In this paper, we describe the design of an electrically large anechoic chamber for usage on millimetre-wave bands. Ansys Savant sotware was used to perform a simulation of the chamber, using physical optics coupled with uniform theory of diffraction (PO/UTD). Moreover, a method based on an open waveguide probe is described in this paper to obtain the electrical properties of the RF absorbers at millimetre-wave frequencies. Two different source antennas were simulated in this work and the corresponding quiet zones predicted. The largest quiet zone was $30\mathrm{m}\mathrm{m}\times 30\mathrm{m}\mathrm{m}\times 50\mathrm{m}\mathrm{m}$ , for a chamber size of $1.2\mathrm{m}\mathrm{m}\times 0.6\mathrm{m}\mathrm{m}\times 0.6\mathrm{m}$ . Full article

In this paper, a novel hardware architecture for neuroevolution is presented, aiming to enable the continuous adaptation of systems working in dynamic environments, by including the training stage intrinsically in the computing edge. It is based on the block-based neural network model, integrated with an evolutionary algorithm that optimizes the weights and the topology of the network simultaneously. Differently to the state-of-the-art, the proposed implementation makes use of advanced dynamic and partial reconfiguration features to reconfigure the network during evolution and, if required, to adapt its size dynamically. This way, the number of logic resources occupied by the network can be adapted by the evolutionary algorithm to the complexity of the problem, the expected quality of the results, or other performance indicators. The proposed architecture, implemented in a Xilinx Zynq-7020 System-on-a-Chip (SoC) FPGA device, reduces the usage of DSPs and BRAMS while introducing a novel synchronization scheme that controls the latency of the circuit. The proposed neuroevolvable architecture has been integrated with the OpenAI toolkit to show how it can efficiently be applied to control problems, with a variable complexity and dynamic behavior. The versatility of the solution is assessed by also targeting classification problems. Full article

In this paper, a sense-amplifier-based flip-flop (SAFF) suitable for low-power high-speed operation is proposed. With the employment of a new sense-amplifier stage as well as a new single-ended latch stage, the power and delay of the flip-flop is greatly reduced. A conditional cut-off strategy is applied to the latch to achieve glitch-free and contention-free operation. Furthermore, the proposed SAFF can provide low voltage operation by adopting MTCMOS optimization. Post-layout simulation results based on a SMIC 55 nm MTCMOS show that the proposed SAFF achieves a 41.3% reduction in the CK-to-Q delay and a 36.99% reduction in power (25% input data toggle rate) compared with the conventional SAFF. Additionally, the delay and the power are smaller than those of the master-slave flip-flop (MSFF). The power-delay-product of the proposed SAFF shows 2.7× and 3.55× improvements compared with the conventional SAFF and MSFF, respectively. The area of the proposed flip-flop is 8.12 μm² (5.8 μm × 1.4 μm), similar to that of the conventional SAFF. With the employment of MTCMOS optimization, the proposed SAFF could provide robust operation even at supply voltages as low as 0.4 V. Full article

Intelligent transport systems (ITS) are a convergence of information technology and transportation systems as seen in the variable speed limit (VSL) system. Since the VSL system controls the speed limit according to the traffic conditions, it can improve the safety and efficiency of a transport network. Many researchers have studied the real-time VSL (RVSL) algorithm based on real-time traffic information from multiple stations recording traffic data. However, this method can suffer from inaccurate selection of the VSL start station (VSS), incorrect VSL calculations, and is unable to quickly react to the changing traffic conditions. Unstable VSL systems result in more congestion on freeways. In this study, an enhanced VSL algorithm (EVSL) is proposed to address the limitations of the existing RVSL algorithm. This selects preliminary VSL start stations (pVSS), which is expected to end congestion using acceleration and allocates final VSSs for each congestion interval using selected pVSS. This controls the vehicles that entered the congestion area based on the selected VSS. We used four metrics to evaluate the performance of the proposed VSL (VSS stability assessment, speed control stability assessment, travel time, and shockwave), which were all enhanced when compared to the standard RVSL algorithm. In addition, the EVSL algorithm showed stable VSL performance, which is critical for road safety. Full article

Network intrusion detection is one of the main problems in ensuring the security of modern computer networks, Wireless Sensor Networks (WSN), and the Internet-of-Things (IoT). In order to develop efficient network-intrusion-detection methods, realistic and up-to-date network flow datasets are required. Despite several recent efforts, there is still a lack of real-world network-based datasets which can capture modern network traffic cases and provide examples of many different types of network attacks and intrusions. To alleviate this need, we present LITNET-2020, a new annotated network benchmark dataset obtained from the real-world academic network. The dataset presents real-world examples of normal and under-attack network traffic. We describe and analyze 85 network flow features of the dataset and 12 attack types. We present the analysis of the dataset features by using statistical analysis and clustering methods. Our results show that the proposed feature set can be effectively used to identify different attack classes in the dataset. The presented network dataset is made freely available for research purposes. Full article

Pointed at a problem that leads to the high complexity of the production management tasks in the multi-stage spinning industry, mixed flow batch production is often the case in response to a customer’s personalized demands. Manual handling cans have a large number of tasks, and there is a long turnover period in their semi-finished products. A novel heuristic research was conducted that considered mixed-flow shop scheduling problems with automated guided vehicle (AGV) distribution and path planning to prevent conflict and deadlock by optimizing distribution efficiency and improving the automation degree of can distribution in a draw-out workshop. In this paper, a cross-region shared resource pool and an inter-regional independent resource pool, two AGV predictive scheduling strategies are established for the ring-spinning combing process. Besides completion time, AGV utilization rate and unit AGV time also analyzed with the bottleneck process of the production line. The results of the optimal computational experiment prove that a draw frame equipped with multi-AGV and coordinated scheduling optimization will significantly improve the efficiency of can distribution. Flow-shop predictive modeling for multi-AGV resources is scarce in the literature, even though this modeling also produces, for each AGV, a control mode and, if essential, a preventive maintenance plan. Full article

For the last four decades, several steering systems for vehicles such as active front steering (AFS), front wheel independent steering (FWIS), 4-wheel steering (4WS) and 4-wheel independent steering (4WIS) have been proposed and developed. However, there have been few approaches for comparison among these steering systems with respect to yaw rate tracking or path tracking performance. This paper presents comparison among AFS, FWIS, 4WS and 4WIS in terms of vehicle stability control. In view of vehicle stability control, these systems are used as an actuator for generation of yaw moment. Direct yaw moment control is adopted to calculate a control yaw moment. Distribution from the control yaw moment into tire forces is achieved by a control allocation method. From the calculated tire forces, the steering angles of FWIS, 4WS and 4WIS are determined with a lateral tire force model. To check the performance of these actuators, simulation is conducted on vehicle simulation packages, CarSim. From the simulation, the advantages of FWIS and 4WIS are revealed over AFS and 4WS. Full article

Finite-state machines (FSMs) and the W method have been widely used in software testing. However, the W method fails to detect post-processing errors in the implementation under test (IUT) because it ends testing when it encounters a previously visited state. To alleviate this issue, we propose an enhanced fault-detection W method. The proposed method does not stop the test, even if it has reached a previously visited state; it continues to test and check the points that the W method misses. Through various case studies, we demonstrated software testing using the W method and the proposed method. From the results, it can be inferred that the proposed method can more explicitly determine the consistency between design and implementation, and it is a better option for testing larger software. Unfortunately, the testing time of the proposed method is approximately 1.4 times longer than that of the W method because of the added paths. However, our method is more appropriate than the W method for software testing in safety-critical systems, even if this method is time consuming. This is because the error-free characteristics of a safety-critical system are more important than anything else. As a result, our method can be used to increase software reliability in safety-critical embedded systems. Full article

A novel wearable solution using soft robotic sensors (SRS) has been investigated to model foot-ankle kinematics during gait cycles. The capacitance of SRS related to foot-ankle basic movements was quantified during the gait movements of 20 participants on a flat surface as well as a cross-sloped surface. In order to evaluate the power of SRS in modeling foot-ankle kinematics, three-dimensional (3D) motion capture data was also collected for analyzing gait movement. Three different approaches were employed to quantify the relationship between the SRS and the 3D motion capture system, including multivariable linear regression, an artificial neural network (ANN), and a time-series long short-term memory (LSTM) network. Models were compared based on the root mean squared error (RMSE) of the prediction of the joint angle of the foot in the sagittal and frontal plane, collected from the motion capture system. There was not a significant difference between the error rates of the three different models. The ANN resulted in an average RMSE of 3.63, being slightly more successful in comparison to the average RMSE values of 3.94 and 3.98 resulting from multivariable linear regression and LSTM, respectively. The low error rate of the models revealed the high performance of SRS in capturing foot-ankle kinematics during the human gait cycle. Full article

To compromise between the system performance and hardware cost, millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems have been regarded as an enabling technology for the fifth generation of mobile communication systems (5G). This paper considers a low-complexity angular-domain compressing based detection (ACD) for uplink multi-user mmWave massive MIMO systems, which involves hybrid analog and digital processing. In analog processing, we perform angular-domain compression on the received signal by exploiting the sparsity of the mmWave channel to reduce the dimension of the signal space. In digital processing, the proposed ACD scheme works well with zero forcing (ZF)/maximum ratio combining (MRC)/minimum mean square error (MMSE) detection schemes. The performance analysis of the proposed ACD scheme is provided in terms of achievable rates, energy efficiency and computational complexity. Simulations are carried out and it shows that compared with existing works, the proposed ACD scheme not only reduces the computational complexity by more than $50\%$ , but also improves the system’s achievable rates and energy efficiency. Full article

Acute lymphoblastic leukemia is a well-known type of pediatric cancer that affects the blood and bone marrow. If left untreated, it ends in fatal conditions due to its proliferation into the circulation system and other indispensable organs. All over the world, leukemia primarily attacks youngsters and grown-ups. The early diagnosis of leukemia is essential for the recovery of patients, particularly in the case of children. Computational tools for medical image analysis, therefore, have significant use and become the focus of research in medical image processing. The particle swarm optimization algorithm (PSO) is employed to segment the nucleus in the leukemia image. The texture, shape, and color features are extracted from the nucleus. In this article, an improved dominance soft set-based decision rules with pruning (IDSSDRP) algorithm is proposed to predict the blast and non-blast cells of leukemia. This approach proceeds with three distinct phases: (i) improved dominance soft set-based attribute reduction using AND operation in multi-soft set theory, (ii) generation of decision rules using dominance soft set, and (iii) rule pruning. The efficiency of the proposed system is compared with other benchmark classification algorithms. The research outcomes demonstrate that the derived rules efficiently classify cancer and non-cancer cells. Classification metrics are applied along with receiver operating characteristic (ROC) curve analysis to evaluate the efficiency of the proposed framework. Full article

Most cyberattacks use malicious codes, and according to AV-TEST, more than 1 billion malicious codes are expected to emerge in 2020. Although such malicious codes have been widely seen around the PC environment, they have been on the rise recently, focusing on IoT devices such as smartphones, refrigerators, irons, and various sensors. As is known, Linux/embedded environments support various architectures, so it is difficult to identify the architecture in which malware operates when analyzing malware. This paper proposes an AI-based malware analysis technology that is not affected by the operating system or architecture platform. The proposed technology works intuitively. It uses platform-independent binary data rather than features based on the structured format of the executable files. We analyzed the strings from binary data to classify malware. The experimental results achieved 94% accuracy on Windows and Linux datasets. Based on this, we expect the proposed technology to work effectively on other platforms and improve through continuous operation/verification. Full article

With the characteristics of simple structure and low cost, the dendritic neuron model (DNM) is used as a neuron model to solve complex problems such as nonlinear problems for achieving high-precision models. Although the DNM obtains higher accuracy and effectiveness than the middle layer of the multilayer perceptron in small-scale classification problems, there are no examples that apply it to large-scale classification problems. To achieve better performance for solving practical problems, an approximate Newton-type method-neural network with random weights for the comparison; and three learning algorithms including back-propagation (BP), biogeography-based optimization (BBO), and a competitive swarm optimizer (CSO) are used in the DNM in this experiment. Moreover, three classification problems are solved by using the above learning algorithms to verify their precision and effectiveness in large-scale classification problems. As a consequence, in the case of execution time, DNM + BP is the optimum; DNM + CSO is the best in terms of both accuracy stability and execution time; and considering the stability of comprehensive performance and the convergence rate, DNM + BBO is a wise choice. Full article

As engineering is required to answer directly and more heartily than before the requirement of society and markets, we want to answer the following questions. What kind of open innovation channels exist, and how can these channels operate as a knowledge funnel to conquer the growth limit of capitalism in the 4th industrial revolution? At first, we built up the concept model of open innovation engineering from a conceptual experiment and attempted to prove this model by literature reviews. Second, we applied this open innovation concept model at the papers of Society of Open Innovation: Technology, Market, and Complexity (SOI) 2019 Special Issues of Electronics as a preliminary study. Additional field researches on each open innovation engineering channel in addition to research on finding out more open innovation engineering channels are required. Full article

A reliable transmission with QoE (Quality of Experience) guarantee is crucial for internet conversational service applications. However, due to the limited network bandwidth bottleneck effect and the drawback of transmission technology, there exists no mature and open QoE technical solution for this service. In this paper, we focused our attention on a load distribution strategy for multipath relay transmission to meet the QoE requirements of conversational real-time HD video services. It consisted of three stages: First, a series of relay nodes was deployed in the backbone network, and a software defined overlay network was constructed to perform the multipath relay transmission for the service. Second, by an analysis of the QoE feature, a bijection was built for each quantitative QoE and its MOS (Mean Opinion Score) score. Finally, considering the influence of the coupling relation between paths on the service quality in multipath relay transmission, fuzzy cooperative game theory was used to design the service load distribution strategy. Many experiments showed that compared with state-of-the-art methods in the single-path transmission scene, the strategy we designed can dynamically adjust the load distribution of each sub-path according to the change in QoS (Quality of Service) information of the transmission path in real time. While meeting the strict real-time constraints of the service, it can effectively avoid the impact of network random congestion on the service QoE. Full article