Command Sequences Research Articles

Optimization of DH Parameters of 6R Robotic Manipulator Using JAYA Approach

Manipulation of robots is carried out by the operators through a sequence of commands. However, the accuracy of the manipulation is still hindered due to parameter uncertainty. This results in less accurate robotic operations and hence affects the job performance. Due to measurement errors and sensor faults, the operation of robots malfunctions. Generally, errors are reduced with the use of high precision sensors and correcting hardware faults. However, corrections can also be made on a software platform to handle the correction process. Presently, the Denavit–Hartenberg (DH) parameters of a robotic manipulator are optimized for forward kinematics problems. The optimization is carried out using the JAYA approach. The 6R MTAB Aristo XT robot is selected as a case study for the experimental validation of the proposed approach. Experimental results reveal that the optimization of DH parameters improves accuracy for forward kinematic estimation problems. The proposed JAYA approach can further be extended to other robotic manipulators for parameter optimization problems.

Free2CAD

CAD modeling, despite being the industry-standard, remains restricted to usage by skilled practitioners due to two key barriers. First, the user must be able to mentally parse a final shape into a valid sequence of supported CAD commands; and second, the user must be sufficiently conversant with CAD software packages to be able to execute the corresponding CAD commands. As a step towards addressing both these challenges, we present Free2CAD wherein the user can simply sketch the final shape and our system parses the input strokes into a sequence of commands expressed in a simplified CAD language. When executed, these commands reproduce the sketched object. Technically, we cast sketch-based CAD modeling as a sequence-to-sequence translation problem, for which we leverage the powerful Transformers neural network architecture. Given the sequence of pen strokes as input, we introduce the new task of grouping strokes that correspond to individual CAD operations. We combine stroke grouping with geometric fitting of the operation parameters, such that intermediate groups are geometrically corrected before being reused, as context, for subsequent steps in the sequence inference. Although trained on synthetically-generated data, we demonstrate that Free2CAD generalizes to sketches created from real-world CAD models as well as to sketches drawn by novice users. Code and data are at https://github.com/Enigma-li/Free2CAD.

Developing a System of Symbolic Macro Commands (Symcommands) of the Processor

The traditional form of recording machine code is assembly language. Its commands correspond directly to individual machine commands or sequences of commands. The syntax of an assembly language program is determined mainly by the instruction system of the specific processor and the directive system of the specific translator. For some platforms, there may be several kinds of assembly language syntax that are not compatible with each other. For example, the most popular assembly language syntaxes for Intel-compatible processors are Intel syntax and AT&T syntax. However, all existing types of assembly language syntax are primarily focused on easy readability by the computer, not the programmer. The system of symbolic macro commands of the processor presented in the article is a more clear form of representation of machine code, which promotes productivity when the programmer works with it, and also minimization of errors.

Some types of works posted on the internet, and the peculiarities of their protection by Ukrainian copyright compared to US law

The article deals with the peculiarities of protection against plagiarism of works posted on the Internet and the peculiarities of their protection by Ukrainian copyright compared with US legislation.
 The ratio of features of the computer program as an object of copyright protection is analyzed. After all, the program derived from the algorithm and is in a sense, its equivalent. This means that some basic features of algorithms are inherent in programs. The program can also be considered as a means of implementing an algorithm, and as such, characterized by certain distinct features from which for the purposes of the program research as an object of copyright protection can be distinguished: unlike the algorithm, which is a sequence of logical-mathematical Transformation operations, the program contains a sequence of commands that describe the process of implementing an algorithm and provide control of this process. The objective form of expression of the program is its recording formalized language of simultaneous computers.
 It is determined that the protection of computer programs by copyright norms, is a great theoretical and practical curiosity as the simplest and economical.
 The jurisdictional and non-legal forms of protection of patent law are characterized, the main ways of protecting intellectual property rights are clarified. The emphasis on the judicial prohibition as a way of protecting intellectual property rights is analyzed by the international index of property rights, in particular the level of protection of intellectual property rights in Ukraine and in the United States. The fact of a low indicator of protection of intellectual property rights in our country is established compared to European countries. The main issues of protection of intellectual property rights in Ukraine are highlighted. It is emphasized the need to adapt national legislation to the legal system of the European Union. There are a number of international treaties regulating intellectual property relations at the international level. The European integration course of Ukraine indicates its desire to adapt their legal system to European standards, and therefore, concluding an Association Agreement with the EU, Ukraine has undertaken to harmonize its intellectual property legislation with European legislation. The provisions of a number of European legal acts regulating the issue of protecting intellectual property rights are given. Problems of collecting evidence base for violation of intellectual property rights remains open issues as a national judicial practice on this issue. It is necessary to create a specialized judiciary that would consider cases of violation of intellectual property rights, including on the Internet. It is necessary to enhance legal responsibility for violations in the field of intellectual property, in particular regarding the distribution of pirate products.

Range minimum queries in minimal space

We consider the problem of computing a sequence of range minimum queries. We assume a sequence of commands that contains values and queries. Our goal is to quickly determine the minimum value that exists between the current position and a previous position i. Range minimum queries are used as a sub-routine of several algorithms, namely related to string processing. We propose a data structure that can process these command sequences. We obtain efficient results for several variations of the problem, in particular we obtain O(1) time per command for the offline version and O(α(n)) amortized time for the online version, where α(n) is the inverse Ackermann function and n the number of values in the sequence. This data structure also has very small space requirements, namely O(ℓ) where ℓ is the maximum number of active i positions. We implemented our data structure and show that it is competitive against existing alternatives. We obtain comparable processing time, in the nanosecond range, and much smaller space requirements.

Program Synthesis Through Learning the Input-Output Behavior of Commands

Program synthesis writes programs on behalf of humans, increasing software development productivity. Existing systems select a proper sequence of commands by assembling them in various ways and analyzing their meanings, which is accurate and fast when a detailed specification is given for each available command, including the syntax and semantics. However, preparing this specification is burdensome and must be repeated to add or modify available commands. We propose a synthesis system that requires moderate groundwork to achieve sufficient accuracy and speed. The proposed system receives the syntax of the available commands and learns their meanings independently by writing programs and observing their input-output behavior. Using the learned knowledge, the system selects a likely sequence of commands and gradually revises them to converge to a target program. We validated the system by synthesizing 1,000 integer-manipulation programs out of 245,410 possible programs. The system synthesized most of the programs within 1,000 revisions, which is 80% faster than the state-of-the-art system based on machine-learned input-output patterns. In addition, greater than 10% of the programs were synthesized within several revisions. We believe that the proposed system provides a basis for synthesis systems based on learning input-output behavior.

Wireless Modal Testing With Multiple Battery-Free Backscatter Sensors

This paper reports the design, implementation and the result of real-world experiment of wireless modal testing with battery-free backscatter sensors. The battery-free backscatter sensor comprises a custom radio frequency integrated circuit (RFIC), a commodity micro electro-mechanical system (MEMS) accelerometer, and an antenna. Sensor data concurrency demanded in modal testing is realized by allocating a dedicated subcarrier to each backscatter sensor. The orchestration of wireless communications in 920 MHz based on Gen2 protocol and the wireless power supply to the backscatter sensor are performed by a software defined interrogator built on LabVIEW communications and USRP. We developed an over the air (OTA) subcarrier frequency allocation with a sequence of WRITE commands of Gen2 protocol, and its performance was confirmed with the experiments in an indoor radio propagation. The accuracy of the proposed wireless structural modal testing was experimentally verified by comparing with a commercial modal testing system with wired accelerometers. Wireless modal testing were performed both with sine sweep excitation and random excitation. The experiment reveals that wireless modal testing up to 100 Hz can be successfully performed by battery-free wireless sensors. It is also revealed that the selection of subcarrier bitrate is important to secure the bandwidth of the measurement while preserving a sufficient number of subcarrier channels.

ПРАВОВОЙ РЕЖИМ СМАРТ-КОНТРАКТОВ: КОД ИЛИ ДОГОВОР

Introduction: the article is devoted to the analysis of legal regulation of smart contracts, the concept, content, and scope of their application. The author analyzes in detail foreign expe- rience of using smart contracts and suggests possible options for expanding the application area. The article also has a separate section that looks at smart contracts as compared with traditional institutions of civil law. Smart contracts are expected to find application in almost all areas of life in the future. As is often the case with new technologies, the use of smart con- tracts raises a number of civil law issues. Blockchain technology makes it possible not only to create new means of payment but also to autonomously manage almost any process. It can be used for individual contracts and even for the creation of autonomous decentralized systems. Purpose: to provide an insight into the institution of smart contracts and define their role in civ- il law. Methods: empirical methods of comparison, description, interpretation; theoretical me- thods of formal and dialectical logic; special scientific methods such as the legal-dogmatic me- thod, the methods of interpretation of legal norms and comparative legal research. Results: smart contracts are computer programs that perform legally significant actions according to predetermined algorithms set out in the form of a so-called program code. In practice, they are especially important in connection with the development of blockchain technology or (more generally) distributed ledger technology. Conclusions: the term ‘smart contract’ was defined by Nick Szabo in the 1990s as a sequence of commands represented in digital form, including transaction protocols that execute these agreements. Thus, smart contracts formulate rules and sanctions for agreements and execute them automatically. These are not necessarily contracts in the legal sense, but they are capable of controlling, tracking, and documenting legally signif- icant actions. Smart contracts can also be implemented using traditional, for example, mechan- ical technologies (e.g. in a vending machine). However, blockchain and distributed ledger tech- nologies make it possible to implement incomparably more complex rules and enforcement me- chanisms and offer a decentralized environment with an integrated settlement system. From a legal point of view, smart contracts perform two functions. On the one hand, they serve as a functional equivalent of a contract since their technological code can identify the services to be exchanged as well as the conditions under which they must be provided. Being the normative order of the digital, this code formulates the program of obligations of the parties. It resembles the legal order of a contract, without necessarily coinciding with it. On the other hand, smart contracts serve as a tool for the execution of contracts – by controlling, monitoring, and docu- menting the exchange of services. They can also facilitate the execution of conventional con- tracts by translating their provisions into a technical code, verifying the occurrence of agreed- upon events, and enforcing contracts. Smart contracts are suitable for contractual relation- ships, for example, for processing payments or delivering goods without the participation of the parties and an intermediate step in the form of direct execution. Smart contracts are gaining more and more popularity, especially in the financial sector. In addition to the so-called token economy (cryptocurrencies, ICO, etc.), there are also discussed algorithmic ETFs, online plat- forms for loans or project financing. Another important area of application is sharing economy. From a legal point of view, smart contracts can either be the subject of a contractual agreement or generate it on their own. There is sometimes put forward a thesis under the motto ‘Code is law’ that smart contracts give rise to a largely autonomous legal system and/ or are not subject to applicable law. However, this appears to be an erroneous conclusion

SOFTWARE METHOD FOR ANALYSIS OF THE PERFORMANCE OF ANTHROPOMORPHIC MANIPULATOR

A universal anthropomorphic manipulator with six rotational degrees of mobility is considered. The nodal points S0, ..., S6 are selected on the trajectory of movement of the manipulator grip. The kinematic analysis of the manipulator was carried out by the method of transforming the coordinates of Denavit - Hartenberg. The mathematical model of the manipulator is compiled by the Lagrange-Euler method. The problem of maximum performance for each generalized coordinate qi (t) is solved using the Pontryagin maximum principle. Mathematical modeling was carried out in the Mathcad environment. The software method for analyzing the speed of the manipulator allows us to consider for each nodal point of the trajectory S0, ..., S6 the set of admissible configurations of the manipulator, solve the problem of maximum speed for each generalized coordinate qi (t) and estimate the minimum time for the implementation of the sequence of state vectors. When solving the problem of maximum speed, the switching time ti1 and the minimum turning time tik are calculated for each generalized coordinate qi (t). The minimum time for the configuration implementation can be found by summing the minimum rotation time tik over six generalized coordinates. Similar calculations are carried out for each nodal point S0, ..., S6 and the corresponding sets of permissible manipulator configurations. The developed software makes it possible, on the basis of the data obtained, to synthesize a sequence of control commands for the manipulator drives. The research results can be used at the design stage, implementation and modernization of robotic systems and manipulators.

API Development Teaching- Learning Platform

Abstract: API (Application Programming Interface) is a sequence of commands, rules, or regulations that enables a software or app to leverage attributes from another application, system, or gadget to improve its own services. In a nutshell, it's a feature that allows apps to connect with one another. The IT industry has a high demand for REST API Development, hence this article provides an interactive teaching and learning platform for REST API Development. Using the LBD (Learning By Doing) concept, the suggested platform seeks to assist users in learning REST API Development. This tool would assist users in learning to design their own APIs by requiring them to practise (either through coding or MCQs). The platform would be based on selfevaluation and reflection models of self-regulated learning, allowing users to learn more effectively. The platform would also try to provide some scaffolding for users that fail test cases, such as assistance in debugging and why they might be failing the test cases. Keywords: REST-API, Teaching Learning Platform, Self-Regulated Learning(SRL), Human Computer Interaction(HCI), Dashboard, Learning by doing(LBD)

PLUTo: Enabling Massively Parallel Computation In DRAM via Lookup Tables

Data movement between main memory and the processor is a key contributor to the execution time and energy consumption of memory-intensive applications. This data movement bottleneck can be alleviated using Processing-in-Memory (PiM). One category of PiM is Processing-using-Memory (PuM), in which computation takes place inside the memory array by exploiting intrinsic analog properties of the memory device. PuM yields high throughput and efficiency, but supports a limited range of operations. As a result, PuM architectures cannot efficiently perform some complex operations (e.g., multiplication, division, exponentiation) without sizeable increases in chip area and design complexity. To overcome this limitation in DRAM-based PuM architectures, we introduce pLUTo (processing-using-memory with lookup table [LUT] operations), a DRAM-based PuM architecture that leverages the high area density of DRAM to enable the massively parallel storing and querying of lookup tables (LUTs). The use of LUTs enables pLUTo to efficiently execute complex operations in-memory via memory reads (i.e., LUT queries) instead of relying on complex extra logic or performing long sequences of DRAM commands. pLUTo outperforms the optimized CPU and GPU baselines in performance/energy efficiency by an average of 1960$\times$/307$\times$ and 4.2$\times$/4$\times$ across the evaluated workloads, and by 33$\times$/8$\times$ and 110$\times$/80$\times$ for the LeNet-5 quantized neural network. pLUTo outperforms a state-of-the-art PiM baseline by 50$\times$/342$\times$ in performance/energy efficiency.

Task-Level Authoring for Remote Robot Teleoperation.

Remote teleoperation of robots can broaden the reach of domain specialists across a wide range of industries such as home maintenance, health care, light manufacturing, and construction. However, current direct control methods are impractical, and existing tools for programming robot remotely have focused on users with significant robotic experience. Extending robot remote programming to end users, i.e., users who are experts in a domain but novices in robotics, requires tools that balance the rich features necessary for complex teleoperation tasks with ease of use. The primary challenge to usability is that novice users are unable to specify complete and robust task plans to allow a robot to perform duties autonomously, particularly in highly variable environments. Our solution is to allow operators to specify shorter sequences of high-level commands, which we call task-level authoring, to create periods of variable robot autonomy. This approach allows inexperienced users to create robot behaviors in uncertain environments by interleaving exploration, specification of behaviors, and execution as separate steps. End users are able to break down the specification of tasks and adapt to the current needs of the interaction and environments, combining the reactivity of direct control to asynchronous operation. In this paper, we describe a prototype system contextualized in light manufacturing and its empirical validation in a user study where 18 participants with some programming experience were able to perform a variety of complex telemanipulation tasks with little training. Our results show that our approach allowed users to create flexible periods of autonomy and solve rich manipulation tasks. Furthermore, participants significantly preferred our system over comparative more direct interfaces, demonstrating the potential of our approach for enabling end users to effectively perform remote robot programming.

Hospital preparedness for mass gathering events and mass casualty incidents in Matera, Italy, European Capital of Culture 2019.

Mass Casualty Incidents (MCI) may occur during Mass Gathering Events (MGE). A failure to prepare and train the health care system for potential MCI, can cause chaos and delays in the response, leading to an increased morbidity and mortality. Education and training of staff are crucial for preparedness. In Italy, hospital Emergency Plans for Massive Influx of Injured (in Italian designated with the acronym PEMAF) are mandatory since the '90's. However, when available, they are usually poorly known by the staff, rarely reviewed and validated. In 2014, Matera, a city in Southern Italy, was designated as the European Capital of Culturefor 2019. As a result, we took this opportunity to revise the "Madonna delle Grazie" PEMAF and to start a program for increasing the awareness of the plan among the medical staff and provide specific training for MCI management. The PEMAF was reviewed through simulations that involved the entire staff. A partnership with the International Association for Medical Response to Major Incidents & Disasters (MRMI) led to the support of experts and to the organization of residential courses based on the MAss Casualty SIMulation tool (MACSIM®). In total, six residential educational events of MACSIM-PEMAF were organized. Individual capacity was tested before and after the education through self-administered semi-quantitative questionnaires. All the available resources were mapped and the functional areas identified. Alert, coordination and command sequences were defined. The communication network was improved. Documentation and registration systems were developed. Standard operational procedures (action cards) were created for the key positions. The knowledge and capacity to function in active roles during a MCI was improved among the participants in the educational program. MGE are great opportunities for the development of the hosting community but also represent an increased risk of MCI. Preparedness is mandatory for health care systems. The educational format MACSIM-PEMAF seems to be adequate to review and improve the existing plans and transfer specific skills to attendants.

Application of Bioinformatics Algorithms for 3RO\PRUSKLF Cyberattacks Detection

The functionality of any system can be represented as a set of commands that lead to a change in the state of the system. The intrusion detection problem for signature-based intrusion detection systems is equivalent to matching the sequences of operational commands executed by the protected system to known attack signatures. Various mutations in attack vectors (including replacing commands with equivalent ones, rearranging the commands and their blocks, adding garbage and empty commands into the sequence) reduce the effectiveness and accuracy of the intrusion detection. The article analyzes the existing solutions in the field of bioinformatics and considers their applicability for solving the problem of identifying polymorphic attacks by signature-based intrusion detection systems. A new approach to the detection of polymorphic attacks based on the suffix tree technology applied in the assembly and verification of the similarity of genomic sequences is discussed. The use of bioinformatics technology allows us to achieve high accuracy of intrusion detection at the level of modern intrusion detection systems (more than 0.90), while surpassing them in terms of cost-effectiveness of storage resources, speed and readiness to changes in attack vectors. To improve the accuracy indicators, a number of modifications of the developed algorithm have been carried out, as a result of which the accuracy of detecting attacks increased by up to 0.95 with the level of mutations in the sequence up to 10%. The developed approach can be used for intrusion detection both in conventional computer networks and in modern reconfigurable network infrastructures with limited resources (Internet of Things, networks of cyber-physical objects, wireless sensor networks).

Robust PDF Document Conversion using Recurrent Neural Networks

The number of published PDF documents in both the academic and commercial world has increased exponentially in recent decades. There is a growing need to make their rich content discoverable to information retrieval tools. Achieving high-quality semantic searches demands that a document's structural components such as title, section headers, paragraphs, (nested) lists, tables and figures (including their captions) are properly identified. Unfortunately, the PDF format is known to not conserve such structural information because it simply represents a document as a stream of low-level printing commands, in which one or more characters are placed in a bounding box with a particular styling. In this paper, we present a novel approach to document structure recovery in PDF using recurrent neural networks to process the low-level PDF data representation directly, instead of relying on a visual re-interpretation of the rendered PDF page, as has been proposed in previous literature. We demonstrate how a sequence of PDF printing commands can be used as input into a neural network and how the network can learn to classify each printing command according to its structural function in the page. This approach has three advantages: First, it can distinguish among more fine-grained labels (typically 10-20 labels as opposed to 1-5 with visual methods), which results in a more accurate and detailed document structure resolution. Second, it can take into account the text flow across pages more naturally compared to visual methods because it can concatenate the printing commands of sequential pages. Last, our proposed method needs less memory and it is computationally less expensive than visual methods. This allows us to deploy such models in production environments at a much lower cost. Through extensive architectural search in combination with advanced feature engineering, we were able to implement a model that yields a weighted average F1 score of 97% across 17 distinct structural labels. The best model we achieved is currently served in production environments on our Corpus Conversion Service (CCS), which was presented at KDD18. This model enhances the capabilities of CCS significantly, as it eliminates the need for human annotated label ground-truth for every unseen document layout. This proved particularly useful when applied to a huge corpus of PDF articles related to COVID-19.

A novel integrating between tool path optimization using an ACO algorithm and interpreter for open architecture CNC system

This article proposes an effective methodology to reduce manufacturing time through the creation of quasi-optimal G command sequences, based on initial machining codes derived from CAD/CAM Service-Oriented Architecture (SOA) software. The optimization steps involved minimizing travel path time for CNC manufacturing machine milling and drilling. Also, identifying the optimal order of operation that enabled the shortest travel path for the cutting tool. These steps resulted in consistent enhancements of approximately 10.41% and 16.58% for milling and drilling machining, respectively. Furthermore, high-performing Ant Colony Optimization (ACO) algorithms were used to optimize the travel path time. In the context of automatic NC program production, the optimization of the cutting tool’s travel path could be achieved by integrating the ACO algorithm and the Open Architecture Control (OAC) into commercial CAD/CAM. In this paper, a new optimized generation of CNC systems, based on combining the Open Architecture Control (OAC) technology supported by the G-code data model and the optimization algorithm are presented.

Implementation of an optimization algorithm using modified Lagrange functions on the example of a steel hinge-rod system

An example of the optimal design of a steel truss with the use of modified Lagrange functions is considered. To solve the problem, it is necessary to select the cross-sectional areas of the truss at a given interval by minimizing its volume, provided that the regulatory requirements for strength and rigidity are met. The external diameters of the sections of the truss elements vary. A detailed algorithm for solving the problem is presented. The algorithm is implemented in the mathematical package MathCAD, which allows you to visually trace the sequence of commands, as well as receive graphs reflecting the state of the problem at each iteration.

Обнаружение вредоносного программного обеспечения с использованием искусственной нейронной сети на основе адаптивно-резонансной теории

The process of detecting malicious code by anti-virus systems is considered. The main part of this process is the procedure for analyzing a file or process. Artificial neural networks based on the adaptive-resonance theory are proposed to use as a method of analysis. The graph2vec vectorization algorithm is used to represent the analyzed program codes in numerical format. Despite the fact that the use of this vectorization method ignores the semantic relationships between the sequence of executable commands, it allows to reduce the analysis time without significant loss of accuracy. The use of an artificial neural network ART-2m with a hierarchical memory structure made it possible to reduce the classification time for a malicious file. Reducing the classification time allows to set more memory levels and increase the similarity parameter, which leads to an improved classification quality. Experiments show that with this approach to detecting malicious software, similar files can be recognized by both size and behavior.

GroupTracer: Automatic Attacker TTP Profile Extraction and Group Cluster in Internet of Things

As Advanced Persistent Threat (APT) becomes increasingly frequent around the world, security experts are starting to look at how to observe, predict, and mitigate the damage from APT attacks. In the meantime, the Internet of things devices are also risky and heavily exposed to the Internet, making them more easily used by hacker organizations to launch APT attacks. An excellent attacker can take down millions of Internet of things devices in a short time. Once the IoT botnet is built, attackers can use it to launch complex attacks which could damage Internet infrastructure and cause network disconnection. This paper proposes GroupTracer, a framework for observing and predicting the Internet of things attacks. GroupTracer is designed to automatically extract the TTP profiles (i.e., tactics, techniques, and procedures) that can describe the behavior of attackers through their tactics, techniques, and processes and dig out the potential attacker groups behind complex attacks. Firstly, it captures attacks by IoT honeypots and extracts relevant fields from logs. Then, attack behaviors are automatically mapped to the ATT&CK framework to achieve automatic TTP profiles extraction. After that, GroupTracer presents four feature groups, including TTP profiles, Time, IP, and URL features, a total of 18 features, mines potential attack groups through hierarchical clustering algorithm, and compares the clustering results with two baseline algorithms. As the ground truth labels are unknown, we apply three internal validation indexes to evaluate the cluster quantity. Experimental results showed that the proposed framework has achieved an excellent performance in exploiting potential groups as the Calinski–Harabasz index reaches 3416.93. Eventually, attack trees are generated for each cluster where nodes indicate attack commands and edges represent command sequences. These attack trees could help better understand each attack group’s actions and techniques.

A Note on Generalized Solution of a Cauchy Problem Given by a Nonhomogeneous Linear Differential System

Abstract Generalized solution of a Cauchy problem given by a nonhomogeneous linear differential system is recovered to this approach. It considers the case of the free term having at most countable number of discontinuity points. The method, called successive approach, uses the solution on the previous interval (except the first one) for the condition on the given interval. The sequence of commands for a computer algebra system to this method is given.