Logic Simulation Research Articles

Effects of The Application of Logic Gate Simulator Media in Improving The Results and Learning Activities of XI Grade Vocational High School Students

This literature review evaluates 12 previous studies on the use of simulation software in learning digital electronics and logic gates, with the aim of analysing its impact on student learning outcomes and activities. Various simulation software such as Proteus, Logisim, Circuit Wizard, and others are used to improve students' understanding of complex concepts, practical skills, and motivation in the subjects of electronics and digital logic. The results show that simulation software effectively improves student learning outcomes, engagement, and motivation by providing practical and interactive experiences without the need for expensive physical components. However, challenges such as limited access to the required hardware and the need for proper teacher training were also highlighted. Despite these challenges, this study shows that simulation software is a promising tool for improving the quality of electronics and digital logic learning if it is properly implemented and supported by adequate infrastructure.

Возможности внедрения инновационных технологий в управление переработкой техногенных месторождений в Российской Федерации

This article highlights the specifics of processing modern man-made deposits in the Russian Federation. Based on the analysis of modern scientific literature, the authors have identified the prospects for processing such deposits in our country. The publication demonstrates the results of a logical simulation analysis, which makes it possible to assess the potential for using raw materials from modern man-made deposits. The possibilities and role of artificial intelligence, blockchain, augmented, virtual, and mixed realities in the complex processing of man-made deposits near large and major cities of the country are also being considered. As a result of the research, it was found that, on the scale of the Russian Federation, it is possible to apply an experimental legal regime for the introduction of innovative technologies and solutions by companies for the purpose of systemat-ic processing of existing technogenic deposits.

Unveiling Cross-checking Opportunities in Verilog Compilers

The landscape of Verilog toolchains for electronic design automation (EDA) is diverse, and their reliability is crucial, as errors can lead to significant debugging challenges and delays in development. Methodologies such as testing and formal verification have been applied to identify and eliminate defects in these toolchains. We propose a framework named VeriXmith to interconnect design tools involved in logical synthesis and simulation for cross-checking. These tools process circuit designs and produce outputs in different languages, such as Verilog netlists from synthesizers and C++ programs from simulators. Since these outputs represent the same circuit semantics, we can leverage this semantic consistency to verify the tools that translate one representation into another. Our approach involves creating semantics extractors to extend the range of circuit representations available for semantic equivalence checking by converting them into a canonical and comparable form. Additionally, we develop mutation operators for Verilog designs to introduce new data/control paths and language constructs, enhancing the diversity of circuit designs as test inputs. By validating semantic equivalence, our framework successfully identifies defects in existing Verilog toolchains. An exploratory experiment uncovers 31 previously unknown bugs in well-known open-source Verilog tools, including Verilator and Yosys.

An integrated simulation system using fuzzy logic and network simulator 3 (ns-3) for actor node selection in wireless sensor and actor networks (WSANs): Performance evaluation considering different parameters

The wireless sensor and actor networks (WSANs) are considered a fundamental technology for the Internet of Things (IoT). These networks comprise numerous sensor and actor nodes and are anticipated to be utilized in various sectors. In WSANs, actor nodes must be positioned and moved optimally to ensure an efficient communication network among the actor nodes, as well as connecting actor nodes with sensor and other actor nodes. This research focuses on the selection process of actor nodes within WSANs. The proposed system selects the optimal actor node by employing fuzzy logic (FL) and the network simulator 3 (ns-3). We investigate the performance of the proposed FL-based system by taking into account three parameters: distance to event from actor (DEA), number of sensors per actor (NSA), and task accomplishment time (TAT). The output parameter is the actor selection decision (ASD). We carried out qualitative evaluation by FL-based system. The simulation results revealed that ASD decreases as TAT, NSA, and DEA increase. We carried out a quantitative evaluation by using the ns-3 simulator. The performance evaluation demonstrated that packet loss increases by increasing NSA. Also, as TAT increases, both packet loss and delay time increase. Among the three actor nodes, Actor2 exhibited the best performance.

A Label Free Fluorescent Aptamer Sensor Based on the Combined Action of Graphene Oxide and SYBR Green I for the Detection of Aflatoxin B1.

Here, based on the characteristics of Graphene oxide(GO) and SYBR Green I(SGI) dye, an enzyme-free and label-free fluorescent biosensor with signal amplification through DNA strand reaction is proposed for the detection of Aflatoxin B1(AFB1) in food safety. Firstly, without the addition of AFB1, the substrate in the system includes a double stranded Apt-S with a long sticky end and two hairpins H1 and H2. Although the complementary pairing of bases may exhibit fluorescence due to the insertion of SGI dyes, the use of GO, which is highly capable of adsorbing single stranded parts and quenching fluorescence, cleverly reduces the background fluorescence. Adding the target AFB1 triggers DNA inter chain reactions, generating a large amount of long double stranded DNA H1-H2, thereby generating strong fluorescence signals under the action of SGI. More importantly, logical theory verification and computer simulation were conducted before biological experiments, providing a theoretical basis for the implementation of the biosensor. After analysis, the fluorescence biosensor exhibits a good linear relationship with AFB1 concentration in the range of 5-50nM, with a detection limit of 0.76nM. It also has good specificity, anti-interference ability, and practical application ability, and has broad application prospects in the field of food safety.

Simulation of fuzzy logic and PI control methods on a bridgeless isolated SEPIC converter for electric vehicle chargers

Studies in literature and the increasing trend of electrification show that electric vehicles (EVs) will become more widespread in the future. However, the growing demand for EV chargers causes an overload on the grid. Furthermore, EV chargers generate power factor distortion and harmonics, which contaminate the grid and lower the quality of power. Therefore, power factor correction (PFC) is applied by EV chargers to mitigate the harmonics. As defined in the IEC 61000-3-2 standard, the total harmonic distortion (THD) shall be less than 5%. In this study, a better PFC operation is achieved with the proposed bridgeless isolated single ended primary inductor converter (BL SEPIC) topology as an EV charger instead of conventional converter topologies that have diode bridge rectifiers (DBR). Also, the study has better THD outputs as compared with the similar bridgeless (BL) topologies in literature thanks to the simulated control methods of the proportion-integration (PI) and fuzzy control. Moreover, these control methods are compared with each other in terms of THD suppression performance, stability, robustness, and computational effort. The results showed that the fuzzy controller has advantages of stability and robustness against the transient conditions, input voltages and load changes for THD suppression while the PI controller has better THD results only for steady state operation with nominal input voltage and full load conditions. The implemented PI and fuzzy controllers are simulated in a MATLAB Simulink environment.

Urban flood risk assessment using fuzzy logic and real-time flood simulation model – a geomatics techniques

Urban flood risk assessment using fuzzy logic and real-time flood simulation model – a geomatics techniques

Logical Simulation of an Automated Technological System of Operations

Logical Simulation of an Automated Technological System of Operations

Timing issues on power side-channel leakage of advanced encryption standard circuits designed by high-level synthesis

In recent years, field programmable gate array (FPGA) have been used in many internet of things (IoT) devices and are equipped with cryptographic circuits to ensure security. However, they are exposed to the risk of cryptographic keys being stolen by side-channel attacks. Countermeasures against side-channel attacks have been developed, but they are becoming more of a threat to IoT devices due to the diversity of attacks. Therefore, it is necessary to understand the basic characteristics of side-channel attacks. Therefore, this study clarifies the relationship between two timing issues, the clock period of the circuit and the power sampling interval, and the amount of side-channel leakage. We design seven advanced encryption standard (AES) circuits with different clock periods and conduct empirical experiments using logic simulations to clarify the correlation between the two timings and the amount of side-channel leakage. T-test is used to evaluate the leakage amount, which is evaluated based on four metrics. From the results, we argue that the clock period and sampling interval do not interfere with each other in the side-channel leakage amount.

A system model to repurpose slag into alternative brick solution for low-cost housing

The world’s leading producer of Platinum Group Metal is South Africa and accounts for 94 percent of world’s platinum. Platinum smelters produces around 10 525,90 tons of slag annual of which accumulates as stockpile, never utilised. More storage area is required for continuous operation of the smelters to store slag. The aim of the research is to repurpose the slag into bricks for low-cost housing. Any Logic simulation model specifically the Discrete Event Modelling (DEM) was employed for the modelling and simulation because of its capabilities compared to other models such as Flexsim, Vensim, ANSYS. The results indicate that 92 human resources are required to have functioning business that is able to manufacture and deliver bricks enough to build 326 houses per month. The operation is labour intensive to ensure more job opportunities are created and a total 368 personnel are employed permanently on all sites. The smelter potentially saves over R1,5 billion per operation and R5,6 billion across 4 sites over a decade by giving the slag away for free. The environmental pollution is improved as five heavy plant equipment is removed from the operation. The operation has potential to generate R392,2 million profit over 10-years.

Analysis and simulation of the operational capacity of a rail motorway terminal

This work aims to analyze the factors that influence the operational time at a railway-motorway intermodal terminal, with a specific focus on the loading and unloading of trains with semi-trailers. This operation is commonly referred to as a rail motorway intermodal process. The terminal under analysis is the Zaragoza-PLAZA intermodal terminal, located in Zaragoza, Spain. Using AnyLogic® PLE, a discrete event and block-based logic simulation software, a model is developed to realistically simulate the terminal's operations, offering potential improvements. The model enables observation of the terminal's behavior by modifying certain parameters. The results obtained can be directly applied to the existing terminal for performance enhancements. Finally, a sensitivity analysis of the model is conducted, allowing us to assess how various factors influence the terminal's operations.

Computer Design of the Regulating Working Element of the Channel Cleaning Equipment

Cleaning devices of channel systems used for irrigation of agricultural plants and mechatronic parts regulating their operations were analyzed, the issues of automation of construction design, measurement and management in this field were examined and the purpose of the work was determined. As the goal of the work, the issue of automation of the construction design, technological measurement and management process of the working body for efficient cleaning of small and medium-sized concrete-covered channels, bathtubs from sludge and weeds was set. A complex scheme of information, algorithmic and software support for the automation of the design, technological measurement and control of the mechatronic parts of the working body used for cleaning the channel and bathtub was proposed, and the issues of logical modeling and simulation of the drawing of 2- and 3-dimensional images of the working body were solved. Algorithms were developed using the production modeling method to automate the process of technological measurement, implementation and management, which accurately regulates the operations of the working body of the mechanical device of complex construction. In Solid Edge 2D, 3D software environments, the determination of the geometric shapes of the individual mechanical parts of the channel cleaning unit with a milling cutter, their sizes and types of materials is ensured, and the algorithm was developed using the logical modeling method. For the automation of the structural design process, the information security of the mechanical parts of the application object and the elements of the new design milling cutter device was created for the management of the database of drawings.

SKALP: Secure key agreement and lightweight protocol for dew‐assisted IoT enabled edge computing

AbstractThe Internet of Things (IoT) is a transformative technology that has found applications in diverse domains, including automation, logistics, grid, transportation, healthcare, and more. In these domains, IoT systems generate a significant amount of data, which can be stored in a cloud. However, cloud computing may not be practical in certain delay‐sensitive IoT applications with complex operations. To address this, fog and edge computing paradigms have been introduced, but they rely on a reliable internet connection for proper functioning. The dew computing paradigm, a novel concept, allows the execution of various applications in the IoT environment, with or without internet connectivity. However, ensuring data confidentiality and integrity during transmission and storage in such an environment remains a significant challenge. Therefore, a fail‐safe and highly effective security mechanism is yet to be proposed. This study introduces a protocol that utilizes the elliptic curve cryptography and secure hash algorithm to design a secure key agreement and lightweight protocol (SKALP). SKALP security is formally analyzed using BAN (Burrows‐Abadi‐Needham) logic, ROM (Random Oracle Model), RoR (Real‐Or‐Random) model, and ProVerif (Protocol Verifier) simulation while informally discussing it to evaluate its resistance against well‐known attacks. Additionally, the performance analysis of SKALP considers the costs associated with communication and computation. The findings from the comparative analysis indicate that the SKALP demonstrates a higher level of superiority than its competitors.

Design and Simulation of Balanced Ternary Priority Encoder

Design and Simulation of Balanced Ternary Priority Encoder

Quantitative Risk Analysis for Construction Projects Considering Risks Correlations and Fuzzy Logic

Construction projects have a high level of uncertainty because of several risk factors. Risks may affect projects in many ways resulting in time delays or cost overruns. Thus, the evaluation of uncertainty is required to get a reliable schedule. This research proposes a method for project scheduling considering risks. Expert judgment is used to identify and analyze risks. Potential risks are identified through Failure Mode Effect Analysis (FMEA). Risks impact is evaluated through fuzzy logic and Monte Carlo Simulation (MCS). The simulation considered the relationship between risks, and risks and activities.

SEAF-IoD: Secure and efficient user authentication framework for the Internet of Drones

SEAF-IoD: Secure and efficient user authentication framework for the Internet of Drones

A Lightweight Symmetric Cryptography based User Authentication Protocol for IoT based Applications

The utilization of IoT is expanding across various domains, including telecare, intelligent home systems, and transportation networks. In these environments, IoT devices generate data gathered on remote servers, requiring external users to authenticate themselves to access the data. However, existing authentication protocols for IoT must meet the crucial requirements of speed, security against multiple attacks, and ensuring user anonymity and un-traceability. The main objective of this work is to find lightweight symmetric cryptography-based user authentication protocol tailored for IoT-based applications, focusing on MIM (Man-in-the-Middle) attack prevention, enhanced anonymity, and secure communication between IoT nodes and remote servers via IoT gateways. Existing protocols often lack sufficient defenses against MIM attacks and do not adequately address the need for enhanced user anonymity and secure communication channels within the IoT framework. Our research has identified that authentication techniques based on pairing are susceptible to attacks targeting temporary session-specific data, impersonation, privileged insiders, and offline password guessing. Furthermore, using bilinear pairing in these techniques requires significant computational and communication resources to address the security as mentioned above concerns. A new authentication mechanism must be proposed and designed explicitly for IoT scenarios. The proposed approach exclusively utilizes hash and exclusive-or operations to ensure suitability within the IoT context; thoroughly evaluated the recommended protocol against existing authentication protocols, employing both informal and formal analytical routines like BAN logic, ROR model, and AVISPA simulation. Our findings suggest protocol not only enhances performance but also enhances security. The proposed approach is a tried-and-true strategy for improving security rules in practical Internet of Things (IoT) settings addressing the inherent challenges posed by authentication requirements in IoT environments. The accuracy 98.93%, and Node detection rate 46.57% were improved which is a better outcome.

Gate-Level Side-Channel Leakage Ranking With Architecture Correlation Analysis

While side-channel leakage is traditionally evaluated from a fabricated chip, it is more time-efficient and cost-effective to do so during the design phase of the chip. We present a methodology to rank the gates of a design according to their contribution to the side-channel leakage of the chip. The methodology relies on logic synthesis, logic simulation, gate-level power estimation, and gate leakage assessment to compute a ranking. The ranking metric can be defined as a specific test by correlating gate-level activity with a leakage model, or else as a non-specific test by evaluating gate-level activity in response to distinct test vector groups. Our results show that only a minority of the gates in a design contribute most of the side-channel leakage. We demonstrate this property for several designs, including a hardware AES coprocessor and a cryptographic hardware/software interface in a five-stage pipelined RISC processor.

Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training

Recurrent Neural Networks (RNNs) are useful in temporal sequence tasks. However, training RNNs involves dense matrix multiplications which require hardware that can support a large number of arithmetic operations and memory accesses. Implementing online training of RNNs on the edge calls for optimized algorithms for an efficient deployment on hardware. Inspired by the spiking neuron model, the Delta RNN exploits temporal sparsity during inference by skipping over the update of hidden states from those inactivated neurons whose change of activation across two timesteps is below a defined threshold. This work describes a training algorithm for Delta RNNs that exploits temporal sparsity in the backward propagation phase to reduce computational requirements for training on the edge. Due to the symmetric computation graphs of forward and backward propagation during training, the gradient computation of inactivated neurons can be skipped. Results show a reduction of ∼80% in matrix operations for training a 56k parameter Delta LSTM on the Fluent Speech Commands dataset with negligible accuracy loss. Logic simulations of a hardware accelerator designed for the training algorithm show 2-10X speedup in matrix computations for an activation sparsity range of 50%-90%. Additionally, we show that the proposed Delta RNN training will be useful for online incremental learning on edge devices with limited computing resources.

AUTOMATION OF PETROLEUM STORAGE TANK LEAKAGE THROUGH PRODUCT TRANSFER CONTROL USING PROGRAMMABLE LOGIC CONTROLLER

Industrial storage tanks have always been a critical part of the petrochemical industry due to their capacity to either act as a buffer to other plant processes or simply to store enormous amounts of fluids for a long period of time in a controlled environment. These petroleum storage tanks are supposedly constructed to follow specific sets of instructions guided by the American Petroleum Industry from the type of material used up to the welding procedure. But due to inefficient construction, unmaintained and uninspected problems, welding defects, and environmental concerns among others, a leak in a storage tank can occur and will be a major problem as this can cause fire, explosion, and environmental hazards. Additionally, due to tensions between Ukraine and the Russian government and the succeeding Russian ban on oil imports, the cost of 1 barrel of oil rises at an alarming since 2020. With that in mind, an automation procedure is proposed by the researchers, to save as much of this oil from leaking and being unusable and to reduce the causes of further accidents. This paper not only seeks to use an existing tank layout, with currently installed level indicator transmitters, motor-operated control valves, and other equipment, but also to introduce flammable gas detectors that could detect the leaked petroleum on the ground and would initiate the automation procedure. The automation setup was realized by flowcharts, PLC, and ladder logic simulation using Picosoft software. Automation procedures are analyzed wherein the tanks are being filled, the trucks are being loaded, a leaking tank has its contents pumped to another tank, and a leaking tank has its contents pumped to the truck loading station. Results show that a minimum number of 8.89 barrels of oil saved could breakeven the cost of an estimated amount of $80-90 dollars per barrel of oil can be saved by the proposed automation.