Miracle-dz/UniFAR-FTUs huggingface dataset:
Steganographic Resources of FPGA-based Systems for Approximate Data Processing

The program code controls the operation of FPGA (Field Programmable Gate Arrays) chips. Through the use of program code it is possible to interfere with the operation of these chips. Operational monitoring (integrity, authenticity, distribution paths) of program code is one of the most effective means of preventing illegal interference with FPGA-based systems. Traditional methods of monitoring program code have the problem of storing control data. A promising approach is to embed the monitoring data into the FPGA program code in a steganographic manner. In this case, the fact of the availability of monitoring data and the fact of monitoring is not obvious to an external observer. There are methods for steganographic embedding of additional data into the FPGA program code. Methods of this kind are based on equivalent transformations of the program code. This paper proposes and experimentally substantiates the presence in the FPGA program code of new resources for steganographic data embedding. These resources arise in the programming code of FPGA systems that perform approximate data processing. In the paper, inessential LUT (Look Up Table) FPGA units are classified as such resources. These units are involved in the calculation of the least significant (discarded during rounding) bits of the result and do not participate in the calculation of the most significant (retained) bits. Also inessential bits of the program code of LUTs are referred to new resources. These bits are bits that are not accessed during the calculation of the result of the operation. The experiments performed have shown the possibility of organizing stego containers in the FPGA program code using the identified additional resources. The volume of such stego containers has been estimated. It is shown that this volume is sufficient for storing monitoring data, which are used for operational monitoring of the FPGA program code.
A Universal Routing Algorithm Based on Intuitionistic Fuzzy Multi-Attribute Decision-Making in Opportunistic Social Networks

With the vigorous development of big data and the 5G era, in the process of communication, the number of information that needs to be forwarded is increasing. The traditional end-to-end communication mode has long been unable to meet the communication needs of modern people. Therefore, it is particularly important to improve the success rate of information forwarding under limited network resources. One method to improve the success rate of information forwarding in opportunistic social networks is to select appropriate relay nodes so as to reduce the number of hops and save network resources. However, the existing routing algorithms only consider how to select a more suitable relay node, but do not exclude untrusted nodes before choosing a suitable relay node. To select a more suitable relay node under the premise of saving network resources, a routing algorithm based on intuitionistic fuzzy decision-making model is proposed. By analyzing the real social scene, the algorithm innovatively proposes two universal measurement indexes of node attributes and quantifies the support degree and opposition degree of node social attributes to help node forward by constructing intuitionistic fuzzy decision-making matrix. The relay nodes are determined more accurately by using the multi-attribute decision-making method. Simulation results show that, in the best case, the forwarding success rate of IFMD algorithm is 0.93, and the average end-to-end delay, network load, and energy consumption are the lowest compared with Epidemic algorithm, Spray and Wait algorithm, NSFRE algorithm, and FCNS algorithm.
Symmetric and Anti-Symmetric Damping Modes of Trivelpiece-Gould Waves in Weakly and Completely Ionized Plasma Waveguides

The collision effects on the low-frequency ion-acoustic Trivelpiece–Gould wave are investigated in weakly and completely ionized plasma waveguides by using the normal mode analysis. In weakly ionized plasma waveguides, it is found that the dependence of the harmonic mode on the absolute value of the scaled damping rate shows the opposite tendency for large and small radii of the cylindrical waveguide. It is also is found that the scaled damping rates for both weakly and completely ionized plasma waveguides decrease with an increase of the electron temperature. It is interesting to note that the scaled damping rate for weakly ionized plasma waveguides shows anti-symmetric behavior when the Trivelpiece–Gould wave propagates in the negative-z direction. However, it is found that the scaled damping rate for completely ionized plasma waveguides shows the symmetric behavior when the Trivelpiece–Gould wave propagates in the negative-z direction.
Efficient Hardware Accelerator for Compressed Sparse Deep Neural Network

SUMMARY This work presents a DNN accelerator architecture specifically designed for performing e ﬃ cient inference on compressed and sparse DNN models. Leveraging the data sparsity, a runtime processing scheme is proposed to deal with the encoded weights and activations directly in the compressed domain without decompressing. Furthermore, a new data ﬂow is proposed to facilitate the reusage of input activations across the fully-connected (FC) layers. The proposed design is implemented and ver-iﬁed using the Xilinx Virtex-7 FPGA. Experimental results show it achieves 1.99 (cid:2) , 1.95 (cid:2) faster and 20.38 (cid:2) , 3.04 (cid:2) more energy e ﬃ cient than CPU and mGPU platforms, respectively, running AlexNet.
Non-Invasive Monitoring of Respiratory Rate and Respiratory Status during Sleep Using a Passive Radio-Frequency Identification System

SUMMARY In recent years, checking sleep quality has become essen- tial from a healthcare perspective. In this paper, we propose a respiratory rate (RR) monitoring system that can be used in the bedroom with- out wearing any sensor devices directly. To develop the system, passive radio-frequency identiﬁcation (RFID) tags are introduced and attached to a blanket, instead of attaching them to the human body. The received signal strength indicator (RSSI) and phase values of the passive RFID tags are continuously obtained using an RFID reader through antennas located at the bedside. The RSSI and phase values change depending on the respi- ration of the person wearing the blanket. Thus, we can estimate the RR using these values. After providing an overview of the proposed system, the RR estimation ﬂow is explained in detail. The processing ﬂow includes noise elimination and irregular breathing period estimation methods. The evaluation demonstrates that the proposed system can estimate the RR and respiratory status without considering the user’s body posture, body type, gender, or change in the RR.
Analysis of comparative effectiveness of state-of-the-art heuristics for CDCL SAT solvers

The Conflict-Driven Clause Learning algorithms for solving the Boolean satisfiability problem comprise the major part of the methods used to solve various instances of the problems that arise in industry and science. In recent years there have been proposed several major heuristics for these algorithms which are assumed to be de facto good for the solvers’ performance over diverse sets of benchmarks. The goal of this paper is to evaluate the contribution of each separate heuristic to the performance of a state-of-the-art solver, see the extent to which they are beneficial, and figure out if the heuristics have any particular features that need to be taken into account.
On Classification Hidden Concepts Language in Specialized Texts Based on Methods of the Intellectual Data Processing

In this article discussed and solved the problems of comparing language concepts in specialized texts, in particular, scientific texts in the Ukrainian language. A corpus of scientific texts and dictionaries as well as stop words and affixes has been formed for processing specialized texts. The resulting texts were analyzed and converted into text frequency-inverse document frequency (TF-IDF) feature representation. To transform the original vector of features, it is proposed to use an algorithm for the synthesis of linear systems, in combination with the T-stochastic neighbor embedding (T-SNE). A series of experiments were performed on test examples for the determination of informational density in the text and classification by keywords in specialized texts using the method of random samples consensus (RANSAC). A method of classification of hidden language concepts was proposed, use of clustering methods (K-means). As a result of the experiment, the structure of the classifier of hidden language concepts was obtained in structured texts. The stability of the proposed method is investigated by using the perturbation of the original data by a variational autoencoder. The obtained structure allowed to achieve a relatively high recognition accuracy (97%-99%) using decision trees and machines of extreme gradient amplification .
Software architectures in smart manufacturing: Review and experiences

Cyber-physical systems based on heterogeneous and distributed devices, applications and services are the core of smart factories. Smart manufacturing systems are highly dependent on software applications and services that enable integration of data from different and heterogeneous sources, as well as support for control and management processes. Development and implementation of specific architecture styles and patterns in smart industrial settings is essential for their performance. Several software architecture styles used in Industry 4.0 environments are discussed and illustrated with examples from literature. Our experience with a prototype of a smart sensor-based layered architecture is presented and discussed. Further work will be directed towards development of service oriented architectures and reengineering method for old fashioned industrial settings.
MTGAN: Extending Test Case set for Deep Learning Image Classifier

SUMMARY During the recent several years, deep learning has achieved excellent results in image recognition, voice processing, and other research areas, which has set o ﬀ a new upsurge of research and application. Internal defects and external malicious attacks may threaten the safe and reliable operation of a deep learning system and even cause unbear-able consequences. The technology of testing deep learning systems is still in its infancy. Traditional software testing technology is not applicable to test deep learning systems. In addition, the characteristics of deep learning such as complex application scenarios, the high dimensionality of input data, and poor interpretability of operation logic bring new challenges to the testing work. This paper focuses on the problem of test case generation and points out that adversarial examples can be used as test cases. Then the paper proposes MTGAN which is a framework to generate test cases for deep learning image classiﬁers based on Generative Adversarial Network. Finally, this paper evaluates the e ﬀ ectiveness of MTGAN. key words: test
Non-Volatile Main Memory Emulator for Embedded Systems Employing Three NVMM Behaviour Models

SUMMARY Emerging byte-addressable non-volatile memory devices attract much attention. A non-volatile main memory (NVMM) built on them enables larger memory size and lower power consumption than a traditional DRAM main memory. To fully utilize an NVMM, both software and hardware must be cooperatively optimized. Simultaneously, even focusing on a memory module, its micro architecture is still being developed though real non-volatile memory modules, such as Intel Optane DC persistent memory (DCPMM), have been on the market. Looking at existing NVMM evaluation environments, software simulators can evaluate various micro architectures with their long simulation time. Emulators can evaluate the whole system fast with less ﬂexibility in their conﬁguration than simulators. Thus, an NVMM emulator that can realize ﬂexible and fast system evaluation still has an important role to explore the optimal system. In this paper, we introduce an NVMM emulator for embedded systems and explore a direction of optimization techniques for NVMMs by using it. It is implemented on an SoC-FPGA board employing three NVMM behaviour models: coarse-grain, ﬁne-grain and DCPMM-based. The coarse and ﬁne models enable NVMM performance evaluations based on extensions of traditional DRAM behaviour. The DCPMM-based model emulates the behaviour of a real DCPMM. Whole evaluation environment is also provided including Linux kernel modiﬁcations and several runtime functions. We ﬁrst validate the developed emulator with an existing NVMM emulator, a cycle-accurate NVMM simulator and a real DCPMM. Then, the program behavior di ﬀ erences among three models are evaluated with SPEC CPU programs. As a result, the ﬁne-grain model reveals the program execution time is a ﬀ ected by the frequency of NVMM memory requests rather than the cache hit ratio. Comparing with the ﬁne-grain model and the coarse-grain model under the condition of the former’s longer total write latency than the latter’s, the former shows lower execution time for four of four-teen programs than the latter because of the bank-level parallelism and the row-bu ﬀ er access locality exploited by the former model.
Applying Computer Graphic Design Software in a Computer-Assisted Instruction Teaching Model of Makeup Design

Methods for teaching contemporary makeup design involve drawing on paper, which requires considerable time and is difficult to edit. To change the makeup color, one must redraw their entire makeup design again, which is both inefficient and not environmentally friendly. Furthermore, design drawings are difficult to preserve. However, computer graphic design has not been used in the teaching of makeup design drawing; instead, learners rely on knowledge from professors and the experience they accumulate through practicing drawing on paper. Computer graphic design software allows users to experiment with various color designs, lines, and shading options before finalizing their makeup design. Thus, this study sought to employ such technology to improve upon conventional hand drawing practice techniques. The experiment was divided into a preliminary experiment and main experiment, where a two-stage questionnaire was conducted. In the preliminary experiment, the researchers compared the time required to complete the hand-drawn and computer-drawn makeup designs. The results revealed that the hand-drawn designs required almost double time than computer-drawn designs to complete. Additionally, time-lapse photography was taken during the computer drawing process; the photos were used to explain—to participants in a digital drawing group in the main experiment—the digital drawing makeup design procedures and the required operation time. The first stage of the main experiment comprised a brush selection experiment. The participants, 39 students from a cosmetology department, completed a Likert-scale questionnaire. They also performed item analysis to discuss and select drawing tools from a graphic design software, which met the requirements for makeup design pertaining to the eyebrow, eyeshadow, eyeliner, blush, nose contour, and lips. The software allowed the students to experiment with different colors in their design and immediately displays the results. In the second stage, an experiment on optimizing brush arrangements was performed by 10 experts, all of whom were teachers from the department of cosmetology, had at least 5 years of teaching experience, and had obtained a Level B (advanced level) Beauty Technician Certificate. Data from a Likert-scale questionnaire were analyzed and narrative analysis was conducted to determine the rating and evaluation priorities for standards pertaining to the eyebrows, eyeshadow, eyeliners, blush, nose contour, and lips. The requirement for design symmetry was achieved by using the mirror function of the software. This function was useful: it enabled students to complete their makeup design in approximately half the time. This study transformed the conventional learning method through interdisciplinary integration, established novel and innovative teaching models, and provides crucial insights into future research on improving teaching practice.
Solution assisted growth mechanism and characterization of ZnS microspheres

The ZnS microspheres were synthesized via simple, efficient and cost-effective hydrothermal method. The x-ray diffraction study revealed nanocrystalline nature of the synthesized ZnS with the cubic crystal structure. Scanning and transmission electron microscopy observations revealed the formation of 3D microspheres that consist of numerous ZnS nanocrystals. The grown microspheres are also interconnected with each other by driving force of attachment. The obtained product has excellent elemental stoichiometric proportion as evidenced by the EDS technique. The electron diffraction pattern reveals the polycrystalline nature of obtained ZnS product. The band gap was measured from UV–Vis spectroscopic study and found to be blue shifted from the bulk band gap value. The PL study exhibits negligibly weak band edge emission and dominant, widespread defect-related green emission. The nucleation of a ZnS nanocrystals and subsequent growth into the microspheres is also discussed.
Heavy metal intoxication

Introduction Although some debate exists as to the subject, elements which are classified under ‘heavy metals’ have come to be those which pose a threat to humans in terms of toxicity. Intoxication with heavy metals is not a typical diagnosis as it is fairly uncommon. This can impose a risk on people who fail to be diagnosed and removed from the source of exposure, increasing morbidity and mortality.
Análisis bibliométrico sobre Educación Financiera en Educación Primaria

espanolLos estilos de aprendizaje a utilizar para la educacion personalizada denotan la presencia de estudiantes que aparentemente no son iguales o peores que el resto, sino que demuestran un talento de altas capacidades que el Estado debe potencializar. Esta investigacion, persigue identificar los indicadores mas comunes de alta capacidad de los estudiantes superdotados, para estimar estilos de aprendizaje en estos grupos, con el objetivo de analizar desde una perspectiva teorica las relaciones existentes entre estilos de aprendizaje, superdotacion intelectual y talento, asi como su valor metodologico para el perfeccionamiento de la labor formativa en la universidad contemporanea. El metodo aplicado es el heuristico, porque interpreta el razonamiento de estudios experimentales de unidades de analisis, desde la ensenanza de los primeros niveles hasta llegar al tercer nivel. Como resultado se tiene que en los estilos de aprendizaje se deben aplicar procesos de razonamiento y pragmatismo en la ensenanza, puesto que los superdotados son ordenados y detallistas en los contenidos. En conclusion, las universidades no estan preparadas para acoger jovenes talentosos, sin embargo, la tutoria diferenciada resulta una via eficaz para ensenarles a los universitarios a profundizar en contenidos cientificos asociados a su formacion y consecuente estimulacion para el desarrollo de potencialidades. EnglishThe learning styles to be used for personalized education denote the presence of students who apparently are not the same or worse than the rest, but rather demonstrate a talent with high abilities that the State must enhance. This research aims to identify the most common indicators of high capacity of gifted students, to estimate learning styles in these groups, with the aim of analyzing from a theoretical perspective the relationships between learning styles, intellectual giftedness and talent, as well as its methodological value for the improvement of the formative work in the contemporary university. The applied method is the heuristic one, because it interprets the reasoning of experimental studies of units of analysis, from the teaching of the first levels to reaching the third level. As a result, learning styles must apply reasoning processes and pragmatism in teaching, since the gifted are ordered and detailed in the content. In conclusion, universities are not prepared to welcome talented young people, however, differentiated tutoring is an effective way to teach university students to delve into the scientific content associated with their training and consequently stimulate the development of potential.
Manipulation and fake news detection on social media: a two domain survey, combining social network analysis and knowledge bases exploitation

Social media have to be seen as an adversarial space because of the presence of adversaries, manipulation and disinformation. On classic sources of information, these challenges are usually handled by qualifying content (truth likelihood), and emitters (actor credibility). To adapt this approach to social media, we use inﬂuence models, behaviour analysis and community detection for emitters characterisation. This can be combined with the exploitation of knowledge bases for automatic fact checking. This paper proposes a review of this multi-domain challenge.
COMPENSATION STRATEGY AND CORPORATE PERFORMANCE OF TELECOMMUNICATION FIRMS IN RIVERS STATE

Compensation strategy is commonly recognized as important strategic issue in firms over the recent past. Compensation strategy tends to play a central role in determining organization’s economic success; hence the interaction concerning the two is gaining more attention among firms globally. Literature states that an optimal alignment as compensation strategy facilitates organization to secure its competitive advantages in specific market place. The drive for this work was to test the link between compensation strategy and corporate performance of telecommunication firms in Rivers State. A sample of 119 employees was drawn from the population of 170 using Taro Yamane (1967) statistical formula; while the Spearman’s Rank order correlation coefficient was used to test the null hypotheses, with the aid of SPSS, leaving 5% to error. Hence, there is a significant relationship between compensation strategy and corporate performance of telecommunication firms in Rivers State. It was thus recommended that Policies that take into consideration competition based pay as employees are aware of the compensation packages of their counterparts in other firms. Policies that take into consideration performance based pay as employees would like to receive rewards that are commensurate with their efforts. Given that employees are always concerned about the quality of compensation they get; Policies should be employed to foster adequate pay for employees in the telecommunication sector.