Reviewerly/exHarmony huggingface dataset:
ATM Cash Flow Prediction and Replenishment Optimization with ANN

ATMs are physical interaction points between financial institutions and real customers.Storing physical cash causes renouncing to get interested.On the other hand, customer satisfaction requires to store the necessary cash amount.This concern becomes even more critical for countries having high-interest rate and overnight interest rates are higher.In this paper, we will show that daily cash withdrawals are predictable and we will propose a cost function for replenishment optimization.Experiments show that proposed model decrease idle balance dramatically.
The Danger of Testing by Selecting Controlled Subsets, with Applications to Spoken-Word Recognition

When examining the effects of a continuous variable x on an outcome y, a researcher might choose to dichotomize on x, dividing the population into two sets-low x and high x-and testing whether these two subpopulations differ with respect to y. Dichotomization has long been known to incur a cost in statistical power, but there remain circumstances in which it is appealing: an experimenter might use it to control for confounding covariates through subset selection, by carefully choosing a subpopulation of Low and a corresponding subpopulation of High that are balanced with respect to a list of control variables, and then comparing the subpopulations' y values. This "divide, select, and test" approach is used in many papers throughout the psycholinguistics literature, and elsewhere. Here we show that, despite the apparent innocuousness, these methodological choices can lead to erroneous results, in two ways. First, if the balanced subsets of Low and High are selected in certain ways, it is possible to conclude a relationship between x and y not present in the full population. Specifically, we show that previously published conclusions drawn from this methodology-about the effect of a particular lexical property on spoken-word recognition-do not in fact appear to hold. Second, if the balanced subsets of Low and High are selected randomly, this methodology frequently fails to show a relationship between x and y that is present in the full population. Our work uncovers a new facet of an ongoing research effort: to identify and reveal the implicit freedoms of experimental design that can lead to false conclusions.
Current Situation and Discussion of Teachers’ Information Literacy in the Era of "Education Informatization 2.0"

China's education informationization has entered a new stage of educational informationization 2.0 which integrates innovation. Based on the analysis of the connotation of educational informatization 2.0, this paper points out the importance of improving teachers' information literacy. In view of the problems existing in the current situation of teachers’ overall information literacy, this paper puts forward some effective strategies to improv teachers' information literacy and integrate information technology into educational reform, such as fostering teachers’ correct educational development concept, creating an information environment conducive to promoting teachers' information literacy, changing training methods and teachers’ learning methods, etc. It highlights the role of educational informatization 2.0 in promoting educational modernization.
Scalable hybrid and ensemble heuristics for economic virtual resource allocation in cloud and fog cyber-physical systems

With the advent of cloud computing, a cost-effective and reliable choice to employ IT infrastructure, the cyber-physical systems (CPS) are transforming into loosely coupled cloud and fog CPS. The sensor information from physical processes at CPS is continuously processed by fog computing nodes and is forwarded for advanced data analytics offered as a service from the cloud. The computation offloaded by fog devices are initiated as Virtual Machines (VMs) in the cloud data center. The effective placement of these VMs into minimum Physical Machines (PMs) involves economic and environmental issues. Recent research works signify the use of First-Fit Decreasing (FFD) based heuristic techniques to address this NP-Hard problem as a vector bin-packing problem. In this research work, we present a set of hybrid heuristics and an ensemble heuristic to improve the solution quality. The simulation results show that the proposed heuristics are highly scalable and economical in comparison with the individual heuristic-based approaches.
Current Pass Optimized Symmetric Pass Gate Adiabatic Logic for Cryptographic Circuits

We propose a new adiabatic logic for cryptographic circuits, called as the Current Pass Optimized Symmetric Pass Gate Adiabatic Logic (CPO-SPGAL). The proposed circuit realizes a flat current waveform by considering the current path. The simulation results demonstrate that the proposed circuit can reduce the current fluctuation by approximately 84% and reduce the energy consumption fluctuation by approximately 79% as compared to the existing SPGAL circuits. This shows that it is more resistant to differential power analysis attacks than conventional circuits.
IoT Çağında Güvenlik Tehditleri ve Çözümleri Üzerine Bir Araştırma

Internet of Things (IoT) is rapidly developing and glamorous technology in which machines and devices are connected and interacted with each other via Internet anywhere anytime.This technology, which brings advantages, facilities and efficiency in many areas from city management to smart buildings, from health-care to industry, from energy to agriculture, etc. has also brought numerous challenges in terms of security.IoT is vulnerable to various types of attacks, malfunctions and misuses due to these challenges reasoning such as resource limitations, heterogeneity, lack of standardization, mobility, architecture.In this paper, we present the state of art for cyber security issues in IoT.We provide a comparison for IoT security in different perspectives including threats, vulnerabilities and some countermeasures.We give some recommendations on the precautions and countermeasures for cyber security issues in IoT.
A Generic Multifactor Authenticated Key Exchange with Physical Unclonable Function

We study how to generally construct a PUF -based multifactor authenticated key exchange ( MAKE ) protocol from any secure password-based authenticated key exchange protocol. We newly consider a new setting in which a user holding a PUF -embedded device desires to perform an authenticate key exchange through multifactor authentication factors (password, biometrics, secret). Our construction is the first PUF -based general MAKE construction. By applying a PUF in a device, our MAKE construction is still secure even if all authentication factors are totally compromised. Our construction is the first PUF -based generic MAKE protocol requiring additional three communication flows without any public key based primitives such as signature.
Reinforcement Learning with Deep Quantum Neural Networks

The advantage of quantum computers over classical computers fuels the recent trend of developing machine learning algorithms on quantum computers, which can potentially lead to breakthroughs and new learning models in this area.The aim of our study is to explore deep quantum reinforcement learning (RL) on photonic quantum computers, which can process information stored in the quantum states of light.These quantum computers can naturally represent continuous variables, making them an ideal platform to create quantum versions of neural networks.Using quantum photonic circuits, we implement Q learning and actor-critic algorithms with multilayer quantum neural networks and test them in the grid world environment.Our experiments show that 1) these quantum algorithms can solve the RL problem and 2) compared to one layer, using three layer quantum networks improves the learning of both algorithms in terms of rewards collected.In summary, our findings suggest that having more layers in deep quantum RL can enhance the learning outcome.
Sensorless control of PMSM using an adaptively tuned SCKF

This study reports the application of an adaptively tuned square-root Cubature Kalman filter (SCKF) for the speed and position estimation of a permanent magnet synchronous motor (PMSM) drive. The proposed estimator is observed to exhibit improved noise rejection characteristics as compared to the hitherto widely applied extended Kalman filter (EKF) observer. A third degree spherical–radial cubature rule is used in the Cubature Kalman filter (CKF) to numerically compute the multivariate moment integrals of the general Bayesian estimation equation. CKF is a non-linear filter which avoids linearisation and the associated errors. The realisation of CKF using the square-root algorithm results in numerical stability, as with the realisation of EKF using the square-root algorithm. Simulation results are presented for a three-phase inverter-fed PMSM, along with the experimental results. The estimator and the control algorithms are realised on the MATLAB real-time environment, interfaced with the hardware using the National Instruments data acquisition system NI PCI-6221.
$$\textsc {Wys}^\star $$ : A DSL for Verified Secure Multi-party Computations

Secure multi-party computation (MPC) enables a set of mutually distrusting parties to cooperatively compute, using a cryptographic protocol, a function over their private data. This paper presents $$\textsc {Wys}^\star $$ , a new domain-specific language (DSL) for writing mixed-mode MPCs. $$\textsc {Wys}^\star $$ is an embedded DSL hosted in F $$^\star $$ , a verification-oriented, effectful programming language. $$\textsc {Wys}^\star $$ source programs are essentially F $$^\star $$ programs written in a custom MPC effect, meaning that the programmers can use F $$^\star $$ 's logic to verify the correctness and security properties of their programs. To reason about the distributed runtime semantics of these programs, we formalize a deep embedding of $$\textsc {Wys}^\star $$ , also in F $$^\star $$ . We mechanize the necessary metatheory to prove that the properties verified for the $$\textsc {Wys}^\star $$ source programs carry over to the distributed, multi-party semantics. Finally, we use F $$^\star $$ 's extraction to extract an interpreter that we have proved matches this semantics, yielding a partially verified implementation. $$\textsc {Wys}^\star $$ is the first DSL to enable formal verification of MPC programs. We have implemented several MPC protocols in $$\textsc {Wys}^\star $$ , including private set intersection, joint median, and an MPC-based card dealing application, and have verified their correctness and security.
Orchestrating Layered Attestations

We present Copland, a language for specifying layered attestations. Layered attestations provide a remote appraiser with structured evidence of the integrity of a target system to support a trust decision. The language is designed to bridge the gap between formal analysis of attestation security guarantees and concrete implementations. We therefore provide two semantic interpretations of terms in our language. The first is a denotational semantics in terms of partially ordered sets of events. This directly connects Copland to prior work on layered attestation. The second is an operational semantics detailing how the data and control flow are executed. This gives explicit implementation guidance for attestation frameworks. We show a formal connection between the two semantics ensuring that any execution according to the operational semantics is consistent with the denotational event semantics. This ensures that formal guarantees resulting from analyzing the event semantics will hold for executions respecting the operational semantics. All results have been formally verified with the Coq proof assistant.
Sparse Nonlinear Feature Selection Algorithm via Local Structure Learning

In this paper, we propose a new unsupervised feature selection algorithm by considering the nonlinear and similarity relationships within the data. To achieve this, we apply the kernel method and local structure learning to consider the nonlinear relationship between features and the local similarity between features. Specifically, we use a kernel function to map each feature of the data into the kernel space. In the high-dimensional kernel space, different features correspond to different weights, and zero weights are unimportant features (e.g. redundant features). Furthermore, we consider the similarity between features through local structure learning, and propose an effective optimization method to solve it. The experimental results show that the proposed algorithm achieves better performance than the comparison algorithm.
A pointer location algorithm for computer visionbased automatic reading recognition of pointer gauges

Abstract In order to implement a computer vision based reading recognition system for pointer gauges, we propose an algorithm to locate the pointer by searching for the minimal bounding rectangle (MBR) of the pointer region. Having determined the center of dial region and the centroids of scale marks, we build up a reference system for reading recognition with the dial region center and the scale mark centroids. To identify the indicating value of a gauge image, we first detect the pointer region based on frame difference, and determine the MBR of the pointer using the longest edge of its convex hull. We then take the centroid of the MBR enclosing the pointer region as the centroid of the pointer. We next take the connection between the pointer centroid to the dial center as the pointer, and calculate the indicating value corresponding to the pointer based on the angle method. Experimental results reveal the effectiveness of the pointer location algorithm in computer vision based reading recognition for pointer gauges.
MODULAR REDUCTION BASED ON THE DIVIDER BY BLOCKING NEGATIVE REMAINDERS

The quality and depth of content Web of Science offers to researchers, authors, publishers, and institutions sets it apart from other research databases. The inclusion of News of NAS RK. Series of geology and technical sciences in the Emerging Sources Citation Index demonstrates our dedication to providing the most relevant and influential content of geology and engineering sciences to our community.Қазақстан Республикасы Ұлттық ғылым академиясы "ҚР ҰҒА Хабарлары.Геология жəне техникалық ғылымдар сериясы" ғылыми журналының
Ensemble classification from deep predictions with test data augmentation

Data augmentation has become a standard step to improve the predictive power and robustness of convolutional neural networks by means of the synthetic generation of new samples depicting different deformations. This step has been traditionally considered to improve the network at the training stage. In this work, however, we study the use of data augmentation at classification time. That is, the test sample is augmented, following the same procedure considered for training, and the decision is taken with an ensemble prediction over all these samples. We present comprehensive experimentation with several datasets and ensemble decisions, considering a rather generic data augmentation procedure. Our results show that performing this step is able to boost the original classification, even when the room for improvement is limited.
Histopathological Imaging–Environment Interactions in Cancer Modeling

Histopathological imaging has been routinely conducted in cancer diagnosis and recently used for modeling other cancer outcomes/phenotypes such as prognosis. Clinical/environmental factors have long been extensively used in cancer modeling. However, there is still a lack of study exploring possible interactions of histopathological imaging features and clinical/environmental risk factors in cancer modeling. In this article, we explore such a possibility and conduct both marginal and joint interaction analysis. Novel statistical methods, which are "borrowed" from gene⁻environment interaction analysis, are employed. Analysis of The Cancer Genome Atlas (TCGA) lung adenocarcinoma (LUAD) data is conducted. More specifically, we examine a biomarker of lung function as well as overall survival. Possible interaction effects are identified. Overall, this study can suggest an alternative way of cancer modeling that innovatively combines histopathological imaging and clinical/environmental data.
Expressive Biosignals

My research introduces expressive biosignals as a novel social cue to improve interpersonal communication. Expressive biosignals are sensed physiological data revealed between people to provide a deeper understanding of each other's psychological states. My prior work has shown the potential for these cues to provide authentic and validating emotional expression, while fostering awareness and social connection between people. In my proposed research, I expand on this work by exploring how social responses to biosignals can benefit communication through empathy-building and social support. This work will scope the design space for expressive biosignals and inform future interventions for a variety of social contexts, including interpersonal relationships and mental health.
Open access resources in the academic libraries’ collection development (The experience of RAS SB State Public Scientific and Technological Library)

The authors discuss the study findings and the Library’s experience in integrating open access resources into the resource base of the information support offered to Siberian researchers and scholars. The dynamic technology of resources organization and use calls for continuous monitoring of the open access resources. Using the open access resources as an object of collection development improves the effectiveness of user services and preservation of socially significant content which impacts the libraries’ importance within the system of scientific communications. The library collection as a library’s strategic element is transforming with widening the formats, generic and specific limitations, and integrating traditional collections with the open access resources. This results in the sophisticating organizational and technological model of collection development. The efficiency of integrated open access library services demonstrate the users’ interest to and demand for them. The open access resources have been being increasingly included into the relevant collection development at the academic libraries. The systematic collection of open access resources can operate as a compensational technological system against other expensive resources. Integrating the open access resources into the collections of the State Public Scientific and Technological Library of the Russian Academy of Sciences Siberian Branch proves to be naturally determined and impacts the prospects for collection development.
Identification of cognitive manipulations that have the greatest impact on students in the internet

The study puts an emphasis on exploring cognitive manipulations contained in the Internet resources (social networks and blogs) that have the greatest impact on students. The study was conducted with 159 students of Don State Technical University. 50 samples of media texts (of various formats) containing cognitive manipulation were taken from social networks sites and blogs. Focus group method, questionnaire, method of Critical Discourse Analysis and methods of mathematical statistics (Principal Component Analysis) were used for data collection and processing. The findings allow us to identify and describe the features of such cognitive manipulation as “presence effect”, “focus on pros”, “halo effect”, “emotional resonance”, “ambiguous language”, “anonymous authority”, “primacy effect”, “exaggeration” and identify the manipulations that have the greatest impact on students. Recommendations aimed at reduction of the impact of manipulative techniques were suggested. The results of the present study may help teachers and psychologists in their work.
A tool centre point calibration method of a dual-robot NDT system for semi-enclosed workpiece testing

Purpose With the development of materials science and technology, composite workpieces are increasingly used. This paper aims to discuss a non-destructive testing (NDT) solution for semi-enclosed composite workpieces. A dual-robot system with one robot that grips an irregular-shaped ultrasonic probe (tool) is established. Design/methodology/approach According to robotics, this paper defines the orientations of the discrete points coordinate frames in trajectory and proposes an orientation constraint rule between the tool coordinate frame and the scanning trajectory. A four-posture calibration method for calibrating the transformation relationship of the irregular-shaped tool frame relative to the robot flange frame is presented in detail. Findings Calibration and verification experiments were performed, and good-quality C-scan images were obtained by applying the constraint rule and the calibration method. Experimental results show that the calibration method used to determine the tool centre point (TCP) position is correct, effective and efficient; the TCP orientation constraint rule can ensure the extension pole of the irregular-shaped ultrasonic probe is parallel to the axis of the semi-enclosed cylindrical workpieces; and the ultrasonic transducer axis is perpendicular to the surface of the workpiece. Originality/value This paper proposes a constraint method for the posture of an irregular-shaped tool in this scheme. Theoretical foundations for the four-posture calibration method of the irregular-shaped tool for dual-robot-assisted ultrasonic NDT are presented in detail. This strategy has been successfully applied in the NDT experiment of semi-enclosed composite workpieces.
DIGITAL COMPETENCE AS ONE OF THE PROFESSIONALLY IMPORTANT COMPETENCIES OF FUTURE TEACHERS

Abstract. In the article digital competence, one of the main components of professional competence of future teachers, is considered. Different approaches of determining the digital competency of future specialists and terminology, used in modern scientific literature to determine the concept of digital competency, have been studied. The analysis of recent scientific work of the proposed problem was carried out. Concepts "competence" and "computer competence" are defined. To integrate with the international educational space, the definition of "digital competence" is appliesd The author substantiates the essence of the concept of "digital competence", defines the components of "digital competence" of future teachers and outlines directions of its development. European standards, which are an important tool for increasing the level of digital competence of specialists in the field of education for identifying digital competences, are analyzed. One of the objectives of the study was to analyze the project of the European Commission “The Digital Competence Framework for Citizens” (DigComp), which is an important tool for increasing the digital competence of specialists in education, training and advanced training. The article defines the definition of digital competence by the European Commission, which defines this competence as one of the key competences for learning through life and is interpreted as a sure, critical and responsible use and interaction with digital technologies for learning, professional activity (work), and participation in society. The article highlights the digital competency standards of the European network of EUROPASS, which include information management, cooperation, communication, content, knowledge, ethics, responsibility, assessment, problem solving and technical operations.