Miracle-dz/UniFAR-FTUs huggingface dataset:
Reducing control bit overhead for X-masking/X-canceling hybrid architecture via pattern partitioning

An X-masking scheme prevents unknown (X) values from shifting into an output response compactor, whereas an X-canceling MISR methodology allows X's to enter the compactor, but then cancels them out through selective XORing. However, both approaches require significantly high volume of the control bits to remove X values to generate X-free output signatures. This paper proposes a method to reduce the control bit overhead by combining X-masking and X-canceling methodologies and exploiting the fact that unknown values tend to have high correlation in the scan cells. In this paper, correlation is considered across whole patterns in order to enhance reuse of control bits. The proposed hybrid method of X-canceling and X-masking reduces test time without losing fault coverage. The experimental results show that the proposed method significantly reduces control bits and test time compared to a conventional X-canceling MISR methodology.
How the Use of PowerPoint Presentation Slides from Textbook Publishers is perceived by Accounting Students in Facilitating Learning Efficacy?

PowerPoint presentations have become a popular aid in educational delivery. As such, textbook publishers have increasingly incorporating PowerPoint slides as part of textbooks supplemental materials. However, the effectiveness of the slides in the classroom remains a question. This study fills the gap and investigates how students perceive publisher-provided PowerPoint slides in promoting successful learning. This study uses a survey and two experimental tests to understand and confirm students' responses to the use of the teaching media. The sample of the study consists of 28 students enrolled in the Principles of accounting course in Semester I, 2018, at Faculty of Economics and Business of Syiah Kuala University, Indonesia. The results show that students perceive PowerPoint is useful for effective learning. Several students who felt the lack of benefits from using this instructional technology are related to the use of English in PowerPoint slides. Therefore, we conducted a sensitivity test by giving students pre-test and post-test after the slides were translated into Indonesian. This process confirms the main results. However, one must be cautious in generalizing these findings because this study has limitations in sample size, and sample characteristics e.g. lacking in English, thus future research may benefit from addressing those limitations. Keywords—Textbook publishers; PowerPoint presentation; Teaching tools, Learning effectiveness, Accounting education.
State control of modular multilevel converters utilizing pole restraining

The modular multilevel converter (MMC) topology is characterized by excellent scalability. Converters with direct connection to high voltages in the range of several 100 kV can be built by stacking comparatively simple modules. The drawback of the technology is the single-phase structure, causing, among others, oscillations of the capacitor voltages which mainly depend on the AC currents. Therefore, dynamic control of MMC is still a challenge. A novel state-control approach is introduced using the pole-restraining control principle.
Remanence Decay Side-Channel: The PUF Case

We present a side-channel attack based on remanence decay in volatile memory and show how it can be exploited effectively to launch a noninvasive cloning attack against SRAM physically unclonable functions (PUFs) - an important class of PUFs typically proposed as lightweight security primitives, which use existing memory on the underlying device. We validate our approach using SRAM PUFs instantiated on two 65-nm CMOS devices. We discuss countermeasures against our attack and propose the constructive use of remanence decay to improve the cloning resistance of SRAM PUFs. Moreover, as a further contribution of independent interest, we show how to use our evaluation results to significantly improve the performance of the recently proposed TARDIS scheme, which is based on remanence decay in SRAM memory and used as a time-keeping mechanism for low-power clockless devices.
Battle over Media Choice: Multiplex Tensions in the Online Community of Wikipedia

Media choice theories conceptualize decisions people make when they are faced with communication media alternatives to fit a communicative need. In this paper we address two gaps in extant research on media choice. First, we show that media choices may be intimately intertwined with the questions of power. The second contribution comes from situating an online community as the focus of media choice research – a novel combination. We conducted an interpretive case study on how power is intermingled with the choice of Internet Relay Chat (IRC) in the Finnish Wikipedia. We found that IRC was viewed in starkly different ways by different actors. Moreover, the IRC was largely associated with the notions of power. In particular, it was related to accession and ability to influence decisionmaking in the community. One party perceived IRC as a useful and open channel for quick-tempo collaborations and informal interactions, while others saw it as an arena for “the elite” to scheme against “the proletariat”. Overall, IRC was a source of “multiplex tensions”: conflicts originating from communication being dispersed into multiple media and from different perceptions towards a medium. The study provides several important implications for theory and practice.
Impact Evaluation of Emergency Vehicle Preemption on Signalized Corridor Operation1

This study reports on a case study examining the impact of emergency vehicle preemption on closely spaced arterial traffic signals. The study was conducted on SR 26 a principal arterial and main thoroughfare connecting Interstate 65 with US 52 on the East side of Lafayette, Indiana. This study examined four coordinated intersections along SR 26 using seven preemption paths and three different transition algorithms (smooth, add, and dwell). The number of preempts in the simulation period varied from one to three preempts for equal simulation periods. The findings generally show that a single preemption call had minimal effect on the overall travel time and delay through the network. The results also indicate that the smooth transitioning algorithm performed the best with most scenarios and paths, for both the arterial and side streets. When multiple emergency vehicles preempt at closely spaced time intervals, the impact of preemption was more severe. For the network studied, the most severe impact observed on arterial travel time was an increase in the average arterial travel time on the order of 20-30 seconds. This study focused on emergency vehicle preemption but the general procedures described here could also be applied to railroad preemption or transit priority.
The ensemble of Naïve Bayes classifiers for hotel searching

The objective of the paper is to present a new ensemble of Naïve Bayes classifiers model for an application of hotel searching. The dataset were collected from 293 reviews of 15 hotels in Phuket. The main idea of the proposed model is to combine two models of Naïve Bayes classifiers with different feature selection techniques. The output of the searching model is a list of hotel names ranking by hotel probability related to user keywords. The searching performance of the ensemble model was compared with two classical searching methods: Boolean searching and Boyer-Moore searching. The results show that the ensemble of Naïve Bayes classifiers model provides the highest average rank_accuracy. In addition, the proposed model also takes the fastest time in searching when compared with the other techniques.
Using Neuroimaging to Predict Behavior: An Overview with a Focus on the Moderating Role of Sociocultural Context

How do we predict how an individual will behave in a particular situation? Across several decades, social scientists have identified many self-report measures that account for individual variability in behavior, yet a large percentage of the variance remains unaccounted for by these introspective reports (Armitage & Conner, 2001; O’Keefe, 2018). Recent advances in analytic approaches and computational tools have provided new, complementary avenues to investigate this difficult question. Non-invasive neuroimaging approaches (e.g., functional magnetic resonance imaging [fMRI], functional near infrared spectroscopy [fNIRS], and electroencephalography [EEG]) measure brain activity while participants view stimuli and make decisions, providing a powerful tool to capture objective measurements of individual differences during task performance (Berkman & Falk, 2013; Tompson, Lieberman, & Falk, 2015). Analytic tools for quantifying patterns of activation within and between brain regions further advance the power of neuroimaging approaches to predict how individuals will behave (Bassett & Sporns, 2017; Kriegeskorte, 2011), as well as how they will interact with one another, and how groups of individuals will make decisions. In short, the foundation of social neuroscience posits that measuring brain activity provides access to psychological processes and neural circuitry that may serve as the underlying mechanisms that explain individual differences in behavior. In this review, we first discuss evidence that demonstrates the association between brain activation and individual decisions and behaviors. Studies within the domains of health and consumer behaviors have identified a consistent set of brain regions associated with individual decisions and behaviors. These brain regions have been implicated in processing information about the reward value of choice and behavioral options (valuation) as well as processing social information about the mental states of others (mentalizing). Second, we discuss evidence that these same brain regions are also linked to aggregate behavior for groups of individuals. Third, we discuss evidence that these brain regions are associated with how individuals will behave in social interactions. Finally, we discuss evidence that the association between brain activation and behavior is moderated by social factors including social network position, culture, and socioeconomic status. Throughout, we highlight recent advances that leverage multivariate and network analysis approaches that emphasize different components of brain activity patterns to understand the neural mechanisms underlying social behavior.
A hybrid algorithm of source localization based on hyperbolic technique in WSN

Electromagnetic (EM) source localization has become a vital issue lately to improve civilian safety, increase the military security and mitigate the disaster effect. The localization is embedded in battle-field surveillance, traffic alert, emergency call 911 (E911), resource allocation and mitigation of disaster effect. The location of the emitter can be determined by bestowing its transmitted signal measured at an array of spatially separated receivers. Several methods have been developed for estimating the EM source location. These methods include Time of Arrival (TOA), Time Difference of Arrival (TDOA), Frequency Difference of arrival (FDOA), Angle of Arrival (AOA) and Received Signal Strength (RSS) of the transmitted emitter signal. Comparing all localization techniques, TDOA and FDOA localization techniques (hyperbolic) are one of the simplest and most cost effective. The sensors situated on an axis in two-dimensional scenario measuring the TDOA and FDOA of the emitting signal from a moving source can estimate its position and velocity from the intersection point of hyperbola, which is created from TDOA and FDOA non-linear equations set. However, the hyperbolas may not be intersected at a single point due to the non-linear localization equations set and measurement noise in wireless sensor network (WSN). It is therefore important to estimate a source position that minimizes its deviations from the actual position. In this paper, a hybrid method combined with maximum likelihood (ML) and genetic algorithm (GA) are proposed to determine the instantaneous position of the moving source by estimating the position and velocity based on hyperbolic techniques (TDOA and FDOA). Firstly ML is applied in the position and velocity localization data. Additionally, GA is implemented to acquire the globally best solution of localization parameters from non-linear equations set of ML solution. The results obtained confirmed that the proposed method achieved the theoretical lower bound for near to far-field with same and different velocity and different baseline of sensors in low to high Gaussian noise level. In this study, explicit solutions are provided by the proposed methods that are not achievable through the established methods in all cases.
Investigation into Aspects of Feedback and Gamification in Computer-Assisted Musical Instrument Tutoring

This thesis investigates how different variations of presentational performance feedback influences the motivation of a learner in a computer-assisted musical instrument tutoring context. Further, the thesis overviews methods to increase students’ engagement with the learning process. Positive and negative content balance in performance feedback is proposed through conducting user testing and evaluation. User testing was carried out using an online browser-based guitar tuition app developed for the purpose of this thesis. A custom-built application allowed full control over varying the balance of positive and negative content within performance feedback for different testing groups. Last experiment was aimed to find aspects of gamification to promote and encourage users to better themselves and to keep learning. A brief description of up-to-date technology used to design and develop the guitar tuition software product is described. Despite the results being inconclusive they appear to indicate that presenting negative feedback is detrimental to the learners’ motivation. Furthermore, gamifying the learning experience and introducing competitive nature of games into musical instrument tuition appear to increase learners’ engagement, and prevent the learner drifting into boredom.
Maximal Ol'shanski Semigroups Let G Be a Real Form for a Complex Lie Group G C . a Complex Ol'shanski Semi

In this article we show for simple complex groups G C that if a subsemigroup S contains a real form G such that G is not isolated in S , then S contains a minimal Ol'shanski semigroup and is contained in a maximal Ol'shanski semigroup. It follows in particular that maximal Ol'shanski semigroups are maximal semigroups.group in G C is one of the form ? (C) = exp(iC)G, where C is an Ad G-invariant convex cone in the Lie algebra g of G. These semigroups are noncommutative analogues of tube domains and play an important role in the representation theory of G ((13], 12]) and also arise in a variety of contexts of harmonic analysis on G ((5]). Their structure is presented in more detail in Section 1. When one tries to establish in a concrete situation that a certain semi-group is an Ol'shanski semigroup, it is generally much easier to show that the appropriate Ol'shanski semigroup is contained in the given semigroup than to show the reverse containment. This paper provides an important theoretical tool for showing the reverse containment in the case of simple groups: if a subsemi-group S contains a real form G of G C such that G is not isolated in S , then S contains a minimal Ol'shanski semigroup and is contained in a maximal Ol'shan-ski semigroup. The preliminary background is recalled in the rst two sections and the proof is given in Sections 3 and 4. Section 5 discusses some important consequences and applications of this result. It is a corollary of what is done here that in the context of simple groups maximal complex Ol'shanski semigroups are maximal semigroups, a fact rst established by Hilgert and Neeb 7, Chapter 8]. The proof given here relies heavily on their earlier work, but there is also a signiicant simplication. In particular, one no longer needs the theory of highest weight representations nor San Martin's theory of invariant control sets 17]. This not only makes the proof shorter and more accessible, but also enables the generalization given in this paper. For related results in the real analytic case, see 8].
Comptabilisation en juste valeur et stabilité fi nancière

Les prix de marché donnent des signaux appropriés susceptibles d’aider la prise de décision des investisseurs. Toutefois, en présence d’incitations faussées et de marchés illiquides, d’autres effets moins favorables introduisent une volatilité artifi cielle qui perturbe les décisions réelles. Dans un contexte de valorisation en valeur de marché, les variations des prix des actifs apparaissent immédiatement dans les bilans des intermédiaires fi nanciers et provoquent des réactions de leur part. Les banques et les intermédiaires fi nanciers ont toujours réagi aux évolutions de l’environnement économique, mais la valorisation en valeur de marché amplifi e et développe de leur part des réactions synchrones, aggravant ainsi les répercussions sur les marchés de capitaux.
Notes on Fluctuations and Correlation Functions in Holographic Renormalization Group Flows

We study the coupled equations describing fluctuations of scalars and the metric about background solutions of N=8 gauged supergravity which are dual to boundary field theories with renormalization group flow. For the case of a kink solution with a single varying scalar, we develop a procedure to decouple the equations, and we solve them in particular examples. However, difficulties occur in the calculation of correlation functions from the fluctuations, presumably because the AdS/CFT correspondence has not yet been properly implemented in the coupled scalar-gravity sector. Some new examples of correlators of operators dual to simpler uncoupled bulk scalars are given and are satisfactory. As byproducts of our study we make some observations relevant to the stability of domain walls in the brane-world scenario and to the Hamilton-Jacobi formulation of holographic RG flows.
Automatic segmentation of cell candidate regions in microscopy images based on an optimization algorithm

Circulating tumor cells (CTCs) is an informative biomarker which assists pathologists in early diagnosis and evaluating therapeutic effects of patients with malignant tumors. The blood from a cancer patient is analyzed by a microscope and a large number of pictures including many cells are generated for each case. Thus, analyzing them is time-consuming work for pathologists, and misdiagnosis may happen since the diagnosis of CTCs tends to depend on the individual skill of pathologist. In this paper, we propose a method which detects cell candidate regions in microscopy images automatically to make quantitative analysis possible by computer. Our proposed method consists of three steps. In the first step, we extract initial cell candidate regions in microscopy images based on the saliency map. In the second step, we choose non-single cell regions from the initial candidates based on the SVM algorithm. In the third step, we separate connected regions into single cell regions based on the branch and bound algorithm. We demonstrated the effectiveness of our proposed method using 540 microscopy images and we achieved a true positive rate of 99.04[%] and a false positive rate of 3.95[%].
A networked device for reproducing multisensory kissing

Kissing is a universal and essential interaction in human communication, yet we are not able to transmit and reproduce the multisensory sensations of kissing over digital communication networks. A networked kissing device is proposed to sense the lip pressure of users and to produce accurate force feedback to simulate kissing sensations. The system is designed to engage multiple sensory modalities during user interaction, including touch, smell, video and voice. This device can be used to augment digital communication by transmitting intimate touch sensations between human and human remotely, or between human and virtual agents.
The Trypanosoma brucei signal recognition particle lacks the Alu-domain-binding proteins: purification and functional analysis of its binding proteins by RNAi

Trypanosomes are protozoan parasites that have a major impact on human health and that of livestock. These parasites represent a very early branch in the eukaryotic linage, and possess unique RNA processing mechanisms. The trypanosome signal recognition particle (SRP) is also unusual in being the first signal recognition particle described in nature to be comprised of two RNA molecules, the 7SL RNA and a tRNA-like molecule. In this study, we further elucidated the unique properties of this particle. The genes encoding three SRP proteins (SRP19, SRP72 and SRP68) were identified by bioinformatics analysis. Silencing of these genes by RNAi suggests that the SRP-mediated protein translocation pathway is essential for growth. The depletion of SRP72 and SRP68 induced sudden death, most probably as a result of toxicity due to the accumulation of the pre-SRP in the nucleolus. Purification of the trypanosome particle to homogeneity, by TAP-tagging, identified four SRP proteins (SRP72, SRP68, SRP54 and SRP19), but no Alu-domain-binding protein homologs. This study highlights the unique features of the trypanosome SRP complex and further supports the hypothesis that the tRNA-like molecule present in this particle may replace the function of the Alu-domain-binding proteins present in many eukaryotic SRP complexes.
A hybrid evolutionary approach for solving constrained optimization problems over finite domains

A novel approach for the integration of evolution programs and constraint-solving techniques over finite domains is presented. This integration provides a problem-independent optimization strategy for large-scale constrained optimization problems over finite domains. In this approach, genetic operators are based on an arc-consistency algorithm, and chromosomes are arc-consistent portions of the search space of the problem. The paper describes the main issues arising in this integration: chromosome representation and evaluation, selection and replacement strategies, and the design of genetic operators. We also present a parallel execution model for a distributed memory architecture of the previous integration. We have adopted a global parallelization approach that preserves the properties, behavior, and fundamentals of the sequential algorithm. Linear speedup is achieved since genetic operators are coarse grained as they perform a search in a discrete space carrying out arc consistency. The implementation has been tested on a GRAY T3E multiprocessor using a complex constrained optimization problem.