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12th IEEE Annual information Technology, Electronics and Mobile Communication Conference, IEMCON 2021

作者： Gamage, Rashmika Rajapaksa, Hasitha Sangeeth, Abhiman Hemachandra, Gimhani Wijekoon, Janaka Nawinna, Dasuni Sri Lanka Institute of Information Technology Department of Computer Science and Software Engineering Malabe 10115 Sri Lanka Sri Lanka Institute of Information Technology Department of Information Technology Malabe 10115 Sri Lanka Sri Lanka Institute of Information Technology Department of Computer System Engineering Malabe 10115 Sri Lanka

ISBN: (纸本)9781665400664

Agriculture planning plays a dominant role in the economic growth and food security of agriculture-based countries such as Sri Lanka. Even though agriculture plays a vital role, there are still several major complications to be addressed. Some of the major complications are lack of knowledge about yield and price resulting in the farmers selecting crops based on experience. Machine learning has a great potential to solve these complications. To this end, this paper proposes a novel system comprises of a mobile application, SMS (Short Message Service), and API (Application Programming Interface) with yield prediction, price prediction, and crop optimization. Several machine learning algorithms were used for yield and price predictions while a generic algorithm was used to optimize crops. The yield was predicted considering the environmental factors while the price was predicted considering supply and demand, import and export, and seasonal effect. To select the best suitable crops to cultivate, the output of yield and price prediction have been used. Yield prediction has been implemented using elastic net, ridge, and multilinear regression. R2 of yield prediction is varied from 0.74 to 0.89 while RMSE value is between 15.69 and 35.05. Price prediction has been implemented using the algorithms of Gradient Boosting Tree, Random Forest, Facebook Prophet, and R2 is varied from 0.72 to 0.92 while RMSE value is between 26.81 and 140.72. Crop optimization has been implemented using the genetic algorithm. © 2021 IEEE.

关键词： Crops

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Research on Face Anti-Spoofing Algorithm Based on Image Fusion

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Computers, Materials & Continua 2021年第9期68卷 3861-3876页

作者： Pingping Yu Jiayu Wang Ning Cao Heiner Dintera School of Information Science and Engineering Hebei University of Science and TechnologyShijiazhuang050000China School of Internet of Things and Software Technology Wuxi Vocational College of Science and TechnologyWuxi214028China German-Russian Institute of Advanced Technologies Karan420126Russia

Along with the rapid development of biometric authentication technology,face recognition has been commercially used in many industries in recent ***,it cannot be ignored that face recognition-based authentication techniques can be easily spoofed using various types of attacks such photographs,videos or forged 3D *** order to solve this problem,this work proposed a face anti-fraud algorithm based on the fusion of thermal infrared images and visible light *** normal temperature distribution of the human face is stable and characteristic,and the important physiological information of the human body can be observed by the infrared thermal ***,based on the thermal infrared image,the pixel value of the pulse sensitive area of the human face is collected,and the human heart rate signal is detected to distinguish between real faces and spoofing *** order to better obtain the texture features of the face,an image fusion algorithm based on DTCWT and the improved Roberts algorithm is ***,DTCWT is used to decompose the thermal infrared image and visible light image of the face to obtain high-and low-frequency ***,the method based on region energy and the improved Roberts algorithm are then used to fuse the coefficients of the high-and low-frequency ***,the DTCWT inverse transform is used to obtain the fused image containing the facial texture *** recognition is carried out on the fused image to realize identity *** results show that this algorithm can effectively resist attacks from photos,videos or *** with the use of visible light images alone for face recognition,this algorithm has higher recognition accuracy and better robustness.

关键词： Anti-spoofing infrared thermal images image fusion heart rate detection

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Speed Control of Motor Based on Improved Glowworm Swarm Optimization

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Computers, Materials & Continua 2021年第10期69卷 503-519页

作者： Zhenzhou Wang Yan Zhang Pingping Yu Ning Cao Heiner Dintera School of Information Science and Engineering Hebei University of Science and TechnologyShijiazhuang050018China School of Internet of Things and Software Technology Wuxi Vocational College of Science and TechnologyWuxi214028China German-Russian Institute of Advanced Technologies Karan420126Russia

To better regulate the speed of brushless DC motors,an improved algorithm based on the original Glowworm Swarm Optimization is *** proposed algorithm solves the problems of poor robustness,slow convergence,and low accuracy exhibited by traditional PID *** selecting the glowworm neighborhood set,an optimization scheme based on the growth and competition behavior of weeds is applied to a single glowworm to prevent falling into a local optimal *** the glowworm’s position is updated,the league selection operator is introduced to search for the global optimal *** the local search ability of the invasive weed optimization with the global search ability of the league selection operator enhances the robustness of the algorithm and also accelerates the convergence speed of the *** mathematical model of the brushless DC motor is established,the PID parameters are tuned and optimized using improved Glowworm Swarm Optimization algorithm,and the speed of the brushless DC motor is *** a Simulink environment,a double closed-loop speed control model was established to simulate the speed control of a brushless DC motor,and this simulation was compared with a traditional PID *** simulation results show that the model based on the improved Glowworm Swarm Optimization algorithm has good robustness and a steady-state response speed for motor speed control.

关键词： PID speed control improved Glowworm Swarm Optimization brushless DC motor

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Learnable Prompt as Pseudo-Imputation: Rethinking the Necessity of Traditional EHR Data Imputation in Downstream Clinical Prediction 25

Learnable Prompt as Pseudo-Imputation: Rethinking the Necess...

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Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1

作者： Weibin Liao Yinghao Zhu Zhongji Zhang Yuhang Wang Zixiang Wang Xu Chu Yasha Wang Liantao Ma School of Computer Science Peking University Beijing China & Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China National Engineering Research Center for Software Engineering Peking University Beijing China School of Software and Microelectronics Peking University Beijing China & Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China School of Computer Science Peking University Beijing China Center on Frontiers of Computing Studies Peking University Beijing China Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China & Peking University Information Technology Institute (Tianjin Binhai) Peking University Tianjin China National Engineering Research Center for Software Engineering Peking University Beijing China & Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing China

ISBN: (纸本)9798400712456

Analyzing the health status of patients based on Electronic Health Records (EHR) is a fundamental research problem in medical informatics. The presence of extensive missing values in EHR makes it challenging for deep neural networks (DNNs) to directly model the patient's health status. Existing DNNs training protocols, including Impute-then-Regress Procedure and Jointly Optimizing of Impute-n-Regress Procedure, require the additional imputation models to reconstruction missing values. However, Impute-then-Regress Procedure introduces the risk of injecting imputed, non-real data into downstream clinical prediction tasks, resulting in power loss, biased estimation, and poorly performing models, while Jointly Optimizing of Impute-n-Regress Procedure is also difficult to generalize due to the complex optimization space and demanding data requirements. Inspired by the recent advanced literature of learnable prompt in the fields of NLP and CV, in this work, we rethought the necessity of the imputation model in downstream clinical tasks, and proposed Learnable Prompt as Pseudo-Imputation (PAI) as a new training protocol to assist EHR analysis. PAI no longer introduces any imputed data but constructs a learnable prompt to model the implicit preferences of the downstream model for missing values, resulting in a significant performance improvement for all state-of-the-arts EHR analysis models on four real-world datasets across two clinical prediction tasks. Further experimental analysis indicates that PAI exhibits higher robustness in situations of data insufficiency and high missing rates. More importantly, as a plug-and-play protocol, PAI can be easily integrated into any existing or even imperceptible future EHR analysis models. The code of this work is deployed publicly available at https://***/MrBlankness/PAI to help the research community reproduce the results and assist the EHR analysis tasks.

关键词： electronic health records

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DEGSTalk: Decomposed Per-Embedding Gaussian Fields for Hair-Preserving Talking Face Synthesis

DEGSTalk: Decomposed Per-Embedding Gaussian Fields for Hair-...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Kaijun Deng Dezhi Zheng Jindong Xie Jinbao Wang Weicheng Xie Linlin Shen Siyang Song Computer Vision Institute School of Computer Science and Software Engineering Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Guangdong Provincial Key Laboratory of Intelligent Information Processing Department of Computer Science University of Exeter

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Accurately synthesizing talking face videos and capturing fine facial features for individuals with long hair presents a significant challenge. To tackle these challenges in existing methods, we propose a decomposed per-embedding Gaussian fields (DEGSTalk), a 3D Gaussian Splatting (3DGS)-based talking face synthesis method for generating realistic talking faces with long hairs. Our DEGSTalk employs Deformable Pre-Embedding Gaussian Fields, which dynamically adjust pre-embedding Gaussian primitives using implicit expression coefficients. This enables precise capture of dynamic facial regions and subtle expressions. Additionally, we propose a Dynamic Hair-Preserving Portrait Rendering technique to enhance the realism of long hair motions in the synthesized videos. Results show that DEGSTalk achieves improved realism and synthesis quality compared to existing approaches, particularly in handling complex facial dynamics and hair preservation. Our code is available at https://***/CVI-SZU/DEGSTalk.

关键词： Hair Training Three-dimensional displays Dynamics Signal processing Rendering (computer graphics) Noise measurement Speech processing Faces Videos

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AI-Based Child Care Parental Control system

AI-Based Child Care Parental Control System

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Advancements in Computing (ICAC), International Conference on

作者： Udara Jayasekara Hansindu Maniyangama Kalhan Vithana Tharana Weerasinghe Janaka Wijekoon Rrubaa Panchendrarajan Department of Computer Science and Software Engineering Sri Lanka Institute of Information Technology Sri Lanka Department of Computer System Engineering Sri Lanka Institute of Information Technology Sri Lanka

ISBN: (纸本)9798350398106

Due to the prevalence of the COVID-19 epidemic around the globe, children were compelled to engage in remote learning through online platforms, hence mobile phone has become one of their predominant devices. Mobile device with Internet access offers a major outlet for education, entertainment, and social connection, but this combination can lead to several significant bad sequences such as online exploitation, harmful addictions, and other negative impacts of online social networking. To address harmful effects, parental controls are becoming more crucial, yet Sri Lankan parents are less aware of this. Consequently, this study proposes a parental control system to monitor their child’s activities. Android, Microsoft Azure, Java, Python, OpenCV, MySQL, and FastAPI are among the most prominent technologies utilized in the proposed application’s development. The suggested approach focuses primarily on the Sri Lankan context and aims to enhance parental digital literacy while safeguarding children from cyber threats. Yielded results showed the proposed mobile application for the identification of toxic words, drugs & alcohol content, game character images, and Instagram Sinhala comments severity as 94%, 95%, 97%, and 55% respectively in controlled experiments.

关键词： Pediatrics Social networking (online) Multimedia Web sites Process control Control systems Real-time systems Mobile applications

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Human Resource Application Development using Person-Job Matching for Placement of Prospective Employees

Human Resource Application Development using Person-Job Matc...

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Advancement in Data Science, E-learning and information systems (ICADEIS), International Conference on

作者： Alifiah Putri Sinung Suakanto Joko Siswanto Farah Fitriavida Arifin Irfan Darmawan Dina Angela Department of Information System Faculty of Software Engineering Telkom University Bandung Indonesia Industrial Engineering Research Group Bandung of Institute Technology Bandung Indonesia Information Techology Research Group Faculty of Industrial Engineering Institut Teknologi Harapan Bangsa Bandung Indonesia

The recruitment process presents a significant challenge for Human Resource (HR) staff, particularly in their ability to objectively assess candidate competencies and align them with job requirements. While qualitative comparisons between resumes and position requirements may yield candidates who appear suitable, this approach proves ineffective in terms of time and cost. Furthermore, many recruiters lack sufficient knowledge of the positions they are hiring for, making it difficult to justify their selection decisions. This research aims to address this challenge by developing an HR person-job matching application for the recruitment of prospective employees. The study focuses on analyzing and designing applications that can quantitatively measure the competencies of candidates and compare them with job requirements using a person-job matching method. The effectiveness of this approach was evaluated by testing it on a sample of employees from small and medium-sized enterprises (SMEs). The study found that out of the 16 employees across three job positions, the person-job matching application achieved an accuracy rate of 75%. This accuracy percentage was determined by comparing the fit value results with the actual conditions of the employees in their respective workplaces. The findings highlight the potential of the HR person-job matching application to enhance the efficiency and effectiveness of recruitment efforts.

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Patterns of Remote Work Environments 22

Patterns of Remote Work Environments

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Proceedings of the 27th European Conference on Pattern Languages of Programs

作者： Kristian Toldy Waheedullah Sulaiman Khail Valentino Vranić Institute of Informatics / Faculty of Informatics and Information Technologies / Information Systems and Software Engineering Slovak University of Technology in Bratislava Slovakia Helmholtz-Zentrum Berlin für Materialien und Energie Gmbh Germany

ISBN: (纸本)9781450395946

People are more and more in a position to work remotely. They face the same problems of establishing and running remote work environments over and over again. In order to help them a bit, six organizational patterns of remote work environments are presented in this paper: Unofficial Meetings, Remote Mentor, Unified Communication Channels, Standard Operating Procedures, information Hub, and Cut Meetings. The patterns come from a firsthand remote work experience obtained in a company focusing on quality assurance through a crowd testing methodology where software companies get real users to test their newest products.

关键词： organizational patterns agile distributed teams communication meeting remote work

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HpC: A Calculus for Hybrid and Mobile systems - Full Version

arXiv

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arXiv 2025年

作者： Xu, Xiong Talpin, Jean-Pierre Wang, Shuling Wu, Hao Zhan, Bohua Liu, Xinxin Zhan, Naijun National Key Laboratory of Space Integrated Information System Institute of Software Chinese Academy of Sciences Beijing China INRIA Centre INRIA à l’Université de Rennes France and SKLCS Institute of Software Chinese Academy of Sciences UCAS Beijing China Huawei Technologies Co. Ltd. Beijing China and SKLCS Institute of Software Chinese Academy of Sciences Beijing China School of Computer Science Peking University Beijing China

Networked cybernetic and physical systems of the Internet of Things (IoT) immerse civilian and industrial infrastructures into an interconnected and dynamic web of hybrid and mobile devices. The key feature of such systems is the hybrid and tight coupling of mobile and pervasive discrete communications in a continuously evolving environment (discrete computations with predominant continuous dynamics). In the aim of ensuring the correctness and reliability of such heterogeneous infrastructures, we introduce the hybrid c-calculus (HpC), to formally capture both mobility, pervasiveness and hybridisation in infrastructures where the network topology and its communicating entities evolve continuously in the physical world. The c-calculus proposed by Robin Milner et al. is a process calculus that can model mobile communications and computations in a very elegant manner. The HpC we propose is a conservative extension of the classical c-calculus, i.e., the extension is "minimal", and yet describes mobility, time and physics of systems, while allowing to lift all theoretical results (e.g. bisimulation) to the context of that extension. We showcase the HpC by considering a realistic handover protocol among mobile devices. © 2025, CC BY.

关键词： Mobile telecommunication systems

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Chatting with GPT-3 for Zero-Shot Human-Like Mobile Automated GUI Testing

arXiv

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arXiv 2023年

作者： Liu, Zhe Chen, Chunyang Wang, Junjie Chen, Mengzhuo Wu, Boyu Che, Xing Wang, Dandan Wang, Qing Laboratory for Internet Software Technologies Institute of Software Chinese Academy of Sciences Beijing China State Key Laboratory of Computer Sciences Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Monash University Melbourne Australia

Mobile apps are indispensable for people’s daily life, and automated GUI (Graphical User Interface) testing is widely used for app quality assurance. There is a growing interest in using learning-based techniques for automated GUI testing which aims at generating human-like actions and interactions. However, the limitations such as low testing coverage, weak generalization, and heavy reliance on training data, make an urgent need for a more effective approach to generate human-like actions to thoroughly test mobile apps. Inspired by the success of the Large Language Model (LLM), e.g., GPT-3 and ChatGPT, in natural language understanding and question answering, we formulate the mobile GUI testing problem as a Q&A task. We propose GPTDroid, asking LLM to chat with the mobile apps by passing the GUI page information to LLM to elicit testing scripts, and executing them to keep passing the app feedback to LLM, iterating the whole process. Within it, we extract the static context of the GUI page and the dynamic context of the iterative testing process, design prompts for inputting this information to LLM, and develop a neural matching network to decode the LLM’s output into actionable steps to execute the app. We evaluate GPTDroid on 86 apps from Google Play, and its activity coverage is 71%, with 32% higher than the best baseline, and can detect 36% more bugs with faster speed than the best baseline. GPTDroid also detects 48 new bugs on the Google Play with 25 of them being confirmed/fixed. We further summarize the capabilities of GPTDroid behind the superior performance, including semantic text input, compound action, long meaningful test trace, and test case prioritization. © 2023, CC0.

关键词： Graphical user interfaces

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