Miracle-dz/UniFAR-FTUs huggingface dataset:
A Perspective on Test Methodologies for Supervised Machine Learning Accelerators

Neural Network (NN) accelerators are essential in many emerging applications e.g., autonomous systems in making mission-critical decisions, health-care solutions to assist with diagnoses, etc. Any soft or hard failure during operation can potentially have catastrophic consequences in many of these applications. For instance, inaccurate classification during object recognition and tracking in autonomous vehicles can lead to crashes and subsequent injuries to the passengers. Therefore, testing Neural Network accelerators to ensure reliability and integrity of the underlying hardware is a crucial task to ensure the functionality, especially the ones that are used in mission-critical applications. Conventional functional, stuck-at and delay tests are not sufficient to characterize the ML systems since they face new test and validation challenges. This paper is aimed to provide a perspective on new test requirements and design for test techniques to cover ML features and detect various type of faults in NN accelerator. We discuss First-In-First-Out (FIFO) and Scratchpad based neural network hardware accelerators and propose test methods to detect the faults as well as fault location in different modules of the accelerator including MAC unit, Activation function module, and Processing Element (PE) registers.
A stigmergetic method based on vector pheromone for target search with swarm robots

ABSTRACT Stigmergy is a common social network mechanism in nature, which allows individuals to achieve effective coordination through the environment, and has shown some successful applications on robotic systems. This paper proposes a stigmergetic target search method based on vector pheromone for swarm robots. Robots generate vector pheromones according to the target signal and release them to the environment for other robots to read, so as to achieve the indirect transfer of information. The method is extended from our previous work which has some shortcoming especially in the updating process of pheromones. This paper improves the previous search method by designing a hybrid pheromone updating rule to achieve more efficient and accurate information exchange. Moreover, the improved search method contains a robot navigation algorithm and a pheromone map building algorithm for guiding robots’ motion and building the pheromone map. Numerical experiments are performed to compare the performance of the improved method with the previous one. Results show that the improved method can enhance the robot’s efficiency and success rate in finding the static and dynamic targets. Meanwhile, it can also improve the speed of map building and the accuracy of the pheromone map.
Securing Sensitive Digital Data Techniques

This paper identifies the correct and wrong approaches of securing digital data. It also proposes further ways of increasing the overall security of data transfer and storage. The variety of data can be encrypted either for comparison only purposes or for further active reuse and update, which implies the need of having a different approach when processing the data flow. Several effective models and techniques of encrypting sensitive digital information are presented in this paper, that excludes all reviewed bad practices.
ALTO for Querying LMAP Results

In the context of Large-Scale Measurement of Broadband Performance (LMAP), measurement results are currently made available to the public either at the finest granularity level (e.g. as a list of results of all individual tests), or in a very high level human- readable format (e.g. as PDF reports). This document argues that there is a need for an intermediate way to provide access to large- scale network measurement results, flexible enough to enable querying of specific and possibly aggregated data. The Application-Layer Traffic Optimization (ALTO) Protocol, defined with the goal to provide applications with network information, seems a good candidate to fulfill such a role. Finally, we describe our methodology for analyzing the United States Federal Communication Commission's (FCC) Measuring Broadband America (MBA) dataset to derive required topology and cost maps suitable for consumption by an ALTO server.
Generating playful palettes from images

Playful Palettes are a recent innovation in how artists can mix, explore, and choose colors in a user interface that combines the benefits of a traditional media painter's palette with non-destructive capabilities of digital tools. We present a technique to generate a Playful Palette that best represents the colors found in an input image, allowing the artist to select colors from the image's gamut, while maintaining full editability of the palette. We show that our approach outperforms recent work in terms of how accurately the image gamut is reproduced, and we present an approximation algorithm that is an order of magnitude faster with an acceptable loss in quality.
A Holy Quran Reader/Reciter Identification System Using Support Vector Machine

Holy Quran Reader Identification is the process of identifying the reader or reciter of the Holy Quran based on several features in the corresponding acoustic wave. In this research, we build our own corpus, which contains 15 known readers of the Holy Quran. The Mel-Frequency Cepstrum Coefficients (MFCC) are used for the extraction of these features from the input acoustic signal. These MFCCs are the reader’s features matrix, which is used for recognition via Support Vector Machine (SVM) and Artificial Neural Networks (ANN). According to our experimental results, the Holy Quran Reader Identification System identifies the reader with 96.59% accuracy when using SVM, in contrast to accuracy of 86.1% when using ANN.
Performance Test Selection Using Machine Learning and a Study of Binning Effect in Memory Allocators

Performance testing is an essential part of the development life cycle that must be done in a timely fashion. However, checking for performance regressions in software can be timeconsuming, especially for complex systems containing multiple lengthy tests cases. The first part of this thesis presents a technique to performance test selection using machine learning. In our approach, we build features using information extracted from the previous software versions to train classifiers that assist developers in deciding whether or not to execute a performance test on a new version. Our results show that the classifiers can be used as a mechanism that aids test selection and consequently avoids unnecessary testing. The second part of this work investigates the binning effect on user-space memory allocators. First, we examine how binning events can be a source of performance outliers in Redis and CPython object allocators. Second, we implement a Pintool to detect the occurrence of binning on Python programs. The tool performs dynamic binary instrumentation on the interpreter and outputs information that helps developers in performing code optimizations. Finally, we use our tool to investigate the presence of binning in various widely used Python libraries.
Taking the web beyond the web : building cross-platform services using web CMS as a backend

Rajala, Sauli Taking the web beyond the web: building cross-platform services using web CMS as a backend Jyväskylä: University of Jyväskylä, 2019, 89 p. Information Systems, Master’s Thesis Supervisor: Semenov, Alexander This paper proposed a UI-framework, which can be used to create cross-platform service from existing web service. Special attention was paid to the user experience in the context of whole cross-platform service. This paper also proposed a new taxonomy for classifying native mobile applications and approaches to cross-platform development. The study was done using design science as research method, and the developed artifact was demonstrated with WordPress and React Native. Existing WordPress website was analyzed, and a part of the website was converted into mobile user interface. Then mobile application was developed with React Native. This led to cross-platform service with two separate platforms (website and native mobile application) using the same data and having the same functionalities. UI-framework was noticed to be functional but insufficient. For example, the user experience in the platform itself should be elaborated on in more details. The new taxonomies for mobile applications and cross-platform development approaches was noticed to be true in the demonstration application. However, when examined in broader scale, taxonomies were found to be insufficient. As conclusion it was noted that this kind of configuration of cross-platform service sets some limitations for both the backend and the mobile application itself. For example, the data should be in structured form in the website.
The penultimate deglaciation: protocol for Paleoclimate Modelling Intercomparison Project (PMIP) phase 4 transient numerical simulations between 140 and 127 ka, version 1.0

Abstract. The penultimate deglaciation (PDG, ∼138–128 thousand years before present, hereafter ka) is the transition from the penultimate glacial maximum (PGM) to the Last Interglacial (LIG, ∼129–116 ka). The LIG stands out as one of the warmest interglacials of the last 800 000 years (hereafter kyr), with high-latitude temperature warmer than today and global sea level likely higher by at least 6 m. Considering the transient nature of the Earth system, the LIG climate and ice-sheet evolution were certainly influenced by the changes occurring during the penultimate deglaciation. It is thus important to investigate, with coupled atmosphere–ocean general circulation models (AOGCMs), the climate and environmental response to the large changes in boundary conditions (i.e. orbital configuration, atmospheric greenhouse gas concentrations, ice-sheet geometry and associated meltwater fluxes) occurring during the penultimate deglaciation. A deglaciation working group has recently been set up as part of the Paleoclimate Modelling Intercomparison Project (PMIP) phase 4, with a protocol to perform transient simulations of the last deglaciation (19–11 ka; although the protocol covers 26–0 ka). Similar to the last deglaciation, the disintegration of continental ice sheets during the penultimate deglaciation led to significant changes in the oceanic circulation during Heinrich Stadial 11 (∼136–129 ka). However, the two deglaciations bear significant differences in magnitude and temporal evolution of climate and environmental changes. Here, as part of the Past Global Changes (PAGES)-PMIP working group on Quaternary interglacials (QUIGS), we propose a protocol to perform transient simulations of the penultimate deglaciation under the auspices of PMIP4. This design includes time-varying changes in orbital forcing, greenhouse gas concentrations, continental ice sheets as well as freshwater input from the disintegration of continental ice sheets. This experiment is designed for AOGCMs to assess the coupled response of the climate system to all forcings. Additional sensitivity experiments are proposed to evaluate the response to each forcing. Finally, a selection of paleo-records representing different parts of the climate system is presented, providing an appropriate benchmark for upcoming model–data comparisons across the penultimate deglaciation.
Bayesian optimization in effective dimensions via kernel-based sensitivity indices

A determining factor to the utility of optimization algorithms is their cost. A strategy to contain this cost is to reduce the dimension of the search space by detecting the most important variables and optimizing over them only. Recently, sensitivity measures that rely on the Hilbert Schmidt Independence criterion (HSIC) adapted to optimization variables have been proposed. In this work, the HSIC sensitivities are used within a new Bayesian global optimization algorithm in order to reduce the dimension of the problem. At each iteration, the activation of optimization variables is challenged in a deterministic or probabilistic manner. Several strategies for filling in the variables that are dropped out are proposed. Numerical tests are carried out at low number of function evaluations that confirm the computational gains brought by the HSIC variable selection and point to the complementarity of the variable selection and fill-in strategies.
Improving The SFA Algorithm by Employing Multi-Source Data

In recent years, discriminative learning methods have widely been used in various areas of Natural Language Processing (NLP). These methods achieve the best performance, when the set of training and testing samples have the same distribution. However, in many applications of NLP, the lack of labeled datasets for some domains is a serious challenge. In such conditions, we need to develop a model based on domains with rich labeled instances and apply it to the domain with no labeled instances. In this research, a method for sentiment classification of opinions into positive and negative groups, which represent the users' feelings, is offered based on multi-source transfer learning. The proposed method here employs Spectral Feature Alignment algorithm to adapt different domains. Furthermore, according to the Majority Voting, accuracy is assigned to classifications trained on different domains based on the Majority Voting Error. Ultimately, decisions are made for each classification based on the calculated error. The Amazon datasets for four different categories, each of which contains 1000 positive and 1000 negative samples, are exploited to train the proposed model. Meanwhile, each category includes unlabeled samples that are used to select pivot features. The accuracy values of 85.5%, 86.4%, 83.5% and 90.1% obtained for Electronics, DVD, Books and Kitchen domains respectively, show the effectiveness of the proposed method compared with similar methods.
Driving Performance Assessment Based on Accurate Position Tracking

A driving performance assessment (DPA) system has been proposed in this paper to evaluate drivers’ skills in training. The system is based on centimeter-level localization of the vehicles, thanks to differential BeiDou Navigation Satellite System (BDS). Given a vehicle’s dimensions, its envelopment has been discretized both temporally and spatially as binary images, while the training area is modeled as a grayscale image where the intensity denotes the penalty of the certain area in unit time. The performance index can be obtained from the summation of images along with time. Experiments have been conducted to demonstrate the accuracy of vehicle tracking and the effectiveness of the proposed assessment system.
Using point-of-view video prompting to teach algebraic equations to high school students with disabilities

The present study evaluated the effectiveness of point-of-view video prompting delivered via an iPad in teaching four participants with disabilities to solve algebraic equations that required use of the distributive property. Participants were taught to independently use the video software on an iPad that presented steps of the targeted skill. A multiple probe across participants design was used to evaluate the effects of the intervention on the percent of equations solved correctly and the percent of steps completed correctly. All participants learned to accurately solve the targeted algebraic equations following the introduction of intervention. In addition, participants’ skills generalized to a similar yet untaught equation type. Participants’ skills maintained at varying levels following treatment. Implications and limitations are discussed. INDEX WORDS: Video modeling, Video prompting, Point-of-view, Video-based instruction, Video-based teaching, Video-based intervention, Video instruction, Video tutorial, High-incidence disabilities, Math instruction, Algebra, Equations, Technology, iPad, Secondary students, High school, Total-task chaining, Task analysis, Imitation USING POINT-OF-VIEW VIDEO PROMPTING TO TEACH ALGEBRAIC EQUATIONS TO HIGH SCHOOL STUDENTS WITH DISABILITIES
Optical Character Recognition with Tesseract

Optical Character Recognition is the machine replication of human perusing. Electronic Conversion of examined pictures where picture can be type composed or printed content. It is executed utilizing Google's open source Optical Character Recognition programming called Tesseract. The OCR accepts picture as the information, gets content from that picture and afterward changes over it into whatever other language that the client needed. This framework can be helpful in different applications like banking, legitimate industry, explorers’ different ventures, and home and office robotization. It for the most part intended for individuals who are unfit to peruse any sort of content archives and to diminish the weight of information passage occupations. [4]
Reading as an Interactive Process.

This study examined the linguistic strategies of strong and weak readers in grades three and six within in the context of Rnmelhart's (1977) interactive model of the reading process. A linguistic prediction task was set up to investigate lupile use of orthographic constraints, syntactic redundancy, and syntactic ant1 semantic knowledge. A program was written for the IBM 5100 desk top computer so the prediction task could be presented as a progressive doze activity. The data were examined using inferential and descriptive statistics as well as by ccnstruting detailed protocols of individual performance. Contrary to prediction, inferential analyses of the data revealed no significant differences between groups of readers. Descr ptive statistics showed some of the problems underlying the application of inferential analyses to the data. Protocol examination, compering the performance of ideal readers with real readera, was the most revealing form of analysis as it showed the individual differences of children in using interactive processes in carrying out the language task. An important feature of this report, therefore, is the comparison between the types of information one obtains by statistical approaches as contrasted with that obtained from qualitative protocol analyses. Such a comparison reflects the current debate on quantitative versus qualitative analysis as recently described by Light and Allemer
PRE as a Service within Smart Grid City

In the context of Smart Grid Cities, legal obligations require that certain personal data must be stored in the long term and protected. To deal with confidentiality issues, we use the concept of Proxy Re-Encryption (PRE) which allows sharing encrypted data. We present the first implementation of the Chow’s algorithm, and propose an optimized instantiation thanks to elliptic curves. This is the first unidirectional algorithm with CCA security that does not rely on pairing, which guarantees its high performance. This allows its use in real conditions. We have implemented it in JavaScript for direct use in a web browser by the user. In order to be able to process the data asynchronously, we then define the notion of PREaaS (Proxy Re-Encryption as a Service) that also allows use in a service-oriented context.
Shape Optimization and Modular Discretization for the Development of a Morphing Wingtip

Better knowledge in the areas of aerodynamics and optimization has allowed designers to develop efficient wingtip structures in recent years. However, the requirements faced by wingtip devices can be considerably different amongst an aircraft’s flight regimes. Traditional static wingtip devices are then a compromise between conflicting requirements, resulting in less than optimal performance within each regime. Alternatively, a morphing wingtip can reconfigure leading to improved performance over a range of dissimilar flight conditions. Developed within this thesis, is a modular morphing wingtip concept that centers on the use of variable geometry truss mechanisms to permit morphing. A conceptual design framework is established to aid in the development of the concept. The framework uses a metaheuristic optimization procedure to determine optimal continuous wingtip configurations. The configurations are then discretized for the modular concept. The functionality of the framework is demonstrated through a design study on a hypothetical wing/winglet within the thesis.
A Novel Wavelet-DCT Feature for EEG-based Biometric Person Recognition

This work introduces a novel feature extraction method for biometric recognition using EEG data. In this method, the wavelet transform is performed first, then the logarithms of the resulting coefficients are computed followed by discrete cosine transform (DCT). Finally, the most dominant (usually the first) DCT coefficients of each wavelet band are used to form the feature vector for person recognition. The sensitivity of the proposed feature was investigated in both identification and verification scenarios. EEG data of only one electrode (Cz) from two publicly available databases were used for this analysis. Accuracies of 89.76% and 96.19% were obtained for the two databases investigated. The results indicate the clear strength of the proposed features in achieving comparable performances with much reduced number of electrodes when compared with similar systems from the published literatures.
Wolof: a grammatical sketch

Wolof is the main vernacular language of Senegal, where it also used as a vehicular language, spoken by most of the Senegalese people as one language of their repertoire. This language belongs to the northern branch of the Atlantic group of the Niger-Congo phylum, and seems relatively isolated in this branch. This grammatical sketch presents its major linguistic features of interest from a typological and areal perspective as follows: the main phonological features are presented in section (1). Sections (2) to (5) are dedicated to word categories and their morphology. This includes, a summary of the basic typological characteristics and word classes of the language (sec. 2), then a presentation of the noun class system, determiners, modifiers, and pronouns (sec. 3), derivation and compounding (sec. 4), and the verbal system (sec. 5). The last section (sec. 6) presents the clause and beyond, covering information structure, the basic clause structure, coordination and paratactic clause chaining, subordination, ending up with sentence patterns. Occasionally, (short-term) diachronic comparison is made to entlighten some problematic aspects of the contemporary Wolof. Wolof shares several morpho-syntactic features with other Atlantic languages (in particular those from the Northern branch excluding Mel languages), such as a noun class system, (remnants of) consonant alternation, a rich set of demonstratives based on spatial deixis, a large inventory of derivational (mostly verbal) suffixes and auxiliaries, a remarkable verbal morphology integrating focus and negation, and an SVO and head-modifier basic word order. This language also has no adjectives but many ideophones. Nevertheless, Wolof departs from other Atlantic languages in several respects. This language has undegone significative changes leading to simplifications or reductions but also to innovative restructurings, both producing some typologically rare features. Some aspects of this evolution are shared by other Atlantic languages but pushed here to remarquable extends without destroying the functionality of the original system.