Miracle-dz/UniFAR-FTUs huggingface dataset:
FGL_Droid: An Efficient Android Malware Detection Method Based on Hybrid Analysis

With the popularity of Android intelligent terminals, malicious applications targeting Android platform are growing rapidly. Therefore, efficient and accurate detection of Android malicious software becomes particularly important. Dynamic API call sequences are widely used in Android malware detection because they can reflect the behaviours of applications accurately. However, the raw dynamic API call sequences are very usually too long to be directly used, and most existing works just use a truncated segment of the sequence or statistical features of the sequence to perform malware detection, which loses the execution order information of applications and consequently results in high false alarm rate. In this work, we propose a method that transforms the dynamic API call sequence into a function call graph, which retains most of the application execution order information with significantly reduced sequence size. To compensate for the missed behaviour information during the transformation, the advanced features of permission requests extracted from the application are utilized. We then propose FGL_Droid, which fusions the transformed function call graph feature and the extracted permission request feature to perform accurate malware detection. Experiments on benchmark dataset show that FGL_Droid achieves a high detection accuracy of 0.975 and a high F-score of 0.978, which are better than the existing methods.
Space vector PWM techniques for dual three-phase AC machine: analysis, performance evaluation and DSP implementation

The major drawback of usual dual three-phase AC machines (6/spl phi/M), when supplied by a voltage source inverter (VSI), is the occurrence of extra harmonic currents. These extra currents circulate only in the stator windings and cause additional losses. One solution to reduce their amplitude is to act on the supply side using dedicated PWM control strategies. The aim of the present paper is to investigate new space vector PWM (SVPWM) techniques suitable for 6/spl phi/M and to perform a detailed analysis and a performance evaluation. The proposed performance criteria, specific to VSI fed 6/spl phi/M, lead to analytical formulas and graphics, which aid the design of high-performance PWM techniques and demonstrate the superiority of proposed SVPWM techniques. Experimental results carried out on a 15 kW prototype machine and using a low cost fixed point TMS320F240 DSP are given and discussed.
Analysis of Deep Transfer Learning Methods for Early Diagnosis of the Covid-19 Disease with Chest X-ray Images

This study aimed to present an analysis of deep transfer learning models to support the early diagnosis of Covid19 disease using X-ray images. For this purpose, the deep transfer learning models VGG-16, VGG-19, Inception V3 and Xception, which were successful in the ImageNet competition, were used to detect Covid-19 disease. Also, 280 chest x-ray images were used for the training data, and 140 chest x-ray images were used for the test data. As a result of the statistical analysis, the most successful model was Inception V3 (%92), the next successful model was Xception (%91), and the VGG-16 and VGG-19 models gave the same result (%88). The proposed deep learning model offers significant advantages in diagnosing covid-19 disease issues such as test costs, test accuracy rate, staff workload, and waiting time for test results.
The Benefits of Training and Development Programs for Lending Organization Personnel: Basis for Development of Training Program

Employee development and training programs are critical to the global success of firms. Not only do these programs enable employees to develop new abilities, but they also enable businesses to increase employee productivity and improve company cultures. Assistance for Central Luzon Lending Inc.(ACLLI), is a newly established organization which aims to provide a training and development program for its employees. The researchers of this study focus on the emerging situation and the need for training and development, its implications on individual performance and the achievement of the institutional goal. The study utilized a mixed-method approach to assess the benefits of a Training and Development Program for a lending organization personnel. This research was conducted in Talavera, Nueva Ecija where the 13 employee- respondents of ACLLI were identified. The data collected from the locale were encoded, tallied, and analyzed. Statistical tools such as Percentage, Frequency Distribution, Weighted Mean, and Thematic analysis were used in analyzing the data gathered. The result shows that most of the respondents strongly agreed the training given equipped me with the knowledge necessary to succeed in my career when it comes to career competencies. Also, the majority of the respondents are highly in favour that they performed better after attending training and development programs relative to their work. Lastly, a training and development plan was crafted by the researchers to help the needs of the employees.
A Low-Code Framework for Complex Crowdsourcing Work Based on Process Modeling

Crowdsourcing has become a new distributed paradigm, which uses online crowds to solve complex problems. Recently, in order to reduce the development workload and research threshold of crowdsourcing applications, crowdsourcing process modeling is attracting more and more attention. However, complex crowdsourcing processes used for creative and open-ended work have remained out of reach for process modeling, because this type of process usually has a dynamic execution, in which the type, number, and order of tasks and subtasks are often unknown in advance but are determined dynamically at runtime. In this paper, we propose a modeling approach and supporting framework to fill this gap. Specifically, we provide a task model composition to allow task creation on demand, while collaborating on tasks in a tree structure to adapt to the dynamic execution. Moreover, we introduce a set of message communication modes to support data exchange among tasks. Finally, we construct a framework named CrowdModeller to embody this approach. Through two evaluations, we demonstrate its effectiveness.
MRI Reconstruction with Separate Magnitude and Phase Priors Based on Dual-Tree Complex Wavelet Transform

The methods of compressed sensing magnetic resonance imaging (CS-MRI) can be divided into two categories roughly based on the number of target variables. One group devotes to estimating the complex-valued MRI image. And the other calculates the magnitude and phase parts of the complex-valued MRI image, respectively, by enforcing separate penalties on them. We propose a new CS-based method based on dual-tree complex wavelet (DT CWT) sparsity, which is under the frame of the second class of CS-MRI. Owing to the separate regularization frame, this method reduces the impact of the phase jumps (that means the jumps or discontinuities of phase values) on magnitude reconstruction. Moreover, by virtue of the excellent features of DT CWT, such as nonoscillating envelope of coefficients and multidirectional selectivity, the proposed method is capable of capturing more details in the magnitude and phase images. The experimental results show that the proposed method recovers the image contour and edges information well and can eliminate the artifacts in magnitude results caused by phase jumps.
Forecasting lake‐/sea‐effect snowstorms, advancement, and challenges

Lake‐/sea‐effect snow forms typically from late fall to winter when a cold air mass moves over the warmer, large water surface. The resulting intense snowfall has many societal impacts on communities living in downwind areas; hence, accurate forecasts of lake‐/sea‐effect snow are essential for safety and preparedness. Forecasting lake‐/sea‐effect snow is extremely challenging, but over the past decades the advancement of numerical forecast models and the expansion of observational networks have incrementally improved the forecasting capability. The recent advancement includes numerical forecast models with high spatiotemporal resolutions that allow simulating vigorous snowstorms at the kilometer‐scale and the frequent inclusion of radar observations in the model. This combination of more accurate weather prediction models as well as ground‐based and remotely sensed observations has aided operational forecasters to make better lake‐/sea‐effect snow forecasts. A remaining challenge is that many observations of precipitation, surface meteorology, evaporation, and heat supply from the water surface are still limited to being land‐based and the information over the water, particularly offshore, remains a gap. This primer overviews the basic mechanisms for lake‐/sea‐effect snow formation, evolution of forecast techniques, and challenges to be addressed in the future.
Analisis Penerapan Project Management Information System (PMIS) Menggunakan Metode Technology Acceptance Model (TAM) Studi Kasus PT. INDOSAT, Tbk

Project Management Information System (PMIS) adalah suatu sistem alat dan teknik yang digunakan dalam manajemen proyek untuk menyampaikan informasi. PMIS digunakan untuk membandingkan baseline dengan actual project dari setiap kegiatan, mengelola material dan merecord catatan untuk tujuan pelaporan. PMIS digunakan untuk menggantikan pekerjaan proyek yang selama ini dilakukan secara manual. Masalahnya adalah apakah Project Management Information System yang telah diimplementasikan sekarang ini dapat memenuhi harapan dari Project Implementator ? Apakah PMIS ini dapat membantu mempercepat pekerjaan proyek ? Kendala-kendala selama ini sewaktu melakukan pekerjaan dokumen project adalah delay dalam hal pengumpulan hasil uji terima yang disebabkan oleh jarak pengiriman, banyaknya dokumen yang harus diproses dalam waktu bersamaan, banyaknya lembaran dokumen yang harus melalui proses approval dan inisiasi pejabat terkait, sehingga membutuhkan waktu dan effort yang tidak sedikit. Semua dokumen tersebut dikerjakan secara manual, baik dalam penyusunan maupun pemeriksaan awal. Permasalahan yang terkandung didalam pertanyaan diatas adalah object penelitian yang diharapkan dapat memberikan jawaban. Penelitian dilakukan dengan melakukan survey kepada pemakai PMIS yang sebelumnya menggunakan sistem secara manual. Penelitian ini menggunakan Technology Acceptance Model (TAM). Penggunaan model TAM didasarkan pada Kenyataan bahwa sejauh ini TAM merupakan sebuah konsep yang dianggap paling baik dalam menjelaskan perilaku user terhadap sistem teknologi informasi baru. Populasi dalam penelitian ini adalah vendor-vendor yang terkait, staf admin project dan project Manager. Analisa dilakukan dengan SEM (Structural Equation Modelling) dengan software AMOS (Analysis of Moment Structures) version 6.0.
Effects of Liquid Urea Application Frequency on the Growth and Grain Yield of Corn (Zea mays L.)

ABSTRACT Efficient nitrogen (N) management is considered one of the most important strategies for increasing sustainable crop yield along with maximizing nitrogen use efficiency (NUE). The aim of the study was to evaluate the effects of liquid urea (LU) application frequency on the growth, yield, and NUE of grain corn (Zea mays L.). The application frequencies urea were two split (2S) applied equally at 10 and 28 days after sowing (DAS), three split (3S) applied equally at 10, 40, and 65 DAS, and four split (4S) applied equally at 10, 30, 50, and 70 DAS organized by following randomized completely block design with four replicates. Results showed that stem diameter, ear length, fresh and dry stover weight, fresh cob weight, husk weight, kernel row/cob, and grain yield were higher in the LU treatments than granular urea (GU). Among all the treatments, the grain corn receiving LU3S had the highest stem diameter (2.03 cm), cob weight (248.25 g), 100 grain weight (29.08 g), N uptake (133.96 kg/ha), and NUE (72.84%). The corn grain yield of LU3S was 6.77 t/ha compared to the GU2S, which was only 4.95 t/ha. The N uptake along with NUE was significantly higher in LU3S treatment than other treatments. The results of this study suggest that the yield and NUE of corn were significantly affected by the urea source and application frequency of LU while LU3S was the most efficient treatment for maximizing the growth and yield of grain corn grown in tropical soil.
Investigating evolutionary computation with smart mutation for three types of Economic Load Dispatch optimisation problem

The Economic Load Dispatch (ELD) problem is an optimisation task concerned with how electricity generating stations can meet their customers’ demands while minimising under/over-generation, and minimising the operational costs of running the generating units. In the conventional or Static Economic Load Dispatch (SELD), an optimal solution is sought in terms of how much power to produce from each of the individual generating units at the power station, while meeting (predicted) customers’ load demands. With the inclusion of a more realistic dynamic view of demand over time and associated constraints, the Dynamic Economic Load Dispatch (DELD) problem is an extension of the SELD, and aims at determining the optimal power generation schedule on a regular basis, revising the power system configuration (subject to constraints) at intervals during the day as demand patterns change. Both the SELD and DELD have been investigated in the recent literature with modern heuristic optimisation approaches providing excellent results in comparison with classical techniques. However, these problems are defined under the assumption of a regulated electricity market, where utilities tend to share their generating resources so as to minimise the total cost of supplying the demanded load. Currently, the electricity distribution scene is progressing towards a restructured, liberalised and competitive market. In this market the utility companies are privatised, and naturally compete with each other to increase their profits, while they also engage in bidding transactions with their customers. This formulation is referred to as: Bid-Based Dynamic Economic Load
The Reproducibility and Usefulness of Estimated Average Glucose for Hyperglycemia Management during Health Checkups: A Retrospective Cross-Sectional Study

HbA1c reflects average glucose levels over 3 months, but it does not measure glycemic variability. This study aimed to determine the reproducibility and usefulness of HbA1c-derived estimated average glucose (eAG) and to analyze the factors associated with eAG during health checkups. This cross-sectional retrospective study consecutively selected subjects who had undergone health checkups at 16 health-promotion centers in 13 Korean cities in 2020. The subjects comprised 182,848 healthy subjects with normoglycemia, 109,555 with impaired fasting glucose (IFG), and 35,632 with diabetes. eAG was calculated using Nathan’s regression equation. In all subjects, fasting plasma glucose (FPG) was found to be fairly strongly correlated with eAG (r = 0.811). When the subjects were divided into FPG subgroups, the strength of the correlation decreased among those with normoglycemia and IFG (p < 0.001). Higher eAG levels were associated with older age, females, higher FPG, and lower HDL-C and triglycerides (p < 0.05). The proportion of subjects with a higher value of FPG than eAG was 46.3% in poorly controlled diabetic patients, compared with only 1.5% in normoglycemic subjects. This suggests eAG could help patients to understand their glycemic variability intuitively and healthcare providers to identify patients who might worsen in hyperglycemia control through measuring the difference between eAG and FPG.
Antioxidant activity and three phenolic compounds from the roots of Taraxacum gracilens Dahlst.

Antioxidant activity and three compounds from the ABSTRACT Background and Aims: The genus Taraxacum is a member of the family Asteraceae. Taraxacum species are widely distributed in the warmer temperate zones of the Northern Hemisphere. The aim of this study was to evaluate the phenolic contents and antioxidant activity of the ethanol extract and its chloroform and ethyl acetate fractions from the roots of Taraxacum gracilens Dahlst. and isolate some of its phenolic compounds. Methods: The roots of T. gracilens Dahlst. werefirst macerated with EtOH and fractionated to obtain chloroform and ethyl acetate fractions, and then phenolic compounds were isolated by column chromatography. The polyphenolic contents and antioxidant activities of the fractions were evaluated by measuring their abilities to inhibit lipid peroxidation induced by Fe 3+ -ascorbate, their reducing powers, and their hydrogen-donor activities. Results: Three phenolic compounds [vanillic acid ( 1 ), caffeic acid ( 2 ) and luteolin ( 3 )] were isolated from the roots of T. grac- ilens Dahlst. The ethyl acetate fraction from the ethanol extract of T. gracilens Dahlst. roots showed the highest antioxidant activity due to its richest phenolic contents, whereas the ethanol extract containing the least phenolics was the weakest in activity. Conclusion: The fractions have potential to act as antioxidant agents. T. gracilens Dahlst. roots were investigated for the first time in literature data in terms of phenolic contents and antioxidant activity.
Beyond a complete failure: the impact of partial capacity degradation on public transport network vulnerability

Disruptions in public transport networks (PTNs) often lead to partial capacity reductions rather than complete closures. This study aims to move beyond the vulnerability analysis of complete failures by investigating the impacts of a range of capacity reductions on PTN performance. The relation between network performance and the degradation of line or link capacities is investigated by establishing a vulnerability curve and related metrics. The analysis framework is applied to a full-scan analysis of planned temporary line-level capacity reductions and an analysis of unplanned link-level capacity reductions on the most central segments in the multi-modal rapid PTN of Stockholm, Sweden. The impacts of capacity reductions are assessed using a non-equilibrium dynamic public transport operations and assignment model. The nonlinear properties of on-board crowding, denied boarding, network effects and route choice result in non-trivial, generally convex, relations which carry implications on disruption planning and real-time management.
String stability of interconnected vehicles : network-aware modelling, analysis and experiments

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Job Autonomy, Workload and Home-work Conflict as Predictors of Job Satisfaction among Employed Women in Academia

Women’s work has been acknowledged as an important tool towards effective leadership and economic development in Nigeria and Africa in general. It is important therefore, to accept their presence and encourage the active role they play in the labour force which at the long run impacts the economy positively knowing full well that they make up noticeable portion of the world’s population. This study evaluated the contribution of job autonomy, workload and home-work conflict to the job satisfaction of employed women in universities in Ogun State, Nigeria. A descriptive survey design was used to draw 200 women through multi-stage sampling technique. Standardized questionnaires were used to obtain responses from respondents. Four hypotheses postulated were analyzed using correlation matrices and multiple regression analysis and the level of significance was at 0.05 level. Findings show that job autonomy, workload, and home-work conflict jointly contributed to job satisfaction with 10.1% variance (Adj. R2 = .101) while workload predicted female employees job satisfaction the most. It was concluded that university management should introduce flexibility in work schedules and restructure job descriptions to allow female employees have more autonomy so as to reduce the effect of home-work conflict and pressure associated with workload.
Low Power Dynamic Comparator Design Using Variable Resistor

In today's reality, where claim for versatile battery functioned gadgets is expanding, a noteworthy plunge is given in the direction of low power approaches for rapid applications. To reduce the feature size is the cause to reduce the power. The comparator is one of the most versatile circuits in analog circuit design. It serves as an input stage of most of the ADCs. The comparator has noteworthy effect on the execution of the objective application which depends on the architecture and form of it. In this thesis, a clock based comparator is analysed in terms of average power dissipation, delay power-delay product (PDP). An investigation of modified double tail dynamic comparator has been carried out using post layout simulations. Based on the analytical expressions, a new comparator circuit that consumes less power has been proposed. Simple modification has been done by adding MOS transistor that works as voltage variable resistor (MOSFET in triode region) to reduce power. The delay of the proposed circuit is also improved as the voltage variable resistor increases the differential voltage in pre amplifier stage. Post layout simulation of the design in 90nm CMOS technology is presented. The average power dissipations of the proposed comparator at two different supply voltages which is 0.6 and 1.2 V are 0.842 µW and 2.68 µW respectively. The clock frequency at which circuit gives proper output of the proposed circuit goes up to 1.33GHz and 1GHz at supply voltages of 1.2V and 0.6V.
Multichannel parallel continuous-variable quantum key distribution with Gaussian modulation

We propose a novel scheme for continuous variable quantum key distribution(CV-QKD) using the subcarrier multiplexing technique which was employed in microwave photonics. This scheme allows to distribute N channels independent Gaussian modulated CV-QKD in parallel with one laser source and several phase modulators. We analyze the influence of nonlinear signal mixing and the security in the asymptotic limit. Results indicate that by using this multiplexing technique, each channel will be introduced a non-Gaussian extra source noise, resulting slightly short of the maximum transmission distance, while the total secret key rate can be considerably increased. This scheme could also be used for key distribution for multi-users and combined with the WDM devices it has the potential to construct a CV-QKD network.