Application-specific Solutions Research Articles

Targeted Drug Delivery: From Chemistry to Robotics at Small Scales

The limited bioavailability, susceptibility to degradation, and adverse side effects of novel drugs often hinder their effective administration. Nanoparticles, with customizable properties and small size, have emerged as potential carriers, though their delivery efficiency remains low. With their ability to navigate fluid environments, micro- and nanorobots offer promising solutions to improve the delivery and retention of drugs at targeted tissues. The design and composition of these motile devices, often inspired by natural locomotion mechanisms, are currently being refined for improved biocompatibility, adaptability, and collective task performance. Recent research has focused on loading these devices with therapeutic agents and evaluating their efficacy in living organisms. While chemotherapy has been predominant, micro- and nanorobots also show significant potential for biological and physical therapies, and hybrid methods combining multiple therapies have demonstrated synergistic benefits. This review identifies major challenges, including the need for application-specific solutions, standardized performance evaluation methods, and the integration of engineering with pharmacology.

Additive Manufacturing of Composite Foam Metamaterial Springs for Vibration Isolation

This research introduces a novel approach for reducing the vibrations experienced by passengers in vehicles using metamaterials embedded in polyurethane foam to improve the existing vibration isolation capacity of car seats. An exploration of quasizero and negative stiffness metamaterials is conducted to develop metamaterial springs that exhibit a region of high‐static and low‐dynamic stiffness to achieve vibration isolation. Metamaterials are developed using low‐cost open‐source additive manufacturing methods and thermoplastic polyurethane filament. This investigation follows a process of determining the geometric, material, and systemic design requirements, to identify the quasizero and negative‐stiffness force–displacement regions. Small‐scale models of a car seat are developed by embedding the designed metamaterials into different grades of polyurethane foam and completing static and dynamic testing. The results demonstrate practical applications for implementing metamaterial springs into polyurethane foam to enhance vibration isolation under dynamic loading. The developed material library and the key geometric variables in the metamaterial design allow for application‐specific solutions where the selection of the appropriate metamaterial and foam combination can be tailored to suit the system requirements.

Conformal laser printing and laser sintering of Ag nanoparticle inks: a digital approach for the additive manufacturing of micro-conductive patterns on patterned flexible substrates

ABSTRACT The laser induced forward transfer and sintering of metal nanoparticle inks has been proven a key enabling technology for flexible electronics. Nevertheless, many challenges concerning the conformal processing of non-planar substrates incorporating thermally sensitive layers are yet to be addressed. In this work, we study the behaviour of conformal laser printing of silver nanoparticle inks on patterned samples comprising sensitive underlying structures, by correlating the laser sintering powers employed to the undesired effects on the adjacent interfaces. The latter include demanding surface topographies with periodic patterns and micro-components exhibiting aspect ratio in the nano to 100-micron scale. We investigate the contribution of crucial processing parameters, such as the per pulse energy, repetition rate and the pulse to pulse spatial and temporal overlap to the overall result. The demonstrated results validate the versatility of laser processing which can offer application specific solutions on different use cases involving multilayered and multimaterial electronics.

Overview of Mobile Cloud Computing

Mobile Cloud Computing (MCC) is a combination of three main parts; they are mobile device, cloud computing and mobile internet. With the help of MCC, a mobile user gets a rich application delivered over the Internet. The capabilities of mobile devices have been improving quickly than computers. Many researchers focus on the area of mobile computing and cloud computing. Cloud computing is the trend in which resources are provided to a local client on an on-demand basis, usually by means of the internet. Mobile cloud computing (MCC) is simply cloud computing in which at least some of the devices involved are mobile. This paper goes over multiple techniques and methods for mobile cloud computing. It explores both general-purpose mobile cloud computing solutions and application-specific solutions. It also discusses instances of mobile cloud computing where mobile devices serve as the cloud rather than the client. Finally it discusses some issues raised by this technology such as privacy and data ownership.

Ubiquitous Acoustic Sensing on Commodity IoT Devices: A Survey

With the proliferation of Internet-of-Things (IoT) devices, acoustic sensing attracts significant attention in recent years. It exploits acoustic transceivers such as microphones and speakers beyond their primary functions, namely recording and playing, to enable novel applications and new user experiences. In this paper, we present the first systematic survey on recent advances in ubiquitous acoustic sensing using commodity IoT hardware with a frequency range below 24 kHz. We propose a general framework that categorizes main building blocks of acoustic sensing systems. This framework encompasses three layers, i.e., <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">device</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">core technique</i> , and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">application</i> . The device layer includes basic hardware components, acoustic platforms, as well as the air-borne and structure-borne channel characteristics. The core technique layer encompasses key mechanisms to generate acoustic signals (waveforms) and to extract useful temporal, spatial, and spectral information from received signals. The application layer builds upon the functions offered by the core techniques to realize different acoustic sensing applications. We highlight unique challenges due to the limitations of physical devices and acoustic channels and how they are mitigated or overcame by core processing techniques and application-specific solutions. Finally, research opportunities and future directions are discussed to spawn further in-depth investigation on IoT-enabled ubiquitous acoustic sensing.

A Comparison of WebRTC and Conventional Videoconferencing for Synchronized Remote Medical Image Presentation.

DICOM viewers must fulfill roles beyond primary diagnostic interpretation, including serving as presentation tools in teaching and multidisciplinary conferences, thereby enabling multiple individuals to review images collaboratively in real time. When in-person gathering is not possible, a variety of solutions have been deployed to maintain the ability for spatially separated users to view medical images simultaneously. These approaches differ in their backend architectures, utilization of application-specific optimizations, and ultimately in their end user satisfaction. In this work, we systematically compare the performance of conventional screensharing using a videoconferencing application with that of a custom, synchronized DICOM viewer linked using Web Real Time Communications (WebRTC) technology. We find superior performance for the WebRTC method with regard to image quality and latency across a range of simulated adverse network conditions, and we show how increasing the number of conference participants differentially affects the bandwidth requirements of the two viewing solutions. In addition, we compare these two approaches in a real-world teaching scenario and gather the feedback of trainee and faculty radiologists, who we found to favor the WebRTC method for its decreased latency, improved image quality, ease of setup, and overall experience. Ultimately, our results demonstrate the value of application-specific solutions for the remote synchronized viewing of medical imaging, which, given the recent increase in reliance on remote collaboration, may constitute a significant consideration for future enterprise viewer procurement decisions.

Grasp Point Optimization and Leakage-Compliant Dimensioning of Energy-Efficient Vacuum-Based Gripping Systems

Vacuum-based handling, used in many applications and industries, offers great flexibility and fast handling processes. However, due to significant energy conversion losses from electrical energy to the useable suction flow, vacuum-based handling is highly energy-inefficient. In preliminary work, we showed that our grasp optimization method offers the potential to save at least 50% of energy by a targeted placement of individual suction cups on the part to be handled. By considering the leakage between gripper and object, this paper aims to extend the grasp optimization method by predicting the effective compressed air consumption depending on object surface roughness, gripper diameter and gripper count. Through balancing of the target pressure difference and the leakage tolerance in combination with the gripper count and gripper diameter, significant reductions of the compressed air, use and therefore the overall energy consumption, can be achieved. With knowledge about the gripper-specific leakage behavior, in the future it will be straightforward for system integrators to minimize the need for oversizing due to process-related uncertainties and therefore to provide application-specific and energy-optimized handling solutions to their customers.

Generic Digital Twin Architecture for Industrial Energy Systems

Digital Twins have been in the focus of research in recent years, trying to achieve the vision of Industry 4.0. In the domain of industrial energy systems, they are applied to facilitate a flexible and optimized operation. With the help of Digital Twins, the industry can participate even stronger in the ongoing renewable energy transition. Current Digital Twin implementations are often application-specific solutions without general architectural concepts and their structures and namings differ, although the basic concepts are quite similar. For this reason, we analyzed concepts, architectures, and frameworks for Digital Twins in the literature to develop a technology-independent Generic Digital Twin Architecture (GDTA), which is aligned with the information technology layers of the Reference Architecture Model Industry 4.0 (RAMI4.0). This alignment facilitates a common naming and understanding of the proposed architectural structure. A proof-of-concept shows the application of Semantic Web technologies for instantiating the proposed GDTA for a use case of a Packed-Bed Thermal Energy Storage (PBTES).

A dynamic distributed boundary node detection algorithm for management zone delineation in Precision Agriculture

Dividing a larger area into smaller subregions is a well addressed problem in Precision Agriculture (PA) where the existing application specific solutions (laboratory based) require human intervention and result in static region demarcation schemes. However, the boundary of a subregion is subject to change with various soil and environmental parameters. On the other hand, Wireless Sensor Networks (WSNs), a potential candidate to produce dynamic subregions due to its real-time decision making capability, are utilized as merely a data collection unit for PA.In an attempt to introduce the in-network decision making feature of WSN in PA, design of a novel three layered WSN-CPS architecture is presented in this work and at layer-I the distributed mechanism for region demarcation is proposed. The proposed scheme identifies nodes based on data values and position information, that serve as the boundary of a subregion and data transmitters to the base station for final decision making. Existing methods for boundary node detection identify network boundary nodes (not designed to demarcate the interior boundary), coverage hole boundary nodes (identifies boundary nodes of a smaller portion in network), and event boundary nodes (not able to identify outer boundary). The proposed work identifies network boundary nodes, coverage hole boundary nodes, and the subregion boundary nodes accurately. It takes various critical situations into account while labelling of nodes and shows its reliability in node failure conditions. Impact of varying transmission range and number of nodes is analyzed on proposed mechanism via simulation. In a comparative study with recent network boundary node detection scheme, decrease of 32% and 30% is seen at 200 and 300 nodes respectively in terms of energy consumption.

Additively Manufactured Dielectric Waveguides for Advanced Concepts for Millimeter-Wave Interconnects

Technology mega trends, such as autonomous driving, multiple-input multiple-output (MIMO), or multi-gigabit communication, drastically increase the demand for ultra-broadband millimeter-wave (mmW) transmission line technologies. A broadband and robust signal and data transmission between components and modules at low cost is a mandatory requirement to ensure high-performance functionality of advanced communication and radar systems. Dielectric waveguides (DWGs) are a highly suitable technology to meet these requirements due to their outstanding transmission capabilities for mmW signals coupled with their high flexibility, low weight, and low cost. Additive manufacturing (AM) processes based on dielectric materials open up new perspectives for fully automated wiring of mmW modules and systems, and they enable cost-efficient application-specific solutions. In this article, we propose novel printed DWG designs with optimized transmission performance. Measurement results of different DWG designs demonstrate the excellent functionality of the proposed transmission line and interconnection concepts. These results and the shown resiliency and practicality of the presented approaches illustrate attractive opportunities for new interconnect technologies based on new manufacturing processes.

Augmenting Operating Systems with OpenCL Accelerators

Heterogeneous computing leverages more than one kind of processors to boost the performance of user-space applications with the heterogeneous programming languages, e.g., OpenCL. While some works have been done to accelerate the computations required by Linux kernel software, they are either application-specific solutions or tightly coupled with the certain computing platforms and are not able to support the general-purpose in-kernel accelerations using different types of processors. In this article, the general-purpose software framework called Kernel acceleration with OpenCL (KOCL), is proposed to tackle the problem. KOCL exposes a set of the high-level programming interfaces for the Linux kernel module developers to offload compute-intensive tasks on different hardware accelerators without managing and coordinating the platform-specific computing and memory resources. The simplified programming efforts are achieved by the developed platform management and memory models, which provide a systematic means of managing the heterogeneous hardware resources. In addition, the one- and zero-copy data-buffering schemes are offered by KOCL, so that the offloaded tasks deliver high performance on the platforms with different memory architectures. We have developed the prototype system to accelerate the Network-Attached Storage server applications. Significant performance improvements are achieved with the three different types of accelerators, i.e., the multicore processor, the integrated GPU, and the discrete GPU, respectively. We believe that KOCL is useful for the design of embedded appliances to evaluate the performance of design alternatives.

Scalable computation of high-order optimization queries

Constrained optimization problems are at the heart of significant applications in a broad range of domains, including finance, transportation, manufacturing, and healthcare. Modeling and solving these problems has relied on application-specific solutions, which are often complex, error-prone, and do not generalize. Our goal is to create a domain-independent, declarative approach, supported and powered by the system where the data relevant to these problems typically resides: the database. We present a complete system that supports package queries , a new query model that extends traditional database queries to handle complex constraints and preferences over answer sets, allowing the declarative specification and efficient evaluation of a significant class of constrained optimization problems---integer linear programs (ILP)---within a database.

Big Data Competence Center ScaDS Dresden/Leipzig: Overview and selected research activities

Since its launch in October 2014, the Competence Center for Scalable Data Services and Solutions (ScaDS) Dresden/Leipzig carries out collaborative research on Big Data methods and their use in challenging data science applications of different domains, leading to both general, and application-specific solutions and services. In this article, we give an overview about the structure of the competence center, its primary goals and research directions. Furthermore, we outline selected research results on scalable data platforms, distributed graph analytics, data augmentation and integration and visual analytics. We also briefly report on planned activities for the second funding period (2018-2021) of the center.

CloudLaunch: Discover and deploy cloud applications

Cloud computing is a common platform for delivering software to end users. However, the process of making complex-to-deploy applications available across different cloud providers requires isolated and uncoordinated application-specific solutions, often locking-in developers to a particular cloud provider. Here, we present the CloudLaunch application as a uniform platform for discovering and deploying applications for different cloud providers. CloudLaunch allows arbitrary applications to be added to a catalog with each application having its own customizable user interface and control over the launch process, while preserving cloud-agnosticism so that authors can easily make their applications available on multiple clouds with minimal effort. It then provides a uniform interface for launching available applications by end users across different cloud providers. Architecture details are presented along with examples of different deployable applications that highlight architectural features.

Portable Systems for Metered Dispensing of Aggressive Liquids.

Precise metering in liquid dispensing applications often requires application-specific solutions due to incompatibilities of the sensor and actuator components with the dispensed liquids. Some reoccurring challenges are aggressive liquids that would damage the sensors or tubing, the need for sterile liquids while the pumps or sensors cannot be sterilized, or media that can clog the sensor channels. Two different dispensing systems are here presented where the dispensing flow rate or volume is indirectly measured through a coupled pressure change or airflow, thus avoiding contact between the sensor and liquid. The controlled pressure-driven dispensing (cPDD) system builds an overpressure in the liquid reservoir by pumping air and controls the opening of the liquid output valve based on the internal pressure development. The FlowCap system uses a liquid pump on the outlet, controlled by the measured inflow of air to the reservoir. Both systems are designed for compactness and portability and offer independent operation, as well as control and communication, over a wireless interface.

Kriging-Based Self-Adaptive Cloud Controllers

Cloud technology is rapidly substituting classic computing solutions, and challenges the community with new problems. In this paper we focus on controllers for cloud application elasticity, and propose a novel solution for self-adaptive cloud controllers based on Kriging models. Cloud controllers are application specific schedulers that allocate resources to applications running in the cloud, aiming to meet the quality of service requirements while optimizing the execution costs. General-purpose cloud resource schedulers provide sub-optimal solutions to the problem with respect to application-specific solutions that we call cloud controllers. In this paper we discuss a general way to design self-adaptive cloud controllers based on Kriging models. We present Kriging models, and show how they can be used for building efficient controllers thanks to their unique characteristics. We report experimental data that confirm the suitability of Kriging models to support efficient cloud control and open the way to the development of a new generation of cloud controllers.

On-Chip Message Passing Sub-System for Embedded Inter-Domain Communication

This letter describes the architecture of an inter-domain message passing hardware sub-system targeting the embedded virtualization field. Embedded virtualization is characterized by application-specific solutions, where functionality is partitioned into a small, fixed number of Virtual Machines, typically under real-time constraints, which must communicate for synchronization and status signaling. In light of the growing use of custom hardware, especially supported by (re)configurable platforms, we show how our hardware sub-system can provide virtualization-safe data transfers, without the need for Hypervisor (software) mediation, through the use of translate-once and virtual-interface hardware mechanisms, allowing direct memory-to-memory copies between different partitions’ input/output buffers, in both direct-transfer and publish-subscribe modes. Our experiments show our architecture is especially suited for the real time domain, outperforming an equivalent software solution in latencies, throughput and jitter, and outperforming state of the art hardware solutions for small message sizes (<512 B).

Towards a Methodology for Design of Prognostic Systems

&#x0D; &#x0D; &#x0D; An effective implementation of prognostic technology can re- duce costs and increase availability of assets. As a result of the rapidly growing interest in prognostics, researchers have independently developed a number of applications for asset-specific modeling and prediction. Consequently, there is some inconsistency in the understanding of key concepts for designing prognostic systems. This further complicates the already-challenging design of new prognostic systems. In order to progress from application-specific solutions towards structured and efficient prognostic implementations, the development of a comprehensive and pragmatic methodology is essential. Prognostic algorithm selection is a key activity to achieve consistency throughout the design process. In this paper we present a design decision framework which guides the designer towards a prognostic algorithm through a cause- effect flowchart. Failure modes, application characteristics, and qualitative and quantitative metrics are used to determine an appropriate approach for the stated problem. The application of the methodology can reduce the time and effort required to develop a prognostic system, ensure that all the possible design options have been considered, and provide a means to compare different prognostic algorithms consistently. The framework has been applied to different prognostic problems within the power industry to illuminate its effectiveness. Case studies are presented to show how the framework guides designers through the choice of prognostic algorithm according to system requirements. The results demonstrate the applicability of the methodology to the design of prognostic systems which consistently meet the established requirements.&#x0D; &#x0D; &#x0D;

Managing Complexity: Solutions from the Mars Science Laboratory Entry, Descent, and Landing Flight System Verification and Validation Campaign

The Mars Science Laboratory Entry, Descent, and Landing systems engineering team was presented with many challenges in its verification and validation campaign. These challenges arose from both the general complexity of the system architecture and the schedule and resource limitations of the test program. As a result, the team had to accommodate a complex set of requirements, test venues, test objectives, and analysis products. Discussed within are logistical problems faced by the team related to managing these complexities in a portion of Entry, Descent, and Landing verification and validation scope known as the flight system domain. The flight system domain encompassed software–software interactions and system-level software–hardware interactions that happened during the Entry, Descent, and Landing phase of the mission and necessitated the use of flight software and/or flight-equivalent hardware for final verification. The following application-specific solutions were developed to mitigate the complexity-driven problems: methods for functional and priority categorization of verification items (requirements); use of the commercial JIRA software bug-tracking tool for verification item management and closure tracking; development of an automated, configuration-controlled test execution framework; and development of tools for semi-automated test analysis and report management. A list of lessons learned was also developed. Both the solutions and lessons learned can be generalized to other space missions and formidable systems engineering problems, especially those with similar resource-limited constraints.

Formal representation of the SS-DB benchmark and experimental evaluation in EXTASCID

Evaluating the performance of scientific data processing systems is a difficult task considering the plethora of application-specific solutions available in this landscape and the lack of a generally-accepted benchmark. The dual structure of scientific data coupled with the complex nature of processing complicate the evaluation procedure further. SS-DB is the first attempt to define a general benchmark for complex scientific processing over raw and derived data. It fails to draw sufficient attention though because of the ambiguous plain language specification and the extraordinary SciDB results. In this paper, we remedy the shortcomings of the original SS-DB specification by providing a formal representation in terms of ArrayQL algebra operators and ArrayQL/SciQL constructs. These are the first formal representations of the SS-DB benchmark. Starting from the formal representation, we give a reference implementation and present benchmark results in EXTASCID, a novel system for scientific data processing. EXTASCID is complete in providing native support both for array and relational data and extensible in executing any user code inside the system by the means of a configurable metaoperator. These features result in significant improvement over SciDB at data loading, extracting derived data, and operations over derived data.