Showing papers on "Application software published in 2020"

WAFFLE: Watermarking in Federated Learning

Abstract: Federated learning is a distributed learning technique where machine learning models are trained on client devices in which the local training data resides. The training is coordinated via a central server which is, typically, controlled by the intended owner of the resulting model. By avoiding the need to transport the training data to the central server, federated learning improves privacy and efficiency. But it raises the risk of model theft by clients because the resulting model is available on every client device. Even if the application software used for local training may attempt to prevent direct access to the model, a malicious client may bypass any such restrictions by reverse engineering the application software. Watermarking is a well-known deterrence method against model theft by providing the means for model owners to demonstrate ownership of their models. Several recent deep neural network (DNN) watermarking techniques use backdooring: training the models with additional mislabeled data. Backdooring requires full access to the training data and control of the training process. This is feasible when a single party trains the model in a centralized manner, but not in a federated learning setting where the training process and training data are distributed among several client devices. In this paper, we present WAFFLE, the first approach to watermark DNN models trained using federated learning. It introduces a retraining step at the server after each aggregation of local models into the global model. We show that WAFFLE efficiently embeds a resilient watermark into models incurring only negligible degradation in test accuracy (-0.17%), and does not require access to training data. We also introduce a novel technique to generate the backdoor used as a watermark. It outperforms prior techniques, imposing no communication, and low computational (+3.2%) overhead.

MEG: A RISCV-based System Emulation Infrastructure for Near-data Processing Using FPGAs and High-bandwidth Memory

Abstract: Emerging three-dimensional (3D) memory technologies, such as the Hybrid Memory Cube (HMC) and High Bandwidth Memory (HBM), provide high-bandwidth and massive memory-level parallelism. With the growing heterogeneity and complexity of computer systems (CPU cores and accelerators, etc.), efficiently integrating emerging memories into existing systems poses new challenges and requires detailed evaluation in a realistic computing environment. In this article, we propose MEG, an open source, configurable, cycle-exact, and RISC-V-based full-system emulation infrastructure using FPGA and HBM. MEG provides a highly modular hardware design and includes a bootable Linux image for a realistic software flow, so that users can perform cross-layer software-hardware co-optimization in a full-system environment. To improve the observability and debuggability of the system, MEG also provides a flexible performance monitoring scheme to guide the performance optimization. The proposed MEG infrastructure can potentially benefit broad communities across computer architecture, system software, and application software. Leveraging MEG, we present two cross-layer system optimizations as illustrative cases to demonstrate the usability of MEG. In the first case study, we present a reconfigurable memory controller to improve the address mapping of standard memory controller. This reconfigurable memory controller along with its OS support allows us to optimize the address mapping scheme to fully exploit the massive parallelism provided by the emerging three-dimensional (3D) memories. In the second case study, we present a lightweight IOMMU design to tackle the unique challenges brought by 3D memory in providing virtual memory support for near-memory accelerators. We provide a prototype implementation of MEG on a Xilinx VU37P FPGA and demonstrate its capability, fidelity, and flexibility on real-world benchmark applications. We hope MEG fills a gap in the space of publicly available FPGA-based full-system emulation infrastructures, specifically targeting memory systems, and inspires further collaborative software/hardware innovations.

Design and Implementation of Web-Based Virtual Mobile Robot Laboratory for Engineering Education

Abstract: A web-based virtual and remote laboratory environment is developed, realized and proposed for real time control and monitoring of a mobile robot in an indoor environment. In this laboratory, a real time and continuous video stream of indoor laboratory environment is viewed by wireless IP camera mounted to the ceiling. The localization of the robot is also implemented using this IP camera. In this environment, a virtual target and virtual obstacles are located anywhere on the video image taken by the user. The robot is guaranteed to arrive at the virtual target avoiding virtual obstacles using the shortest path. The video stream of the robot’s navigation is monitored through the web environment. The robot is controlled by a BeagleBoard-xM single board computer. The PC web server symmetrically communicates with the other web server on the BeagleBoard-xM, executing developed application software. Since genetic algorithms generate alternative solutions, it is utilized as a path planning algorithm. Parameters such as population size and maximum generation of genetic algorithms applied to get the shortest path for the robot are tuned via the web-based virtual laboratory environment. The robot is also controlled manually through the web environment. At the conclusion of the experiments, the results are monitored on the web-based virtual laboratory environment. A low-cost mobile robot virtual remote laboratory is designed and implemented for engineering education in this paper. Consequently, survey and some experimental works, of the usability and performance of the RRC-Lab (remote robot control-laboratory) system are confirmed by students.

Research and Development of Data Security Multidimensional Protection System in Cloud Computing Environment

Abstract: In the cloud computing environment, most application software and data are transferred to the cloud computing data center, network service provider, all applications and data management and maintenance work are entrusted to the cloud computing service providers to complete. The feature of cloud computing provides convenience for users and brings many security challenges. In this paper, firstly, the architecture of cloud computing applications were discussed and studied in the organization and, for virtualization, cloud computing, large-scale, dynamic and extensible, based on cloud computing security challenges, summarizes the advantages and safety and environmental protection measures, on the basis of in this paper, we propose a dynamic hash authentication scheme based on Merkle tree. With the user dimension as the letter and the management technology as the side, the trust of empowerment management system is put forward. Focus on data encryption technology, from data, design and demotion are cloud storage security solutions. In addition, in view of the problems existing in the information security standard, we put forward the combination of the cloud security standard and the evaluation system, and improve the multi-dimensional cloud protection system and implementation.

PHIST: A Pipelined, Hybrid-Parallel Iterative Solver Toolkit

Abstract: The increasing complexity of hardware and software environments in high-performance computing poses big challenges on the development of sustainable and hardware-efficient numerical software. This article addresses these challenges in the context of sparse solvers. Existing solutions typically target sustainability, flexibility, or performance, but rarely all of them.Our new library PHIST provides implementations of solvers for sparse linear systems and eigenvalue problems. It is a productivity platform for performance-aware developers of algorithms and application software with abstractions that do not obscure the view on hardware-software interaction.The PHIST software architecture and the PHIST development process were designed to overcome shortcomings of existing packages. An interface layer for basic sparse linear algebra functionality that can be provided by multiple backends ensures sustainability, and PHIST supports common techniques for improving scalability and performance of algorithms such as blocking and kernel fusion.We showcase these concepts using the PHIST implementation of a block Jacobi-Davidson solver for non-Hermitian and generalized eigenproblems. We study its performance on a multi-core CPU, a GPU, and a large-scale many-core system. Furthermore, we show how an existing implementation of a block Krylov-Schur method in the Trilinos package Anasazi can benefit from the performance engineering techniques used in PHIST.

Reproducible Workflow on a Public Cloud for Computational Fluid Dynamics

Abstract: In a new effort to make our research transparent and reproducible by others, we developed a workflow to run and share computational studies on the public cloud Microsoft Azure. It uses Docker containers to create an image of the application software stack. We also adopt several tools that facilitate creating and managing virtual machines on compute nodes and submitting jobs to these nodes. The configuration files for these tools are part of an expanded “reproducibility package” that includes workflow definitions for cloud computing, in addition to input files and instructions. This facilitates recreating the cloud environment to rerun the computations under the same conditions. Although cloud providers have improved their offerings, many researchers using high-performance computing (HPC) are still skeptical about cloud computing. Thus, we ran benchmarks for tightly coupled applications to confirm that the latest HPC nodes of Microsoft Azure are indeed a viable alternative to traditional on-site HPC clusters. We also show that cloud offerings are now adequate to complete computational fluid dynamics studies with in-house research software that uses parallel computing with GPUs. Finally, we share with the community what we have learned from nearly two years of using Azure cloud to enhance the transparency and reproducibility in our computational simulations.

PushPin: towards production-quality peer-to-peer collaboration

Abstract: Fully peer-to-peer application software promises many benefits over cloud software, in particular, being able to function indefinitely without requiring servers. Research on distributed consistency mechanisms such as CRDTs has laid the foundation for P2P data synchronisation and collaboration. In this paper we report on our experience in taking these technologies beyond research prototypes, and working towards commercial-grade P2P collaboration software. We identify approaches that work well in our experience, such as the functional reactive programming paradigm, and highlight areas in need of further research, such as the reliability of NAT traversal and usability challenges.

Achieving determinism in adaptive AUTOSAR

Abstract: AUTOSAR Adaptive Platform (AP) is an emerging industry standard that tackles the challenges of modern auto-motive software design, but does not provide adequate mechanisms to enforce deterministic execution This poses profound challenges to testing and maintenance of the application software, which is particularly problematic for safety-critical applications In this paper, we analyze the problem of nondeterminism in AP and propose a framework for the design of deterministic automotive software that transparently integrates with the AP communication mechanisms We illustrate our approach in a case study based on the brake assistant demonstrator application that is provided by the AUTOSAR consortium We show that the original implementation is nondeterministic and discuss a deterministic solution based on our framework

Методика рекурсивной оценки качества программных комплексов управления группировками беспилотных летательных аппаратов

Abstract: Modern technologies for developing highly sophisticated application software for robotic systems, which include unmanned aerial vehicles, are focused not on the use of classical methods and quality metrics, but on the dynamic use of recursive methods in the framework of the so-called spiral development model. The approximate evaluation nature of qualimetric analysis is compensated by the multiple (iterative) quality assessment procedures for the same components of the program code in the process of their development, creation and debugging. The article presents the developed methodology for the recursive assessment of the quality of software systems for managing groups of unmanned aerial vehicles, considered as a systemological toolkit for the head of software development and based on multiple assessments of the quality of application software for each iteration of its development (when each successive assessment of the current quality is expressed through its previous value). the difference of the methodology is its focus on the iterative-stage or recursive nature of the development of software systems for managing groups of unmanned aerial vehicles within the SCRUM technological system.

Adaptive task scheduling method in multi-tenant cloud computing

Abstract: Cloud security is the primary need for the vital Information Technology industry. It adopts dynamic qualities and enhances various heterogeneous resources for its applications. Cloud environment enables virtual technologies using virtual machine placement method. Therefore any virtual machines can move between any physical devices for achieving cost optimization and network traffic minimization sake. Multi-tenancy means the use of multiple systems applications or data from various organizations residing on a single physical device. Here a single instance of the application software running on the service providers’ platform can be accessed by multiple clients simultaneously. Multi-tenancy concept refers to both public as well as private cloud model which relates to all the three layers in cloud computing system. Adaptive particle swarm optimization is proposed in this paper which also addresses the multi-tenancy process which enables high resource utilization service under cloud storage network.

Designing and Developing Artificial Intelligence Applications Troubleshooting Computers as Learning Aids

Abstract: The learning to analyze problems and do improvements on hardware and installation of application software is part of the basic competencies of knowledge and skills of computers and basic networks. Based on observations, the learning process has not been able to provide a real picture of the problems that often occur on computers. The purpose of this study is to design and develop learning aids through artificial intelligence applications on computer troubleshooting. The research method used is R & D (Research and Development) with a 4-D model. The results of the study this is the application being valid, practical and effective. Based on the results of the study, it can be concluded that the application of artificial intelligence to computer troubleshooting has been successfully designed and developed.

C-NSA: a hybrid approach based on artificial immune algorithms for anomaly detection in web traffic

Abstract: Security vulnerabilities in web traffic can directly lead to data leak. Preventing these data leaks to a large extent has become an important problem to solve. Besides, the accurate detection and prevention of abnormal changes in web traffic is of great importance. In this study, a hybrid approach, called C-NSA, based on the negative selection algorithm (NSA) and clonal selection algorithm (CSA) of artificial immune systems for the detection of abnormal web traffic on the network is proposed and a user-friendly application software is developed. The real and synthetic data in the Yahoo Webscope S5 dataset are used for web traffic and the data are split into windows using the window sliding. In the experimental studies, the abnormal web traffic data is detected by monitoring the changes in the number of activated detectors in the C-NSA. It is observed that the average accuracy performance of finding anomalies in real web traffic data is 94.30% and the overall classification accuracy is 98.22% based on proposed approach. In addition, false positive rate of the proposed approach using C-NSA is obtained as 0.029. In addition, the results in synthetic web traffic data using C-NSA are achieved as average 98.57% classification accuracy.

A dynamic reconfiguration mechanism to increase the reliability of GPGPUs

Abstract: General Purpose Graphic Processing Units (GPGPUs) are effective solutions for high-demanding data processing applications. Recently, they started to be used even in safety-critical applications, such as autonomous car driving systems. GPGPUs are implemented using the latest semiconductor technologies, which are more prone to faults arising during the lifetime operation. However, until now fault mitigation solutions were not extensively included in GPGPUs, due to the limited reliability requirements of the applications they were originally intended for (e.g., gaming or multimedia). This work proposes a dynamically configurable self- repairing mechanism aimed at mitigating the impact of permanent faults in the Scalar Processor (SP) cores in GPGPUs. The mechanism is based on spare modules that can be used to replace faulty SPs when a fault is detected. A configuration instruction allows dynamically controlling in software the selection of the set of active SPs in the SM. The method is extremely flexible since it does not require any change in the application software. Experimental results show that the solution introduces a moderate area overhead while allowing continue working even in the case of any permanent faults affecting the SPs.

A Survey on Deep Learning-Based Source Code Defect Analysis

Abstract: With the rapid development of information technology, various software applications are flooding our daily lives. The development of these application software inevitably generates a lot of source code. How to detect and analyze various defects in the source code, such as API/Function call errors, array misuse, and expression syntax error, etc., which is known as source code defect analysis (SCDA), has attracted the attention of many researchers in the academic field. Since artificial intelligence (AI) technology has achieved excellent results in the field of image processing and natural language processing, researchers have tried to use deep learning algorithms in AI to automatically extract and analyze features of source code. Therefore, we review the recent deep learning-based source code defect analysis methods, including abstract syntax tree-based methods, program dependency graph-based methods, and other deep learning-based methods. Compared to traditional methods, the deep learning-based code defect analysis methods can realize the automatic extraction of source code defect features. This means that there is no longer a need for human experts to pre-define code features, which avoids errors caused by humans to a certain extent. The application research of AI in the source code defect analysis is an interesting and challenging development direction, and we believe it has broad development prospects.

Method of Achieving Interoperability of Applied Software Based on the Analysis of Their Data

Abstract: To get the most benefit from using an application program, it is necessary that it can freely exchange data with the programs surrounding it. To achieve this goal, a method has been developed to achieve the interoperability of application software based on the analysis of their data, using the unique frequency characteristics of the data to identify them, which are necessary for their exchange.

Mission Planning Application Software for Solar Powered UAVs

Abstract: ix

Mobile application: donate day

Abstract: Mobile application has gradually become a popular application software because it only requires inexpensive electronic devices such as mobile phones and tablets to operate This paper therefore presents an Android mobile app application that allowed users to donate their items to charitable organizations in Malaysia The study adopted quantitative research to study people's behavior towards charitable donation and gathered opinion on the mobile donation app The survey was conducted online with samples of 20 respondents The paper also adopted the Rapid Application Development (RAD) approach to develop this mobile app's system The RAD approach enabled the development of the mobile app prototype to be completed quickly and enabled end users to test the mobile app to provide recommendations and make changes easily The results of the system tests indicated that the mobile app achieved the goals of the study, but the respondents also responded to several improvements needed for the prototype

Optimization of Design and Management of a Hydroponic Greenhouse by Using BIM Application Software

Abstract: Received: 10 October 2019 Accepted: 26 February 2020 The paper deals with hydroponic greenhouses that can be used both for crops cultivation and as a space for hosting events, thanks to its transformability characteristics. The project combines the concepts of circular economy and agricultural activity, creating environmentally sustainable hydroponic greenhouses, from the design to the management phase, thanks to the use of a multidisciplinary BIM approach (Building Information Modelling). The use of application software in BIM logic such as MC4® Energy and Arch Energy (Tool developed by Sapienza University of Rome) for the energetic performance evaluation and Tally® Environmental Impact Tool for LCA Analysis, has improved the design of a modular and flexible architecture, energy-efficient and water-efficient, with advanced climate control. The project offers a possible solution to the main future challenges of food production such as the limited space, the urbanization process, the scarce availability of resources such as water, fossil fuels, minerals and the increasing demands of consumers in terms of functionality and product quality.

Software Components of an IoT Monitoring Platform in Google Cloud Platform: A Descriptive Research and an Architectural Proposal

Abstract: As software engineers, it is not an easy task to build a software solution that customers consider easy to use, cost-benefit balanced, secured, high available and prepared for high demand. There are many solutions for building a monitoring platform with these previous attributes and we need to consider all the technical factors to achieve this goal. We proposed an agile methodology for the project management approach, acquired the necessary equipment and services and hired the staff to design and develop a monitoring platform in Google Cloud Platform (GCP) with edge frameworks and technologies. We implemented a software working solution composed of five applications (app) or services and configured services in the GCP: IoT data web service, frontend web app, backend web app, IoT app, and mobile app. They were developed using Python, ReactJS, and Java and deployed in Google Cloud Platform for being used in personal computers, laptops, mobile devices, and IoT devices. We defined this architecture with its main basis in a cloud platform that used the publish/subscribe pattern for efficient data ingestion and reporting.

Implementation of Secure Web Conferencing

Abstract: Currently, the online video conference system usually needs to install this application software. Therefore, the software needs to be developed duplicate version for different operating systems (OS), e.g., Android, Windows and MacOS. However, web-based video conference system is OS independent so as to save development cost. In the paper, we present an implementation of a web-based video conference solution by using WebRTC [1]. It can be used for meeting and chat with a browser. Instead of client-server centralized design, in a cyber-video meeting, each member transmits media stream to each other peer-to-peer. Additionally, the media stream is encrypted, and a management mechanism is developed to manage the entry of conference room personnel and achieve a secure multi-party video conference. We also overcome peer-to-peer (P2P)web NAT traversal of media transmission. Our solution covers four main features: P2P Web NAT traversal, dynamic join and leave, access control, dynamic video resolution adjustment.

Design and validation of the boot software for the instrument control unit of the PLATO mission

Abstract: PLAnetary Transits and Oscillations of stars (PLATO) is a mission belonging to the European Space Agency Cosmic Vision program which objective is to find and study extrasolar planetary systems. PLATO is composed of 26 telescopes which will observe uninterruptedly Sun like stars in order to identify a periodic decrease of the star brightness indicating the possible transit of an exoplanet. The PLATO on-board Data Processing System (DPS) consists of an Instrument Control Unit (ICU) and several distributed Digital Processing Units (DPUs) connected together by a SpaceWire network. The ICU collects and compresses scientific data from the DPUs and it implements the main data interface towards the satellite for telemetry and telecommands. The focus of this paper is on the Boot Software (BSW) of the ICU. The BSW is executed on a LEON3FT processor to perform system initialization, hardware checks, telecommand/telemetry management and the start of the ICU Application Software (ASW) responsible of the PLATO sub-system management necessary for the mission objectives. ICU BSW is the only boot software on-board PLATO and its high criticality level requires stringent verification/validation activities and a high-quality control of the software product which is achieved through extensive quality plans, multi-level testing and static analysis of software code. This paper describes the BSW dependable architecture along with the methods used to achieve the required performances, including FDIR techniques. Two engineering models of the ICU are going to be developed and the foreseen functional and performance tests will be presented in this paper.

A Hardware Root-of-Trust Design for Low-Power SoC Edge Devices

Abstract: In this work, we introduce a hardware root-of-trust architecture for low-power edge devices. An accelerator-based SoC design that includes the hardware root-of-trust architecture is developed. An example application for the device is presented. We examine attacks based on physical access given the significant threat they pose to unattended edge systems. The hardware root-of-trust provides security features to ensure the integrity of the SoC execution environment when deployed in uncontrolled, unattended locations. E-fused boot memory ensures the boot code and other security critical software is not compromised after deployment. Digitally signed programmable instruction memory prevents execution of code from untrusted sources. A programmable finite state machine is used to enforce access policies to device resources even if the application software on the device is compromised. Access policies isolate the execution states of application and security-critical software. The hardware root-of-trust architecture saves energy with a lower hardware overhead than a separate secure enclave while eliminating software attack surfaces for access control policies.

Reliability of Software Applications in Integrated Modular Avionics

Abstract: The integrated modular avionics (IMA) network consists of a number of computing modules capable of supporting numerous applications of differing critical and non-critical levels. In opposition to traditional hardware-oriented architectures, the IMA concept proposes an integrated software-oriented architecture with application software portable across an assembly of common hardware modules. IMA allows focusing on running applications instead of managing infrastructure. The IMA software runs in a certain partition (container). In practice, when organizing partition-based access to applications, it is important to know the availability of a separate dedicated container with application in active operation. In this case if the failure of another service for another application has come, for this particular IMA partition such failure in another partition from the position of reliability is not critical. In the article the availability of a dedicated IMA container in the system with partition-based IMA architecture is studied. The mathematical model of the reliability of a separate dedicated container with active application in the real conditions of operation is developed. Expressions for availability of application operation in dedicated IMA container are developed.

POSTER: Data Leakage Detection for Health Information System based on Memory Introspection

Abstract: The abundance of highly sensitive personal information in the Health Information System (HIS) has made it a prime target of data breach attacks. However, securing the system with existing Data Leakage Prevention (DLP) solutions is difficult due to a lack of security perimeter and diverse composition of software components. We propose the use of hypervisor-based memory introspection for implementing data leakage detection in such an environment. The approach looks for the presence of sensitive raw data in the memory of both the client machines and the server machines, transcending the dependence of pre-existing security perimeters. It is inherently compatible with different types of application software and robust against transport or at-rest data encryption. A prototype has been built on the Bareflank hypervisor and the OpenEMR platform. The evaluation results confirmed the effectiveness of the approach.

Design of Teaching Model of Ideological and Political Education Network Course Based on Educational Cloud Platform

Abstract: This paper proposes that education cloud service platform is based on the deployment of “cloud computing” technology, constitutes a pool of educational application software resources, and provides one-stop application services for teachers and education management departments, covering office management, online learning, teaching and research, and teaching and application of educational information. In all aspects, it meets the various application needs of educational informationization and digital campus construction, and achieves a high degree of unity in the management of teachers' individual applications and education authorities. This article is based on the student-centered education theory and education information technology, and takes the education cloud platform as the main body, develops and designs the “Ideological and Political Education” online course, and analyzes its characteristics. Make full use of the network and modern education and teaching equipment to enhance the county's teachers' ability to apply information technology and education management, and promote the balanced development of the district's education.

A Framework for System Interfacing of Voice User Interface for Personal Computers

Abstract: Human Computer Interaction has changed significantly throughout the years. The introduction of the screen and keyboard gave rise to the command line interface. Subsequently, the Graphical User Interface (GUI) was introduced. However, the complexity of applications grew with the increase in the computing power of personal computers. The introduction of voice to interact with personal computers as the principal method of interaction was thus indispensable. Voice User Interface (VUI) is such an interfacing mechanism that makes use of auditory information (speech) provided by the user to interact with a computer. While proposing an architecture for a Voice User Interface we also propose a framework that can be used by a general VUI to integrate with the underlying Operating System. The framework overcomes the difficulty in interfacing with low-level system APIs and integrating multiple application software APIs.

Refining Micro Services Placement over Multiple Kubernetes-orchestrated Clusters employing Resource Monitoring

Abstract: In the cloud field, there is an increasing demand for globalized services and corresponding execution environments that overcome local limitations and selectively utilize optimal resources. Utilizing multi-cloud deployments and operations rather than using a single cloud is an effective way to satisfy the increasing demand. In particular, we need to provide cloud-native environment to organically support services based on a microservices architecture. In this paper, we propose a cloud-native workload profiling system with Kubernetes-orchestrated multi-cluster configuration. The contributions of this paper are as follows. (i) We design the operating software over multiple cloud-native cluster to select optimal resources by monitoring. (ii) For operating the multiple clusters through the design, we define and design specific general service workloads. Also, we implement the workloads in application software (iii) To seek optimal resources, we deployed the general workloads and monitored resource usage repeatedly in detail. We calculate resource variation in comparison with initial resource usage and average resource usage after deploying the service workloads. Also, we analyze the resource monitoring result. We expect this methodology can find proper resources for service workload types.

Psychological Analysis of User Interface Design in Computer Software

Abstract: Currently, technology and machine-based design ideas can hardly solve the massive problems in the user interface (UI) design of application software. The "people-oriented" and "user-friendly" design ideas are put forward to address this issue. These ideas have gradually gained attention and been valued by people. The user interface design of software (including fixed standard, semantics, etc.) should start with human cognitive psychology, and comply with human perceptual characteristics based on the normal thinking and action characteristics of people for the human-computer interface design.

Overview of Mobile Applications for CNC Programming

Abstract: This paper describes free application software designed for smartphones running Android. In recent years, more such applications have emerged and are classified here into three groups: simulation software, learning software and CNC engraving software. The paper describes some typical applications for these three types of software.

Smartphone Application Using a Visual Programming Language to Compute Drying/Solar Drying Characteristics of Agricultural Products

Abstract: Drying is an important process for food security. A software application on a smartphone can be used to prevent mistakes while carrying out the calculations for drying investigation and research using several mathematical equations. The objective of this research was to develop a software program on cellphones depending on some of the important mathematical equations which are used to conduct some of the drying/solar drying characteristics to assist researchers and engineers who work in the food engineering field for sustainable development. This innovative software application can be installed on mobiles in Android and iOS systems to save effort and time. Mathematical models were developed to compute drying/solar drying calculations. These mathematical models were integrated into the flowchart to develop a software program using visual programming language in the operating system and create the user interface. The collected data from references were used to compare the results from the normal way of calculations with results from the developed software. The results were agreed for both normal calculations and the software. This application software can calculate the moisture content of product, drying ratio, quantity of removed moisture from the fresh products, required heat to evaporate moisture from fresh product, and efficiency of the solar collector.