Hasil untuk "Information technology"

Mahmoud M. Omran, Mohamed Emam, Mariam Gamaleldin et al.

Abstract Background Breast cancer (BC) is a critical cause of cancer-related death globally. The heterogeneity of BC subtypes poses challenges in understanding molecular mechanisms, early diagnosis, and disease management. Recent studies suggest that integrating multi-omics layers can significantly enhance BC subtype identification. However, evaluating different multi-omics integration methods for BC subtyping remains ambiguous. Methods In this study, we conducted a multi-omics integration analysis on 960 BC patient samples, incorporating three omics layers: Host transcriptomics, epigenomics, and shotgun microbiome. We compared two integration approaches the statistical-based approach (MOFA+) and a deep learning-based approach (MOGCN) for this integration. We evaluated both methods using complementary evaluation criteria. First, we assessed the ability of selected features to discriminate between BC subtypes using both linear and nonlinear classification models. Second, we analyzed the biological relevance of the selected features to key BC pathways, focusing on transcriptomics-driven insights. Results Our results showed that MOFA+ outperformed MOGCN in feature selection, achieving the highest F1 score (0.75) in the nonlinear classification model, with MOFA+ also identifying 121 relevant pathways compared to 100 from MOGCN. Notably, one of the key pathways Fc gamma R-mediated phagocytosis and the SNARE pathway was implicated, offering insights into immune responses and tumor progression. Conclusion These findings suggest that MOFA+ is a more effective unsupervised tool for feature selection in BC subtyping. Our study underscores the potential of multi-omics integration to improve BC subtype prediction and provides critical insights for advancing personalized medicine in BC.

Robin Delabays, Giulia De Pasquale, Florian Dörfler et al.

Abstract A plethora of methods have been developed in the past two decades to infer the underlying network structure of an interconnected system from its collective dynamics. However, methods capable of inferring nonpairwise interactions are only starting to appear. Here, we develop an inference algorithm based on sparse identification of nonlinear dynamics (SINDy) to reconstruct hypergraphs and simplicial complexes from time-series data. Our model-free method does not require information about node dynamics or coupling functions, making it applicable to complex systems that do not have a reliable mathematical description. We first benchmark the new method on synthetic data generated from Kuramoto and Lorenz dynamics. We then use it to infer the effective connectivity in the brain from resting-state EEG data, which reveals significant contributions from non-pairwise interactions in shaping the macroscopic brain dynamics.

Zhan Zhang, Daoyu Shu, Guihe Gu et al.

Semantic segmentation of ultra-high-resolution remote sensing (UHR-RS) imagery plays a critical role in land use and land cover analysis, yet it remains computationally intensive due to the enormous input size and high spatial complexity. Existing studies have commonly employed strategies such as patch-wise processing, multi-scale model architectures, lightweight networks, and representation sparsification to reduce resource demands, but they have often struggled to maintain long-range contextual awareness and scalability for inputs of arbitrary size. To address this, we propose RingFormer-Seg, a scalable Vision Transformer framework that enables long-range context learning through multi-device parallelism in UHR-RS image segmentation. RingFormer-Seg decomposes the input into spatial subregions and processes them through a distributed three-stage pipeline. First, the Saliency-Aware Token Filter (STF) selects informative tokens to reduce redundancy. Next, the Efficient Local Context Module (ELCM) enhances intra-region features via memory-efficient attention. Finally, the Cross-Device Context Router (CDCR) exchanges token-level information across devices to capture global dependencies. Fine-grained detail is preserved through the residual integration of unselected tokens, and a hierarchical decoder generates high-resolution segmentation outputs. We conducted extensive experiments on three benchmarks covering UHR-RS images from 2048 × 2048 to 8192 × 8192 pixels. Results show that our framework achieves top segmentation accuracy while significantly improving computational efficiency across the DeepGlobe, Wuhan, and Guangdong datasets. RingFormer-Seg offers a versatile solution for UHR-RS image segmentation and demonstrates potential for practical deployment in nationwide land cover mapping, supporting informed decision-making in land resource management, environmental policy planning, and sustainable development.

Joko Siswanto, Sri Yulianto Joko Prasetyo, Sutarto Wijono et al.

Accurate predictions of the number of public transport passengers on buses in each region are crucial for operations. They are required by the planning and management authority for bus public transport. A deep learning-based LSTM prediction model is proposed to predict the number of passengers in 4 bus public transportation areas (central, north, south, and west), evaluated by MSLE, MAPE, and SMAPE with dropout, neuron, and train-test variations. The CSV dataset obtained from Auckland Transport(AT) New Zealand metro patronage report on bus performance(1/01/2019-31/07/2023) is used for evaluation. The best prediction model was obtained from the lowest evaluation value and relatively fast time with a dropout of 0.2, 32 neurons, and train-test 80-20. The prediction model on training and testing data improves with the suitability of tuning for four predictions for the next 12 months with mutual fluctuations. The strong negative correlation is central-south, while the strong positive correlation is north-west. Predictions are less closely interconnected and dependent, namely central-south. With its potential to significantly impact policy-making, this prediction model can increase public transport mobility in each region, leading to a more efficient and accessible public transport system and ultimately enhancing the public's daily lives. This research has practical implications for public transport authorities, as it can guide them in making informed decisions about service planning and resource allocation.

Christian Fidel Revilla Arizaca

There is no doubt about how the Covid-19 pandemic has changed education around the world. In this context, the use of Information and Communication Technology (ICT) has been fundamental for continue delivering classes during quarantine season. Thus, this paper tries to analyze what was the use of ICT in two Peruvian universities through semi-structured interviews with 21 students who are in the last years of their careers. The preliminary results show that there were no adequate plans to deliver that kind of education, that most professors did not take advantage of these tools, and that the students experienced different difficulties in having adequate formation during virtual classes.

Jiaao Wu, Zhihao Liu, Haohua Zhang et al.

Magnesium hydride (MgH2) is an exceptional material for hydrogen storage, but its high desorption temperature and slow kinetics limit its applicability. In this study, the hydrogen storage performance of MgH2 was enhanced using highly dispersed Ni-nanoparticle–doped hollow spherical vanadium nitride (Ni/VN), which was synthesized via a solvothermal process. The MgH2 system doped with the synthesized Ni/VN exhibited an outstanding hydrogen-storage capability. Specifically, 5.6 wt.% of H2 was released within 1 h at a relatively low temperature of 513 K, whereas 6.4 wt.% of H2 was released within 180 s at 598 K, followed by an almost complete dehydrogenation after 10 min at 598 K. At 423 K, the developed material absorbed ∼6.0 wt.% of H2 within 5 min. The activation energy for dehydrogenation was determined to be 78.07 ± 2.91 kJ·mol−1, which was considerably lower than that of MgH2 produced by ball milling (120.89 ± 5.74 kJ·mol−1), corresponding to a reduction of 35.4%. It was deduced that the formation of Mg2Ni/Mg2NiH4 (hydrogen pump) through the reaction of Ni nanoparticles during dehydrogenation/hydrogenation facilitated hydrogen transport and synergistically catalyzed hydrogen absorption and desorption by MgH2, improving its hydrogen storage capability. These findings offer novel perspectives for the utilization of MgH2 in large-scale applications.

S. Yu. Dudnikov, M. P. Bulat, L. O. Vokin et al.

The problem of simulation of efficient ducted fan type propulsors is considered. From experience of operation of twin blades in fantails of helicopters, it is known that this configuration creates less noise compared to a uniform arrangement of the blades around the circumference. However, the flow behind such fan is less uniform than that of a conventional ducted fan. For multicopter-type unmanned aircraft and air taxis, the key problem is flight in take-off and landing modes as well as acoustic and vortex fields created by propulsors in these modes. The decrease in the noise level in propellers with twin blades can potentially be accompanied by an increase in non-stationary vortex effects on the aircraft as well as a decrease in specific thrust. The objectives were to develop a method for simulation of ducted fan propellers in the takeoff and landing mode, to determine the optimal angle between the blades, and to compare a ducted fan with twin X-shaped blades to conventional blade position. Turbulent flows were calculated using transient Reynold-averaged Navier-Stokes equations, complemented by SST turbulence model, and large eddy simulation with WALE subgrid viscosity model. The calculations used the modification γ–Reθ Transition SST of the Langtry-Menter turbulence model, where there are relations for the intermittency criterion, which made it possible to consider the laminar-turbulent transition and the appearance of thin laminar separation bubbles that affect both the thrust of the propeller and the nonuniformity of the flow behind it. Testing was carried out on four-bladed propellers according to the known results of the TsAGI reference experiments. Testing of the γ–Reθ Transition SST Langtry-Menter turbulence model showed that it reproduces the dependence of the thrust coefficient and power factor on the blade angle better than the standard SST model. Calculations have shown that there is a clearly defined optimum angle between the paired blades. A comparison of three-bladed, six-bladed single and six-bladed propellers with twin blades showed that the latter option has slightly better thrust characteristics and creates a significantly lower noise level on the ground. The studied characteristics of ducted fans demonstrate the prospects for the use of propellers with twin blades in aircraft with vertical takeoff and landing. The developed numerical method can be directly used for industrial calculations of propellers and fans.

Bowen Han, Xiaodong Qu, Xiaopeng Yang et al.

Distributed array radar achieves high angular resolution and measurement accuracy, which could provide a solution to suppress digital radio frequency memory (DRFM) repeater jamming. However, owing to the large aperture of a distributed radar, the far-field plane wave assumption is no longer satisfied. Consequently, traditional adaptive beamforming methods cannot work effectively due to mismatched steering vectors. To address this issue, a DRFM repeater jamming suppression method based on joint range-angle sparse recovery and beamforming for distributed array radar is proposed in this paper. First, the steering vectors of the distributed array are reconstructed according to the spherical wave model under near-field conditions. Then, a joint range-angle sparse dictionary is generated using reconstructed steering vectors, and the range-angle position of jamming is estimated using the weighted L1-norm singular value decomposition (W-L1-SVD) algorithm. Finally, beamforming with joint range-angle nulling is implemented based on the linear constrained minimum variance (LCMV) algorithm for jamming suppression. The performance and effectiveness of proposed method is validated by simulations and experiments on an actual ground-based distributed array radar system.

Richard Fechner, Jens Dörpinghaus, Anja Firll

Albana Ilo, Helmut Bruckner, Markus Olofsgard et al.

The EU policymakers have adopted legislation to support communities taking responsibility for the energy transition. However, their development and integration are still in their early stages: many studies are performed without considering the overlapped social, economic, political, electrical, and information technology tasks simultaneously. This paper is the first to look at energy communities in their entirety, from the roles of the actors to the organisation, regulation, technical solution, and the market, to the use and business cases. The waterfall methodology was used throughout the work. The results show that energy communities can be viable by becoming reliable players so DSOs can better integrate the acquired flexibility and other services into their processes without compromising power supply. Their technical integration requires a coordinated operation and control of the entire power grid, including transmission and distribution, and the end-users, as proposed by the <i>LINK</i> holistic solution. The suggested fractal-based market structure, with the national, regional and local markets harmonised with the grid, facilitates the direct participation of small customers and distributed resources to the energy market. The results of this work may help policymakers, regulators, and industry representatives define new energy policies and processes related to research and development programs for implementing fully integrated renewable energy communities.

Mahdi Moeinikia, Shahram Mehravar Giglouu, Salim Kazami et al.

Background: Today, e-learning has become one of the basic components of education process, especially in higher education. Institutions and universities employ e-learning extensively in their educational operations. In light of this, the goal of the current research was to determine the advantages, disadvantages, possibilities, and dangers associated with e-learning in the Iranian higher education system.Method: The present research is applied in terms of purpose and with a qualitatively exploratory approach. The participants of present study were experts in the field of e-learning in public universities of the Ministry of Science, Research and Technology in 2021.Using purposive sampling and snowball sampling methods, 16 e-learning experts were selected as the participants. Semi-structured interviews were used to collect data and thematic analysis was employed to analyze the obtained data. Results: After analyzing the obtained data from the interview, the total number of 116 free codes were extracted from interviews content was 116 codes, which were classified in 18 concepts and finally were identified strengths (Use of office automation in universities, Establishment of information and communication technology centers in universities, Development of e-learning in universities, Familiarity of faculty members and students with virtual environments, The place of e-learning in upstream documents and university perspectives), weaknesses (Lack of proper infrastructure, equipment and facilities for e-learning, Lack of specialized manpower, Lack of formal regulations for e-learning in the field of higher education, Insufficient knowledge about e-learning), threats (Threats related to cost, facilities and time, Management threats, Threats to change the nature of the university, Threats related to interactions) and training opportunities (Increas access to e-learning, Expanding international and intercultural interactions, Environmental benefits, Providing economic opportunities , Development of educational justice) of e-learning in Iranian higher education system. Conclusion: Considering the research findings, to develop educational justice and the possibility of more population access to the University of the Student community, reviewing existing approaches and educational methods and using e-learning as a new educational strategy for higher education system are necessary

Bjoern‐O Gohlke, Fabian Zincke, Andreas Eckert et al.

Chenyuan Teng, Chenyuan Teng, Yichao Ding et al.

Bushing is an indispensable component in high voltage direct current (HVDC) transmission project. As the main insulating material possesses poor thermal conductivity and negative temperature coefficient (NTC) electrical resistivity, HVDC bushing suffers from the distortion of electro-thermal-coupled fields. Therefore, it is urgent to reveal the influence of electrical resistivity-temperature characteristic and thermal conductivity on the DC electric field distribution within bushing insulation, guiding the design and application advanced insulating materials. Here, the simulation of temperature and DC electric field distribution within a 400 kV bushing are carried out. The results show that the optimization of NTC effect and thermal conductivity of an insulating material is able to obtain a more uniform electric field distribution through homogenizing the electric resistivity distribution within bushing insulation. The activation energy of the insulating material has a similar variation trend with the maximum electric field within bushing insulation, which has a potential to represent the temperature dependence of electrical resistivity of insulating materials. It also shows that the reduction of DC electric field by increasing the thermal conductivity has a saturation feature. As a result, the suppression of the NTC effect should be considered together to obtain a smaller electric field within HVDC bushing. The research study provides a new idea to regulate the DC electric field distribution, which is beneficial to the design of advanced insulating materials.

João Junior, Moysés Lima, Leandro Balico et al.

In wireless sensor networks (WSNs), power consumption is an important aspect when designing routing protocols. When compared to other components of a sensor node, the power required by radio transmitters is responsible for most of the consumption. One way to optimize energy consumption is by using energy-aware protocols. Such protocols take into consideration the residual energy information (i.e., remaining battery power) when making decisions, providing energy efficiency through the careful management of energy consumption. In this work, we go further and propose a new routing protocol that uses not only the residual energy information, but also the available renewable energy information from renewable energy sources such as solar cells. We then present the Renewable Energy-Based Routing (REBORN) algorithm, an energy-aware geographic routing algorithm, capable of managing both the residual and the available energy. Our results clearly show the advantages and the efficiency achieved by our REBORN algorithm when compared to other proposed energy-aware approaches.

Darren Quick, Kim-Kwang Raymond Choo

The growth in the prevalence of the plethora of digital devices has resulted in growing volumes of disparate data, with potential relevance to criminal and civil investigations. With the increase in data volume, there is an opportunity to build greater case-related knowledge and discover evidence, with implications at all stages of the digital forensic analysis process. The growth in digital devices will potentially further contribute to the growth in big digital forensic data, with a need for practitioners to consider a wider range of data and devices that may be relevant to an investigation. A process of data reduction by selective imaging and quick analysis, coupled with automated data extraction, gives potential to undertake the analysis of the growing volume of data in a timely manner. In this paper, we outline a process of bulk digital forensic data analysis including disparate device data. We research the process with a research data corpus and apply our process to real-world data. The challenges of the growing volume of devices and data will require forensic practitioners to expand their ability to undertake research into newly developed data structures, and be able to explain this to the court, judge, jury, and investigators.

Hartarto Junaedi, Jaya Pranata, Mochamad Hariadi et al.

Teknologi komputer saat ini telah banyak digunakan dalam pengembangan animasi atau permainan komputer. Salah satu teknologi itu adalah machinima yaitu suatu sistem yang menggunakan teknologi mesin grafik 3D untuk menghasilkan produk sinematik secara real time. Dalam proses pembuatan produk sinematik itu penempatan posisi kamera sangat memegang peranan penting. Penempatan posisi kamera ini tentu harus sesuai dengan kaidah-kaidah sinematografi. Penelitian ini akan mengusulkan sebuah pendekatan agen cerdas dengan multi perilaku untuk menempatkan kamera virtual dalam lingkungan virtual secara otomatis sesuai dengan gaya seorang sutradara. Setiap kamera virtual itu akan memiliki perilaku yang berbeda berdasarkan kaidah sinematografi sehingga memiliki Point of View (POV) yang berbeda. Untuk memberikan perilaku pada kamera virtual akan digunakan pendekatan berbasis logika fuzzy dengan menggunakan metode mamdani. Jumlah variabel masukan yang digunakan sejumlah tiga dan variabel keluaran sejumlah tiga dengan membership function antara tiga sampai lima. Penelitian ini akan menggunakan simulasi permainan komputer dengan tiga kamera virtual dengan perilaku yang berbeda untuk merekam adegan yang sama dan hasilnya akan divalidasi berdasarkan hasil pengamatan dengan komunitas juru foto.  Pada akhirnya dapat diambil kesimpulan bahwa pendekatan logika fuzzy dapat digunakan untuk memberikan sebuah perilaku atau gaya sutradara pada kamera virtual. Abstract Computer technology is has been used widely in the development of animation or computer games. One of the technologies is machinima, a system that uses reak time 3D graphics engine technology to produce cinematic products. In the process of develop a cinematic product, camera positioning is a very important component. The camera positioning must be comply with cinematography’s rule. This research will propose an intelligent multi agent behavior to positining a virtual camera in a virtual environment automatically according to the director’s style. Each virtual camera will have a different behavior based on cinematographic rules so that it has a different Point of View (POV). To assign a behavior on the virtual camera will be based on  fuzzy logic using the mamdani method. The number of input variables are three and the output variables are three with the number membership functions between three to five. This research will program  a computer game simulation with three multi behavior virtual cameras to capture some scene and the results will be validated based on observations with the photographer community. Finally it can be concluded that the fuzzy logic approach can be used to assign some behavior to a virtual camera.

Sri Ambar Pratiwi, I Made Sukarsa, I Ketut Adi Purnawan

Android adalah sistem operasi bergerak (mobile operating system) yang mengadopsi sistem operasi Linux, namun telah dimodifikasi. Android merupakan sistem operasi yang terbuka bagi para pengembang untuk menciptakan aplikasi mereka sendiri secara bebas. Bisnis online memiliki prospek yang cukup besar pada saat ini dan dimasa mendatang dimana hampir semua orang menginginkan kepraktisan dan kemudahan dalam hal memenuhi kebutuhan. Perdagangan produk bunga biasanya dipasarkan dengan pasif atau dengan menempati sebuah tempat untuk memasarkannya atau yang biasa disebut toko bunga atau sudah ada yang menggunakan Online Marketing melalui email dan web. Aplikasi pemesanan bunga berbasis android ini bertujuan untuk mempermudah pemasaran produk dan menjangkau konsumen melalui smartphone yang dimiliki masing-masing konsumen. Software yang digunakan dalam pembuatan aplikasi ini adalah Eclipse dengan menggunakan metode Hybrid Apps yaitu gabungan Java dengan PHP dengan menggunakan fungsi WebView.   Kata Kunci : Android, Online Marketing, Toko Bunga, Eclipse, Hybrid Apps, Webview.

Eddie Sefululya Mukooyo, Andrew Lutwama, Ian Guyton Munabi et al.

INTRODUCTION: globally the use of information and communication technologies (ICTs) in healthcare, eHealth, is on the increase. This increased use is accompanied with several challenges requiring uniformly understood and accepted regulations. Developing such regulations requires the engagement of all stakeholders. In this manuscript we explored the priorities of various eHealth stakeholders in Uganda to inform the eHealth policy review process. METHODS: we used a Delphi approach during the initial programmed plenary of a consultative workshop in which participants were asked to identify and post their topmost priority related to eHealth under one of the seven components of the eHealth environment as described in the WHO national eHealth toolkit. We used an additional qualitative analytical method to further group the participant sorted priorities into sub clusters to support additional interpretation using the toolkit. RESULTS: the components of the eHealth environment ranked as follows with respect to descending number of postings: information services and applications (36 postings), information and technology standard (31 postings), leadership and governance (22 postings), strategic planning (21 postings), infrastructure(14 postings), financial management (2 postings) and others (6 postings). CONCLUSION: Uganda's eHealth environment is in the developing and building up stage (II). In this environment the policy and implementation strategy should strengthen linkages in core systems, create a foundation for investment, ensure legal certainty and create a strong eHealth enabling environment.