What Do Software Developers Need to Know to Build Secure Energy-Efficient Android Applications?

Energy consumption and cycle time are two contradictory optimization objectives for the robotic assembly line balancing problem (RALBP). Indeed, minimizing the cycle time leads to choosing the fastest robots, while minimizing the energy consumption leads to choosing the robots with the smallest powers. In the context of RALBP, cycle time minimization has been extensively studied while energy minimization has been much less considered. Studies dealing with simultaneous minimization of the two later are even scarcer. A bi‐objective RALBP considering simultaneous minimization of cycle time and energy consumption is studied in this paper. The energy consumption is calculated based on recent papers from the literature. It includes energy consumed during both operation time and idle time. In this paper, a pseudo‐polynomial case is solved thanks to an exact algorithm called split. This latter enumerates all Pareto‐optimal solutions corresponding to a given giant sequence of operations. Split is then used as a decoder in a metaheuristic operating in a reduced search space where giant sequences encode solutions. An experimental study is performed on instances taken from the literature to test the suggested encoding–decoding scheme. It shows that the suggested approach yields competitive results compared to the literature.

The high energy consumption associated with acceleration requires electric vehicles (EVs) to accelerate to a chosen speed optimally, particularly in urban driving cycles. Existing methods deal with the minimization of acceleration energy without considering the acceleration duration. This paper focuses on solving a multiobjective optimization problem (MOOP) with two conflicting objectives: minimization of acceleration duration and minimization of energy consumption. Two approaches were used to reach a desired speed: using a single acceleration value and using multiple acceleration values. For each approach, demonstrative speed changes were chosen, and the problem was solved using multiobjective genetic algorithms (MOGAs). The results (Pareto-optimal fronts) obtained by these two approaches were compared using suitable performance metrics. To validate the reliability of MOGA results, statistical analysis was carried out. Furthermore, a nonparametric study, i.e., the Wilcoxon signed-rank test, was conducted to compare the effectiveness of both approaches. It was found that multiple accelerations were more effective in minimizing the duration and energy consumption than a single acceleration. For the same duration, multiple accelerations reduced energy consumption by up to 2%. Sensitivity analysis for both approaches with electric motor model parameters was conducted. The simulation results of EV acceleration using the preferred optimal solution based on driving comfort and the Pareto front's knee suggested a strong implication toward driving assistance.

In software testing process, test data generation represents an important step for high quality software, even for mobile devices. As proposed in previous works, a potential source for random data generation is represented by the UI layout files that are used for almost all mobile platforms (Android, iOS, Windows Phone/Mobile). This paper continues the previous work and presents a test data generation system based on Android layout files. The test data generator uses DSL files as input and generates test data that conform to several testing principles. The generated test data could be stored in XML files or any format required by the testing frameworks.

With the wide deployment of mobile network, it’s very important to utilize mobile networks resource efficiently and decrease energy consumption of wireless terminals for constructing green mobile computing. This paper mainly studies minimization problem of energy consumption in data transmission under the given data generation rate and transmission delay demand in wireless links. Firstly, a finite horizon optimal stopping problem with transmission data quantity constraint and energy consumption minimization is constructed, and then we prove the existence of optimal stopping rule and offer the solutions and processes. At last, we obtain the optimal transmission rate threshold of the sending terminal for each channel detection slot time, so as to form the optimization strategy of energy consumption for data transmission based on optimal stopping theory. The simulation results show that the strategy proposed by this paper has lower average energy consumption and higher average delivery success ratio than other strategies, and achieves better optimization effect in energy consumption.

The effect of applying an energy pulse to the heart during ventricular fibrillation is described by the probability of successful defibrillation or success rate. Seven to ten (8.60 +/- 0.84: mean +/- standard deviation) defibrillation trials per energy were randomly attempted at energies which span the defibrillation success rate versus energy curve. We obtained 70.0 +/- 8.4 episodes per dog. We fit the defibrillation success rate versus energy relationship from ten dogs (20.5 +/- 1.5 kg) to four types of curves: linear, exponential, probit transformed linear, and logit transformed linear. The correlation coefficients for each fit are 0.917 +/- 0.057, 0.944 +/- 0.014, 0.926 +/- 0.51, and 0.889 +/- 0.098, respectively. We therefore conclude that the exponential curve best describes the DSRE relationship. This suggests the existence of an energy below which defibrillation does not occur. At higher energies, the exponential curve asymptotically approaches a 100% success rate, which indicates that increasing the energy produces a diminishing benefit to defibrillation success rate. The estimated energies with a 0% defibrillation success rate are surprisingly consistent among dogs, with 2.072 +/- 0.553 J. The estimated energy with an 80% defibrillation success rate is 5.217 +/- 1.091 J. The estimated defibrillation success rate corresponding to the defibrillation threshold of 3.59 +/- 1.06 J is consistent with 0.516 +/- 0.144. The estimated energies with a 0% success rate correlate well with the defibrillation thresholds with R = 0.772; P = 0.0088. Since implantable defibrillators have a limited energy supply, we determined energy efficiency by dividing defibrillation success rate by the applied energy and energy consumption by dividing the applied energy by the defibrillation success rate. The most efficient defibrillation energy occurs at the maximum energy efficiency and the minimum energy consumption. The most efficient defibrillation energy of 4.34 +/- 0.97 J determined from the exponential fit has a success rate of 0.70 +/- 0.06. The most efficient defibrillation energy can be predicted from the defibrillation threshold. Clinically, a 70% success rate may not be adequate. We, therefore, compared the energy efficiency and consumption of energies with 90% and 95% success rates to the most efficient defibrillation energy. About a 50% increase in energy from the most efficient defibrillation energy is necessary for a 90% success rate which results in about a 13% loss in energy efficiency and about a 16% increase in energy consumption. About an 84% energy increase is necessary for a 95% success rate which results in about a 24% loss in energy efficiency and about a 33% increase in energy consumption.(ABSTRACT TRUNCATED AT 400 WORDS)

In the context of modern Android application development, security issues and secure programming are considered unignorable aspects to ensure the safety of Android applications while still guarantee the development speed. The lack of attention to security factors in the software development process or the delay of traditional security assurance methods are the main causes of unsafe Android software. Those unsafe Android applications contain many vulnerabilities and a high risk of leaking user information, especially since Android applications are rapidly developed and published. Developers must adhere to a secure development process to counter Android application risks to avoid data leakage or access control flaws. Security has to be integrated throughout the application development process to secure the software development life cycle. This paper presents two main research contributions: summarizing common security issues in Android applications and developing a plug-in for Android Studio to support secure programming, 9Fix. The low-time-cost 9Fix plug-in can inspect your vulnerable code and instantly suggest an alternative secure code for developers in programming time that helps to improve the security and instruct the developers on how to write a secure code. Moreover, the developers can add their own security rules to 9Fix so 9Fix can adapt smoothly in a specific situation. We also demonstrate the effectiveness and the convenience based on the student feedback by experimenting with the 9Fix plugin.

Introduction. The efficiency and normal work of electrotechnological processes and installations in their operation dynamic modes is characterized by the time of transition from initial to final state, low energy consumption, accuracy in transients and stability of the desired final state. It is proposed, from a single position on the basis of special optimal control, to combine transition and stabilization systems both in terms of determining the control algorithm with minimal energy consumption in the function of the object states and determining the parameters and conditions of movement with minimal deviation from a given trajectory providing the optimal transmission time and energy saving in a stable closed system of an object control. Materials and Methods. The principle of maximum is used as the main method for finding optimal program control, which for the study of special modes was supplemented with the apparatus of the position generality conditions for nonlinear objects with the coordinate space expansion, taking into account the occurrence of time and optimality criterion. The position generality apparatus is also used to solve energy-saving problems through using linearization in a large source object. Quasi-optimality in terms of transition time and energy consumption is achieved through minimizing energy according to the program motion parameter, which has a contradictory effect on the transition time and control amplitude. Results. To assess computational difficulties, transition time, energy saving, accuracy and stability, an example of inertial object control according to various criteria is given. The structure of a closed quasi-optimal system with stationary feedback, which is simple in technical implementation, is obtained. Discussion and Conclusion. The formalization of the approach to the construction of quasi-optimal systems based on the position generality allows it to be used in multi-criteria optimization tasks and computer-aided design systems for energy-intensive industrial, transport, and agricultural electrical installations.

The borehole heat exchanger (BHE) is an efficient and economic tool for extracting geothermal energy within ground source heat pumps (GSHPs). The layout and cross-section tube configuration of the BHE is one of the crucial bottlenecks that strongly influenced the effectiveness of the BHEs, which recently attracted numerous attention.Hence, the interest in retrofitting cost-efficient configurations of BHEs is recently regarded as an improvement pathfor maximizing geothermal energy production. In this study, novel geothermal borehole heat exchangers with elliptic and oval double U-tube (2U) configurations are investigated and compared to a traditional circular 2U BHE.This paper explains the development of traditional circular 2U-tube BHEs that makes an optimally designed model for maximizing the heat extraction rates and minimizing the energy consumption characteristics and BHE number. A 3-D numerical model was developed and validated by relevant field experiments (Tianjin geothermal project). The numerical study was performed on four cases corresponding to different widths of elliptic and oval 2U BHEs configurations. Furthermore, a sensitivity analysis was performed to parametrically investigate the impacts of key design and operational parameters on heat extraction performance. Additionally, a 3-D numerical model coupled with a finite line heat source model was also developed to perform case studies for energy consumption analysis for two goals of optimization. The results show that the oval 2U BHE (type II) outperformed the other investigated 2U BHE configurations, which increased the maximal and mean heat transfer rate by up to 54.0% and 12.30%, respectively, compared to circular 2U BHE. While the elliptic 2U-tube BHE (type II) was minimal pressure drop and energy consumption rates, which showed a pressure drop of 36.20% lower than the circular 2U BHE. In the case study findings, the utilization of elliptic 2U-tube BHE (type II) can not only reduce the BHE number by 6.70% but also minimize the energy consumption of the water pump and the entire system by 36.9% and 8.2%, compared to that of traditional circular 2U-tube BHE, respectively.

Energy consumption of numerical control (NC) machine tools is one of the key issues in modern industrial field. This study focuses on reducing the energy consumed by a five-axis machining center by changing only the workpiece setting position. Previous studies show that the movements along each axis in five-axis machining centers depend on the workpiece setting position, regardless of whether the same operation is performed. In addition, the energy consumptions required for the movements are different along each axis. From these considerations, an optimum workpiece setting position that can minimize the energy consumed during these motions is assumed to exist. To verify this assumption, in this study, the energy consumed by the feed drive systems of an actual five-axis machining center is first measured and then estimated using the proposed model in this study. The model for estimating the energy consumption comprises the friction, motor, and amplifier losses along each axis. The total energy consumption can be estimated by adding the energy consumptions along each axis. The effect of the workpiece setting position on the energy consumption is investigated by employing the cone-frustum cutting motion with simultaneous five-axis motions. The energy consumption that depends on the workpiece setting position is first measured and then estimated. The results confirm that the proposed model can estimate the energy consumption accurately. Moreover, the energy consumption is confirmed to depend on the workpiece setting position; the minimum energy consumption is found to be 20% lower than the maximum one.

This paper studied the characteristics of time and energy consumption of gear hobbing in batch production of small modulus gear. A method of integrating design of experiment, response surface method and multi-objective salp swarm algorithm (DOE/RSM/MMSA) is proposed for the complex optimization of machining parameters (namely hob rotation speed, cutting feed and depth of cut) in gear hobbing process. This paper uses three-level factorial design method to design gear hobbing experiments, and carries out mathematical and statistical analysis on the experimental results. It is found that cutting feed is the most significant machining parameter followed by hob rotation speed and depth of cut to reduce processing time and energy consumption. The prediction model of processing time and energy consumption in gear hobbing process is obtained through response surface methodology. The relative error rates of the predicted value and the actual value of the processing time and energy consumption are 0.11% and 0.09% respectively, indicating the validity of the model. Multi-objective salp swarm algorithm is used to optimize the machining parameters to minimizing processing time and energy consumption. Finally, through the comparison with the existing research results, it is concluded that the optimized machining parameters have better processing effect to achieve minimized processing time and energy consumption, which shows the effectiveness and rationality of the method proposed, and provides references for the decision-making of machining parameters in workshop.

Manufacturing industries these days are more concerned about the energy consumption due to the increasing energy cost. It is observed that industries can achieve significant savings in the energy cost even when a small percentage of energy consumption is reduced. In a manufacturing industry, assembly lines are equipped with robots to perform the assembly tasks and there is a need for efficiently balancing the assembly line by reducing the energy consumption during the production phase. The authors could not find any research on optimizing energy consumption in U-shaped robotic assembly line systems to date. The objective of this paper is to propose an optimization models with an objective of minimizing the energy consumption in a U-shaped robotic assembly line when the number of workstations are fixed. Since the assembly line balancing problems falls under the category of NP-hard, an efficient bio inspired algorithm is implemented to solve the problem. The model proposed is very well applicable for automobile assembly line where robots are employed. The energy consumption is evaluated on the benchmark data and energy consumption obtained by the U-shaped robotic assembly line is compared with the energy consumption obtained with straight robotic assembly line. The cycle time of the layouts are also compared. The results obtained using this proposed model can be used for the decision making process in the industry. The paper also proposes an optimization model for minimizing the cycle time. The energy consumption of the assembly line when the cycle time is minimized is evaluated and presented.

This paper focuses on software quality assurance in android application development with focus on approaches to confirm software quality in android applications. In this work, we compare the waterfall model with agile-scrum methodologies to realize software quality assurance with special focus on mobile applications. This research allows us to answer, “Which process model and practices are available for android software development along with focus on quality assurance?” The other research focus in this paper is “How auditors, developers and testers play their defined roles to maintain quality in mobile application development?” Agility for software development has transformed into a preferred and favored method for mobile application development. The major aim of this research is to contribute for a better knowledge for mobile application development methodologies practiced by the organizations for the development of applications based on systematic literature review.

In cognitive radio communication, energy and time consumption has a key role to ensure reliable primary user signal detection. A two stage (coarse fine) spectrum sensing has drawn well-deserved attention for wideband cognitive radio communication. In this paper, it is analyzed the required time and energy for sensing, switching and transmission for wideband channel with different practical scenario by coarse fine sensing. Moreover, we have proposed multi antenna assisted energy detection based signal detection for coarse fine sensing in the fading environment. An effective solution is developed by utilizing multiple antennas to minimize the sensing time and energy consumption while maintaining the quality of service (QoS). The proposed method improves the efficiency to obtain desired vacant band for data transmission with low energy compared with conventional system.

Optimization of cutting parameters for minimizing energy consumption in turning of AISI 6061 T6 using Taguchi methodology and ANOVA

Many regular business operations are transforming into digital services, increasing advanced multi-platforms, rapid operational alignment, flexibility, and environmental impact through energy consumption, hardware waste, and technology investments. Flexible and sustainable system development models emphasizing energy efficiency can help innovate software development as digital servicing applications shift. This research is motivated by the need to improve energy consumption in early software design and development due to rising technological efficiency and sustainability demands. Although effective in iterative development and stakeholder engagement, traditional Agile methodologies often struggle with long-term sustainability and energy efficiency. Extended Agile, combining Agile, layered architecture, and aspect-oriented frameworks (ALAI), promises to improve system modularity, flexibility, maintainability, and sustainability. This study’s findings are not just theoretical, but also practically relevant, as they explore the energy efficiency of ALAI software development methodologies, using graduate admission information system services (GAISS) as an example. GAISS is a complex system that handles the entire process of graduate admissions, from application submission to final decision. The study quantifies the energy usage of a student-list webpage by analyzing Microsoft IIS server logs from February 2022 to May 2024. Directly applicable findings show that the GAISS based on the ALAI framework reduces energy consumption by 10.7914% compared to traditional Agile software developments. ALAI used 892.80 kWh versus Agile’s 1000.80 kWh during operations, saving energy. These findings demonstrate the benefits of integrating aspect-oriented frameworks and layering approaches into Agile methodologies, contributing to sustainable software development discourse. The study emphasizes the importance of energy-efficient frameworks such as ALAI to reduce software systems’ environmental impact and promote software development sustainability. The findings of this study, with their practical relevance, assist software developers and organizations in choosing software design and development methods that maximize operational efficiency and environmental sustainability.