Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhanced Differential Evolution using center-based sampling

The classical Differential Evolution (DE) has showed to perform efficiently in solving both benchmark functions and real-world problems. However, DE, similar to other evolutionary algorithms deteriorate in performance during solving high-dimensional problems. Opposition-based Differential Evolution (ODE) was introduced and, in general, has shown better performance comparing to classical DE for solving large-scale problems. In this paper, we propose an enhancement to ODE in order to improve its ability to solve large-scale problems more effectively. The proposed modified version of ODE is called Center-Based Differential Evolution (CDE) which utilizes the exact algorithm of ODE except replacing of opposite points with center-based individuals. This paper compares DE and ODE with the proposed algorithm, CDE. Furthermore, CDE with dynamic range (CDEd) will be compared to CDE with fixed range (CDEf). Experimental verifications are conducted on seven well-known shifted large-scale benchmark functions for dimensions of 100 and 500, including detailed parameter analysis for CDE. The shifted version of the functions ensures there is no bias towards the center of search space, in favor of CDE algorithm. The results clearly show that the CDE outperforms DE and ODE during solving large-scale problems, and also clarifies the superiority of CDEd to CDEf.
zxcvbn: Low-Budget Password Strength Estimation

For over 30 years, password requirements and feedback have largely remained a product of LUDS: counts of lowerand uppercase letters, digits and symbols. LUDS remains ubiquitous despite being a conclusively burdensome and ineffective security practice. zxcvbn is an alternative password strength estimator that is small, fast, and crucially no harder than LUDS to adopt. Using leaked passwords, we compare its estimations to the best of four modern guessing attacks and show it to be accurate and conservative at low magnitudes, suitable for mitigating online attacks. We find 1.5 MB of compressed storage is sufficient to accurately estimate the best-known guessing attacks up to 105 guesses, or 104 and 103 guesses, respectively, given 245 kB and 29 kB. zxcvbn can be adopted with 4 lines of code and downloaded in seconds. It runs in milliseconds and works as-is on web, iOS and Android.
Construction of a dimeric repressor: dissection of subunit interfaces in Lac repressor.

Formation of the lactose repressor tetramer is postulated to involve two subunit interfaces, one primarily contributing to monomer-monomer assembly to dimer and the second to dimer-dimer association to tetramer. The latter interface requires a heptad repeat of three leucines at the C-terminus of lac repressor that is presumed to form an abbreviated coiled-coil motif [Chakerian, A. E. , Tesmer, V. M. , Manly, S. P., Brackett, J. K. , Lynch, M. J., Hoh, J. T. , & Matthews, K. S. (1991) J. Biol. Chem. 266, 1371-1374; Alberti, S. , Oehler, S. , von Wilcken-Bergmann, B. , Krämer, H. , & Müller-Hill, B. (1991) New Biol. 3, 57-62; Chen, J., & Matthews, K. S. (1992) J. Biol. Chem. 267, 13843-13850]. To strengthen the dimer-dimer interface, this motif was extended by the addition of one and two leucine heptad repeat units to the C-terminus by site-specific insertion mutagenesis. The tetrameric products displayed operator and inducer affinity essentially indistinguishable from the wild-type repressor. In order to probe the effect of the elongated coiled-coil on assembly of the repressor tetramer, the other of the two postulated subunit interfaces was disrupted by introducing a point mutation (Y282D) that yields a monomeric protein in the wild-type background. Both elongated mutant repressors were able to assemble into dimeric species, apparently due to the strengthened subunit association at the C-terminal region compared to the wild-type repressor. These results further confirm the role of a coiled-coil structure in the formation of tetramer in the lac repressor. (ABSTRACT TRUNCATED AT 250 WORDS)
Dual-arm robot box taping with kinesthetic teaching

Recent advances in anthropomorphic, and dual-arm robots have led to an increased interest in bimanual manipulation. One of the advantages of bimaual manipulation is the feasibility to transfer human tasks into the robot, which robots can operate in either domestic or industrial settings. Although dual-arm robot resembles human fixture, high level planning for specific task is necessary to operate the robot. In this paper, bimanual manipulation with dual-arm robot in industrial setting is introduced and application of kinesthetic teaching in box taping process is described.
Information Retrieval System and challenges with Dataspace

The advance of technology has seen increase in applications that integrate new kinds of information, such as multimedia and scientific data, unstructured, semi-structured, structured or heterogeneous data being created and stored is exploding is collectively called “Dataspace”. Data being generated from various heterogeneous sources like, digital images, audio, video , online transactions, online social media , data from sensor nodes , click streams for different domains including, retails, medical , healthcare , energy, and day to day life utilities. Information Retrieval from heterogeneous information systems is required but challenging at the same as data is stored and represented in different data models in different information systems. Information integrated from heterogeneous data sources into single data source are faced upon by major challenge of information transformation were in different formats and constraints in data transformation are used in data integration for the purpose of integrating information systems, at the same is not cost effective.
Employee perceptions of BYOD in South Africa: Employers are turning a blind eye?

As mobile Information and Communication Technologies (ICTs) become greater entrenched in society and with the nature of work changing, more and more international organizations are embracing and/or considering formalizing the phenomenon of 'Bring Your Own Device' (BYOD). The gist of BYOD is the use of privately owned devices and software to access and work with organizational resources. There is however little that is known about the degree to which organizations in South Africa are embracing the BYOD phenomenon. In this paper, we explored how employees in organizations in South Africa perceive the use of their privately owned devices for work. The results from 61 employees suggest that there is a strong awareness of the BYOD concept among employees. Employees also appear to believe that although their employers are aware of the use of privately owned devices for work, the employers are reluctant to formally create BYOD organizational strategies. The findings suggest that the laxity of employers in South Africa to deal with the BYOD phenomenon as an issue of strategic importance could result in considerable security challenges for organizational data.
Detection of Sinusoidal Signals in Frequency Domain

Periodogram is a simple and efficient way to detect and estimate parameters of sinusoidal signals. In this paper, we evaluate the detection performance of the periodogram and its variants such as Bartlett, Welch methods, and a proposed Bartlett-based method. Performance evaluation through the receiver operating characteristics (ROCs) of the mentioned methods are presented and compared. Previous studies showed that, the standard periodogram used to give the best detection performance. In the present work, analytical derivation and simulation results showed that, the proposed method gives a better detection performance outperforming the standard periodogram at the expense of tolerable reduction of the frequency resolution
Detection of Toxoplasma gondii Oocysts in Water Sample Concentrates by Real-Time PCR

ABSTRACT PCR techniques in combination with conventional parasite concentration procedures have potential for the sensitive and specific detection of Toxoplasma gondii oocysts in water. Three real-time PCR assays based on the B1 gene and a 529-bp repetitive element were analyzed for the detection of T. gondii tachyzoites and oocysts. Lower sensitivity and specificity were obtained with the B1 gene-based PCR than with the 529-bp repeat-based PCR. New procedures for the real-time PCR detection of T. gondii oocysts in concentrates of surface water were developed and tested in conjunction with a method for the direct extraction of inhibitor-free DNA from water. This technique detected as few as one oocyst seeded to 0.5 ml of packed pellets from water samples concentrated by Envirocheck filters. Thus, this real-time PCR may provide a detection method alternative to the traditional mouse assay and microscopy.
Categorizing and ranking search engine's results by semantic similarity

An automatic method for text categorizing and ranking search engine's results by semantic similarity is proposed in this paper. We first obtain nouns and verbs from snippets obtained from search engine using Name Entity Recognition and part-of speech. A semantic similarity algorithm based on WordNet is proposed to calculate the similarity of each snippet to each of the pre-defined categories. A balanced similarity ranking method combined with Google's rank and timeliness of the pages is proposed to rank these snippets. Preliminary experiments with 500 labeled questions from TREC03 show that 72.7% are correctly categorized.
Improving the Exchange of Requirements and Specifications between Business Partners

Increasingly complex supplier-relationships dominate product development, independent of industries and products. Mostly the primary source of risks and later problems is insufficient coherence with requirements engineering methodology and collaboration between different business partners during the project. This article based on experiences from various industries and projects provides insight into how to effectively collaborate in requirements engineering. Methods and tools are one side of the medal, but true collaboration also means having a platform to effectively and efficiently exchange requirements, specifications and their entire change management across impacted stakeholders. The Requirements Interchange Format (RIF) has quickly moved forward over the past two years first in automotive and currently starting in domains such as medical and aerospace. This paper describes typical RE collaboration scenarios and what we recommend in order to mitigate risks and thus effectively manage complex supplier relationships. We will not “sell” any tool but rather indicate how RIF is applied in order to share, communicate and collaborate across different tools.
Web-based design and manufacturing support systems: Implementation perspectives

With the great progress of web technology in the past few years, many approaches have been proposed to implementing web-based systems for design and manufacturing. However, the implementation of the approaches and associated systems is not an easy task because design and manufacturing are normally sophisticated engineering operations. In this paper the authors present an engineering approach for implementing web-based design and manufacturing support systems. The implementation issues are critically discussed with an exemplar-a web-based bearing design support system developed by the authors. These issues include design information integration, remote execution of the systems, use of Java programming, client - server architecture, open computing and user interface design, and the human - computer interaction aspects.
Using Artificial Neural Networks and Support Vector Regression to Model the Lyapunov Exponent

Finding the salient patterns in chaotic data has been the holy grail of Chaos Theory. Examples of chaotic data include the fluctuations of the stock market, weather, and many other natural systems. Real world data has proven to be extremely difficult to predict due to it high dimensionality and the potential for noise. It has been shown that artificial neural networks have been able to accurately calculate the Lyapunov Exponent, a feature that determines the divergence of two initially close trajectories and thus chaos. A variation of the support vector machine called support vector regression is used in function approximation and applying this tool to chaotic data may yield another model that can also be used in the prediction of the Lyapunov Exponent. Since support vector machines have been found to arrive at a prediction much faster than the artificial neural network, it may prove to be the model to use in time sensitive applications.
Stimulus selection at different stages of paired-associate learning.

Ss learned paired associates with compound stimuli (word + nonsense). Transfer was tested to individual components after varying amounts of training on the compounds. Ss who were trained to a single perfect trial showed no more transfer to nonsense components than Ss trained to 4 of 8 correct responses to the compounds; however, Ss receiving 10 overtraining trials on compounds showed substantially more transfer to the nonsense components. Then a group of Ss was given training after learning a list of compound stimuli to criterion, but during the extended training other items were added so that the list was not mastered while the initial items were receiving overtraining. This group showed no more transfer to nonsense components than a group trained just to criterion. The data are generally consistent with the hypothesis that Ss actively select among stimulus aspects until the list is mastered, and then relax the selection of attention during overtraining. It can be accepted now that when stimuli of paired associates are complex, 5"s often learn pairs by associating the response with a part of the stimulus. Underwood (1963) reviewed several items of evidence and concluded that £s carry on a process of stimulus selection, thereby producing a disparity between the nominal stimulus (presented by E} and the functional stimulus (with which 5 associates the response). Since Underwood's review, further studies by Newman and Taylor (1963), Jenkins and Bailey (1964), Cohen and Musgrave (1964), and Houston (1964) all have provided further demonstrations that after learning a list of pairs with complex stimuli, there are cases in which 5" can give the correct response to one element of a stimulus compound but not to another.
Automatic segmentation of human ribcage from 3D medical dataset for diagnosis

Segmentation of human ribcage or bony thorax is essential for computer-aided biopsy or during any surgical procedures that requires removal of tumor from any region of the thoracic cavity. In this study, we have proposed an algorithm that will automatically segment the ribcage from CT dataset available from hospital and online resources. The images are pre-processed and a threshold is applied to the set of images containing the ribcage area. The images are further validated with various validation techniques and projected on a 3D platform, for a better understanding of the results obtained. The output will allow the treating physicians to find the shortest distance to insert needle from the outer surface of the body to the region of interest. It will also help in setting landmarks before proceeding for any major surgery.
BioCichlid: central dogma-based 3D visualization system of time-course microarray data on a hierarchical biological network

SUMMARY BioCichlid is a 3D visualization system of time-course microarray data on molecular networks, aiming at interpretation of gene expression data by transcriptional relationships based on the central dogma with physical and genetic interactions. BioCichlid visualizes both physical (protein) and genetic (regulatory) network layers, and provides animation of time-course gene expression data on the genetic network layer. Transcriptional regulations are represented to bridge the physical network (transcription factors) and genetic network (regulated genes) layers, thus integrating promoter analysis into the pathway mapping. BioCichlid enhances the interpretation of microarray data and allows for revealing the underlying mechanisms causing differential gene expressions. AVAILABILITY BioCichlid is freely available and can be accessed at http://newton.tmd. ac.jp/. Source codes for both biocichlid server and client are also available.
From physics to pharmacology?

Over the last 50 years there has been an explosion of biological data, leading to the realization that to fully explain biological mechanisms it is necessary to interpret them as complex dynamical systems. The first stage of this interpretation is to determine which components (proteins, genes or metabolites) of the system interact. This is usually represented by a graph or network. The behavior of this network can then be investigated using mathematical modeling. In vivo these biological networks show several remarkable (and seemingly paradoxical) properties including robustness, plasticity and sensitivity. Erroneous behavior of these networks is often associated with disease. Hence understanding the system-level properties can have important implications for the treatment of disease. Systems biology is an organized approach to quantitatively describe and elucidate the behavior of these complex networks. This review focuses on the progress and future challenges of a systems approach to biology.
A Question-Answering System Using Unit Estimation and Probabilistic Near-Terms IR

Our question-answering system incorporates several new methods. One is unit estimation, which is useful when the answer is a numerical expression and the question sentence does not include any unit expression. This method can be used to estimate a unit expression for the answer by using a statistical test and corpus data and thus improves the results for such questions. Another new method is called probabilistic near-terms information retrieval. This method enables us to use full-size documents in document retrieval without dividing documentsinto passages and is useful when the answer is not within the passage where relevant terms occur. We confirmed the effectiveness of the unit estimation by using a statistical test (a T-test) and found that the probabilistic near-terms information retrieval improved the performance in Task-1 and Task-2.
How to evaluate interaction between causes: a review of practices in cardiovascular epidemiology

Hallqvist J et al. (Institute of Environmental Medicine and Department of International Health and Social Medicine, Karolinska Institute, Stockholm, Sweden). How to evaluate interaction between causes: a review of practices in cardiovascular epidemiology (Review). J Intern Med 1996; 239: 377–82.
Partial-state stabilization and optimal feedback control

In this paper, we develop a unified framework to address the problem of optimal nonlinear analysis and feedback control for partial stability and partial-state stabilization. Partial asymptotic stability of the closed-loop nonlinear system is guaranteed by means of a Lyapunov function that is positive definite and decrescent with respect to part of the system state which can clearly be seen to be the solution to the steady-state form of the Hamilton-Jacobi-Bellman equation, and hence, guaranteeing both partial stability and optimality. The overall framework provides the foundation for extending optimal linear-quadratic controller synthesis to nonlinear-nonquadratic optimal partial-state stabilization. Connections to optimal linear and nonlinear regulation for linear and nonlinear time-varying systems with quadratic and nonlinear nonquadratic cost functionals are also provided. An illustrative numerical example is presented to demonstrate the efficacy of the proposed linear and nonlinear partial stabilization framework.
Image Classification Using Sparse Coding and Spatial Pyramid Matching

Recently, the Support Vector Machine (SVM) using Spatial Pyramid Matching (SPM) kernel has achieved remarkable successful in image classification. The classification accuracy can be improved further when combining the sparse coding with SPM. However, the existing methods give the same weight of patches of SPM at different levels. Clearly the discriminative powers of SPM at different levels are distinct and there are correlation relationships among the sparse coding bases vectors, which usually have negative influence on the classification accuracy. This paper assigns different weights to the patches at different levels of SPM, and then proposes a new spatial pyramid matching kernel. Furthermore, the Principle Component Analysis (PCA) is employed to reduce the dimension of the feature vectors in order to decrease correlation among vectors and speed up the SVM training process. The preprocessing can enhance the discriminative ability of the new kernel as well. Experiments carried out on Caltech101 and Caltech256 datasets show that the new SPM kernel outperforms the existing methods in terms of the classification accuracy. Index Terms - Sparse coding, Spatial pyramid matching, Support vector machine, Image classification.
HRank: A Path based Ranking Framework in Heterogeneous Information Network

Recently, there is a surge of interests on heterogeneous information network analysis. As a newly emerging network model, heterogeneous information networks have many unique features (e.g., complex structure and rich semantics) and a number of interesting data mining tasks have been exploited in this kind of networks, such as similarity measure, clustering, and classification. Although evaluating the importance of objects has been well studied in homogeneous networks, it is not yet exploited in heterogeneous networks. In this paper, we study the ranking problem in heterogeneous networks and propose the HRank framework to evaluate the importance of multiple types of objects and meta paths. Since the importance of objects depends upon the meta paths in heterogeneous networks, HRank develops a path based random walk process. Moreover, a constrained meta path is proposed to subtly capture the rich semantics in heterogeneous networks. Furthermore, HRank can simultaneously determine the importance of objects and meta paths through applying the tensor analysis. Extensive experiments on three real datasets show that HRank can effectively evaluate the importance of objects and paths together. Moreover, the constrained meta path shows its potential on mining subtle semantics by obtaining more accurate ranking results.