Hardware Innovation Research Articles

Actuator optimization and deep learning-based control of pediatric knee exoskeleton for community-based mobility assistance

Lightweight and smart exoskeletons offer the potential to improve mobility in children. State-of-the-art pediatric exoskeletons are typically clinic-based since they are either tethered or portable but cumbersome and their design is often not optimized across a range of environments and users. To facilitate pediatric exoskeleton in community settings, we first proposed an actuator optimization framework that identified the optimal design parameters for both motor and transmission while minimizing the actuator mass and satisfying the output torque, speed, bandwidth, and resistance torque requirements. Guided by the optimization results, we customized a simple, lightweight actuator that met all mechatronic constraints for our portable exoskeleton (1.78 kg unilateral). Secondly, we adopted deep learning (Long Short Term Memory) based on gait phase estimation to facilitate stable control for community use. The models accurately estimated the gait phase on irregular walking patterns (accuracy 94.60%) without explicit training in children (typically developing and with cerebral palsy). The controller results demonstrated an elevated ability to adapt to the irregular gait patterns of the child with cerebral palsy. The experimental results in the child with typical development and four healthy adults demonstrated accurate assistive torque tracking performance (accuracy 97.00%) at different walking speeds (i.e., under uncertain torque to wearers). This work presented a holistic solution that includes both hardware innovation (actuator optimization framework) and software innovation (deep learning-based control) towards the paradigm shift of pediatric exoskeletons from clinic to community setting.

3D Scanner

Abstract: This research paper presents a revolutionary 3D scanner incorporating an IR Sharp Sensor for capturing objects in all dimensions. The scanner's cutting-edge hardware ensures precise measurements, while the IR Sharp Sensor enables detailed and lifelike 3D model creation. Stored data on a micro-SD card allows easy access on computers, providing user-friendly visualization. Integration with e-commerce websites offers customers a comprehensive view of products through 360-degree viewing, enhancing the online shopping experience. Furthermore, the scanner's capabilities are extended to create virtual environments, enabling immersive experiences and simulations. This research aims to advance 3D scanning technology, merging hardware innovation, software development, and diverse applications

Best Practice in Open Source Scientific Designs Pre-Covid-19

Before the COVID-19 pandemic, open source hardware development grew steadily. However, the pandemic rapidly accelerated the global acceptance of open source hardware solutions. While open source software has long been vital in the ICT sector, this concept now extends to physical hardware production. Notably, the medical and energy fields have prominently embraced this shift, utilizing 3D printing to actualize open source designs. This study explores pre-pandemic Open Source Scientific practices, aiming to extract insights for a stronger future open source framework. Through an in-depth case study, we illuminate best practices, exemplary applications, and propose a framework for upcoming open source hardware projects. Additionally, this paper categorizes key areas of open source hardware innovation, outlining key sections and areas, thus offering a comprehensive view of the open source hardware landscape.

Manufacturing innovation to drive down cell therapy costs

Chimeric antigen receptor T cells (CAR-T) have demonstrated their potential to revolutionize cancer treatment. However, manufacturing remains a challenge. Multiple manufacturing innovations [e.g., vector and gene engineering, process improvements, hardware innovation, digital innovation, and point-of-care (POC) manufacturing] have the potential to help realize the full potential of CAR-T therapies.

Synergic Combination of Hardware and Software Innovations for Energy Efficiency and Process Control Improvement: A Steel Industry Application

The present paper proposes a steel industry case study focused on a reheating furnace and a rolling mill. Hardware and software innovations were successfully combined in order to obtain process control and energy efficiency improvement. The reheating furnace at study is pusher type and processes billets. The hardware innovation is related to the installation of an insulated tunnel at the end of the reheating furnace, in order to guarantee a higher heat retention of the billets before their path along the rolling mill stands. The software innovation refers to the design and the installation of an Advanced Process Control system which manipulates the gas flow rate and the stoichiometric ratio of the furnace zones in order to satisfy the control specifications on billets and furnace variables. The control system is based on Model Predictive Control strategy and on a virtual sensor which tracks and estimates the billet features inside/outside the furnace. The designed controller was commissioned on the real plant, providing significant performances in terms of service factor, process control, and energy efficiency.

Chasing Carbon: The Elusive Environmental Footprint of Computing

Given recent algorithm, software, and hardware innovation, computing has enabled a plethora of new applications. As computing becomes increasingly ubiquitous, however, so does its environmental impact. This article brings the issue to the attention of computer-systems researchers. Our analysis, built on industry-reported characterization, quantifies the environmental effects of computing in terms of carbon emissions. Broadly, carbon emissions have two sources: operational energy consumption, and hardware manufacturing and infrastructure. Although carbon emissions from the former are decreasing, thanks to algorithmic, software, and hardware innovations that boost performance and power efficiency, the overall carbon footprint of computer systems continues to grow. This work quantifies the carbon output of computer systems to show that most emissions related to modern mobile and data-center equipment come from hardware manufacturing and infrastructure. We, therefore, outline future directions for minimizing the environmental impact of computing systems.

Guided Perio-Prosthodontic Rehabilitation of Heavy Bruxists

To investigate the opportunities and limits in predefining new gingival and alveolar bone contour in combined surgical-restorative treatments with the aid of superimposition of DICOM, intraoral scan (IOS) and pre-operative digital prosthodontic wax-up; to fuel discussions to define scientific research protocols; to formulate needs for software and hardware innovation to improve existing protocols. Milled bite-planes establish physiological vertical dimension after severe wear; the vertical dimension dictates in smile design the amount of acceptable lengthening on the incisal-occlusal aspect of the teeth; golden proportions define the position of the cervical tooth margin and thus the gingival contour; considering biological width and phenotype new alveolar profile is determined; templates are produced to guide osteoplasty; temporary crowns are rebased and cemented with open flap; flaps are sutured after cleaning cement; during healing, if necessary, temporaries are adjusted for function or papilla fill; final IOS of the temporaries is captured; CAD/CAM final restorations are delivered. Satisfying clinical results are obtained with simultaneous periodontal recontouring surgery and restorative temporization. Mainstream CAD and planning software does not provide segmentation tools that allow for accurate design on both teeth, soft tissue, and bone surface. As a consequence templates will not physically adapt to the bone. Premilled temporaries need to be rebased. Perfect prediction of free-hands tooth preparation is impossible. There is a need for innovation to improve the segmentation of superimposed files that represent different anatomical layers and structures.

Application-Aware Quality-Energy Optimization: Mathematical Models Enabled Simultaneous Quality and Energy-Sensitive Optimal Memory Design

Energy efficiency is nowadays a well-known principal design goal across all layers of computing systems (e.g., sensors, mobile, cloud). With diminishing benefits from CMOS technology scaling and increasing demands from unprecedented data size, new memory hardware innovation is greatly needed to enhance energy efficiency of computing systems. Recently, quality-aware hardware design techniques have been developed from different stack layers (device/circuit/architecture/system) to enable near-threshold/sub-threshold voltage operation by trading off between quality and power efficiency. Specifically, based on the energy-quality trade-off and application requirement, memory hardware is designed for the work mode with maximum quality first (step1-design for the work mode) and then the supply voltage will be adjusted in the sleep mode with just-enough quality to achieve maximum efficiency (step2-adjust in the sleep mode). We first propose mathematical models for this two-step design method to avoid time-consuming and laborious ASIC design iterations in traditional hardware design process. However, such a two-step design method focuses more at the application quality than the energy efficiency in all cases. In addition, as the supply voltage in the second step depends on the design from the first step, the solution space of the second step may be greatly limited, far from the true minimum supply voltage. To handle these issues, we propose a new design concept, the simultaneous quality and energy-sensitive optimal design (SQEOD), in which the two objectives are considered simultaneously rather than by two separate steps. By introducing a system-wised importance weight parameter in the modeling process, our method demonstrates system-specific SQEOD mathematical models for different memory designs with various requirements on the application quality and/or energy efficiency. The results of the numerical studies on embedded memory design show that the proposed models provide a useful and fast tool to enable the optimal hardware designs.

Recent Advances in Solid-State Nuclear Magnetic Resonance Techniques for Materials Research

Establishing structure–property correlations is of paramount importance to materials research. The ability to selectively detect observable magnetization from transitions between quantized spin states of nuclei makes nuclear magnetic resonance (NMR) spectroscopy a powerful probe to characterize solids at the atomic level. In this article, we review recent advances in NMR techniques in six areas: spectral resolution, sensitivity, atomic correlations, ion dynamics, materials imaging, and hardware innovation. In particular, we focus on the applications of these techniques to materials research. Specific examples are given following the general introduction of each topic and technique to illustrate how they are applied. In conclusion, we suggest future directions for advanced solid-state NMR spectroscopy and imaging in interdisciplinary research.

Kickstarting Semiconductor Innovation with Open Source Hardware

Hardware innovation is slowing, yet software innovation is flourishing, in large part because of a thriving open source ecosystem. Open source can similarly boost hardware development, but the way forward will require industry, academia, and hardware enthusiasts to address five significant issues.

The Teardown: Samsung Galaxy S7

JUST HOW innovative is Samsung's latest top-of-the-range Galaxy S7 smartphone? Muchhyped waterproofing aside, both the S7 and its curved-screen sister, the S7 Edge, are primarily performance plays. And once you look at the hardware innovation, it proves an impressive piece of engineering. The company itself has made much of the fact that the S7 uses liquid cooling, but this comes in the form of a well-established technique, the heat pipe. Albeit, according to iFixit's Teardown team, a tiny one that allows liquid to travel along it as vapour with a width of less than 0.5mm. Still, the S7 is not the first phone to use this technology even if it has been tremendously scaled down.

Vision 20/20: Simultaneous CT-MRI--Next chapter of multimodality imaging.

Multimodality imaging systems such as positron emission tomography-computed tomography (PET-CT) and MRI-PET are widely available, but a simultaneous CT-MRI instrument has not been developed. Synergies between independent modalities, e.g., CT, MRI, and PET/SPECT can be realized with image registration, but such postprocessing suffers from registration errors that can be avoided with synchronized data acquisition. The clinical potential of simultaneous CT-MRI is significant, especially in cardiovascular and oncologic applications where studies of the vulnerable plaque, response to cancer therapy, and kinetic and dynamic mechanisms of targeted agents are limited by current imaging technologies. The rationale, feasibility, and realization of simultaneous CT-MRI are described in this perspective paper. The enabling technologies include interior tomography, unique gantry designs, open magnet and RF sequences, and source and detector adaptation. Based on the experience with PET-CT, PET-MRI, and MRI-LINAC instrumentation where hardware innovation and performance optimization were instrumental to construct commercial systems, the authors provide top-level concepts for simultaneous CT-MRI to meet clinical requirements and new challenges. Simultaneous CT-MRI fills a major gap of modality coupling and represents a key step toward the so-called "omnitomography" defined as the integration of all relevant imaging modalities for systems biology and precision medicine.

MGH–USC Human Connectome Project datasets with ultra-high b-value diffusion MRI

The MGH–USC CONNECTOM MRI scanner housed at the Massachusetts General Hospital (MGH) is a major hardware innovation of the Human Connectome Project (HCP). The 3T CONNECTOM scanner is capable of producing a magnetic field gradient of up to 300mT/m strength for in vivo human brain imaging, which greatly shortens the time spent on diffusion encoding, and decreases the signal loss due to T2 decay. To demonstrate the capability of the novel gradient system, data of healthy adult participants were acquired for this MGH–USC Adult Diffusion Dataset (N=35), minimally preprocessed, and shared through the Laboratory of Neuro Imaging Image Data Archive (LONI IDA) and the WU–Minn Connectome Database (ConnectomeDB). Another purpose of sharing the data is to facilitate methodological studies of diffusion MRI (dMRI) analyses utilizing high diffusion contrast, which perhaps is not easily feasible with standard MR gradient system. In addition, acquisition of the MGH–Harvard–USC Lifespan Dataset is currently underway to include 120 healthy participants ranging from 8 to 90 years old, which will also be shared through LONI IDA and ConnectomeDB. Here we describe the efforts of the MGH–USC HCP consortium in acquiring and sharing the ultra-high b-value diffusion MRI data and provide a report on data preprocessing and access. We conclude with a demonstration of the example data, along with results of standard diffusion analyses, including q-ball Orientation Distribution Function (ODF) reconstruction and tractography.

DIABLO

Motivated by rapid software and hardware innovation in warehouse-scale computing (WSC), we visit the problem of warehouse-scale network design evaluation. A WSC is composed of about 30 arrays or clusters, each of which contains about 3000 servers, leading to a total of about 100,000 servers per WSC. We found many prior experiments have been conducted on relatively small physical testbeds, and they often assume the workload is static and that computations are only loosely coupled with the adaptive networking stack. We present a novel and cost-efficient FPGAbased evaluation methodology, called Datacenter-In-A-Box at LOw cost (DIABLO), which treats arrays as whole computers with tightly integrated hardware and software. We have built a 3,000-node prototype running the full WSC software stack. Using our prototype, we have successfully reproduced a few WSC phenomena, such as TCP Incast and memcached request latency long tail, and found that results do indeed change with both scale and with version of the full software stack.

DIABLO

Motivated by rapid software and hardware innovation in warehouse-scale computing (WSC), we visit the problem of warehouse-scale network design evaluation. A WSC is composed of about 30 arrays or clusters, each of which contains about 3000 servers, leading to a total of about 100,000 servers per WSC. We found many prior experiments have been conducted on relatively small physical testbeds, and they often assume the workload is static and that computations are only loosely coupled with the adaptive networking stack. We present a novel and cost-efficient FPGAbased evaluation methodology, called Datacenter-In-A-Box at LOw cost (DIABLO), which treats arrays as whole computers with tightly integrated hardware and software. We have built a 3,000-node prototype running the full WSC software stack. Using our prototype, we have successfully reproduced a few WSC phenomena, such as TCP Incast and memcached request latency long tail, and found that results do indeed change with both scale and with version of the full software stack.

AN INTEGRATED FRAMEWORK UTILISING SOFTWARE AGENT REASONING AND ONTOLOGY MODELS FOR SENSOR BASED BUILDING MONITORING

Smart building monitoring demands a new software infrastructure that can elaborate building domain knowledge in order to provide advanced and intelligent functionalities. Conventional facility management (FM) software tools lack semantically rich components, and that limits the capability of supporting software for automatic information sharing, resource negotiation and to assist in timely decision making. Recent hardware innovation on compact ZigBee sensor devices, software developments on ontology and intelligent software agent paradigms provide a good opportunity to develop tools that can further improve current FM practices. This paper introduces an integrated framework which includes a ZigBee based sensor network and underlying multi-agent software (MAS) components. Several different types of sensors were integrated with the ZigBee host devices to produce compact multi-functional sensor units. The MAS framework incorporates the belief-desire-intention (BDI) abstraction with ontology support (provided via explicit knowledge bases). The different software agent types have been developed to work with sensor hardware to conduct resource negotiation, to optimize battery utilization, to monitor building space in a non-intrusive way and to reason about its usage through real time ontology model queries. The deployed sensor network shows promising intelligent characteristics, and it has been applied in several on-going research projects as an underlying decision making service. More applications and larger deployments have been planned for future work.

초우량 조직을 위한 품질경영혁신 도전 -한국과 중국의 비교-

Purpose: Quality Innovation Managements recently focus on developing relationship with customers to meet their requirements and enhance loyalty in the competitive environments in Countries. The purpose of this study is to explore the effects of innovation, quality, satisfaction and customer loyalty. Methods: After reviewing the literatures, the structural equation modeling (SEM) was conducted test the research model. The data was collected from Quality Leader by the questionnaire In Korea and China. Results: The results of SEM show that hardware innovation quality have a positive effect on customer satisfaction. Customer Satisfaction have a positive effect on customer satisfaction. Conclusion: The authors demonstrate that the hardware innovation quality is related positively to customer satisfaction. And customer satisfaction has a positive effect on customer loyalty. A number of notable findings are reported including the empirical verification that hardware innovation quality, customer satisfaction, and customer loyalty may all be directly related to business performance.

Computer assisted Minimally Invasive Surgery: Is medical Computer Vision the answer to improving laparosurgery?

Minimally Invasive Surgery (MIS) is one of the most effective methods of modern surgical intervention that has considerable advantages compared with open surgery, including reduced trauma, pain, and post-operative recovery time. MIS has improved substantially over the years, chiefly due to new hardware innovations, including HD cameras and flexible head endoscopes. However, MIS continues to be hindered by several problems. In addition to hardware innovation, Computer Vision (CV) has been proposed as a way to overcome some of its current limitations. However, the research literature lacks a coherent picture of how the limitations can be best overcome by hardware, CV or a combination of the two. In this paper we focus on laparoscopic MIS, and list these limitations into 5 clear categories. We detail the effectiveness of hardware and CV solutions with respect to each limitation, from which we base the following hypothesis: CV is both complementary and necessary to hardware development, to overcome all 5 limitations in laparoscopy. Our paper is of value to laparoscopy surgeons, by conveying what is expected to be achieved in computer-aided laparoscopy over the next decade. It is also of value to medical CV researchers, by clarifying which problems are best solved with CV, in light of the hardware developments likely to occur over the next decade.

Is hardware innovation over?

My colleagues, promotion committees, research funding agencies and business people often wonder if there is need for any architecture research. There seems to be no room to dislodge Intel IA-32. Even the number of new Application-Specific Integrated Circuits (ASICs) seems to be declining each year, because of the ever-increasing development cost. This viewpoint ignores another reality which is that the future will be dominated by mobile devices such as smart phones and the infrastructure needed to support consumer services on these devices. This is already restructuring the IT industry. To the first-order, in the mobile world functionality is determined by what can be supported within a 3W power budget. The only way to reduce power by one to two orders of magnitude is via functionally specialized hardware blocks. A fundamental shift is needed in the current design flow of systems-on-a-chip (SoCs) to produce them in a less-risky and cost-effective manner. In this talk we will present, via examples, a method of designing systems that facilitates the synthesis of complex SoCs from reusable "IP" modules. The technical challenge is to provide a method for connecting modules in a parallel setting so that the functionality and the performance of the composite are predictable.

What's new

Regular readers of this column will realise that this is not a random ragbag of business information news stories. There are clear recurrent themes and strategic directions being taken by both the consumers and providers of business information. We have grouped the items under the key agenda areas — the way the information industry is restructuring in the face of the harshest economic climate in more than 20 years; the richness of the many new business information products that have been developed or reworked in some way; the myriad paths of technology development, through software and hardware innovation, affecting business information use; and, last but not least, the growing impact of social networks and their nexus with established business information products.