Reviewerly/exHarmony huggingface dataset:
Spectre without shared memory

The Spectre attack by Kocher et al. [11] reads arbitrary data from colocated processes by exploiting two common features of modern processors: speculative execution and shared caches. While theoretically the attack works in many different settings, the current variations all require that the attacker share with the target a memory region that includes vulnerable code which accepts input from the attacker.
Speech Bandwidth Extension Aided by Hybrid Model Transform Domain Data Hiding

Public telephone systems are limited to narrowband (NB) frequency range of 300-3400Hz, which affects the quality and intelligibility of telephony speech. In this paper, a new Hybrid Model Transform Domain Speech Bandwidth Extension (HMTDBWE) algorithm is proposed to transmit the missing speech frequencies of wideband (WB) speech over a steganographic channel. The proposed Discrete Wavelet Transform-Fast Fourier Transform-Based Data Hiding (DWTFFTBDH) technique is developed to incorporate the hidden spectral envelope parameters within the narrowband speech signal and transmitted over the channel. This hidden information is recovered reliably at the receiver side to produce a reconstructed wideband telephony speech of much higher quality. The simulation results of the proposed method show improved speech quality over the other data hiding methods.
Path Planning for a Land Leveler

This study proposes an algorithm to determine the route of a land leveler, which is a type of agricultural machine for leveling and flattening the surfaces of fields. First, we propose the land leveler problem (LLP), which is formulated as a combinatorial optimization problem. Second, it is verified that the LLP can be solved with dynamic programming. Finally, our algorithm and its complexity are described, and the results of our approach are presented.
Fate of Entanglement for Initial Separable States in Quantum Neural Network

This study is related to the fate of entanglement for initial separable states in a quantum neural network (QNN) model, which is in contact with the data environments locally. The duration of entanglement in quantum systems becomes extremely important when we consider it as a valuable resource. Thus, the effects of various initial states on the occurrence or decay of entanglement are investigated in the presence of information reservoirs. Especially in this study, central spin model has been examined as a quantum version of neural networks by taking inspiration from the biological models. Our model consists of a central spin system with two nodes to which the nodes are coupled to independent spin baths. Numerical results clearly show that different initial states have a profound effect on the fate of the entanglement. It also shows that the entanglement lifetime can be adjusted by regulating the reservoir states. The results can be used in realistic communication network situations to improve the performance of entanglement formation or distribution.
QASA

For information consumers, being able to obtain a short and accurate answer for a query is one of the most desirable features. This motivation, along with the rise of deep learning, has led to a boom in open-domain Question Answering (QA) research. While the problem of machine comprehension has received multiple success with the help of large training corpora and the emergence of attention mechanism, the development of document retrieval in open-domain QA is lagged behind. In this work, we propose a novel encoding method for learning question-aware self-attentive document representations. By applying pair-wise ranking approach to these encodings, we build a Document Retriever, called QASA, which is then integrated with a machine reader to form a complete open-domain QA system. Our system is thoroughly evaluated using QUASAR-T dataset and shows surpassing results compared to other state-of-the-art methods.
GPK

We introduce a novel typing technique for special symbols in the keyboard-only environment. The technique, called GPK (Gliding on Physical Keyboard), consists of two steps for entering special symbols. First, a user draws the special symbol on the keyboard by gliding over keys; Second, the user can select the desired symbol from the predicted symbols generated by GPK. Users can also switch from this mode to normal typing mode. We also present an application of this input technique based on web browsers. A user study with nine participants who are familiar with keyboard input showed the input efficiency of GPK. We compared the typing efficiency of GPK with other special symbol typing methods. We could deploy this method to office environments where users have desktop computers with a keyboard only. It could also inspire future work of integrating this method into word processors, document preparation systems and web environments.
A Novel Algorithm for DNA Sequence Compression

Deoxyribonucleic Acid (DNA) sequences vary in terms of their size and fall within the range of billions of nucleotides. The value increases to twice or thrice its original value annually. Techniques of data compression and related methods that originate from the information theory are frequently understood as relevant for the field of data communication, exploration, and storage. In the present situation, it is vital to store data for biological sequences. The compressBest algorithm proposed in the paper for the compression of DNA sequences helps attain a better compression ratio and is much faster when compared to the existing compression techniques. compressBest algorithm is applicable to compression of DNA sequences with a reduction in storage space. The proposed algorithm is tested over the data from the UCI repository.
Decision Support System for The Weaning of Rex Rabbit Using Simple Additive Weighting ( SAW ) Method

Weaning REX rabbits child is one of the keys to success in raising or cultivating rabbits. Unsuitable weaning can result in very high mortality or mortality risks, while weaning for too long results in decreased productivity and the possible marriage of children with rabbit parent. The research done is to design and build the application of decision support system (DSS) with Simple Additive Weighting method (SAW) with 5 criteria as supporting of DSS calculation that are body weight (gram), body length (cm), still breastfeeding or not, already independent for food or not and Gender. The webased DSS application created is tested by using the calculation system compared with research data. Based on the test of 36 rabbit children which is derived from previous research results obtained showed that the application of the DSS are built 100% the same result.
On the analogy between quantum circuit design automation and virtual network embedding

Quantum computing and network virtualisation share more similarities than it would seem on first thought: both reach their potential by using the underlying hardware as efficiently as possible - a classical computer science problem. Quantum computing research has already been focusing on key problems related to the scarcity of the quantum hardware, hoping that once scalable quantum computers will be available, quantum circuit design automation methods (QCDA) are mature. Consequently, a significant methodological apparatus exists for a technology envisioned to scale in the future. Likewise, the optimisation of resource assignment for virtual networks has received much attention in the literature. As such, any scalability improvement of virtual network embedding (VNE) would be of high practical importance in the present. There is an interesting and promising relationship between VNE and QCDA. This work introduces the possibility to use QCDA methodology for VNE, and vice versa. VNE problem instances can be modeled using the quantum circuit formalism, and we offer some basic examples. To the best of our knowledge, this is the first work that highlights this analogy.
Two-Dimensional Directional Lifting Schemes

We consider a two-dimensional directional lifting scheme on a frequency plane R 2 that is useful for an efficient multidirectional wavelet expansion or transformation. In particular, we focus on the lifting scheme as an elementary modification of a set of biorthogonal filters that hold biorthogonality. The proposed method is a straightforward extension of the original lifting scheme on R that offers a custom design of biorthogonal filters with directional properties.
Cognition, conflict, and doctrine: How groupthink fails on a Clausewitz landscape

Real-time conflict takes place on Clausewitz landscapes most notably marked by fog-of-war and frictional limits, uncertainties, and misperceptions. Imposition of such factors on an opponent is, in fact, a standard tactic of confrontation, from courts of law to commerce, from political campaigns to the battlefield. Time-constrained optimization models of institutional effectiveness, based on ‘anytime algorithm’ methods, suggest that the burden of doctrinal groupthink may become synergistic with fog-of-war and friction to greatly compromise the ability of an institution to respond to shadow price demands imposed by a contending agent or environment. A different, and more direct, approach via a ‘simple’ stochastic model, provides similar insight.
RECSRF: Novel Technique to Evaluate Program Security using Dynamic Disassembly of Machine Instructions

Modern software systems have nearly an uncontrolled growth in complex requirements that is fueled by the need to interact with multiple other complex systems. While some of the complexity increases are due to activities such as bug fixes which are unavoidable, other activities such as expanding and enhancing functionality of a software system becomes a risky endeavor to undertake with respect to security as responding to the potential vulnerabilities due to complexity increases require scarce resources including technical expertise and time. This paper introduces RECSRF; a novel framework to quantitatively evaluate the security of an execution in line with the security risk impact it makes over the particular microprocessor on which it executes. RECSRF consists of two components; a novel concept called The Run-time Execution Complexity (REC) of a program execution, which evaluates the trade-off between performance vs. security, while adhering to Control Flow Integrity (CFI) of programs, and an information theoretic technique to approximate the Security Risk Factor (SRF), which approximates the risk of a particular execution by analyzing dynamically disassembled machine instructions of a particular microprocessor. The RECSRF value allows software designers to select the most secure resource combination among a given set of resources, and software implementers to decide whether to proceed or not with a software change. The method can also be used to detect control flow hijacks at runtime by using it as an application level intrusion detection mechanism which allows transforming the same to an application level intrusion preventer upon successful implementation.
Library and information sciences in 2017–2018: The focuses and findings of theses research

The author reviews and analyzes theses in the disciplines 05.25.03 – Library science, bibliography and bibliology, and 05.25.05 – Information systems and processes, defended at Moscow State Institute of Culture, Dissertation Committee D 210.010.01 in support of candidature and doctorate for a degree in pedagogy and engineering. The dissertations by A. V. Trusov, E. V. Russkikh, O. O. Kondratenko, K. E. Sokolinsky, D. A. Bashirov, I. A. Vaganova and M. A. Kharintseva are discussed. The bibliographic data, information on supervisors, official opponents and organization, research findings, and issues discussed at a viva voce, are cited for each of the theses. The process of the dissertation discussion by scientific community and the members of the dissertation committee is reviewed. The Dissertation Committee offered several practical applications for the solutions as suggested by the candidates. The prospects for further studies are revealed, prospective scientific problems are set up. The publication activities of the applicants are analyzed; the open sites (conferences, professional forums) where theses findings are tested are defined. The journals interested in the publications of new masters and doctors are named.
The Culture Arts Education Experiences of Students with Disabilities participating in Arts Instructor Support Projects for Special Schools

The purpose of this study was to examine the experience of students with disabilities participating in culture arts education supported by Arts Instructor Support Projects for special schools and find their needs and recognition, problems and improvement direction of culture arts education. The data were collected through depths interviews with students with disabilities from July 9, 2018 to September 21, 2018. Participants of the study were 10 students with disabilities of special school in B city participating in culture arts education supported by Arts Instructor Support Projects for more than two years. The questionnaire consisted of five semi-structured questionnaires based on the previous research, and the interview data were analyzed by the continuous comparative analysis method. For validity and reliability, triangulation method, inter-coder reliability, and participant identification technique were conducted. As a result, fore main subjects, eight top topics, and thirteen sub topics were derived. The results of this study are as follows. First, most students with disabilities recognized lack of space for culture arts education and professional lecturers, and showed low confidence in arts instructors′expertise in special education. Second, most students with disabilities perceived that classroom and teaching methods considering the level. However, through artistic activities, it was shown that memory and emotional stability were improved. Third, although the relationship with the art teacher was not positive, the students with disabilities tried to understand the art instructor, and the art instructors recognized the artistic talents of the students with disabilities and connected with the profession. Fourth, students with disabilities dreamed of becoming an artist but choose other professions because of economic problems. The results show that despite unsatisfied and insufficient support by arts instructor support projects for special schools, artistic talents of students with disabilities have been developed through culture arts education. Based on this findings, improvement direction of culture arts education is suggested for students with disabilities.
Recording application with managerial prediction features for skenoo business

Recording information on sales and purchases transactions is a part that cannot be separated from business activities. This information should be recorded and stored as historical financial information. Recording a historical financial information is critical for all business sizes. Skenoo is a family business that is engaged in the automotive sector as a distributor and final seller of motorcycle tires. Currently, Skenoo business is growing by selling motorcycle spare parts, selling car tires, and other automotive needs. To face this development, keeping a good record is an important thing to achieve its business objectives. The increased stock of goods requires careful logging to produce good accounting and management reports. This study discusses the design system for accounting recording on Skenoo business that supports accounting managerial and prediction on the stock of goods calculation that is useful for decision making, which at the time of this study is written, still done manually. The results of this study provide convenience in recording inventory Skenoo goods based on sales and purchase transactions. The financial statements, which has never created before, can be created automatically.
Single Horizontal Camera-Based Object Tracking Quadcopter Using StaGaus Algorithm

This research is a solution to the problem of a hardware platform of object tracking drones. This platform can be used to build further advancements such as selfie drones, follow-me drones for adventure sports and robot pets. StaGaus algorithm has been derived using first principles and is compared against standard algorithms like SRDCF. The algorithm is tested on, an on-board two Android phones for real-time telemetry. This paper demonstrates that StaGaus works even on memory- and performance-constrained devices. In order to standardise the development of object tracking drones’ algorithms, we have built a customised ROS-based Gazebo simulator from scratch. This simulator is capable of simulating multiple robots of multiple types. This uses actual physics Open Dynamics Engine which has been compared against the existing simulators. Finally, as a by-product, this design proved that the cost of the proposed physical quadcopter is low.
Semantic analysis for paraphrase identification using semantic role labeling

Reuse of documents has been prominently appeared during the course of digitalization of information contents owing to the widespread of internet and smartphones in various complex forms such as inserting words, omitting and substituting, changing word order, and etc. Especially, when a word in document is substituted with a similar word, it would be an issue not to consider it as a subject of measurement for the existing morphological similarity measurement method. In order to resolve this kind of problem, various researches have been conducted on the similarity measurement considering semantic information. This study is to propose a measurement method on semantic similarity being characterized as semantic role information in sentences acquired by semantic role labeling. To assess the performance of this proposed method, it was compared with the method of substring similarity being utilized for similarity measurement for existing documents. As a result, we could identify that the proposed method performed similar with the conventional method for the plagiarized documents which were rarely modified whereas it had improved results for paraphrasing sentences which were changed in structure.
A Penalty Method Based-Spring Design optimization Using Bio-inspired Computation Approach

Manufacturers and engineers face the challenges of delivering a quality product at minimum cost, so optimization becomes utmost important. Therefore, the decision of the best approach to adopt in the event of resource availability could be possible by a critical study of the different algorithms. Nature-inspired computation has shown significant result in compression spring design optimization especially cuckoo search and Firefly algorithms with varying strengths and weaknesses. Also, African Buffalo optimization (ABO) algorithm has shown reasonable performance in other application areas. This study evaluates the comparative performance of the cuckoo search, Firefly, and African buffalo optimization algorithms in spring design optimization. Penalty function was employed to handle the constraint across the three algorithms. Three criteria were used to evaluate their performance. The result showed that the ABO algorithm is a more stable and cost-effective approach than the other two algorithms. Future work could be extended to other engineering benchmark problems.
A Multi-Table Image Recognition System Based on Deep Learning and Edge Detection

In order to recognize the information in multi-table images, we use deep learning and edge detection and propose a multi-table image recognition system based on deep learning and edge detection. After the image is preprocessed to the standard image, the table area in the image sample is located by Hough transform, morphological function and edge detection technology, and the cells in the table area are extracted from the image sample. The projection analysis method separates and extracts a single character in the cell, and finally uses a recognition model based on the deep learning convolution neural network to recognize each single character image. After experiments, we find that the system has the advantages of fast and accuracy, which brings great convenience and benefit to the companies engaged in information
ARC

Asynchronous Remote Communities (ARC) methodology has been used to explore HCI topics in a range of contexts. This innovative methodology takes advantage of the technological tools and platforms that are often the subject of HCI research to extend existing methods of data collection, pushing methodology beyond historical modes and allowing better connection with populations who have previously been left out of the research process. This SIG will make space for researchers and practitioners who are interested in using ARC methodology to connect with people who have already used ARC and discuss challenges and opportunities with this methodology, and how to extend similar kinds of innovative, distributed computing based methods into new contexts.
Verification-based test case generation for information-flow properties

Digital systems accumulate ever more personal data, and the potential of privacy breaches leading to gross privacy violations continuously increases. Information flow security deals with the problem of how certain program outputs are influenced by certain inputs. This paper handles the problem of testing information flow properties of object oriented programs. We present a symbolic-execution-based approach to automatic test case generation for four variations of the noninterference property. We also extend existing test coverage criteria and discuss their suitability for information flow test suites. We have implemented our approach using the KeY verification system, and have evaluated the implementation.
Multi-View Fusion Neural Network with Application in the Manufacturing Industry

In recent years the research community and industry have paid high attention to the field of machine learning, especially deep learning. Nowadays many real-world classification or rather prediction applications are implemented by neural network models. We propose a multi-view fusion neural network with application in the manufacturing industry. Image information of multiple cameras is fused and used by the proposed model to predict the state of a manufacturing machine. Experiments show that the overall classification performance is increased from a baseline of 92.7% to 99.5% by the fusion model.
Low-Complexity Systolic Multiplier for GF(2<sup>m</sup>) using Toeplitz Matrix-Vector Product Method

Low-complexity systolic multipliers for GF(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> ) are required in several high-performance cryptographic systems. In this paper, we propose a novel design strategy to derive efficient systolic multiplier for GF(2 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> ) based on Toeplitz Matrix-Vector Product (TMVP) approach. The proposed work is carried out through two coherent interdependent stages. (i) A novel multiplication algorithm based on TMVP method to obtain subquadratic space complexity is proposed first. (ii) The proposed algorithm is then mapped unto to a novel and efficient architecture which is optimized further to derive a low-complexity systolic structure. The complexity analysis and comparison show that the proposed design outperforms the existing work. The proposed design can thus be used in many practical cryptosystems.