scholarly journals Smart sensor tights: Movement tracking of the lower limbs in football

2021 ◽  
Vol 2 ◽  
Author(s):  
Annemarijn Steijlen ◽  
Bastiaan Burgers ◽  
Erik Wilmes ◽  
Jeroen Bastemeijer ◽  
Bram Bastiaansen ◽  
...  
Keyword(s):  
Technical Assistance ◽  
Field Tests ◽  
Measurement Range ◽  
Lower Limbs ◽  
Processing Unit ◽  
Smart Sensor ◽  
Orientation Data ◽  
Central Processing ◽  
Earth Magnetic Field ◽  
Angular Velocities

Abstract This article presents a novel smart sensor garment with integrated miniaturized inertial measurements units (IMUs) that can be used to monitor lower body kinematics during daily training activities, without the need of extensive technical assistance throughout the measurements. The smart sensor tights enclose five ultra-light sensor modules that measure linear accelerations, angular velocities, and the earth magnetic field in three directions. The modules are located at the pelvis, thighs, and shanks. The garment enables continuous measurement in the field at high sample rates (250 Hz) and the sensors have a large measurement range (32 g, 4,000°/s). They are read out by a central processing unit through an SPI bus, and connected to a centralized battery in the waistband. A fully functioning prototype was built to perform validation studies in a lab setting and in a field setting. In the lab validation study, the IMU data (converted to limb orientation data) were compared with the kinematic data of an optoelectronic measurement system and good validity (CMCs >0.8) was shown. In the field tests, participants experienced the tights as comfortable to wear and they did not feel restricted in their movements. These results show the potential of using the smart sensor tights on a regular base to derive lower limb kinematics in the field.

scholarly journals Design and Implementation of an IoT-Oriented Strain Smart Sensor with Exploratory Capabilities on Energy Harvesting and Magnetorheological Elastomer Transducers

2020 ◽  
Vol 10 (12) ◽  
pp. 4387 ◽  
Author(s):  
Jorge de-J. Lozoya-Santos ◽  
L. C. Félix-Herrán ◽  
Juan C. Tudón-Martínez ◽  
Adriana Vargas-Martinez ◽  
Ricardo A. Ramirez-Mendoza
Keyword(s):  
Energy Harvesting ◽  
Internet Of Things ◽  
Cantilever Beam ◽  
Smart Materials ◽  
Mechanical Strain ◽  
Piezoelectric Sensors ◽  
Processing Unit ◽  
Smart Sensor ◽  
Magnetorheological Elastomer ◽  
Central Processing

This work designed and implemented a new low-cost, Internet of Things-oriented, wireless smart sensor prototype to measure mechanical strain. The research effort explores the use of smart materials as transducers, e.g., a magnetorheological elastomer as an electrical-resistance sensor, and a cantilever beam with piezoelectric sensors to harvest energy from vibrations. The study includes subsequent and validated results with a magnetorheological elastomer transducer that contained multiwall carbon nanotubes with iron particles, generated voltage tests from an energy-harvesting system that functions with an array of piezoelectric sensors embedded in a rubber-based cantilever beam, wireless communication to send data from the sensor’s central processing unit towards a website that displays and stores the handled data, and an integrated manufactured prototype. Experiments showed that electrical-resistivity variation versus measured strain, and the voltage-generation capability from vibrations have the potential to be employed in smart sensors that could be integrated into commercial solutions to measure strain in automotive and aircraft systems, and civil structures. The reported experiments included cloud-computing capabilities towards a potential Internet of Things application of the smart sensor in the context of monitoring automotive-chassis vibrations and airfoil damage for further analysis and diagnostics, and in general structural-health-monitoring applications.

Perangkat keras komputer

2020 ◽  
Author(s):  
Roudati jannah
Keyword(s):  
Data Storage ◽  
Central Processing Unit ◽  
External Memory ◽  
Storage Device ◽  
Input Device ◽  
Processing Unit ◽  
Central Processing ◽  
Output Device

Perangkat keras komputer adalah bagian dari sistem komputer sebagai perangkat yang dapat diraba, dilihat secara fisik, dan bertindak untuk menjalankan instruksi dari perangkat lunak (software). Perangkat keras komputer juga disebut dengan hardware. Hardware berperan secara menyeluruh terhadap kinerja suatu sistem komputer. Prinsipnya sistem komputer selalu memiliki perangkat keras masukan (input/input device system) – perangkat keras premprosesan (processing/central processing unit) – perangkat keras luaran (output/output device system) – perangkat tambahan yang sifatnya opsional (peripheral) dan tempat penyimpanan data (storage device system/external memory).

CENTRAL PROCESSING UNIT (CPU)

2020 ◽  
Author(s):  
Ika Milia wahyunu Siregar
Keyword(s):  
Processing System ◽  
Central Processing Unit ◽  
Processing Unit ◽  
Central Processing

Perkembangan IT di dunia sangat pesat, mulai dari perkembangan sofware hingga hardware. Teknologi sekarang telah mendominasi sebagian besar di permukaan bumi ini. Karena semakin cepatnya perkembangan Teknologi, kita sebagai pengguna bisa ketinggalan informasi mengenai teknologi baru apabila kita tidak up to date dalam pengetahuan teknologi ini. Hal itu dapat membuat kita mudah tergiur dan tertipu dengan berbagai iklan teknologi tanpa memikirkan sisi negatifnya. Sebagai pengguna dari komputer, kita sebaiknya tahu seputar mengenai komponen-komponen komputer. Komputer adalah serangkaian mesin elektronik yang terdiri dari jutaan komponen yang dapat saling bekerja sama, serta membentuk sebuah sistem kerja yang rapi dan teliti. Sistem ini kemudian digunakan untuk dapat melaksanakan pekerjaan secara otomatis, berdasarkan instruksi (program) yang diberikan kepadanya. Istilah Hardware komputer atau perangkat keras komputer, merupakan benda yang secara fisik dapat dipegang, dipindahkan dan dilihat. Central Processing System/ Central Processing Unit (CPU) adalah salah satu jenis perangkat keras yang berfungsi sebagai tempat untuk pengolahan data atau juga dapat dikatakan sebagai otak dari segala aktivitas pengolahan seperti penghitungan, pengurutan, pencarian, penulisan, pembacaan dan sebagainya.

Perangkat lunak komputer

2020 ◽  
Author(s):  
Intan khadijah simatupang
Keyword(s):  
Data Storage ◽  
Central Processing Unit ◽  
External Memory ◽  
Storage Device ◽  
Input Device ◽  
Processing Unit ◽  
Central Processing ◽  
Output Device

Komputer adalah serangkaian mesin elektronik yang terdiri dari jutaan komponen yang dapat saling bekerja sama, serta membentuk sebuah sistem kerja yang rapi dan teliti. Sistem ini kemudian digunakan untuk dapat melaksanakan pekerjaan secara otomatis, berdasarkan instruksi (program) yang diberikan kepadanya. Istilah Hardware computer atau perangkat keras komputer, merupakan benda yang secara fisik dapat dipegang, dipindahkan dan dilihat. Software komputer atau perangkat lunak komputer merupakan kumpulan instruksi (program/prosedur) untuk dapat melaksanakan pekerjaan secara otomatis dengan cara mengolah atau memproses kumpulan instruksi (data) yang diberikan. Pada prinsipnya sistem komputer selalu memiliki perangkat keras masukan (input/input device system) – perangkat keras pemprosesan (processing/ central processing unit) – perangkat keras keluaran (output/output device system), perangkat tambahan yang sifatnya opsional (peripheral) dan tempat penyimpanan data (Storage device system/external memory).

PERANGKAT KERAS ( HARDWARE ) PADA KOMPUTER

2020 ◽  
Author(s):  
Siti Kumala Dewi
Keyword(s):  
Processing System ◽  
Central Processing Unit ◽  
Input Device ◽  
Processing Unit ◽  
Central Processing ◽  
Output Device ◽  
System P ◽  
System 2

Perangkat keras komputer adalah bagian dari sistem komputer sebagai perangkat yang dapat diraba, dilihat secara fisik, dan bertindak untuk menjalankan instruksi dari perangkat lunak (software). Perangkat keras komputer juga disebut dengan hardware. Hardware berperan secara menyeluruh terhadap kinerja suatu sistem komputer. Berdasarkan fungsinya, perangkat keras terbagi menjadi :1.Sistem Perangkat Keras Masukan (Input Device System )2.Sistem Pemrosesan ( Central Processing System/ Central Processing Unit(CPU)3.Sistem Perangkat Keras Keluaran ( Output Device System )4.Sistem Perangkat Keras Tambahan (Peripheral/Accessories Device System)

Spatial modeling of air pollution based on data streams from geosensor networks

2018 ◽  
Vol 930 (12) ◽  
pp. 39-43 ◽  
Author(s):  
V.P. Savinikh ◽  
A.A. Maiorov ◽  
A.V. Materuhin
Keyword(s):  
Air Pollution ◽  
Data Streams ◽  
Spatial Modeling ◽  
Spatial Model ◽  
Large City ◽  
Field Tests ◽  
Processing Unit ◽  
Geosensor Network ◽  
Spatio Temporal ◽  
Different Sources

The article is a brief summary of current research results of the authors in the field of spatial modeling of air pollution based on spatio-temporal data streams from geosensor networks. The urban environment is characterized by the presence of a large number of different sources of emissions and rapidly proceeding processes of contamination spread. So for the development of an adequate spatial model is required to make measurements with a large spatial and temporal resolution. It is shown that geosensor network provide researchers with the opportunity to obtain data with the necessary spatio-temporal detail. The article describes a prototype of a geosensor network to build a detailed spatial model of air pollution in a large city. To create a geosensor in the prototype of the system, calibrated gas sensors for a nitrogen dioxide and carbon monoxide concentrations measurement were interfaced to the module, which consist of processing unit and communication unit. At present, the authors of the article conduct field tests of the prototype developed.

scholarly journals Numerical simulation of flattened heat pipe with double heat sources for CPU and GPU cooling application in laptop computers

2020 ◽  
Author(s):  
Wisoot Sanhan ◽  
Kambiz Vafai ◽  
Niti Kammuang-Lue ◽  
Pradit Terdtoon ◽  
Phrut Sakulchangsatjatai
Keyword(s):  
Experimental Data ◽  
Heat Pipe ◽  
Graphics Processing Unit ◽  
Processing Unit ◽  
Heat Sources ◽  
Final Thickness ◽  
Laptop Computers ◽  
Central Processing ◽  
Graphics Processing ◽  
Good Agreement

Abstract An investigation of the effect of the thermal performance of the flattened heat pipe on its double heat sources acting as central processing unit and graphics processing unit in laptop computers is presented in this work. A finite element method is used for predicting the flattening effect of the heat pipe. The cylindrical heat pipe with a diameter of 6 mm and the total length of 200 mm is flattened into three final thicknesses of 2, 3, and 4 mm. The heat pipe is placed under a horizontal configuration and heated with heater 1 and heater 2, 40 W in combination. The numerical model shows good agreement compared with the experimental data with the standard deviation of 1.85%. The results also show that flattening the cylindrical heat pipe to 66.7 and 41.7% of its original diameter could reduce its normalized thermal resistance by 5.2%. The optimized final thickness or the best design final thickness for the heat pipe is found to be 2.5 mm.

ILIS--An integrated laboratory information system. I. Biochemistry and hematology.

1982 ◽  
Vol 28 (2) ◽  
pp. 271-276 ◽  
Author(s):  
S U Deshpande
Keyword(s):  
Medical Records ◽  
Data Entry ◽  
Large Data ◽  
Work Load ◽  
Processing Unit ◽  
Patient Identification ◽  
Central Processing ◽  
Cathode Ray Tubes ◽  
Clinical Laboratories ◽  
On Line

Abstract IBM System 34 (central processing unit, 128 kilobytes; fixed disks, 128.4 megabytes) with seven cathode-ray tubes has been used by our clinical laboratories for the last 30 months. All data-entry programs are in a conversational mode, for on-line corrections of possible errors in patient identification and results. Daily reports are removed from the medical records after temporary and permanent cumulative weekly reports are received, which keep a three-month track of the results. The main advantages of the system are: (a) the increasing laboratory work load can be handled with the same staff; (b) the volume of the medical record files on the patients is decreased; (c) an easily retrievable large data base of results is formed for research purposes; (d) faster billing; and (e) the computer system is run without engaging any additional staff.

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