Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental Spiking Neural Network: Solving the XOR Paradigm with Metaheuristics

This work presents a supervised training strategy applied to a biorealistic Spiking Neural Network (SNN) with feedforward 2-2-1 architecture. This network uses Izhikevich neurons with regular-spiking behavior. The input layer, which has 2 nodes, generates temporal pulse trains that pass through synaptic conductances. These conductances transform voltages into currents. The receiving currents by 2 hidden-neurons also generate voltage pulses into synaptic conductances towards the output neuron. Each synaptic conductance has 2-parallel Alpha functions, whose weighting factors are found by the Efficient Artificial Bee Colony Algorithm (EABC Algorithm). This is a variant of the Artificial Bee Colony Algorithm (ABC Algorithm). The efficacy of the EABC algorithm in this SNN is shown solving the XOR paradigm.
Deploying Edge Computing Nodes for Large-Scale IoT: A Diversity Aware Approach

The recent advances in microelectronics and communications have led to the development of large-scale Internet of Things (IoT) networks, where tremendous sensory data is generated and needs to be processed. To support real-time processing for large-scale IoT, deploying edge servers with storage and computational capability is a promising approach. In this paper, we carefully analyze the impacting factors and key challenges for edge node (EN) deployment. We then propose a novel three-phase deployment approach which considers both traffic diversity and the wireless diversity of IoT. The proposed work aims at providing real-time processing service for the IoT network and reducing the required number of ENs. We conducted extensive simulation experiments, the results show that compared to the existing works that overlooked the two kinds of diversities, the proposed work greatly reduces the number of ENs and improves the throughput between IoT and ENs.
SEER-MCache: A Prefetchable Memory Object Caching System for IoT Real-Time Data Processing

Memory object caching systems, such as Memcached and Redis, have been proved to be a simple and high-efficient middleware for improving the performance of Internet of Things (IoT) devices querying the database in cloud. However, its performance guarantee is built on the fact that the target data, queried by the IoT device, will be accessed many times and hit in the caching system. Therefore, when database system is handling the unrepeated IoT queries, it usually presents the suboptimal performance, which greatly impairs the efficiency of real-time data processing on IoT devices. To improve this issue, we propose Seer-MCache, the memory object caching system with a smart prefetching (read-ahead) function, to fill up the caching system with the desired data before the intensive IoT queries arriving. Seer-MCache includes a set of rules to launch the specific behaviors of read-head. These rules are able to be customized according to the workload characteristics and system load. We implement a prototype system in Redis (caching layer) and MySQL server (database system). Extensive experiments are conducted to verify the effectiveness of Seer-MCache, the results show that Seer-MCache can improve the performance of read-intensive workload up to 61% (39.5% in average). Meanwhile, the cost of the read-ahead behavior is moderate and controllable.
Calcium transfer across the outer mantle epithelium in the Pacific oyster, Crassostrea gigas

Calcium transport is essential for bivalves to be able to build and maintain their shells. Ionized calcium (Ca2+) is taken up from the environment and eventually transported through the outer mantle epithelium (OME) to the shell growth area. However, the mechanisms behind this process are poorly understood. The objective of the present study was to characterize the Ca2+ transfer performed by the OME of the Pacific oyster, Crassostrea gigas, as well as to develop an Ussing chamber technique for the functional assessment of transport activities in epithelia of marine bivalves. Kinetic studies revealed that the Ca2+ transfer across the OME consists of one saturable and one linear component, of which the saturable component fits best to Michaelis–Menten kinetics and is characterized by a Km of 6.2 mM and a Vmax of 3.3 nM min−1. The transcellular transfer of Ca2+ accounts for approximately 60% of the total Ca2+ transfer across the OME of C. gigas at environmental Ca2+ concentrations. The use of the pharmacological inhibitors: verapamil, ouabain and caloxin 1a1 revealed that voltage-gated Ca2+-channels, plasma-membrane Ca2+-ATPase and Na+/Ca2+-exchanger all participate in the transcellular Ca2+ transfer across the OME and a model for this Ca2+ transfer is presented and discussed.
Micro-UAV onboard vehicle detection: architecture and experiments

In this paper, an onboard processing architecture is proposed for micro fixed-wing unmanned aerial vehicle (UAV). The typical application scenarios include online detection of moving vehicles on the ground. The detection architecture is compatible with extremely limited computing resources provided by the micro UAVs. Eventually, the multi-vehicle detector is composed of saliency-based region proposal and neural network supported classifier. A typical convolutional neural network, connected with the Cifar10 dataset [1], is selected as the classifier, by performance comparisons driven by the annotated datasets. Furthermore, both “progress balance” and “quantity balance” strategies are developed and compared for training sample structure optimizing to reduce misclassification and leakage classification. Under such circumstances, experiments are conducted with onboard imagery of flying micro fixed-wing vehicles during surveillance on multiple moving vehicles on the ground. Experimental results validate the feasibility and effectiveness of the proposed onboard detection architecture. Typically, four-vehicle mAP is promoted from 52.50% to 57.76% by using the unified progress and quantity dataset balance strategy.
Two Elements MIMO Antenna with Asymmetric Coplanar Strip Metamaterial Configuration and EBG Hybrid Isolation

This paper introduces a compact asymmetric coplanar strip (ACS)-fed composite right/left handed (CRLH) multiple input multiple output (MIMO) antenna for multiband operation. The ACS-fed MIMO antenna is designed using two triple band antenna elements, operating at 4.6 GHz, 4.9 GHz and 5.4 GHz with good matching (reflection coefficient is less than −20 dB). By using mushroom like electromagnetic bandgap structure, further mutual coupling isolation (better than 30 dB) is achieved. The overall MIMO antenna size is compact (46.5 × 26 mm2). The MIMO antenna has less than 0.02 envelope correlation coefficient (ECC) and maximum than 9.98 dB diversity gain. The results are simulated using full wave simulations.
Adaptive Full-Duplex Jamming Receiver for Secure D2D Links in Random Networks

Device-to-device (D2D) communication raises new transmission secrecy protection challenges, since conventional physical layer security approaches, such as multiple antennas and cooperation techniques, are invalid due to its resource/size constraints. The full-duplex (FD) jamming receiver, which radiates jamming signals to confuse eavesdroppers when receiving the desired signal simultaneously, is a promising candidate. Unlike existing endeavors that assume the FD jamming receiver always improves the secrecy performance compared with the half-duplex (HD) receiver, we show that this assumption highly depends on the instantaneous residual self-interference cancellation level and may be invalid. We propose an adaptive jamming receiver operating in a switched FD/HD mode for a D2D link in random networks. Subject to the secrecy outage probability constraint, we optimize the transceiver parameters, such as signal/jamming powers, secrecy rates, and mode switch criteria, to maximize the secrecy throughput. Most of the optimization operations are taken off-line and only very limited on-line calculations are required to make the scheme with low complexity. Furthermore, some interesting insights are provided, such as the secrecy throughput is a quasi-concave function. Numerical results are demonstrated to verify our theoretical findings, and to show its superiority compared with the receiver operating in the FD or HD mode only.
Exposing Memory Access Patterns to Improve Instruction and Memory Efficiency in GPUs

Modern computing workloads often have high memory intensity, requiring high bandwidth access to memory. The memory request patterns of these workloads vary and include regular strided accesses and indirect (pointer-based) accesses. Such applications require a large number of address generation instructions and a high degree of memory-level parallelism. This article proposes new memory instructions that exploit strided and indirect memory request patterns and improve efficiency in GPU architectures. The new instructions reduce address calculation instructions by offloading addressing to dedicated hardware, and reduce destructive memory request interference by grouping related requests together. Our results show that we can eliminate 33% of dynamic instructions across 16 GPU benchmarks. These improvements result in an overall runtime improvement of 26%, an energy reduction of 18%, and a reduction in energy-delay product of 32%.
Prevention of depression in first-year university students with high harm avoidance

Abstract High harm avoidance (HA) scores on the temperament and character inventory appear to be a risk factor for depressive disorders and suicide. Since 2012, we have conducted group cognitive behavioral therapy (G-CBT) interventions for students at Nagasaki University with high HA and without depressive disorders, with the aim of preventing depression. Here, we report on the effects of the G-CBT at 1-year follow-up for the 2012 to 2015 period. Forty-two participants with high HA were included in the final analysis. Outcomes were measured with the Beck Depression Inventory II, Manifest Anxiety Scale, 28-item General Health Questionnaire, and Brief Core Schema Scales at baseline, and at 6-month, and 1-year follow-ups. Repeated-measures analyses of variance revealed a significant decrease in mean depressive symptom scores at the 6-month follow-up point; this decrease was maintained at 1 year. Improvements in cognitive schemas were also seen at 6 months and 1 year. We observed improvements in cognitive schemas associated with depression as a result of the G-CBT intervention, with effects maintained at 1 year post-intervention. This intervention may be effective in positively modifying the cognitions of students with HA and preventing future depression.
From verification to synthesis under cost-utility constraints

Various algorithms and tools for the formal verification of systems with respect to their quantitative behavior have been developed in the past decades. Many of these techniques inherently support the automated synthesis of strategies that guarantee the satisfaction of performance or reliability constraints by resolving controllable nondeterministic choices in an adequate way. More recently, such techniques have been further developed towards the analysis or strategy synthesis under multiple cost and utility constraints. This article deals with Markov decision processes (MDPs) for modeling systems and their environment and provides an overview of recent directions for different types of synthesis problems in MDPs that aim to achieve an acceptable cost-utility tradeoff.
Health Information and the Quality and Safety of Care for People With Disability: An Analysis of Australian Reports of Reviewable Deaths in Residential Care

Objective Many Australians with disability live in residential care and require assistance to manage their health information across hybrid care settings encompassing residential care, primary and tertiary care, and allied health. In this study, we examined case study reports on people with disability living in residential care in New South Wales, Australia to (a) identify threats to the quality of care and safety for this vulnerable patient group in relation to health documentation and information infrastructure and (b) evaluate the applicability of a conceptual health information infrastructure model. Methods All 99 case studies were extracted from eight New South Wales Ombudsmen reports of reviewable deaths for a directed content analysis applying a conceptual model of health information infrastructure in residential care. Results Ninety-one percent of case studies (n = 90) contained information relation to documentation. Forty-seven percent of case studies (n = 47) linked failures in documentation to risk of death, and 12% (n = 12) described best practice use of documentation. Threats to quality of care and safety related to poor “coordination” of information, including information not being implemented, poor “communication” across services, and discrepancies between “policy and practice” in health management. Conclusions The conceptual model demonstrated how “coordination” and “communication” of health information relate to tensions between “policy and practice,” influencing the safety and quality of care for people with disability in residential care. The model was a good fit to investigate how health information infrastructure may affect the quality of residential care and could inform holistic digital solutions to deliver safer, integrated, and higher quality care for people with disability.
Phosphatidylinositol 3,5-bisphosphate regulates the transition between trans-SNARE complex formation and vacuole membrane fusion

Phosphoinositides (PIs) regulate a myriad of cellular functions including membrane fusion, as exemplified by the yeast vacuole, which uses various PIs at different stages of fusion. In light of this, the effect of phosphatidylinositol 3,5-bisphosphate (PI(3,5)P2) on vacuole fusion remains unknown. PI(3,5)P2 is made by the PI3P 5-kinase Fab1 and has been characterized as a regulator of vacuole fission during hyperosmotic shock, where it interacts with the TRP Ca2+ channel Yvc1. Here we demonstrate that exogenously added dioctanoyl (C8) PI(3,5)P2 abolishes homotypic vacuole fusion. This effect was not linked to Yvc1, as fusion was equally affected using yvc1Δ vacuoles. Thus, the effects of C8-PI(3,5)P2 on fusion and fission operate through distinct mechanisms. Further testing showed that C8-PI(3,5)P2 inhibited vacuole fusion after trans-SNARE pairing. Although SNARE complex formation was unaffected, we found that C8-PI(3,5)P2 blocked outer leaflet lipid mixing. Overproduction of endogenous PI(3,5)P2 by the fab1T2250A hyperactive kinase mutant also inhibited the lipid mixing stage, bolstering the model in which PI(3,5)P2 inhibits fusion when present at elevated levels. Taken together, this work identifies a novel function for PI(3,5)P2 as a regulator of vacuolar fusion. Moreover, it suggests that this lipid acts as a molecular switch between fission and fusion.
Optimization of Least Significant Bit Steganography Using Genetic Algorithm to Improve Data Security

Instant message is one of popular application for chatting. This application was already equipped with many security features, but most of these applications saved their chat history in the smartphone database. With so many apps on the internet, recover your chat from the application database is not difficult. Our chat could be recovered using the tools, but most of this application cannot retrieve images with the same quality as what we send in conversation. Steganography using Least Significant Bit (LSB) could embed the message in the picture, but this method is more accessible to detect. One of the techniques that could identify the amount of character inserted using LSB is RS Steganalysis. This paper proposes LSB enhancement using Genetic Algorithm to obscure RS Steganalysis. Genetic Algorithm is used to randomize the embedding character in the pixel so the resulting image (stegoimage) would be hard to analyze. The result showed that the stego-image was difficult to recover or analyze by the general extraction method of Least Significant Bit because Genetic Algorithm has randomly embedded the placement of secret message. The experimental results also demonstrated that the Genetic Algorithm is used to obscure RS Steganalysis while maintaining image quality. Using iteration of the experiment showed fitness value decreasing and get better at 5.855 which only alter 5.3% of 65.536 pixels. The increasing amount of character embedded is also increased RS Steganalysis error.
A Car as a Semantic Web Thing: Motivation and Demonstration

Car signal data is usually hard to access, understand and integrate for non automotive domain experts.In this paper, we use semantic technologies for enriching signal data in the automotive industry and access it through Web of Things interactions. This combination allows the access and integration of car data from the web.We built VSSo, a Vehicle Signal ontology based on SOSA/SSN Observations and Actuations, and generated WoT Actions, Events and Properties, enriched with domain metadata. We mapped VSSo to a Web of Things ontology and we developed a Web of Things protocol binding with LwM2M, and made an implementation in a real car.This implementation resulted in a first working prototype, and a number of future improvements required in order to be compliant with automotive standards.
Impact of Voltage Harmonics on Condition Assessment of Polluted Insulator through a Simulation Model

The condition assessment of outdoor high voltage insulators is of prime importance to power utilities. There are numerous indicators used for inferring the surface condition of an insulator based on an analysis of measured leakage current. To date, the assumption by most researchers has been that the supply voltage subject on insulators is sinusoidal with little or no harmonic induced distortion. However, in real-life due to ever increasing trend of using power electronics devices in power network, significant amount of harmonic distortion is common and insulators in the power system are directly subjected to this distortion. Therefore, the effectiveness of all those present indices under purely sinusoidal voltage will become questionable in presence of distorted supply voltage. This work aims to investigate the effect of voltage harmonic contents on the measured leakage current of polluted insulators via a developed simulation model. In this paper, by considering the practical supply voltage distortion, authors have shown the major drawback of present indices based condition assessment techniques. Authors have also tried to provide an optimal solution by proposing a Crest Factor (CF) based distinctive index to overcome the problem, based on simulation results.
Shaping Energy for the Stabilization of an Unmanned Aircfrat

Based on output-feedback, we solve the regulation control problem for a planar vertical take-off and landing device (PVTOL). We use the well-known energy shaped approach together with the I&I method, to derive the corresponding controller. We apply the theorem of LaSalle in the convergence analysis. We validate the obtained control method through numerical experiments.
The Harmonic-Rejection Mixer [A Circuit for All Seasons]

The harmonic-rejection mixer (HRM) dates back to 2001 [1] but has been finding increasingly wider application in radio-frequency (RF) transceivers [2]-[4]. The popularity of HRMs stems from two trends in RF design: the incentive to minimize the number of high-frequency filters and the demand for wide-band radios. In this article, we study the HRM's operation principle and design issues.
Low-Power HEVC 1-D IDCT Hardware Architecture

This paper presents a low-power (High Efficiency Video Coding) HEVC 1-D IDCT (One-Dimension Inverse Discrete Cosine Transform) hardware architecture, employing a bypass engine to reduce power dissipation. The bypass engine reduces power by replacing the regular 1-D IDCT algorithm by much simpler operations when applicable. Due to an average applicability rate of 87.57%, the low-power HEVC 1-D IDCT can substantially reduce the power dissipation with a slight area overhead. ASIC synthesis results estimates the power dissipation in 3.12 mW when operating at 789.32 MHz. Such frequency is enough to real-time encoding of Ultra-High Definition (UHD 4K) videos at 60 frames per second. Moreover, the presented energy saving hardware architecture can reduce 26% in power dissipation when compared to the regular 1-D IDCT hardware architecture.
Circular Patch Array Absorber Design for Oblique Incidence by Using Winding Ratio Model of Transformer

This paper proposes a design method of a circular patch array absorber for oblique incidence by using an equivalent circuit with a transformer. In the equivalent circuit with the transformer, a matching angle of the absorber can be determined by using the winding ratio of the transformer. Hence, a calculation model for obtaining an arbitrary winding ratio of the transformer by using an arrangement period (winding ratio model) is developed. The winding ratio calculated by using the developed model is agreement in with that of simulated by using an electromagnetic (EM) simulator. The absorbers for 30<inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> and 45 <inline-formula><tex-math notation="LaTeX">$^\circ$</tex-math></inline-formula> at 5 GHz are designed by using the developed model, and the incident angle characteristics of the designed absorbers are measured. As the result, the measured and the simulated matching angle are agreed within 5<inline-formula><tex-math notation="LaTeX">$^\circ$ </tex-math></inline-formula>. Therefore, the validity of the proposed method is indicated.
Self Monitoring, Failure-Detection and Decision-Making System to Support E-TrashBot (EEPIS Trash Bin Robot) Operations: Preliminary Report

This paper proposes a self-monitoring and decisionmaking system which is applied to E-TrashBot (EEPIS Trash Bin Robot) to support its operations in collecting trashes. To support its task, we equipped it with an ability to monitor its availability status by considering the remaining batteries condition and the level of fullness of its bin. A bayesian approach is used to decide when the robot should always works or stop by considering three status: the level of fullness of the bin, the level of battery voltage used by motors, and the level of battery voltage used by the embedded personal computer (PC). The robot is also equipped with an ability to communicate with the operator over internet of things (IoT) which is specifically developed by us using TelegramBot. It can sends its status when the robot decides to stop due to a certain condition or it is experiencing a failure or it is contacted by the operator. Our preliminary experiments show that each sub-system can work as we expected.
Experimental study on operator-based integral sliding mode robust nonlinear control for WPT systems

In our previous research on wireless power transfer systems, an operator-based sliding mode control design was proposed to regulate the output voltage. However, the steady-state error exists in the nonlinear control system. In this paper, an operator-based integral sliding mode robust nonlinear control design scheme is proposed to eliminate the steady-state error in the wireless power transfer system. Besides, the robust stability is guaranteed by using robust right coprime factorization approach. Results of simulations and experiments are presented to prove the effectiveness of the proposed control design scheme.