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Background The aim of the present paper is to construct an emulator of a complex biological system simulator using a machine learning approach. More specifically, the simulator is a patient-specific model that integrates metabolic, nutritional, and lifestyle data to predict the metabolic and inflammatory processes underlying the development of type-2 diabetes in absence of familiarity. Given the very high incidence of type-2 diabetes, the implementation of this predictive model on mobile devices could provide a useful instrument to assess the risk of the disease for aware individuals. The high computational cost of the developed model, being a mixture of agent-based and ordinary differential equations and providing a dynamic multivariate output, makes the simulator executable only on powerful workstations but not on mobile devices. Hence the need to implement an emulator with a reduced computational cost that can be executed on mobile devices to provide real-time self-monitoring. Results Similarly to our previous work, we propose an emulator based on a machine learning algorithm but here we consider a different approach which turn out to have better performances, indeed in terms of root mean square error we have an improvement of two order magnitude. We tested the proposed emulator on samples containing different number of simulated trajectories, and it turned out that the fitted trajectories are able to predict with high accuracy the entire dynamics of the simulator output variables. We apply the emulator to control the level of inflammation while leveraging on the nutritional input. Conclusion The proposed emulator can be implemented and executed on mobile health devices to perform quick-and-easy self-monitoring assessments.

The ready availability of advanced visualization tools on picture archiving and communication systems workstations or even standard laptops through server-based or cloud-based solutions has enabled greater adoption of these techniques. We describe how radiologists can tailor imaging techniques for optimal 3D reconstructions provide a brief overview of the standard and newer "on-screen" techniques. We describe the process of creating 3D printed models for surgical simulation and education, with examples from the authors' institution and the existing literature. Finally, the review highlights current uses and potential future use cases for virtual reality and augmented reality applications in a pediatric neuroimaging setting.

Pop is increasingly assimilating the compositional practices of hip-hop and EDM (electronic dance music). This shift is driven by a new generation of Digital Audio Workstations (DAWs). These are le...

Moving target detection is involved in many engineering applications, but basketball has some difficulties because of the time-varying speed and uncertain path. The purpose of this paper is to use computer vision image analysis to identify the path and speed of a basketball goal, so as to meet the needs of recognition and achieve trajectory prediction. This research mainly discusses the basketball goal recognition method based on computer vision. In the research process, Kalman filter is used to improve the KCF tracking algorithm to track the basketball path. The algorithm of this research is based on MATLAB, so it can avoid the mixed programming of MATLAB and other languages and reduce the difficulty of interface design software. In the aspect of data acquisition, the extended EPROM is used to store user programs, and parallel interface chips (such as 8255A) can be configured in the system to output switch control signals and display and print operations. The automatic basketball bowling counter based on 8031 microprocessor is used as the host computer. After the level conversion by MAX232, it is connected with the RS232C serial port of PC, and the collected data is sent to the workstation recording the results. In order to consider the convenience of user operation, the GUI design of MATLAB is used to facilitate the exchange of information between users and computers so that users can see the competition results intuitively. The processing frame rate of the tested video image can reach 60 frames/second, more than 25 frames/second, which meet the real-time requirements of the system. The results show that the basketball goal recognition method used in this study has strong anti-interference ability and stable performance.

Algoritma kriptografi RSA menjadi metode yang paling sulit diretas karena kerumitan persamaan matematis yang digunakan. Semakin rumit persamaan matematis yang digunakan, semakin besar pula daya komputasi yang digunakan untuk memproses algoritma tersebut. Penggunaan Single-Board Computer (SBC) mulai digunakan untuk menggantikan alat pemrosesan komputasi seperti komputer personal baik berupa laptop maupun workstation. Penetlitian ini bertujuan untuk mengetahui hasil optimasi pemroresan enkirpsi dan dekripsi RSA menggunakan SBC yang tersusun sebagai bentuk cluster. Metode yang digunakan adalah metode pemrosesan enkripsi dan dekripsi RSA dengan pembagian beban komputasi yang diterapkan dalam arsitektur SBC berdasarkan ketersediaan sumberdaya pada tiap SBC dalam cluster SBC. Cluster SBC yang dibangun terdiri atas 5 buah SBC Raspberry Pi 4 model B yang terkoneksi melalui sebuah switch 8 port. Hasil penelitian yang didapat adalah proses enkripsi dan dekripsi pada cluster SBC dapat mengalahkan komputer tunggal. Cluster SBC yang memiliki 16 core dari 4 buah prosesor worker SBC berjalan lebih cepat dibandingkan komputer tunggal yang memiliki 4 core dari prosesornya. Selain itu, efisiensi juga didapat dari biaya yang dikeluarkan untuk membeli perangkat. Dengan biaya pembelian yang sama, performa yang didapat lebih tinggi pada cluster SBC sehingga SBC dapat dijadikan alternatif pemrosesan enkripsi dan dekripsi.

ECMA-74 Annex C.15 prescribes procedures for acoustical testing of personal computers and workstations. The dramatic advances in computer technology and use over the past two decades motivated the formation of an IT industry workgroup shortly after InterNoise 2018 to update the annex for these changes. The updated procedures, which will be published in the 18th edition of ECMA-74, are described. The updated procedures comprise new operating conditions: 1) web browsing, 2) office productivity, 3) media content creation, and 4) power user/gaming, in addition to the idle condition, and how computer system power and performance settings, which affect computer noise, are to be set and reported.

Industry 4.0 paradigm has introduced a set of technological advances into the productive means. However, the training of the operators is somehow neglected. An operator without the necessary skills will take risks or will provoke problems that might appear at any point of the productive process. Therefore, training the operators is required to acquire the necessary skills to interact with the machines in the most productive and safest way possible. Virtual Reality (VR) is a good option to train people. However, the development of a VR system is usually expensive and slow due to the 3D design process and the creation and edition of VR training sessions. This paper presents a methodology to develop VR tutorials and training courses for professional preparation in industrial jobs, providing usable virtual tools to solve the following problems: i) how to create of the virtual model of workstations by its 3D reconstruction, ii) how to apply the expected behavior to the 3D models, and iii) how to prepare online tutorials and train workers in the virtual environment.

We consider the problem of low-rank approximation of massive dense nonnegative tensor data, for example, to discover latent patterns in video and imaging applications. As the size of data sets grows, single workstations are hitting bottlenecks in both computation time and available memory. We propose a distributed-memory parallel computing solution to handle massive data sets, loading the input data across the memories of multiple nodes, and performing efficient and scalable parallel algorithms to compute the low-rank approximation. We present a software package called Parallel Low-rank Approximation with Nonnegativity Constraints, which implements our solution and allows for extension in terms of data (dense or sparse, matrices or tensors of any order), algorithm (e.g., from multiplicative updating techniques to alternating direction method of multipliers), and architecture (we exploit GPUs to accelerate the computation in this work). We describe our parallel distributions and algorithms, which are careful to avoid unnecessary communication and computation, show how to extend the software to include new algorithms and/or constraints, and report efficiency and scalability results for both synthetic and real-world data sets.

A flexible manufacturing system (FMS) is the model used for the system produced in the manufacturing industry, and it consists of the number of interconnected workstation. Inflexible manufacturing system scheduling of jobs has become a serious problem, even for a short breakdown of the machine and for the unexpected arrival of the product. To overcome this problem, a flexible manufacturing system using fuzzy rules is proposed. In this proposed model, four input variables are considered: (1) machine allocated processing time; (2) priority of the machine; (3) priority of the due date; and (4) priority of the setup time. The priority based on the job is the fuzzy variable, which shows the status of the job, based on which the next job will be selected for the processing in the machine. In this model, the machine will be selected first, and then, the scheduling is done based on the multi-criteria scheduling system. The obtained results are compared with the existing system and from the results. The improved scheduling strategy provides better results for the scheduling problem.

Diagnosis on the basis of a computerized acoustic examination may play an incredibly important role in early diagnosis and in monitoring and even improving effective pathological speech diagnostics. Various acoustic metrics test the health of the voice. The precision of these parameters also has to do with algorithms for the detection of speech noise. The idea is to detect the disease pathology from the voice. First, we apply the feature extraction on the SVD dataset. After the feature extraction, the system input goes into the 27 neuronal layer neural networks that are convolutional and recurrent neural network. We divided the dataset into training and testing, and after 10 k-fold validation, the reported accuracies of CNN and RNN are 87.11% and 86.52%, respectively. A 10-fold cross-validation is used to evaluate the performance of the classifier. On a Linux workstation with one NVidia Titan X GPU, program code was written in Python using the TensorFlow package.

In the manufacturing company, an efficient production floor affects the productivity of the company. Thus, a well design production floor layout assists the company to achieve its objectives. In this regard, this study aims to design a new alternative production floor layout for the XYZ manufacturing company. The company facing the facility layout problem (FLP) where their workstation on the production floor was not located based on the activity-relationship. Thus, the company struggles to reduce the distance travel of their workers from one station to another by re-layout their production floor. The Systematic Layout Planning (SLP) method was used to determine the best new alternative layout for the company. Subsequently, the AnyLogic simulation software was utilized to test the effectiveness of the layout by using the number of steps as the parameter. As a result, it is found that the total number of steps of workers in the production floor can be reduced from 16,554 steps (in existing layout) to 15,956 steps (in new alternative layout).

In this article, we review past and current system architectures displaying self-organization in the domain of manufacturing. Based on a corpus of 84 reference papers, we find that multiagent systems (MAS) play a significant role in self-organization, especially MAS featuring bio-inspired algorithms for agent coordination. The emergence of new classes of cyber-physical systems further strengthens the prevalence of MAS on the subject. As outcome of our review, we devise the MOSAIK model, a generic model synthesizing all system architectures found in our corpus. The MOSAIK model can be used as a reference for formally comparing distinct architectures. We also use it to identify gaps for future research on self-organizing manufacturing systems. The model includes the central concepts of Agent and Artifact, which suggest that the Web is an adequate communication infrastructure for modern manufacturing systems: Agents become (autonomous) Web Agents and Artifacts become resources exposed by Web servers.

The current introduction of Industry 4.0 is very challenging for industrial companies. On the one hand, there is an urge to implement concepts such as digital worker assistance systems or cyber-physical production systems, but besides theoretical work, there is very little research that shows examples of its practical implementation. Furthermore, there is currently a lack of a clear model of how sensor-based worker assistance systems for data acquisition and analytics can be designed and systematically implemented. In the present research, a model for a vision-based worker assistance system for assembly was developed based on an industrial case study regarding a manual assembly line. The proposed model consists of five integrated modules: data acquisition, data preprocessing, data storage, data analysis, and simulation. The data acquisition module was constructed in the assembly workstation of the production line by implementing a depth camera, which together with an algorithm developed in Python for preprocessing, tracks the activities of the operator and inserts the processing times into a SQL table of the data storage module. This module contains all the relevant information of the production system, from the shop floor to the Manufacturing Execution System, enabling vertical integration. The data analysis module, aimed at the streaming and predictive analytics, was deployed in the RStudio platform. Likewise, the simulation module was conceptualized to retrieve real-time data from the shop floor and to select the best strategy. To evaluate the model testing of the proposed system in real production was performed. The results of this use case provide useful information for academia as well as practitioners how to implement vision-based worker assistance systems.

Advanced CAD technology helps its users unleash their ingenuity by enabling them to do what has never been done in product design. The next generation technology offers state of the art design environment with swifter loading times and newer options to elucidate the model. Work has progressively been done by global coders employed by the CAD software companies, writing complex codes so as to make the design process smooth and rapid. The advanced CAD technology also asks for high graphic resolution and storage space. For this, advanced workstations have been deployed. The challenges faced by designers in CAD industry vary from increasingly intricate products dependent on good CAD infrastructure to ever decreasing time between the initiation and completion of a production process, and these can only be achieved with an articulate software that combines the best tools onto a single platform. To understand the difference in what the advanced CAD technology has to offer and primitive CAD tools lack in, a 3D CAD model of Single Plate Clutch was designed and modelled, initially on obsolete CAD platform currently not suitable for 3D modelling (Autocad, in this case), and then on contemporary advanced CAD platform (Siemens NX12). The whole process comprised of modelling, assembly and drafting of the machine. Thereafter, differences in terms of time consumed, ease of designing and quality of design produced (conformity towards manufacturability) were recorded. Finally, it was concluded that the advanced CAD platform offered more functionality and successfully meets the requirements of the growing CAD industry.

Good Quality and higher productivity play important role in manufacturing industries. Delivering improved quality product at reduced price in stiff-cut throat competitive market condition needs optimization of process. Welding is one of basic manufacturing process adopted by many industries for the production work. Weld quality inspection is carried out after welding is performed and product are rejected if defects are identified resulting in to repetition of whole cycle. To study and develop credible diagnosis system for welding On-line quality control in industry is customary of strategies. Sensors located in various region of welding play a significant role in online monitoring for process diagnostics. Experimental investigations will help to map weld quality in early stage with real time monitoring weld temperature, voltage, acoustic etc. with help of sensors placed around welding region. Arc column interface data can be captured using sensor and transferred via controllers displayed on mobile or workstation for live monitoring. In present paper authors have put an attempt to find need of submerged arc welding (SAW) arc column behaviour, its varied effect on weld quality, characterization of defect with sensor signals, methods used for monitoring and techniques to make intelligent welding expert system using Internet of Thing (IoT). Smart manufacturing is demanding change in the path of digitalization revolution. Adoption of Internet of Things (IoT) in the welding imparts assistances to overcome constraint based on adaptive control strategy leading to smart welding. Modern manufacturing environment is increasing reliant on high performance monitoring systems.

The paper shows the features of the development of an automated stepper motor control workstation using the visual programming environment of the ZETLAB SCADA system, which reduces the development time by using ready-made hardware and software modules. The control scheme of the stepper motor driver based on the digital modules ZET 7176, ZET 7160-s of the ZETSENSOR series, interacting on the basis of the CAN 2.0 interface, is considered. The absence of hardware inputs of the ZET 7160-s module responsible for working with end and emergency switches, which complicate the implementation of algorithms for precise positioning of the control object, is noted. The software limitation of the firmware of the ZET 7160-s hardware module and the graphic component “ZET 7xxx_1 configuration” of the visual programming environment of the ZETLAB SCADA system is shown, which does not provide sequential input of the same motion parameters to the stepper motor control module.

Computer laboratories of educational institutions have increased the information technology infrastructure. However, it is very much exposed to several threats and vulnerabilities when it comes to the information that was kept in several workstations inside the laboratory. The study addressed the security issues in terms of the use of the computer laboratories using the barcode technology in regulating the entry point of the students and logging in the attendance log. It will only allow student users who were currently enrolled based on the schedule laboratory time and who has an account in mymu server.

Graphical abstract, Highlights • We present PySTACHIO, a refined version of our spot tracking algorithm. • We demonstrate highly improved performance over previous MATLAB versions. • PySTACHIO can accurately estimate stoichiometries and 2D diffusion coefficients. • Performance is comparable to state-of-the-art packages on challenge data. • PySTACHIO has both GUI and command line interfaces and can be hosted as a web app., As camera pixel arrays have grown larger and faster, and optical microscopy techniques ever more refined, there has been an explosion in the quantity of data acquired during routine light microscopy. At the single-molecule level, analysis involves multiple steps and can rapidly become computationally expensive, in some cases intractable on office workstations. Complex bespoke software can present high activation barriers to entry for new users. Here, we redevelop our quantitative single-molecule analysis routines into an optimized and extensible Python program, with GUI and command-line implementations to facilitate use on local machines and remote clusters, by beginners and advanced users alike. We demonstrate that its performance is on par with previous MATLAB implementations but runs an order of magnitude faster. We tested it against challenge data and demonstrate its performance is comparable to state-of-the-art analysis platforms. We show the code can extract fluorescence intensity values for single reporter dye molecules and, using these, estimate molecular stoichiometries and cellular copy numbers of fluorescently-labeled biomolecules. It can evaluate 2D diffusion coefficients for the characteristically short single-particle tracking data. To facilitate benchmarking we include data simulation routines to compare different analysis programs. Finally, we show that it works with 2-color data and enables colocalization analysis based on overlap integration, to infer interactions between differently labelled biomolecules. By making this freely available we aim to make complex light microscopy single-molecule analysis more democratized.

Current radiology training for medical students and residents predominantly consists of reviewing teaching files, attending lectures, reading textbooks and online sources, as well as one-on-one teaching at the workstation. In the case of medical schools, radiology training is quite passive. In addition, the variety of important and high-yield cases that trainees are exposed to may be limited in scope. We utilized an open-source dcm4chee-based Picture Archiving and Communication System (PACS) named “Weasis” in order to simulate a radiologist’s practice in the real world, using anonymized report-free complete cases that could easily be uploaded live during read-outs for training purposes. MySQL was used for database management and JBOSS as application server. In addition, we integrated Weasis into a web-based reporting system through Java programming language using the MyEclipse development environment. A freeware, platform-independent, image database was established to simulate a real-world PACS. The sever was implemented on a dedicated non-workstation PC connected to the hospital secure network. As the client access is through a webpage, the cases can be viewed from any computer connected to the hospital network. The reporting system allows for evaluation purposes and providing feedback to the trainees. Brief survey results are available. Implementation of such a low-cost, versatile, and customizable tool provides a new opportunity for training programs in offering medical students with an active and more realistic radiology experience, junior radiology residents with potentially better preparation for independent call, and senior resident and fellows with the ability to fine-tune high-level specialty-level knowledge.

Traditionally, the infrastructure required for broadcast media creation has consisted of specialized graphics workstations, high-performance storage arrays, complex networking, and video wiring, all of which are capital-intensive and expensive to maintain. Over the past two years, NBCUniversal has developed a cloud infrastructure model to provide on-air media creation as a service to its creative teams. Utilizing GPU-enabled cloud-based virtual machines, dynamically scalable high-performance cloud-native storage, and infrastructure-as-code methodologies, we are now able to provide full end-to-end media production workflows in the public cloud. With an automation-forward approach, we know exactly what is going to be applied, how it will propagate through the infrastructure, and what dependencies are involved. Elastic scalability of compute and storage eliminates over-provisioning (and its related capital investments) and provides the ability to dynamically add/remove resources as necessary. This paper aims to highlight the technical details of our programmatically reproducible solution as well as the challenges and benefits of media creation in the cloud .

Over the years there has been a fixed idea that components just enter the assembly floor and that assembled products leave it subsequently after certain operations have been executed on such products. Besides, there is a common notion that only small and simple products can be assembled on the so called “assembly nests”; however, the dimensions of objects assembled inside these keep increasing. Nowadays, even an aircraft, a boat, etc. can also be assembled on a moving trolley. This is possible given to the fact that the trolley with the product and with the operators themselves may come to the same storage of parts, while the system does not need to be balanced in time. On the other hand, in assembly nested layouts, the productivity of one operator is usually higher than the productivity on the line station and this because such lines are not often time balanced. Besides, this is also enhanced by the fact that more than one operator can work on a single nest. In this regard, the present paper seeks to identify the ways of combining or assembling components into products, and to analyse quality of the abovementioned assembly approaches.

Current terminal devices, such as Personal computers (PCs), diskless workstation, mobile terminals and embedded Internet of things (IoT) devices, are facing several challenges, including limited computing capabilities and storage resources, complex maintenance and management of the software and data, as well as secure service provisioning. Facing these challenges, Cloud computing (CC) and Edge computing (EC) encourage the terminal devices to shift compute-intensive works to the cloud servers or edge nodes. Different from CC and EC, Transparent computing (TC) is a novel user-centric computing paradigm in which the hardware and software are separated in different places. Specificaly, all the software, including Operating systems (OSes), applications programs and management tools, are deposited on the servers and transmitted on demand to terminal devices in a transparent way, while the computation is performed on terminals. In this article, we give a broad survey on transparent computing about the development and current status and compare the differences with CC and EC. To realize the provisioning of the cross-platform service, TC shields hardware differences of heterogeneous devices and builds standardized hardware and software interfaces. From the perspective of security, TC entails high-level security mechanisms and the Meta OS can detect malware and OS-level attacks. Specifically, we first review the development courses of network computing paradigms and the motivation of TC. Then, we present a comparison of several emerging computing paradigms and TC from three perspectives, i.e., virtualization, location for computing, and location for storage. We also show the basic architecture of TC, development process, current status, and key enabling technologies of TC for PCs and lightweight terminals. Lastly, several new challenges and future research directions are indicated to inspire continuous investigations. We believe that this survey can help readers to obtain complete information about TC.

The SPARC instruction set architecture (ISA) has been used in various processors in workstations, embedded systems, and in mission-critical industries such as aviation and space engineering. Hence, it is important to provide formal frameworks that facilitate the verification of hardware and software that run on or interface with these processors. In this work, we give the first formal model for multi-core SPARC ISA and Total Store Ordering (TSO) memory model in Isabelle/HOL. We present two levels of modelling for the ISA: The low-level ISA model, which is executable, covers many features specific to SPARC processors, such as delayed-write for control registers, windowed general registers, and more complex memory access. We have tested our model extensively against a LEON3 simulation board, the test covers both single-step executions and sequential execution of programs. We also prove some important properties for our formal model, including a non-interference property for the LEON3 processor. The high-level ISA model is an abstraction of the low-level model and it provides an interface for memory operations in multi-core processors. On top of the high-level ISA model, we formalise two TSO memory models: one is an adaptation of the axiomatic SPARC TSO model (Sindhu et al. in Formal specification of memory models, Springer, Boston, 1992; SPARC in The SPARC architecture manual version 8, 1992. http://gaisler.com/doc/sparcv8.pdf ), the other is a new operational TSO model which is suitable for verifying execution results. We prove that the operational model is sound and complete with respect to the axiomatic model. Finally, we give verification examples with two case studies drawn from the SPARCv9 manual.

This paper presents a design process of workstation with ergonomic features for University Kuala Lumpur MIDI Classroom. The workstation is expected to support body posture, with the aim to increase comfortability of a user usage for long periods in a class. Besides that, the workstation will ensure a conducive and responsive learning environment. Discomfort and an improper position can negatively affect overall health and productivity. A new design of workstation, which allows user to sit in ideal sitting position suggested by ergonomist and easy transition from one teaching mode to the next. The researcher has designed and developed a new workstation which has ideal ergonomic sitting working position and capable accommodate 50th percentile human size. These positions were used to evaluate the comfort of the workstation. Subjective evaluations, including comparison of the prototype and standard workstation setup, were carried out using human subjects and ergonomic principles. Result showed that the new workstation is much more comfortable, supporting the body in a balanced way. Users have the freedom to stretch and relax in different working positions before they feel any noticeable discomfort. As a result, it lets user sit for a longer period without strain, thus resulting in higher productivity and concentration in classroom.

Medical students mast understand the concept of algorithm. There are three main ways for algorithm writing and representation. The main and most convenient is the well-known flowcharts. Therefore, we need special software for creating flowcharts of medical algorithms of diagnosis and treatments.The most common recommendations are about using Microsoft solutions: “insert figures” button/command in Microsoft Word, or Microsoft Visio for professional cases. Also there are large number software utilities for building UML diagrams. Our goal is selecting the standard for flowcharts and finding good software. There are 4 alternative flowchart rules: standard ISO 5807:1985, Dragon-schemas, and two versions of Unified Modeling Language (ISO/IEC standards). The merits of the new solutions are actual only for large and complex algorithms and it takes more time for learn and use. Unfortunately, we have only two practical classes by course syllabus. So we select simplified version of old standard ISO 5807: 1985.The requirements mast be defined before making choice about software. There are several basic requirements. Application launch on the workstations instead of server or cloud. By this way we will not dependent of quality of internet or LAN services. Compatibility with most popular versions of Windows. Availability as freeware and we need rights for installing multiple copies. Regular updating software versions. Functionality and usability, the "intuitive interface."By this set of requirements, we select “yEd Graph Editor” software, because it is easy to learn and use, have all of diagram shapes, can save and export results, and it is freeware. Students understand how to make the base actions in this environment in a few minutes - after the first demonstration. Now there is enough time for drawing a complex algorithm flowchart during the lesson. And student have time for making corrections and update flowchart after teacher checking.We used this software over the last two years and we can recommend to use "yEd Graph Editor" in the case of limited time for practical classes. Key words: algorithm, computer science, flowcharts, software.

This paper focuses on proposing a system for centralization of the IT infrastructure by building upon the concept of Diskless Booting. The client stations are configured to boot over an existing network using the Network Boot. The Client Station lacks an actual Hard Drive, which is responsible for storing the boot files and other necessary files. It consists of other hardware excluding the Hard Drive such as, RAM, Processor, etc. The network consists of DHCP (Dynamic Host Configuration Protocol) server which assigns IP addresses to several client stations connected. The NIS (Network Information Service) server stores the login credentials of all the users, enabling the users to login from any client station without any restrictions. The NFS (Network File System) server makes the files available for the user, even on the absence of local secondary storage. Security is ensured by SHA (Security Hash Algorithm), which encrypts the sensitive data by creating the hash values. Individual ports and services can be kept secured by using the Firewall service. The open source Cockpit Tool provides a GUI with which the administrator can conveniently carry out several admin-oriented tasks, such as memory management, user management.

Due to the high-quality standards required by the process control industry such as liquid-level control, it is desired to implement sophisticated controllers that ensure the proper functioning of the process. Currently most industrial controllers are of the classic PID type. These controllers do a good job in reducing the system error and have simple structure and can be tuned easily when compared to fuzzy gain scheduled PID controllers. However, classic PID controllers do not perform well when the controlled system possesses largely varying dynamics at different operating conditions. Another limitation of classic PID controllers is that their operation depends on the tuning of the proportional, derivative, and integral gains. This paper presents a comparative study between a fuzzy gain scheduled PID controller and a classic PID controller commonly implemented in the process control industry. A comprehensive mathematical model for the Festo MPS PA compact workstation is developed for future use for control system design of the MPS PA compact workstation. Based on the experimental results, the fuzzy gain scheduled PID controller demonstrated supremacy on the PID control strategy. The presented analysis is verified by the implementation of the fuzzy gain scheduled PID control algorithm in the MPS PA compact workstation using custom-built LabVIEW interface. Experimental results verified the effectiveness of the proposed control scheme.

3D-printed laboratory devices can enable ambitious research purposes even at a low-budget level. To follow this trend, here we describe the construction, calibration, and usage of the FINDUS (Fully Integrable Noncommercial Dispensing Utility System). We report the successful 3D printing and assembly of a liquid-handling workstation for less than $400. Using this setup, we achieve reliable and flexible liquid-dispensing automation with relative pipetting errors of less than 0.3%. We show our system is well suited for several showcase applications from both the biology and chemistry fields. In support of the open-source spirit, we make all 3D models, assembly instructions, and source code available for free download, rebuild, and modification.

At present, the daily and combat activities of almost any army in the world are largely determined by the quality of information and space support. At the same time, the quality of support depends largely on the stability of the functioning of such unique technical facilities as spacecraft flight control centers. Based on the features of building new and upgrading existing flight control centers, their susceptibility to destructive information influences has been established. In this regard, the only way to guarantee the recovery of the information management system after information and technical impact was determined, namely, the complete redeployment of automated workplaces, including the reinstalling of operating systems, general software and special software. To ensure the efficiency of recovery of the system under consideration, the need to automate the deployment of software for automated workstations of the spacecraft flight control center was justified. The results of the analysis of existing approaches to software deployment have shown the need for implementation directly disrespecting methods. Based on this, the complex software deployment process was formalized, and the structure of the automated software deployment system for automated workstations of the spacecraft flight control center was proposed, the use of which will ensure the necessary level of stability in the implementation of technological cycles of spacecraft control in particular, and the quality of information and space support for troops in General.

[ES] AUTIS dispone de un producto denominado SVS que agrupa diferentes tecnologías de detección de defectos basadas en cámaras de visión artificial Gigabit Ethernet. Para procesar todas las imágenes y detectar los defectos necesita un rack computacional formado por Workstation y switches industriales. El objetivo principal de este proyecto es desarrollar una toolkit que nos permita modificar de forma programática la configuración del switch y de la Workstation. La primera tarea será el análisis y el entendimiento del rack computacional de SVS. Bajo la tutela del personal senior de AUTIS, se llevará a cabo el desarrollo de esta aplicación que tendrá como herramientas: ¿ LabVIEW como entorno de desarrollo de la toolkit, ya que servirá para integrarla en el código actual de SVS. ¿ Scripting PowerShell para equipos de red Cisco y Dell, que permita la migración de las comunicaciones de unos servidores a otros de manera automática en función de la elección del usuario. ¿ En LabVIEW se encuentra desarrollada una gran parte de la aplicación actual, por lo que utilizaremos este lenguaje para implementar el desarrollo., [EN] AUTIS has a product called SVS that brings together different defect detection technologies based on Gigabit Ethernet artificial vision cameras. In order to process all the images and detect the defects it needs a computational rack made up of Workstation and industrial switch. The main objective of this project is to develop a toolkit that allows us to programmatically modify the switch and Workstation configuration. The first task will be the analysis and understanding of the SVS computational rack. Under the guidance of AUTIS senior staff, the development of this application will be carried out with the following tools: ¿ LabVIEW as the toolkit development environment, as it will serve to integrate it into the current SVS code. ¿ PowerShell scripting for Cisco and Dell network equipment, which allows the migration of communications from one server to another automatically according to the user¿s choice. ¿ A large part of the current application is developed in LabVIEW, so we will use this language to implement the development.

Summary Variant Call Format (VCF) files with results of sequencing projects take a lot of space. We propose the VCFShark, which is able to compress VCF files up to an order of magnitude better than the de facto standards (gzipped VCF and BCF). The advantage over competitors is the greatest when compressing VCF files containing large amounts of genotype data. The processing speeds up to 100 MB/s and main memory requirements lower than 30 GB allow to use our tool at typical workstations even for large datasets. Availability and implementation https://github.com/refresh-bio/vcfshark. Supplementary information Supplementary data are available at Bioinformatics online.

High-performance computing comprises thousands of processing powers in order to deliver higher performance computation than a typical desktop computer or workstation in order to solve large problems in science, engineering, or business. The scheduling of these machines has an important impact on their performance. HPC’s job scheduling is intended to develop an operational strategy which utilises resources efficiently and avoids delays. An optimised schedule results in greater efficiency of the parallel machine. In addition, processes and network heterogeneity is another difficulty for the scheduling algorithm. Another problem for parallel job scheduling is user fairness. One of the issues in this field of study is providing a balanced schedule that enhances efficiency and user fairness. ROA-CONS is a new job scheduling method proposed in this paper. It describes a new scheduling approach, which is a combination of an updated conservative backfilling approach further optimised by the raccoon optimisation algorithm. This algorithm also proposes a technique of selection that combines job waiting and response time optimisation with user fairness. It contributes to the development of a symmetrical schedule that increases user satisfaction and performance. In comparison with other well-known job scheduling algorithms, the simulation assesses the effectiveness of the proposed method. The results demonstrate that the proposed strategy offers improved schedules that reduce the overall system’s job waiting and response times.

We present Labkit, a user-friendly Fiji plugin for the segmentation of microscopy image data. It offers easy to use manual and automated image segmentation routines that can be rapidly applied to single- and multi-channel images as well as to timelapse movies in 2D or 3D. Labkit is specifically designed to work efficiently on big image data and enables users of consumer laptops to conveniently work with multiple-terabyte images. This efficiency is achieved by using ImgLib2 and BigDataViewer as the foundation of our software. Furthermore, memory efficient and fast random forest based pixel classification inspired by the Waikato Environment for Knowledge Analysis (Weka) is implemented. Optionally we harness the power of graphics processing units (GPU) to gain additional runtime performance. Labkit is easy to install on virtually all laptops and workstations. Additionally, Labkit is compatible with high performance computing (HPC) clusters for distributed processing of big image data. The ability to use pixel classifiers trained in Labkit via the ImageJ macro language enables our users to integrate this functionality as a processing step in automated image processing workflows. Last but not least, Labkit comes with rich online resources such as tutorials and examples that will help users to familiarize themselves with available features and how to best use Labkit in a number of practical real-world use-cases.

MotivationCore sequencing facilities produce huge amounts of sequencing data that need to be analysed with automated workflows to ensure reproducibility and traceability. Eoulsan is a versatile open-source workflow engine meeting the needs of core facilities, by automating the analysis of a large number of samples. Its core design separates the description of the workflow from the actual commands to be run. This originality simplifies its usage as the user does not need to handle code, while ensuring reproducibility. Eoulsan was initially developed for bulk RNA-seq data, but the transcriptomics applications have recently widened with the advent of long-read sequencing and single-cell technologies, calling for the development of new workflows.ResultWe present Eoulsan 2, a major update that (i) enhances the workflow manager itself, (ii) facilitates the development of new modules, and (iii) expands its applications to long reads RNA-seq (Oxford Nanopore Technologies) and scRNA-seq (Smart-seq2 and 10x Genomics). The workflow manager has been rewritten, with support for execution on a larger choice of computational infrastructure (workstations, Hadoop clusters, and various job schedulers for cluster usage). Eoulsan now facilitates the development of new modules, by reusing wrappers developed for the Galaxy platform, with support for container images (Docker or Singularity) packaging tools to execute. Finally, Eoulsan natively integrates novel modules for bulk RNA-seq, as well as others specifically designed for processing long read RNA-seq and scRNA-seq. Eoulsan 2 is distributed with ready-to-use workflows and companion tutorials.Availability and implementationEoulsan is implemented in Java, supported on Linux systems and distributed under the LGPL and CeCILL-C licenses at: http://outils.genomique.biologie.ens.fr/eoulsan/. The source code and sample workflows are available on GitHub: https://github.com/GenomicParisCentre/eoulsan. A GitHub repository for modules using the Galaxy tool XML syntax is further provided at: https://github.com/GenomicParisCentre/eoulsan-toolsContacteoulsan@bio.ens.psl.eu

Objective A neural networks approach has been proposed to handle various inputs such as postural, anthropometric and environmental variables in order to estimate self-reported discomfort in picking tasks. An input reduction method has been proposed, reducing the input variables to the minimum data required to estimate self-reported discomfort with similar accuracy as the neural network fed with all variables. Background Previous works have attempted to explore the relationship between several factors and self-reported discomfort using observational methods. The results showed that this relationship was not a simple linear relationship. Another study used neural networks to model the function returning reported discomfort according to static posture, age, and anthropometrics variables. The results demonstrated the model’s ability to predict reported discomfort. But all the available variables were used to design the neural network. Method Eleven subjects carried-out picking tasks with various masses (0, 1, 3 kg) and imposed duration (5, 10, or 15 s). Continuous REBA score, anthropometric and environmental data were computed, and subjects’ discomfort were collected. The data set of this work consisted in the computed continuous REBA score, anthropometric, environmental data and collected subjects’ discomfort. Results The results showed that the correlation between the estimated and experimental tested data was equal to 0.775 when using all the 14 available variables. After data reduction, only 6 variables were left, with a very close performance when predicting discomfort. Conclusion A neural network approach has been proposed to estimate self-reported discomfort according to a minimum set of postural, anthropometric and environmental variables in picking tasks. Application This method has the potential to support ergonomists in workstation designing processes, by adding discomfort prediction to virtual manikins’ behaviors in simulation tools.

Zieg, J. and Zawada, D.G., 2021. Improving ESRI ArcGIS performance of coastal and seafloor analyses with the Python multiprocessing module. Journal of Coastal Research, 37(6), 1288–1293. Coconut Creek (Florida), ISSN 0749-0208. Coastal research frequently involves the use of a GIS to analyze large areas for changes in response to major weather events, human action, and other factors. The GIS workflows used to conduct these analyses can be complex and sometimes require multiple days to complete. Long runtimes often exist even on modern high-powered workstations if the GIS software does not use parallel computing techniques, which prevents it from fully utilizing the capabilities of multicore processors. If a GIS application supports a programming interface that allows geoprocessing tools to be called from an external program, then GIS workflows can use parallel functionality embedded in that programming language to divide the load of a large workflow among multiple child processes. In ArcMap and ArcGIS Pro, this technique can be implemented by using the Python programming interface and the multiprocessing module in Python to run geoprocessing tools in child processes. This method was used in the Seafloor Elevation Change Analysis Tool (SECAT), a Python script written for ArcMap and ArcGIS Pro that calculates changes in seafloor elevation over time using two different digital elevation models. Running SECAT with between one and eight child processes on two different datasets improved execution times by at least a factor of 2.4. These results demonstrate that using the Python multiprocessing module can significantly accelerate a variety of time-consuming workflows.

The integration of real, physical objects into virtual scenarios enables direct haptic feedback for the user. In addition to the interaction with small, hand-held, hybrid objects, i.e., objects that exist both in the virtual and real environments, it is also possible to interact with more massive objects, such as tables and chairs. A virtual assembly scenario for both a seated and a standing assembly workstation to be used in conjunction with a standing-height drill station was developed and matching physical and virtual representations of the furniture, a movable work chair, was added. The virtual world was dynamically aligned to the real object by means of tracking hardware, so that virtuality and reality shared the same spatial position in relation to the user. Within a study, the participants had to carry out a manual assembly task on both workstations, thus physically and dynamically interacting with and using (sitting down on, getting up from) the real chair integrated in the virtual scenario of the seated workbench. The chair was absent in the scenario of the standing assembly workbench. The collected data on subjective cognitive workload, user experience and presence are supposed to provide an initial indication of the influence of such physical objects in the virtual world. Furthermore, the question of how trust in physical objects can be increased in the virtual world is investigated.

Internet of Things (IoT) has revolutionized the way of living. The word “automatic” can be seen come into the practice with the advent of IoT. Humans and interact with devices and devices can interact with humans and also with each other. this has made life exceptionally easy. we are now surrounded by Smart Cities, Smart Devices, Smart Cars, and likewise through the IoT. Along with the advantages, come few limitations as well. The major limitation of interconnecting and establishing communication between the devices is the power consumption. Being part of a developing nation, this limitation becomes all the more challenging. The purpose of discussing the Energy-saving from Electrical Device Scrutiny and Control systems based on the Internet of Things is imperative because a hefty amount of energy is disbursed by lighting appliances, so making enhanced proficiency and hasty fault detection device may be a substantial challenge. To overwhelm this matter, appropriate energy-saving procedures and lighting control are to be executed. In the proposed model, we have two types of models which approaches are tracked counting on the character of application for on-premise ranges with narrowed buildings IEEE 802.11n wireless technology is active where all the appliances are connected with a standard Wi-Fi network. In the other model have related to the street lamp with a hefty number of devices connected only in a single wired way, a wired configuration is hired to avoid range issues.

Objective This study aimed to assess the prevalence of neck pain and to identify associated occupational factors in Portuguese office workers. Background There is still necessary to quantify the association of the use of new technologies with neck pain in office workers. Methods Six hundred-and-one office workers completed online questionnaires with questions related to anthropometric parameters, work-related variables, workstation setup, and musculoskeletal pain from the Portuguese version of the Standardized Nordic Musculoskeletal Questionnaire. Results The prevalence of neck pain was 56.1%. An average of 35.6% of the office workers with neck pain reported pain in more than three body segments. The significantly risk factors were “age between 50 and 65” [OR: 1.92 (1.26–2.91) P = 0.002], “working without break for 2 h” [OR: 1.82 (1.00–3.31) P = 0.05], “more than 3 h” [OR: 2.41 (1.35–4.10) P = 0.003], screen localization not centered” [OR: 2.01 (1.01–4.00) P = 0.045], and “use of computer mouse more than 50% of the worktime” [OR: 2.05 (1.14–3.71) P = 0.017]. Conclusion There was a high prevalence of neck pain and a considerable number of painful body segments in office workers. Age, working without break, screen localization and the use of computer mouse where the significant risk factors associated with the development of neck pain. Relevance to industry A high prevalence of neck pain and number of areas with pain in office workers require a detailed pain mechanism assessment. There were associated occupational risk factors for the development of neck pain. Call for concerted actions to explore optimal and efficient management plans.

Nowadays, it is becoming increasingly important to use the most efficient and most suitable computational resources for algorithmic tools that extract meaningful information from big data and make smart decisions. In this paper, a comparative analysis is provided for performance measurements of various machine learning and bioinformatics software including scikit-learn, Tensorflow, WEKA, libSVM, ThunderSVM, GMTK, PSI-BLAST, and HHblits with big data applications on different high performance computer systems and workstations. The programs are executed in a wide range of conditions such as single-core central processing unit (CPU), multi-core CPU, and graphical processing unit (GPU) depending on the availability of implementation. The optimum number of CPU cores are obtained for selected software. It is found that the running times depend on many factors including the CPU/GPU version, available RAM, the number of CPU cores allocated, and the algorithm used. If parallel implementations are available for a given software, the best running times are typically obtained by GPU, followed by multi-core CPU, and single-core CPU. Though there is no best system that performs better than others in all applications studied, it is anticipated that the results obtained will help researchers and practitioners to select the most appropriate computational resources for their machine learning and bioinformatics projects.

Artificial intelligence Computerized modelling is the best solution to manage immense information and storage in the IoT Network. Furthermore, IoT these days becoming more increasingly well-known with the development of high speed web systems and many advanced sensors that can be coordinated into a microcontroller. The information flows in the virtual environment presently will have these sensors data and the client information that can be send and receive information from the workstations using the peer to peer networking and computing. With the increase in the quantity of workstation and an ever increasing number of sensors, a few information might confront issues on the storage, delay, area constraint and congestion in the systems. To keep away from these issues, numerous mathematical calculations have been proposed in the recent past which has not been developed an fruitful solution for this issues.. In this work, an advanced fuzzy hybridized Artificial Intelligence system has been proposed to management the request on IoT platform. The significance of request management and computing has been processed in this paper. The experiment results show prominent outcomes than traditional methods.

INTERLEAF, INC., was an early entry into the computer-based publishing business, initially based on computer workstations and focusing on technical publishing. The company was formed in 1981, shipped its fi rst product in 1984, which included a variety of hardware and software innovations, and was in a strong position to go public in 1986. In the later 1980s, other companies entered the business in competition with Interleaf, and personal computers then had the power that once required an expensive workstation; there was also standardization around window systems such as the X Window System, Motif on top of X, and Microsoft Windows. Also some of Interleaf's innovations were no longer competitive advantages as the industry coalesced around alternative technologies such as PostScript and Acrobat Reader. Redirecting its business strategy once and then again, Interleaf continued on with up and down success until 2000 when it was acquired by Broad Vision.