A unified radio control architecture for prototyping adaptive wireless protocols

Experimental optimization of wireless protocols and validation of novel solutions is often problematic, due to limited configuration space present in commercial wireless interfaces as well as complexity of monolithic driver implementation on SDR-based experimentation platforms. To overcome these limitations a novel software architecture is proposed, called WiSHFUL, devised to allow: i) maximal exploitation of radio functionalities available in current radio chips, and ii) clean separation between the logic for optimizing the radio protocols (i.e. radio control) and the definition of these protocols

Application Design of Farmbot based on Internet of Things (IoT)

The agribusiness sector is the largest economic sector and the most important part of the Indonesian national economy, but the agribusiness sector begins to experience threats in fulfilling human food. Fulfillment of food faced some challenges including an increase in population, which means rising food, urbanization resulting in a decrease in the number of farmers and dietary changes, limited resources (land and air), changes to facilitate and waste food. This corresponds to the data issued by the United Nations, which is the fulfillment of food from approximately 9.6 billion people in the world in 2050 [2]. Along with that, the agricultural land area also decreased due to the transfer of agricultural land function. Farmbot can increase agricultural production to solve human food because it can manage crops within 24 hours without stopping. Farmbot is liquid of agricultural robots that can plant seeds with regular, watering plants and monitoring plant growth. Farmbot can be controlled through an application interface that allows remote access from any location in easy Internet-connected devices. In this study, it will create an automation system that can plant seeds, watering agricultural crops by controlling air production, monitoring plant conditions, plant databases by using applications and designing algorithms to detect crops. Besides, other ways can measure the moisture of the soil to scheduling watering as a watering parameter. To implement this feature can work using a robotic hand with a CNC (Computer Numeric Control) gesture system that would be controlled by the Arduino and Raspberry PI. Following are the procedures for implementing agricultural automation with IoT applications (Internet of Things), seedlings with the help of seeders that stored in plant databases, watering and direct monitoring by users who use camera help

Advanced information processing system: Input/output system services

The functional requirements and detailed specifications for the Input/Output (I/O) Systems Services of the Advanced Information Processing System (AIPS) are discussed. The introductory section is provided to outline the overall architecture and functional requirements of the AIPS system. Section 1.1 gives a brief overview of the AIPS architecture as well as a detailed description of the AIPS fault tolerant network architecture, while section 1.2 provides an introduction to the AIPS systems software. Sections 2 and 3 describe the functional requirements and design and detailed specifications of the I/O User Interface and Communications Management modules of the I/O System Services, respectively. Section 4 illustrates the use of the I/O System Services, while Section 5 concludes with a summary of results and suggestions for future work in this area

C-MOS array design techniques: SUMC multiprocessor system study

The current capabilities of LSI techniques for speed and reliability, plus the possibilities of assembling large configurations of LSI logic and storage elements, have demanded the study of multiprocessors and multiprocessing techniques, problems, and potentialities. Evaluated are three previous systems studies for a space ultrareliable modular computer multiprocessing system, and a new multiprocessing system is proposed that is flexibly configured with up to four central processors, four 1/0 processors, and 16 main memory units, plus auxiliary memory and peripheral devices. This multiprocessor system features a multilevel interrupt, qualified S/360 compatibility for ground-based generation of programs, virtual memory management of a storage hierarchy through 1/0 processors, and multiport access to multiple and shared memory units

A Study on Automated Micro Irrigation Using Soil Moisture Sensors

Micro irrigation is the modern method of irrigation. By this method water is irrigated through drippers, sprinklers, foggers and by other emitters on surface and sub surface of the land. Micro irrigation can be given by tubes and drippers which deliver water directly to the base of each plant or crop. Drip irrigation, sprinkler irrigation, bubbler irrigation and sub-surface irrigation are the different types of irrigation. Soil moisture is the key variable in controlling the exchange of water and heat energy between the land surface and atmosphere. Soil moisture sensor measures the volumetric water content in the soil. Automation in micro irrigation is a system by which all the operations related to supply of irrigation water or fertilizer to the crop are carried out automatically with minimum manual interventions using soil moisture sensors

Enhancing Productivity and Performance Portability of General-Purpose Parallel Programming

This work focuses on compiler and run-time techniques for improving the productivity and the performance portability of general-purpose parallel programming. More specifically, we focus on shared-memory task-parallel languages, where the programmer explicitly exposes parallelism in the form of short tasks that may outnumber the cores by orders of magnitude. The compiler, the run-time, and the platform (henceforth the system) are responsible for harnessing this unpredictable amount of parallelism, which can vary from none to excessive, towards efficient execution. The challenge arises from the aspiration to support fine-grained irregular computations and nested parallelism. This work is even more ambitious by also aspiring to lay the foundations to efficiently support declarative code, where the programmer exposes all available parallelism, using high-level language constructs such as parallel loops, reducers or futures. The appeal of declarative code is twofold for general-purpose programming: it is often easier for the programmer who does not have to worry about the granularity of the exposed parallelism, and it achieves better performance portability by avoiding overfitting to a small range of platforms and inputs for which the programmer is coarsening. Furthermore, PRAM algorithms, an important class of parallel algorithms, naturally lend themselves to declarative programming, so supporting it is a necessary condition for capitalizing on the wealth of the PRAM theory. Unfortunately, declarative codes often expose such an overwhelming number of fine-grained tasks that existing systems fail to deliver performance. Our contributions can be partitioned into three components. First, we tackle the issue of coarsening, which declarative code leaves to the system. We identify two goals of coarsening and advocate tackling them separately, using static compiler transformations for one and dynamic run-time approaches for the other. Additionally, we present evidence that the current practice of burdening the programmer with coarsening either leads to codes with poor performance-portability, or to a significantly increased programming effort. This is a ``show-stopper'' for general-purpose programming. To compare the performance portability among approaches, we define an experimental framework and two metrics, and we demonstrate that our approaches are preferable. We close the chapter on coarsening by presenting compiler transformations that automatically coarsen some types of very fine-grained codes. Second, we propose Lazy Scheduling, an innovative run-time scheduling technique that infers the platform load at run-time, using information already maintained. Based on the inferred load, Lazy Scheduling adapts the amount of available parallelism it exposes for parallel execution and, thus, saves parallelism overheads that existing approaches pay. We implement Lazy Scheduling and present experimental results on four different platforms. The results show that Lazy Scheduling is vastly superior for declarative codes and competitive, if not better, for coarsened codes. Moreover, Lazy Scheduling is also superior in terms of performance-portability, supporting our thesis that it is possible to achieve reasonable efficiency and performance portability with declarative codes. Finally, we also implement Lazy Scheduling on XMT, an experimental manycore platform developed at the University of Maryland, which was designed to support codes derived from PRAM algorithms. On XMT, we manage to harness the existing hardware support for scheduling flat parallelism to compose it with Lazy Scheduling, which supports nested parallelism. In the resulting hybrid scheduler, the hardware and software work in synergy to overcome each other's weaknesses. We show the performance composability of the hardware and software schedulers, both in an abstract cost model and experimentally, as the hybrid always performs better than the software scheduler alone. Furthermore, the cost model is validated by using it to predict if it is preferable to execute a code sequentially, with outer parallelism, or with nested parallelism, depending on the input, the available hardware parallelism and the calling context of the parallel code

A study of systems implementation languages for the POCCNET system

The results are presented of a study of systems implementation languages for the Payload Operations Control Center Network (POCCNET). Criteria are developed for evaluating the languages, and fifteen existing languages are evaluated on the basis of these criteria

ORGANA: A Robotic Assistant for Automated Chemistry Experimentation and Characterization

Chemistry experimentation is often resource- and labor-intensive. Despite the many benefits incurred by the integration of advanced and special-purpose lab equipment, many aspects of experimentation are still manually conducted by chemists, for example, polishing an electrode in electrochemistry experiments. Traditional lab automation infrastructure faces challenges when it comes to flexibly adapting to new chemistry experiments. To address this issue, we propose a human-friendly and flexible robotic system, ORGANA, that automates a diverse set of chemistry experiments. It is capable of interacting with chemists in the lab through natural language, using Large Language Models (LLMs). ORGANA keeps scientists informed by providing timely reports that incorporate statistical analyses. Additionally, it actively engages with users when necessary for disambiguation or troubleshooting. ORGANA can reason over user input to derive experiment goals, and plan long sequences of both high-level tasks and low-level robot actions while using feedback from the visual perception of the environment. It also supports scheduling and parallel execution for experiments that require resource allocation and coordination between multiple robots and experiment stations. We show that ORGANA successfully conducts a diverse set of chemistry experiments, including solubility assessment, pH measurement, recrystallization, and electrochemistry experiments. For the latter, we show that ORGANA robustly executes a long-horizon plan, comprising 19 steps executed in parallel, to characterize the electrochemical properties of quinone derivatives, a class of molecules used in rechargeable flow batteries. Our user study indicates that ORGANA significantly improves many aspects of user experience while reducing their physical workload. More details about ORGANA can be found at https://ac-rad.github.io/organa/