Software Layer Research Articles

Radiation monitoring with plant-based biotas and an automated micronucleus scoring approach

In this work, we investigated the response of the stem cells from the roots of Allium Cepa (meristems) to ionizing and non-ionizing radiations of different qualities. Allium cepa (Onion) is a well-established in-vivo standard model, widely used in cytogenetic studies for different environmental pollutants. Endpoints, such as chromosomal aberrations (CAs), micronuclei (MNs), and disturbance in the mitotic cycle of root meristematic cells of onion are frequently used to determine the cytotoxic and genotoxic potential of different environmental pollutants. Traditionally, these studies have been carried out to assess chemical toxicity, while the toxicity of ionizing radiation has been studied less extensively. We also examined the repurposing of a previously described optical microscope system originally designed for automated non-fluorescent micronucleus (MN) scoring in binucleated peripheral lymphocytes. The microscope system relies on hardware and software layers in parallel in order to optimize the performance in automated MN scoring.

Machine Learning-Enhanced Radio Tomographic Device for Energy Optimization in Smart Buildings

Smart buildings are becoming a new standard in construction, which allows for many possibilities to introduce ergonomics and energy savings. These contain simple improvements, such as controlling lights and optimizing heating or air conditioning systems in the building, but also more complex ones, such as indoor movement tracking of building users. One of the necessary components is an indoor localization system, especially without any device worn by the person being located. These types of solutions are important in locating people inside smart buildings, managing hospitals of the future and other similar institutions. The article presents a prototype of an innovative energy-efficient device for radio tomography, in which the hardware and software layers of the solution are presented. The presented example consists of 32 radio sensors based on a Bluetooth 5 protocol controlled by a central unit. The preciseness of the system was verified both visually and quantitatively by the image reconstruction as a result of solving the inverse tomographic problem using three neural networks.

A Multi-Port Hardware Energy Meter System for Data Centers and Server Farms Monitoring.

Nowadays the rationalization of electrical energy consumption is a serious concern worldwide. Energy consumption reduction and energy efficiency appear to be the two paths to addressing this target. To achieve this goal, many different techniques are promoted, among them, the integration of (artificial) intelligence in the energy workflow is gaining importance. All these approaches have a common need: data. Data that should be collected and provided in a reliable, accurate, secure, and efficient way. For this purpose, sensing technologies that enable ubiquitous data acquisition and the new communication infrastructure that ensure low latency and high density are the key. This article presents a sensing solution devoted to the precise gathering of energy parameters such as voltage, current, active power, and power factor for server farms and datacenters, computing infrastructures that are growing meaningfully to meet the demand for network applications. The designed system enables disaggregated acquisition of energy data from a large number of devices and characterization of their consumption behavior, both in real time. In this work, the creation of a complete multiport power meter system is detailed. The study reports all the steps needed to create the prototype, from the analysis of electronic components, the selection of sensors, the design of the Printed Circuit Board (PCB), the configuration and calibration of the hardware and embedded system, and the implementation of the software layer. The power meter application is geared toward data centers and server farms and has been tested by connecting it to a laboratory server rack, although its designs can be easily adapted to other scenarios where gathering the energy consumption information was needed. The novelty of the system is based on high scalability built upon two factors. Firstly, the one-on-one approach followed to acquire the data from each power source, even if they belong to the same physical equipment, so the system can correlate extremely well the execution of processes with the energy data. Thus, the potential of data to develop tailored solutions rises. Second, the use of temporal multiplexing to keep the real-time data delivery even for a very high number of sources. All these ensure compatibility with standard IoT networks and applications, as the data markup language is used (enabling database storage and computing system processing) and the interconnection is done by well-known protocols.

Projekt i wykonanie bezzałogowego pojazdu podwodnego o napędzie hybrydowym – REBA

The article presents the design and implementation of an unmanned underwater vehicle with hybrid propulsion system. The vehicle can be controlled remotely as well as it has the ability to reach the indicated area in order to carry out reconnaissance and attack by detonating the carried load or self-destructing. The article presents both the hardware and software layers as well as the results of preliminary tests.

RSLSP: An Effective Recovery Scheme for Flash Memory Leveraging Shadow Paging

The flash storage is a non-volatile semiconductor device that is constantly powered and has several advantages such as small size, lower power consumption, fast access, convenient portability, heat dissipation, shock resistance, data retention next to a power off, and random access. Flash memory is presently being incorporated with distinct embedded system devices such as with digital cameras, smart phones, personal digital assistants (PDA), and sensor devices. Nevertheless, a flash memory entails special features such as “erase-before-write” and “wear-leveling”, an FTL (flash translation layer) upon the software layer should be included. Although, the power off recovery plays a significant role in portable devices, most FTL algorithms did not consider the power off recovery scheme. In this paper, we proposed an effective scheme for the recovery of flash memory leveraging the shadow paging concept for storage devices using flash memory. To combat the sudden power off problem, the suggested RSLSP approach saves and keeps the map block data as a combination of two tables, i.e., first is the original block and the second block is a replica for the original one. Our proposed strategy not only improves the capacity of a flash memory device as compared to the state-of-the-art schemes suggested in the literature, but is also compatible with the existing FTL-based schemes.

Optimization of Load Balancing Algorithms to Deal with Ddos Attacks Using Whale ‎optimization Algorithm

Load balancing algorithms are used to deal with DDoS attacks to identify the optimal server and are responsible for the optimal allocation of requests to the servers. The managing method of the distribution of the requests between servers directly impacts network performance. Denial of service (DDoS) attacks are malicious attempts to interrupt regular operation or network traffic in a targeted manner, making disturbances in internet traffic by disrupting the infrastructure of different servers and thus causing problems such as slow site performance. This paper addresses the optimization of load balancing algorithms to deal with DDoS attacks using Whale Optimization Algorithm (WOA) with other closest algorithms (Round-Robin (RR), Particle Swarm Optimization (PSO), and Genetic Algorithms (GA)). The results obtained from implementing these algorithms showed that the WOA performed better than other algorithms in term of speed up the response time to client requests. The whale optimization algorithm can prevent unexpected traffic and block the regular operation of Internet websites by providing a proper plan for distributing requests between servers and reducing the average response speed. So, the authors can prevent DDoS attacks by applying the whale optimization algorithm. It necessary be noted that the use of HAProxy to prevent DDoS is not enough, and depending on the type of attack, several layers of software and hardware security necessary be used

STBEAT: Software Update on Trusted Environment Based on ARM TrustZone

In recent years, since edge computing has become more and more popular, its security issues have become apparent and have received unprecedented attention. Thus, the current research concentrates on security not only regarding devices such as PCs, smartphones, tablets, and IoTs, but also the automobile industry. However, since attack vectors have become more sophisticated than ever, we cannot just protect the zone above the system software layer in a certain operating system, such as Linux, for example. In addition, the challenges in IoT devices, such as power consumption, performance efficiency, and authentication management, still need to be solved. Since most IoT devices are controlled remotely, the security regarding system maintenance and upgrades has become a big issue. Therefore, a mechanism that can maintain IoT devices within a trusted environment based on localhost or over-the-air (OTA) will be a viable solution. We propose a mechanism called STBEAT, integrating an open-source project with ARM TrustZone to solve the challenges of upgrading the IoT system and updating system files more safely. This paper focuses on the ARMv7 architecture and utilizes the security stack from TrustZone to OP-TEE under the STM32 board package, and finally obtains the security key from the trusted application, which is used to conduct the cryptographic operations and then install the newer image on the MMC interface. To sum up, we propose a novel software update strategy and integrated ARM TrustZone security extension to beef up the embedded ecosystem.

Encryption AXI Transaction Core for Enhanced FPGA Security

The current hot topic in cyber-security is not constrained to software layers. As attacks on electronic circuits have become more usual and dangerous, hardening digital System-on-Chips has become crucial. This article presents a novel electronic core to encrypt and decrypt data between two digital modules through an Advanced eXtensible Interface (AXI) connection. The core is compatible with AXI and is based on a Trivium stream cipher. Its implementation has been tested on a Zynq platform. The core prevents unauthorized data extraction by encrypting data on the fly. In addition, it takes up a small area—242 LUTs—and, as the core’s AXI to AXI path is fully combinational, it does not interfere with the system’s overall performance, with a maximum AXI clock frequency of 175 MHz.

A Proposed Unified Standard IoT-Based Architecture Based on 7-Layers Framework (Case Applied: Car Accident System)

Internet of Things (IoT) is one of the famous applications of internet commuting and of cloud computing, and it is a widely used applications by organizations or by individuals, i.e., smart city, smart home, etc. There are many different IoT platforms that have been developed and used by IoT cloud providers to provide services to their subscribers. These different platforms lead to difficulty understand of each platform by developers. So, the need of IoT standard system is highly required to mitigate the diversity of building IoT-based system using different software layers. In this paper, a unified IoT-based architecture has been proposed based on 7-layers framework to be as a de facto standard to the most of IoT-based applications. Moreover, the proposed architecture has been applied using the car accident system which is a known application of IoT based application using CubCarbon Wireless Senser Networks (WSN) simulator. The proposed architecture shows the consistency between its 7-layers and promising to be as a considered unified IoT architecture.

Bidirectional Relationship Between Primary Sjögren Syndrome and Non-Hodgkin Lymphoma: A Nationwide Taiwanese Population-based Study.

<h3>ABSTRACT</h3> DeepImageJ is a user-friendly plugin that enables the generic use in FIJI/ImageJ of pre-trained deep learning (DL) models provided by their developers. The plugin acts as a software layer between TensorFlow and FIJI/ImageJ, runs on a standard CPU-based computer and can be used without any DL expertise. Beyond its direct use, we expect DeepImageJ to contribute to the spread and assessment of DL models in life-sciences applications and bioimage informatics.

A Review on the Mechanism Mitigating and Eliminating Internet Crimes using Modern Technologies

There is no doubting that contemporary technology creates new hazards, and these threats are many and significant, directly harming people's lives and threatening their stability. Because of the increased use of computers and Internet-connected cellphones in recent years, the problem of cybercrime has expanded substantially. Unquestionably, this kind of crime is now a reality that jeopardizes people's reputations and lives, therefore we must be aware of it to prevent being a victim. The exponential growth in internet connectedness is closely tied to a rise in cyberattack incidences, frequently with significant consequences. Malware is the weapon of choice for carrying out malicious intent in cyberspace, whether by exploiting pre-existing flaws or exploiting the unique properties of new technology. There is an urgent need in the cybersecurity area to develop more inventive and effective virus defense techniques. To do this, we first give an overview of the most often exploited vulnerabilities in the current hardware, software, and network layers. This follows criticism of the most recent mitigation efforts and the reasons why they may or may not be helpful. Following that, We'll talk about new attack methods for cutting-edge technologies including social networking, cloud computing, mobile technology, as well as critical infrastructure. We conclude by sharing our speculative findings on potential future research avenues.

HESS Opinions: Participatory Digital eARth Twin Hydrology systems (DARTHs) for everyone – a blueprint for hydrologists

Abstract. The “Digital Earth” (DE) metaphor is very useful for both end users and hydrological modelers (i.e., the coders). In this opinion paper, we analyze different categories of models with the view of making them part of Digital eARth Twin Hydrology systems (DARTHs). We stress the idea that DARTHs are not models, rather they are an appropriate infrastructure that hosts (certain types of) models and provides some basic services for connecting to input data. We also argue that a modeling-by-component strategy is the right one for accomplishing the requirements of the DE. Five technological steps are envisioned to move from the current state of the art of modeling. In step 1, models are decomposed into interacting modules with, for instance, the agnostic parts dealing with inputs and outputs separated from the model-specific parts that contain the algorithms. In steps 2 to 4, the appropriate software layers are added to gain transparent model execution in the cloud, independently of the hardware and the operating system of computer, without human intervention. Finally, step 5 allows models to be selected as if they were interchangeable with others without giving deceptive answers. This step includes the use of hypothesis testing, the inclusion of error of estimates, the adoption of literate programming and guidelines to obtain informative clean code. The urgency for DARTHs to be open source is supported here in light of the open-science movement and its ideas. Therefore, it is argued that DARTHs must promote a new participatory way of performing hydrological science, in which researchers can contribute cooperatively to characterize and control model outcomes in various territories. Finally, three enabling technologies are also discussed in the context of DARTHs – Earth observations (EOs), high-performance computing (HPC) and machine learning (ML) – as well as how these technologies can be integrated in the overall system to both boost the research activity of scientists and generate knowledge.

E2HRL: An Energy-efficient Hardware Accelerator for Hierarchical Deep Reinforcement Learning

Recently, Reinforcement Learning (RL) has shown great performance in solving sequential decision-making and control in dynamic environment problems. Despite its achievements, deploying Deep Neural Network (DNN)-based RL is expensive in terms of time and power due to the large number of episodes required to train agents with high dimensional image representations. Additionally, at the interference the large energy footprint of deep neural networks can be a major drawback. Embedded edge devices as the main platform for deploying RL applications are intrinsically resource-constrained and deploying deep neural network-based RL on them is a challenging task. As a result, reducing the number of actions taken by the RL agent to learn desired policy, along with the energy-efficient deployment of RL, is crucial. In this article, we propose Energy Efficient Hierarchical Reinforcement Learning (E2HRL), which is a scalable hardware architecture for RL applications. E2HRL utilizes a cross-layer design methodology for achieving better energy efficiency, smaller model size, higher accuracy, and system integration at the software and hardware layers. Our proposed model for RL agent is designed based on the learning hierarchical policies, which makes the network architecture more efficient for implementation on mobile devices. We evaluated our model in three different RL environments with different level of complexity. Simulation results with our analysis illustrate that hierarchical policy learning with several levels of control improves RL agents training efficiency and the agent learns the desired policy faster compared to a non-hierarchical model. This improvement is specifically more observable as the environment or the task becomes more complex with multiple objective subgoals. We tested our model with different hyperparameters to achieve the maximum reward by the RL agent while minimizing the model size, parameters, and required number of operations. E2HRL model enables efficient deployment of RL agent on resource-constraint-embedded devices with the proposed custom hardware architecture that is scalable and fully parameterized with respect to the number of input channels, filter size, and depth. The number of processing engines (PE) in the proposed hardware can vary between 1 to 8, which provides the flexibility of tradeoff of different factors such as latency, throughput, power, and energy efficiency. By performing a systematic hardware parameter analysis and design space exploration, we implemented the most energy-efficient hardware architectures of E2HRL on Xilinx Artix-7 FPGA and NVIDIA Jetson TX2. Comparing the implementation results shows Jetson TX2 boards achieve 0.1 ∼ 1.3 GOP/S/W energy efficiency while Artix-7 FPGA achieves 1.1 ∼ 11.4 GOP/S/W, which denotes 8.8× ∼ 11× better energy efficiency of E2HRL when model is implemented on FPGA. Additionally, compared to similar works our design shows better performance and energy efficiency.

Pictures from the Atomic Force Microscope: Temporal Representation in the Moving Image

Historically, artists and scientists predominantly created moving images of scientific phenomena using optical instrumentation such as cameras and light microscopes that enable direct observation of their subject. However, the perception and representation of nanoscale phenomena, which are too small to be detected by optical systems, rely upon complex technological mediation via layers of instrumentation, hardware and software. This mediation has profound implications for the perception of phenomena that exist outside the range of the human sensory system. This article describes the scientific representations of temporality in the work of Eadweard Muybridge and Étienne-Jules Marey and the complications of visualising the nanoscale. I analyse imperceptible phenomena in the contemporary moving image and draw upon my creative practice with the Atomic Force Microscope (AFM), using this instrument as a framework for discussing the temporal and sensorial challenges of working with nanoscale phenomena. This creative practice-based research resulted in the creation of several experimental moving image works collected under the title Wildly Oscillating Molecules. Through the adoption of scientific instrumentation and data for creative production, the collection of moving image practices discussed uncover temporal and sensorial assumptions and suggest alternative experiential encounters with scientific phenomena.

Quantum computing

Quantum computing promises to be the next disruptive technology, with numerous possible applications and implications for organizations and markets. Quantum computers exploit principles of quantum mechanics, such as superposition and entanglement, to represent data and perform operations on them. Both of these principles enable quantum computers to solve very specific, complex problems significantly faster than standard computers. Against this backdrop, this fundamental gives a brief overview of the three layers of a quantum computer: hardware, system software, and application layer. Furthermore, we introduce potential application areas of quantum computing and possible research directions for the field of information systems.

Hybrid Software Deployment Strategy for Complex Industrial Systems

Complex industrial systems run the different pieces of software in several interconnected physical layers. The software update in such an environment must be performed in the shortest possible period with the lowest possible resource usage. Namely, it is critical to minimize the data traffic, decrease software downtime, and reduce the impact of the transitional stage during the update process. To meet these requirements and to unify the update process, the common software node structure along with a hybrid software deployment strategy is proposed. The hybrid strategy is defined as a combination of the existing and well-tested techniques—blue/green, canary, and feature flags. The main aim was to utilize their positive sides and to obtain a better overall effect. The approach was tested in the simulation environment, based on the realistic factory layout, and running the software related to the enterprise resource planning (ERP) level. For successful updates, the proposed hybrid deployment method reduced downtime on server nodes to less than 5% and on client nodes to a half compared with the standard approach. The volume of data traffic reduction in a configuration with sentinel nodes is reduced by one-third. The presented results look promising, especially in cases of erroneous updates when a roll back is needed, where the downtime on the server nodes is reduced to the level of 3%. Achieved results are used to define the set of recommendations that could be extended for the other software layers, followed by a discussion about further potential problems and strategy variations.

Reactive synthesis of software robots in RPA from user interface logs

Robotic Process Automation (RPA) is an emerging technology in the field of Business Process Management (BPM) that enables the automation of intensive repetitive tasks (or simply routines). RPA solutions access the user interface (UI) layer of software (SW) applications and provide a virtual workforce of SW robots that are able to mimic human keyboard and mouse interactions with a UI as if a real person was doing them. To take full advantage of this technology, organizations leverage the support of skilled human experts that preliminarily observe how routines are executed on the UI of the involved SW applications, and then implement the executable RPA scripts required to automate the routines enactment by SW robots on a target computer system. However, the current practice is time-consuming and error-prone, as it strongly relies on the ability of the human experts to correctly interpret the routines (and their variants) to automate. In this paper, to tackle this issue, we use a design science research method to develop an approach, called SmartRPA, which is able to interpret the UI logs keeping track of many routine executions, and to automatically synthesize SW robots that emulate the most suitable routine variant for any specific intermediate user input that is required during the routine execution. The approach is implemented as an open-source tool and evaluated with four non-functional requirements employing both syntectic and real-world data.

Robust System Design IEEE IOLTS 2021

You are reading the Editorial of the Special Section of IEEE Transactions on Device and Materials Reliability with a collection of the best papers of the 2021 (27^th) edition of IEEE IOLTS, an established IEEE symposium which focuses on all critical challenges and important solutions for computing and electronic circuits and systems <i>robust design</i>. Robustness from the IOLTS technical point of view spans across the technology, circuit, microarchitecture, architecture, system, and software layers.

Analysis of rank-based latency aware fog scheduling using validating internet of things at large scales

With the increase in internet of things (IoT) applications' range and scale, it is essential to test the applications before deploying them in the real world. Most common approaches utilize simulations and testbeds; however, these methods lack real-time failure scenarios and the capability to scale, respectively. A virtual environment is a suitable approach that overcomes these drawbacks further, IoT applications using cloud computing have evolved to shift some computing and storage capabilities to the edge networks for ensuring adherence to strict latency constraints for real-time applications. This led to the emergence of fog computing which provides lower latency and better security, among other advantages. As for any processing tasks, scheduling becomes a critical concern for matching the tasks with the devices having appropriate resources. This paper analyzes a hybridized fog scheduling algorithm based on a ranking approach considering latency as the main parameter. It builds a software layer for scheduling on top of the validating internet of things at large scales (VIoLET) infrastructure. The results are compared with the round-robin scheduling algorithm, and it is found that the hybridized algorithm provides closer actual latency values to the expected.

Application of Model Driven Valuation Methodology for Maximum Throughput in Oil and Gas Pipeline Engineering Operations

The focus of this paper is on economic success for engineers and related experts whose primary line of business is tied to the field of pipeline mechanisms in the oil and gas industry. General purpose programming languages and computer aided design systems cannot express oil and gas pipeline engineering domain concepts appropriately, which means that domain experts in the oil and gas industry find it cumbersome to operate at optimal using conventional software in their line of business. This paper, therefore, presented a model driven valuation technique that enable the engineer simply input values corresponding to familiar notations such as pipe diameter, fittings, flow metrics etc.) on an interface to get done the kind of design, simulation artifact and other pipeline configurations without having to use any general-purpose programming system. The policies and mechanics of the valuation coupled software system production process incorporated inherent properties from MATLAB application programmer interface (API) to integrate the domain characteristics and concepts. The result became a new layer of reusable software capable of processing these domain characteristics and concepts to produce desired artefacts. A collection that supports further layers of accessible software connected through interfaces. This system is recommended to industries with a principal business interest in the oil and gas industry with the hope that crafting pipeline configurations for effective oil and gas supply within the value chain can be achieved with ease. Keywords: pipeline project, consistent valuation data, design interests, model driven design, domain driven design, design scenarios, economic success.