS algorithms for SAT is called WalkSAT, which has wide influence and performs well on most of random 3-SAT instances. However, the performance of WalkSAT lags far behind on random 3-SAT instances equal to or greater than the phase transition ratio. Motivated by this limitation, in the present work, firstly an allocation strategy is introduced and utilized in WalkSAT to determine the initial assignment, leading to a new algorithm called WalkSATvav. The experimental results show that WalkSATvav significantly outperforms the state-of-the-art SLS solvers on random 3-SAT instances at the phase transition for SAT Competition 2017. However, WalkSATvav cannot rival its competitors on random 3-SAT instances greater than the phase transition ratio. Accordingly, WalkSATvav is further improved for such instances by utilizing a combination of an improved genetic algorithm and an improved ant colony algorithm, which complement each other in guiding the search direction. The resulting algorithm, called WalkSATga, is far better than WalkSAT and significantly outperforms some previous known SLS solvers on random 3-SAT instances greater than the phase transition ratio from SAT Competition 2017. Finally, a new SAT solver called WalkSATlg, which combines WalkSATvav and WalkSATga, is proposed, which is competitive with the winner of random satisfiable category of SAT competition 2017 on random 3-SAT problem