Comparative Analysis of Open Source Frameworks for Machine Learning with Use Case in Single-Threaded and Multi-Threaded Modes

The basic features of some of the most versatile and popular open source frameworks for machine learning (TensorFlow, Deep Learning4j, and H2O) are considered and compared. Their comparative analysis was performed and conclusions were made as to the advantages and disadvantages of these platforms. The performance tests for the de facto standard MNIST data set were carried out on H2O framework for deep learning algorithms designed for CPU and GPU platforms for single-threaded and multithreaded modes of operation.Comment: 4 pages, 6 figures, 4 tables; XIIth International Scientific and Technical Conference on Computer Sciences and Information Technologies (CSIT 2017), Lviv, Ukrain

Business integration between manufacturing and transport-logistics firms

Purpose - This paper analyses how manufacturers and transport-logistics service providers (TLSPs) work together and integrate their business processes. The information technologies used to support the integration, the processes currently integrated, and the expected future integration, are searched. Design/methodology/approach - Six in-depth case studies were conducted among leading companies in the electrical, electronics, mechanical, food processing, and transport-logistics industries. The data was collected using comprehensive semi-structured interviews. Findings - Most of the firms are coupled electronically through EDI. The current business integration practices are primarily restricted to some sub-processes in three key SC processes: Customer service management, order fulfillment and backwards logistics. In the future the manufacturers want a better integration with the TLSPs, but at the same time, manufacturers would like to have the freedom of breaking the relationship, if the party does not fulfill the requisites and expectations. The future developments associated to the "commoditization" of TLSPs’ services would reinforce this trend. Originality/value - This research has shed light on a relatively unexplored area related to the integration between manufacturers and transport-logistics firms. Our research has highlighted the complexity of the integration between the two echelons, and has helped to the identification of current areas of integration. This research has also contributed to understand how the integration occurs in real contexts, by uncovering with a high degree of detail, what manufactures do to integrate their business with the TLSPsSupply chain management; Business process integration; Information technologies (IT); Standardization; Manufacturers; Transport and Logistics Service Providers (TLSPs)

Implementation of Robot Operating System in Beaglebone Black based Mobile Robot for Obstacle Avoidance Application

The Robot Operating System (ROS) is a collection of tools, libraries, and conventions that focus on simplifying the task of creating a complex and advanced robotics system. Its standard framework can be shared with another robotics system that has a similar platform and suitable for being introduced as an educational tool in robotics. However, the problems found out in the current robot platform available in the market are expensive and encapsulated. The development of an open source robot platform is encouraged. Therefore, this research is carried out to design and develop an ROS based obstacle avoidance system for existing differential-wheeled mobile robot. The ROS was installed under Ubuntu 14.04 on a Beaglebone Black embedded computer system. Then, the ROS was implemented together with the obstacle avoidance system to establish the communication between program nodes. The mobile robot was then designed and developed to examine the obstacle avoidance application. The debugging process was carried out to check the obstacle avoidance system application based on the communication between nodes. This process is important in examining the message publishing and subscribing from all nodes. The obstacle avoidance mobile robot has been successfully tested where the communication between nodes was running without any problem

Performance Analysis of Open Source Machine Learning Frameworks for Various Parameters in Single-Threaded and Multi-Threaded Modes

The basic features of some of the most versatile and popular open source frameworks for machine learning (TensorFlow, Deep Learning4j, and H2O) are considered and compared. Their comparative analysis was performed and conclusions were made as to the advantages and disadvantages of these platforms. The performance tests for the de facto standard MNIST data set were carried out on H2O framework for deep learning algorithms designed for CPU and GPU platforms for single-threaded and multithreaded modes of operation Also, we present the results of testing neural networks architectures on H2O platform for various activation functions, stopping metrics, and other parameters of machine learning algorithm. It was demonstrated for the use case of MNIST database of handwritten digits in single-threaded mode that blind selection of these parameters can hugely increase (by 2-3 orders) the runtime without the significant increase of precision. This result can have crucial influence for optimization of available and new machine learning methods, especially for image recognition problems.Comment: 15 pages, 11 figures, 4 tables; this paper summarizes the activities which were started recently and described shortly in the previous conference presentations arXiv:1706.02248 and arXiv:1707.04940; it is accepted for Springer book series "Advances in Intelligent Systems and Computing

Design of a Controller for Simultaneous Control of Multiple Systems in Wireless Scenario

Wireless technology is becoming an ever-emerging part of human life with new services and products being released every month. Thus wireless communications brings huge benefits to the user or users. The used Radio Frequency (RF) Module is basically an Advanced Virtual RISC (AVR) microcontroller based communication system. The RF Module used in our project contains two units transmitter and receiver. The transmitter module converts parallel data into serial by using HT12E encoder prior to wireless transmission. The encoded data get received by receiver and converts or decodes the serial data into parallel by using HT12D decoder. After converting the data into parallel form which is made use by AVR16A micro controller to generate instructions for operation of relays connected to two different bulbs

Design of a GSM based digital door lock

The proposed project is intended to design an access control system using GSM technology. GSM (Global System for Mobile communication) is a digital mobile telephony system that uses a variation of Time Division Multiple Accesses (TDMA) and most widely uses the three digital wireless telephony technologies i.e., TDMA, CDMA & FDMA. The present project is an innovative idea for providing security by restricting the access of certain areas to certain people only. In this case of security, the opening & closing of the gate of the restricted areas is done through SMS. A GSM modem is used for this purpose. It allows only authenticated SIM cards or number for the access purpose rejecting all other unauthenticated SIM card users. When an ‘OPEN ’SMS is sent, the gate opens up and then closes automatically

Internet of Things Architectures, Technologies, Applications, Challenges, and Future Directions for Enhanced Living Environments and Healthcare Systems: A Review

Internet of Things (IoT) is an evolution of the Internet and has been gaining increased attention from researchers in both academic and industrial environments. Successive technological enhancements make the development of intelligent systems with a high capacity for communication and data collection possible, providing several opportunities for numerous IoT applications, particularly healthcare systems. Despite all the advantages, there are still several open issues that represent the main challenges for IoT, e.g., accessibility, portability, interoperability, information security, and privacy. IoT provides important characteristics to healthcare systems, such as availability, mobility, and scalability, that o er an architectural basis for numerous high technological healthcare applications, such as real-time patient monitoring, environmental and indoor quality monitoring, and ubiquitous and pervasive information access that benefits health professionals and patients. The constant scientific innovations make it possible to develop IoT devices through countless services for sensing, data fusing, and logging capabilities that lead to several advancements for enhanced living environments (ELEs). This paper reviews the current state of the art on IoT architectures for ELEs and healthcare systems, with a focus on the technologies, applications, challenges, opportunities, open-source platforms, and operating systems. Furthermore, this document synthesizes the existing body of knowledge and identifies common threads and gaps that open up new significant and challenging future research directions.info:eu-repo/semantics/publishedVersio

Raspcare: A Telemedicine Platform for the Treatment and Monitoring of Patients with Chronic Diseases

Metabolic and electrophysiological measures must remain within normal values to maintain the quality of life of chronic patients. Furthermore, depending on the age and disease stage of the individual, automatic identification of risk situations is critical for emergency support. To achieve these goals, this study proposes a technological solution termed Raspcare to help both the patients in their self-care and the medical teams monitoring the patients. The solution consists of a domestic gateway equipped with a microcontroller and various interfaces to allow interaction between the platform and household devices, such as televisions, biometric sensors, blood glucose metres, non-invasive pressure gauges, smartphones and smartwatches, among others. The gateway implements a Linux OS application responsible for executing the user’s health plan, which involves periodic measurements, medications and dietary care. Moreover, the application has data processing algorithms to establish alerts for the automatic detection of abnormal measurements and falls