Software Features Research Articles

RESEARCH ON DEEP LEARNING TECHNOLOGY TO DETECT MALICIOUS FOR HEALTHCARE SYSTEM

With the popularity of smart phones, Android has a large number of users. Android allows download and installation of other unofficial healthcare system applications, so it has attracted the attention of malware developers for healthcare system. However, most of the papers proposed a variety of different methods to improve accuracy, and the samples tested by each method in the experimental part are different, which may cause errors in comparison. It shows that permission is an important of the development as mobile phone storage. Therefore, this paper proposed Android’s Permission and application program interface (API) as two features to perform machine learning to detect malicious programs business intelligence. It also uses machine learning method and other two algorithms to detect malicious programs. The average accuracy of using hybrid detection of unknown malicious programs reaches 89%, and the hit rate near 90%. The results show that under the same sample situation, the accuracy rate of the hybrid method used Random Forest is higher than the other two analyses. Compared with the dynamic analysis with others, it used the hybrid method and dynamic analysis has a high accuracy rate. The contribution of this paper is as follows: the advantage of static detection is that it does not need to execute Android application package (APK) features be extracted, and the speed is the fastest among the three detection modules. The features of dynamic detection for healthcare system are generated through the executed APK, and more powerful features can be extracted. Hybrid detection uses two method features, and extract most advantageous features to generate detection modules to detect APKs. The accuracy of static results about 87% in average, 88% for dynamic, and 89% for hybrid.

Commodity characteristics of tropical fruits

The purpose of this article is to analyze the commodity characteristics of the most common types of tropical fruits. The article considers the commodity characteristics of tropical fruits presented on the Russian market, taking into account the peculiarities of their nutritional value, chemical composition, structure, assortment, quality and useful properties assessment. It has been established that tropical fruits are distinguished by low calorie content (except for avocados), the presence of natural sugars, valuable mineral and vitamin composition, as well as the presence of biooxidants represented by tannins and dyes. Promising pomological varieties of tropical fruits under consideration are indicated; general and specific quality indicators envisioned in the modified standards, and their useful properties are identified. The features of packaging and storage of tropical fruits, including the specific conditions for their ripening, are analyzed

Grade-3 Learners’ Performance and Conceptual Understanding Development in Technology-Enhanced Teaching With Interactive Mathematics Software

<p style="text-align: justify;">This study presented the effect of interactive mathematics (IM) software assisted-teaching on primary three learners' conceptual understanding and performance. The cognitive theory of multimedia learning (CTML) supported the quasi-experimental design of this study drawing on IM software features that fit a multimedia tool for effective learning. This study used a sample of 138 lower primary learners. Learners’ test scores and examples of their work provided data to be analyzed. Learners' conceptual understanding was measured using the percentage of learners who performed a particular item and analyzed using sample learners' work while the overall performance was measured using the mean class scores. From the data analysis, IM-assisted teaching influenced conceptual understanding and performance based on a .05 p-value, the effect size of significance, and learning gains. The analysis of learners’ workings revealed different errors in addition, subtraction, division, and multiplication, which were remarkably reduced in the post-test by IM-supported teaching. This evidenced conceptual understanding development by IM-supported teaching. The study suggested the integration of IM in the Rwandan Competence-Based curriculum and its use as an instructional tool in teaching and learning mathematics at the primary level. Besides, it was recommended that Rwanda Education Board support teachers in developing basic computer skills to effectively create and monitor a multimedia learning environment for effective learning. Furthermore, further similar research would improve the literature about interactive technologies in supporting quality mathematics delivery and outcomes.</p>

LibEMM: A fictious wave domain 3D CSEM modelling library bridging sequential and parallel GPU implementation

This paper delivers a software - libEMM - for 3D controlled-source electromagnetics (CSEM) modelling in fictitious wave domain, based on the newly developed high-order finite-difference time-domain (FDTD) method on non-uniform grid. The numerical simulation can be carried out over a number of parallel processors using MPI-based high performance computing architecture. The FDTD kernel coded in C has been parallelized with OpenMP for speedup using local shared memory. In addition, the software features a GPU implementation of the same algorithm based on CUDA programming language, which can be cross-validated and compared in terms of efficiency. A perspective of libEMM on the horizon is its application to 3D CSEM inversion in land and marine environment. Program summaryProgram Title: libEMMCPC Library link to program files:https://doi.org/10.17632/p769t7c5bk.1Developer's repository link:https://github.com/yangpl/libEMMLicensing provisions: GNU General Public License v3.0Programming language: C, CUDA, Fortran, ShellExternal dependencies: MPI [1], FFTW [2], CUDA [3]Nature of problem: Controlled-source electromagnetics (CSEM)Solution method: High-order finite-difference time-domain (FDTD) on non-uniform grid by fictious wave domain transformation References[1]https://www.mpich.org/[2]http://fftw.org/[3]https://developer.nvidia.com/cuda-toolkit

ОРГАНІЗАЦІЙНО-МЕТОДИЧНІ ОСОБЛИВОСТІ РЕАЛІЗАЦІЇ ДИСТАНЦІЙНОГО НАВЧАННЯ ФІЗИКИ В ЗАКЛАДАХ ВИЩОЇ ОСВІТИ

The article actualizes the problem of organizational and methodological support for distance learning in Physics. Organizational, regulatory, technological, software and methodological features of its implementation in Higher Education Institutions are determined. The article summarizes the experience and analyses the features of organizing distance learning in Higher Education as an effective tool for supporting the Educational Process in Physics and ensuring free access of applicants to high-quality educational services in conditions of unpredictable impacts. Attention is focused on the need to improve the techniques and methods of organizing independent work of students in the process of distance learning Physics, the formation of practical skills and abilities in them, the development of digital literacy as an important component of self-educational and professional competence, stimulating the cognitive activity of applicants, monitoring and evaluating academic achievements during online training. It is noted about the trends in the development of educational and methodological support for the educational process in Physics in the conditions of distance learning in fully functional didactic kits and complexes that combine traditional teaching tools, electronic educational resources, and digital laboratories. It is noted about the expediency of purposeful improvement of information and communication competence of teachers, the formation of their readiness for a qualitative transformation of the methodology, methods and forms of organizing the educational process in new conditions, improving the systematic training of scientific and pedagogical workers for the introduction of distance education, expanding the practice of international internships in order to obtain skills in the effective use of modern means of supporting distance learning.

ДИЗАЙН ОЦІНЮВАННЯ НА ОСНОВІ ТЕОРІЇ КОНСТРУКТИВНОГО УЗГОДЖЕННЯ

The article actualizes the problem of organizational and methodological support for distance learning in Physics. Organizational, regulatory, technological, software and methodological features of its implementation in Higher Education Institutions are determined. The article summarizes the experience and analyses the features of organizing distance learning in Higher Education as an effective tool for supporting the Educational Process in Physics and ensuring free access of applicants to high-quality educational services in conditions of unpredictable impacts. Attention is focused on the need to improve the techniques and methods of organizing independent work of students in the process of distance learning Physics, the formation of practical skills and abilities in them, the development of digital literacy as an important component of self-educational and professional competence, stimulating the cognitive activity of applicants, monitoring and evaluating academic achievements during online training. It is noted about the trends in the development of educational and methodological support for the educational process in Physics in the conditions of distance learning in fully functional didactic kits and complexes that combine traditional teaching tools, electronic educational resources, and digital laboratories.

Ardosia: Simulating Circuits and Robotic Systems in a Single Learning Platform

Circuit simulation, together with practical sessions, is considered a fundamental tool to assist the teaching of electronics. Robotics offers rich real-world applications that foster student interest in developing engineering projects. Despite the potential benefits of uniting these two realities, software tools that combine circuits and robotic systems in a single simulation platform are scarce. This paper presents Ardosia, a simulation software that combines electronics and robotics in a single simulation arena. The electronics aspects of the simulation are handled by the Falstad Circuit Simulator, a software with proven success in promoting student interest and learning outcomes. Importantly, this software features significant interactive and visualization characteristics that are deemed valuable to enhance conceptual understanding. Non-electrical physics simulation is performed by a special purpose engine, designed to simulate sensor and actuator behavior in a 2D world. In combination, the two simulation engines yield a model where electronic circuits are embodied in the world through robot sensors and actuators interacting together and with the surroundings. Such a simulator is intended to promote the use of robotics projects in electronics education, since students will be equipped with a software to conveniently design and evaluate robotic systems, through simulation, before applying their ideas in an experimental setting. The paper presents an overview of Ardosia, complemented with examples of use in electronics education and a validation experiment comparing simulation with real-world data.

Production and Optimization of Briquettes from Sugarcane Bagasse using Blends of Waste Paper and Clay as Binders

Demand for green environments has stimulated research on the migration from conventional to renewable energy sources. In the case of combustible energy for domestic applications, briquettes produced from biomass have proven to be a good replacement for wood fuel. In this study, investigation on the performance analysis and optimization of mix ratio of briquettes produced from sugarcane bagasse using composite binders (waste paper and clay) was carried out. Box-Behnken Design feature of the Design Expert software was employed for the optimization of the briquettes mix ratio. Briquettes were produced from sugarcane bagasse based on the optimum conditions of 9.12% clay, 12.57% waste paper, 78.31% proportion of sugarcane bagasse and 5 KN compaction pressure. The produced briquette was found to have a compressive strength of 6.4715 MPa and 0.857 g/min burning rate. The results of the study shows that the experimental values were close to the predicted values with a percentage error of 3.11% for compressive strength and1.79% for burning rate which confirms the validity and adequacy of the predicted models.

SEISMIC WAVE RECORDER DESIGN FOR DEVELOPMENT FOOTSTEP HUMAN DETECTION ALGORITHMS

The article shoving the results of development seismic signal recorder for purpose of registration human footstep seismic signals. Design of recorder was adopted for collection seismic signals and store it on PC, for next seismic signal processing and creation signal detection and classification algorithms.
 The article provides an overview of the types of seismic waves, their classification is given. The conditions for the propagation of seismic waves are determined, and the features of Rayleigh waves are clarified. The design structure of the seismic sensor has been developed. The specifics of the functioning of the seismic sensor are described, the place and conditions of power supply and placement of the external interface are recognized. The specifics of using the sensor of an electromechanical transducer - geophone and the features of measurements using a stationary earth are described. It is shown that the development of a seismic signal sensor circuit implies the placement of input amplifiers in its structure. The main amplitude-frequency and phase-frequency characteristics of the geophone are presented. Geophone equivalent circuit, amplifier circuit, low-pass filter circuit are presented. Illustrations of types of seismograms are given, recommendations on the features of digital signal processing are given. The order of seismic signal processing is connected with its transmission from the sensor through the amplifying stage, passing through a low-pass filter in order to minimize noise and interference. The next step is to send a signal to the ADC. From the presented graphs of sensitivity and phase shift of the geophone, it follows that special attention should be paid to the curve corresponding to the sensor with an open output. This configuration of the sensor is optimal in the context of the formation of the maximum equal frequency response.
 As papers result was proposed structural and schematic design for all main recorders blocks and software features that required for properly using recorder. Tests in real conditions on test sites have shown the correctness of the choice of schemes of technical solutions for the task of registering seismic waves.

Using Artificial Intelligence to Identify Damaged Goods by the External Appearance of the Package when Performing Logistics Operations

A proposed promising method for recognising damaged goods by external appearance of packaging using a learning neural network considers the predicted long-term growth in the volume of transported goods, the increasing influence of economic and territorial factors on transportation processes, the complexity of logistics services and the increase in requirements for their quality, the spread of information technology and the improvement of artificial intelligence tools. The objective of the study is to describe the principles of using an artificial neural network to identify damaged goods by their external appearance. The relevance of the problem is confirmed by data on damage to goods during transportation. The methods used in the study help collecting and analysing data, describing and comparing existing and promising technologies, monitoring and modelling the process of cargo handling, and summarising the results. The analysis of common and promising methods of prevention and detection of cargo damage is backed by the results of research on detecting defects on various surfaces and recognising signs and colours in motion using intelligent technologies. The problems of recognising damages on packaging in complex and unfavourable conditions for machine vision are solved with the help of a convolutional neural network. In accordance with the proposed algorithm, image capture is carried out using standard video surveillance cameras. From the image entered into the neural network, fragments with characteristic features are distinguished, which are further checked for compliance with damage patterns. Following damage contour analysis, the neural network recognises the cargo as damaged. The process of training the neural network and integrating the proposed tool throughout the supply chain ensures the recognition of actually damaged goods and elimination of errors associated with minor permissible damage and packaging features. The proposed concept does not require the installation of additional equipment and does not imply a significant cost of damaged cargo recognition services. The paper offers and describes processes of video recording of the cargo flow, loading an image into a neural network, and a model for recognising damaged cargo by the external appearance of the package.

Salt Packaging Redesign Using Quality Function Deployment (Qfd) Method to Increase Sales (Case Study: Saboh Hate Farmers Group, Kuala Idi Cut, East Aceh)

Salt is one of the great potentials on the coast of East Aceh Regency which can be developed to boost the economic growth of the community. The location of the research was carried out in the Saboh Hate group located in Darul Aman District, Kuala Idi Cut Village, Aron Muda Hamlet, East Aceh Regency, Aceh Province. Currently, the salt on the market has an attractive packaging design, while the Saboh Hate Farmers Group does not yet have a good or simple packaging, so research is needed to design packaging that can increase competitiveness. The purpose of this study is to determine the characteristics of the salt packaging that consumers want at the Saboh Hate Farmer Group through packaging redesign. The method used is statistical test and Quality Function Deployment (QFD). The research phase includes observation and interviews through questionnaires and processing data through statistical tests, SPSS 20 and House of Quality (HOQ). The results show the characteristics of the salt packaging that consumers want based on the relative weight results including the information needed for salt packaging including weight, halal brand and logo with a value of 28.28%, the salt packaging material used is ordinary clear plastic with a value of 24.27%, The color of the desired salt packaging design is blue with a value of 23.71 and the size of the salt packaging that consumers want is generally a 250 g package with a value of 23.71%.

Surface Realization Architecture for Low-resourced African Languages

There has been growing interest in building surface realization systems to support the automatic generation of text in African languages. Such tools focus on converting abstract representations of meaning to a text. Since African languages are low-resourced, economical use of resources and general maintainability are key considerations. However, there is no existing surface realizer architecture that possesses most of the maintainability characteristics (e.g., modularity, reusability, and analyzability) that will lead to maintainable software that can be used for the languages. Moreover, there is no consensus surface realization architecture created for other languages that can be adapted for the languages in question. In this work, we solve this by creating a novel surface realizer architecture suitable for low-resourced African languages that abides by the features of maintainable software. Its design comes after a granular analysis, classification, and comparison of the architectures used by 77 existing NLG systems. We compare our architecture to existing architectures and show that it supports the most features of a maintainable software product.

Continuous Metadata in Continuous Integration, Stream Processing and Enterprise DataOps

ABSTRACTImplementations of metadata tend to favor centralized, static metadata. This depiction is at variance with the past decade of focus on big data, cloud native architectures and streaming platforms. Big data velocity can demand a correspondingly dynamic view of metadata. These trends, which include DevOps, CI/CD, DataOps and data fabric, are surveyed. Several specific cloud native tools are reviewed and weaknesses in their current metadata use are identified. Implementations are suggested which better exploit capabilities of streaming platform paradigms, in which metadata is continuously collected in dynamic contexts. Future cloud native software features are identified which could enable streamed metadata to power real time data fusion or fine tune automated reasoning through real time ontology updates.

A Novel Hybrid Deep Learning Model for Detecting and Classifying Non-Functional Requirements of Mobile Apps Issues

As a result of the speed and availability of the Internet, mobile devices and apps are in widespread usage throughout the world. Thus, they can be seen in the hands of nearly every person, helping us in our daily activities to accomplish many tasks with less effort and without wasting time. However, many issues occur while using mobile apps, which can be considered as issues of functional or non-functional requirements (NFRs). Users can add their comments as a review on the mobile app stores that provide for technical feedback, which can be used to improve the software quality and features of the mobile apps. Minimum attention has been given to such comments by scholars in addressing, detecting, and classifying issues related to NFRs, which are still considered challenging. The purpose of this paper is to propose a hybrid deep learning model to detect and classify NFRs (according to usability, reliability, performance, and supportability) of mobile apps using natural language processing methods. The hybrid model combines three deep learning (DL) architectures: a recurrent neural network (RNN) and two long short-term memory (LSTM) models. It starts with a dataset construction extracted from the user textual reviews that contain significant information in the Arabic language. Several experiments were conducted using machine learning classifiers (MCLs) and DL, such as ANN, LSTM, and bidirectional LSTM architecture to measure the performance of the proposed hybrid deep learning model. The experimental results show that the performance of the proposed hybrid deep learning model outperforms all other models in terms of the F1 score measure, which reached 96%. This model helps mobile developers improve the quality of their apps to meet user satisfaction and expectations by detecting and classifying issues relating to NFRs.

Flying Robot Technology (Drone) Trends: A Review in the Building and Construction Industry

AbstractWith the emergence of Industry 4.0, the use of robotic technologies is among today’s trends. The innovations that this revolution brought to robotic construction in the fields of communication, control, and software also improve flying robot technology. In the study, the place and importance of drone technology, which is one of the flying robot technologies at the intersection of Industry 4.0 and AEC (architecture, engineering, and construction) industry, in architecture is defined. The research aims to analyze the digital fabrication studies with drone technology in the field of architecture by reviewing the literature and to reveal how these applications are followed. Studies with drones, which are the technology of the future, are presented by creating a timeline. Drone studies in the building and construction industry were classified according to drone type, gripper and software features and comparative analyses were made. As a result, it is desired to show the development of drone technology in architecture, examine how it is used, and create a reference study in the light of existing examples for its use in future applications.

Ensuring sustainability in sensory sciences

Ensuring sustainability in sensory sciences

Exploring the usability and user experience of social media apps through a text mining approach

Abstract This study aims to evaluate the applicability of a text mining approach for extracting UUX-related issues from a dataset of user comments and not to evaluate the Instagram (IG) app. This study analyses textual data mined from reviews in English written by IG mobile application users. The article’s authors used text mining (based on the LDA algorithm) to identify the main UUX-related topics. Next, they mapped the identified topics with known theoretical constructs to place them in their nomological network relevant to the usability (the 5Es framework by Quesenbery) and UX (the Honeycomb model by Morville). Finally, to expand the study with an emotional diagnosis, sentiment analysis was performed on two levels: (i) for each recognised topic, and (ii) for the full dataset to uncover general insights into users’ emotions within all reviews. The case study of the IG app confirms the usefulness of user feedback data for software development and points out that the review data have the potential for the early detection of frustration and negative feelings introduced during the use of the application. Conducting conventional UUX evaluations with users is problematic since they are remotely located, and the user-generated content of a social app undergoes continuous and frequent changes. Thus, the consecutive stages of the proposed methodology, based on text mining algorithms, constitute a proposed framework for examining the user-perceived quality projection of applications from user feedback, and they are the main contribution of this article. The used approach can be valuable for helping developers, designers and researchers to reveal user problems and fulfil user satisfaction regarding UUX aspects for specific software features.

Strategi Pempek XYZ Memenangkan Pangsa Pasar Melalui Kualitas Produk

There are so many culinary business opportunities, one of which is pempek because apart from being easy to produce, it is also in great demand. This regional food has tough competition between producers. So novice business people who are in the pempek business, they need to present quality products. Pempek XYZ has been established for four years, market segmentation has not varied, packaging design features are still minimal, product variants are still the same as competitors, and promotions are still minimal, but they want wider market access to increase pempek sales revenue. This research aims to identify pempek XYZ market segmentation and product quality and develop a strategy to attract consumers by improving product quality. The method used is the interview. The analysis techniques are STP analysis (segmentation, targeting, position), eight dimensions of product quality analysis, and SWOT analysis. The results showed that the target market for pempek XYZ was not diverse, it was still the middle-income family. Product quality must be improved through improvements in packaging design, features, product variants, and product benefits. The strategy is to have distributors, agents, and retailers (salesmen), provide modified product information, complete halal features, BPOM permits, production and expiration dates, product storage recommendations, explanation of composition on the packaging, create bonus coupons, post as products not just filling and healthy but able to provide new experiences through the addition of variants and value of pempek XYZ in the form of facilities that will trigger consumers to continue to explore product features, explore many moments, explore tastes and explore packaging designs when consuming pempek.

MOSPPA: monitoring system for palletised packaging recognition and tracking

The paper industry manufactures corrugated cardboard packaging, which is unassembled and stacked on pallets to be supplied to its customers. Human operators usually classify these pallets according to the physical features of the cardboard packaging. This process can be slow, causing congestion on the production line. To optimise the logistics of this process, we propose a visual recognition and tracking pipeline that monitors the palletised packaging while it is moving inside the factory on roller conveyors. Our pipeline has a two-stage architecture composed of Convolutional Neural Networks, one for oriented pallet detection and recognition, and another with which to track identified pallets. We carried out an extensive study using different methods for the pallet detection and tracking tasks and discovered that the oriented object detection approach was the most suitable. Our proposal recognises and tracks different configurations and visual appearance of palletised packaging, providing statistical data in real time with which to assist human operators in decision-making. We tested the precision-performance of the system at the Smurfit Kappa facilities. Our proposal attained an Average Precision (AP) of 0.93 at 14 Frames Per Second (FPS), losing only 1% of detections. Our system is, therefore, able to optimise and speed up the process of logistic distribution.

Effectiveness of Computer-Aided Instruction on Students’ Conceptual Understanding in Life Science

The study aimed to determine the effectiveness of computer-aided instruction (CAI) on students’ conceptual understanding in Life Science. The objectives of the study is to develop lesson plans with computer-aided instruction packages; assess the developed lesson plans in terms of congruency of objectives, learning experiences, assessment of learning outcomes, features of computer-aided instruction packages, and to determine the effect of CAI on students’ conceptual understanding. The study utilized the pre-experimental method. The study involved 27 students who took a Bioenergetics Achievement Test (B.A.T) before and after CAI. It was found out that developed daily lesson plans are excellent; congruency of lesson objectives (WM = 4.80), learning experiences (WM =4.76), assessment of learning outcomes (WM =4.79), and features of computer-aided instruction (WM =4.39). The test of the difference between the pre-test and post-test scores showed a significant result (t26=-14.30, p<0.01), and it was supported with the positive increase on the Learning Gain Score (LGS=3.18) which showed an increase in conceptual understanding and mastery in the learning competencies. Hence, there is sufficient evidence to show that the students’ scores improved significantly after being taught in computer-aided instruction. Therefore, the developed lesson plans with the integration of computer-aided instruction are excellently and effectively improved the students' conceptual understanding and mastery of the learning competencies.