Visible Fidelity Collector of a Zooplankton Sample from the Near-Bottom of the Deep Sea

The multi-net visible fidelity zooplankton collector is designed to obtain near-bottom fidelity zooplankton. The collector is sent to the designated sampling location based on the information provided by the camera and altimeter. The host computer sends instructions to control the opening of the net port for sample collection and closing of the sampling cylinder cover after sampling. The collector contains three trawls so that three samples can be collected for each test, and environmental parameters can be collected simultaneously. After sampling, The sample maintains its fidelity, that is, maintaining the temperature and pressure of the seabed sample after sampling. Two experiments were carried out in the Western Pacific, and six bottles of zooplankton samples were successfully obtained. The development of a multi-net visible zooplankton collector is of great significance for the collection of near-bottom zooplankton.

Controlling mechanical arms using 3D coordinates gotten from the AR technology

How to control the movement of the mechanical arm is a challenging topic recently. It requires much time and energy to program every joint. This paper proposes a new method based on 3D coordinates of the human arm joints, which helps the mechanical arm to imitate the movement of human arms and only needs to calculate angles of human arms’ joints according to the 3D coordinates. Here in this process the key is to get the information of 3D coordinates of human arms. This paper applies an AR (Augmented Reality) application of body detection with LiDAR on iPad Pro 2020 to get 3D coordinates. Then the calculated angle information is transferred from the host computer to the Arduino board controlling the movement of the mechanical arm. Eventually the same movements will be made by the mechanical arm and the human arm.

Design of Motor Condition Online Monitoring System Based on LabVIEW

In the rail transit industry, the electric locomotive’s electric motor is used as the driving core, and its installation and working environment are often harsh, and the probability of failure will increase accordingly. If the motor fails during the operation of the locomotive, it will cause huge economic losses, and even threaten people’s lives and property. In order to grasp the running status of the motor in real time, an online monitoring system of the motor status is designed. This system collects the three parameters of temperature, current and speed, and inputs the three-parameter data into the single-chip microcomputer. The single-chip microcomputer transmits the data to the host computer through calculation. The host computer analyzes and displays the data through LabVIEW to realize online monitoring of the motor status. Experiments show that the system has a good man-machine interface, a wide speed range, high accuracy, fast response speed, and strong anti-interference ability, which is of great practical value for online monitoring of motors.

Software-Defined Radio Beamforming System for 5G/Radar Applications

Based on the flexibility of software-defined radio (SDR) techniques applied to an array of antennas, this article presents a beamforming architecture designed to operate in millimeter-wave bands (28 GHz), with possible applications in radar and 5G systems. The system structure, including its main constituents such as the radio frequency (RF) frontend modules, the radiating elements as well as the baseband processing on the host computer are widely described. Beamforming is achieved by digitally controlling the signals that feed the antennas. The experimental measurements performed in an anechoic chamber validate the proposed approach.

Design of Smart Card Chip Reader Based on STM32

<p>This paper designs a smart card chip reader based on STM32, and gives a block diagram of the overall design of the system. It introduces the design of the peripheral hardware circuit of the main control chip STM32F103CBT6 and the RF processing chip THM3070, and the format of data communication between each part and flow chart. The communication between the host computer and the reader adopts the USB CCID protocol, which supports the USB full-speed communication rate of 12Mbps, improves the interrupt response, and overcomes the shortcomings of the traditional serial port-based readers with low communication speed and poor interrupt response. At the same time, it realizes data interaction with the PC/SC standard PC application and has better versatility</p>

Identifikasi Malicious Host dalam Local Area Network Menggunakan Teknik Graph Clustering dan Filtering

<p>Keamanan pada <em>Local Area Network</em> (LAN) sekarang ini adalah masalah serius yang harus diperhatikan. Penyebab LAN menjadi tidak aman dikarenakan teknologi <em>firewall </em>tidak mampu melindungi <em>host</em> (komputer) dalam LAN dari penyebaran <em>malware</em>. Penyebaran <em>malware</em> yang terdapat dalam LAN dilakukan oleh <em>host</em> di dalam LAN yang disebut sebagai <em>malicious host</em>. Tindakan untuk mengurangi penyebaran <em>malware</em> dalam LAN dapat dilakukan dengan mengidentifikasi <em>malicious host</em>. Penelitian ini mengusulkan metode identifikasi <em>malicious host</em> berdasarkan aktivitas ARP <em>request</em> dengan menggunakan teknik <em>graph clustering-filtering</em>. Teknik <em>graph clustering</em>-<em>filtering</em> merupakan langkah-langkah pengelompokan serta penyaringan <em>node</em> dan <em>edge</em> berdasarkan parameter dari <em>graph</em> seperti <em>weight edge</em>, <em>out-degree node</em> dan <em>weight out-degree node </em>yang bertujuan untuk mengidentifikasi <em>malicious host</em>. Berdasarkan parameter dari <em>graph </em>seperti <em>out-degree node </em>dan <em>weight out-degree node, </em>penghitungan persentase aktivitas<em> host</em> dapat dilakukan untuk menunjukkan seberapa besar tingkat aktivitas <em>host</em> dalam melakukan <em>broadcast</em> ARP <em>request, </em>sehingga hasil penghitungan persentase aktivitas <em>host </em>dapat menentukan <em>host</em> yang diidentifikasi sebagai <em>malicious host. </em>Hasil penerapan teknik <em>graph</em> <em>clustering</em>-<em>filtering</em> terhadap 511 <em>node</em> dan 4144 <em>edge </em>didapatkan melalui pengamatan dan pengambilan data selama 3 jam dalam LAN kampus dapat divisualisasikan menjadi hanya 22 <em>node</em> dan 328 <em>edge</em>. Hasil penghitungan berdasarkan persentase jumlah aktivitas <em>host</em> menunjukkan 22 <em>node</em> menjadi 6 <em>node</em> yang diperkirakan sebagai <em>malicious host</em>. Dengan demikian, visualisasi <em>graph</em> menggunakan teknik <em>graph clustering-filtering</em> dan persentase aktivitas <em>host</em> dapat mengidentifikasi jumlah <em>host</em> yang dicurigai sebagai <em>malicious</em> <em>host</em>.</p><p><strong><em><br /></em></strong></p><p><strong><em>Abstract</em></strong></p><p><em>Local Area Network (LAN) security is a serious problem to consider. The cause of LAN becomes insecure because firewall technology is not able to protect the host (computer) in LAN from spreading malware. The spread of malware contained within a LAN is carried out by hosts in the LAN which are referred to as malicious hosts. Actions to reduce the spread of malware in the LAN can be done by identifying malicious hosts. This paper proposes a method of identifying malicious hosts based on ARP request activities using graph clustering-filtering techniques. Graph clustering-filtering techniques are steps of grouping and filtering nodes and edges based on graph parameters such as weight edges, out-degree nodes and weight out-degree nodes that aim to identify malicious hosts. Based on parameters from the graph such as out-degree node and weight out-degree node, the calculation of the percentage of host activity can be done to show how much the level of host activity in broadcasting an ARP request, so that the result of calculating the percentage of host activity can determine a host that is categorized as a malicious host. The results of graph visualization using graph clustering-filtering technique can display fewer nodes and edges, from 511 nodes and 4144 edges to 22 nodes and 328 edges observed and collected in a LAN within 3 hour in the campus LAN. The results of the calculation of the percentage of host activity show hosts from 22 nodes become only 6 nodes which are suspected as malicious hosts. Overall, graph visualization with graph clustering-filtering techniques and the percentage of host activity can find a number of hosts identified as malicious hosts.</em></p>

Digitalization In Scanning And Remote Shutdown Host of Computer Using Apache Cordova Framework

<p class="Abstract">Internet of Things is one concept in technology 4.0, this technology combine of two component, that is internet and mechine. Internet use to send signal from mechine to second device like mobilephone or from the mobilephone to mechine to execution task. Information Technnology infrastructure in industrial company has many complexity in network, hardware, or software. Especially for hardware like desktop computer or laptop, ech employee has one of them. And many of them, sometime forget to shutdown they computer or they has purpose did not shutdown they computer just for download the big file. Indirectly, the computer that run more than 24 hours in industrial company, it will be degrade service of life, and the consumption of electricity need the high cost. In this paper, our purpose is how to reduce computer that not needed run 24 hours can be monitor and can be shutdown in the out of company area. This is need concept of internet of things and digitalitation to make it. For this problem can be used monitoring system by mobile application, this system will be show about the host computer still be on, and can be remote shutdown with mobile device. This application use cordova to build it and the command from mobile be send to server to shutdown computer that still online. </p>