Hasil untuk "Information technology"

Chun Hei Michael Shiu, Hei Victor Cheng, Lele Wang

The graph alignment problem aims to identify the vertex correspondence between two correlated graphs. Most existing studies focus on the scenario in which the two graphs share the same vertex set. However, in many real-world applications, such as computer vision, social network analysis, and bioinformatics, the task often involves locating a small graph pattern within a larger graph. Existing graph alignment algorithms and analysis cannot directly address these scenarios because they are not designed to identify the specific subset of vertices where the small graph pattern resides within the larger graph. Motivated by this limitation, we introduce the subgraph alignment problem, which seeks to recover both the vertex set and/or the vertex correspondence of a small graph pattern embedded in a larger graph. In the special case where the small graph pattern is an induced subgraph of the larger graph and both the vertex set and correspondence are to be recovered, the problem reduces to the subgraph isomorphism problem, which is NP-complete in the worst case. In this paper, we formally formulate the subgraph alignment problem by proposing the Erdos-Renyi subgraph pair model together with some appropriate recovery criterion. We then establish almost-tight information-theoretic results for the subgraph alignment problem and present some novel approaches for the analysis.

Qiang Yang, Yichang Shou, Yongqi Zhao et al.

Quantitative phase microscopy (QPM) has been an effective technique to examine stain-free biomedical tissues and cells. The development of simple and compact QPM technology with planar optical components enhances system integration and portability. Here, we propose a QPM technique by inserting a metasurface-assisted optical differential system to replace the bulky optical elements in the conventional microscope. The differential scheme allows for the separation of amplitude and phase information for a complex field, offering an opportunity to quantitatively analyze the phase distribution of samples. The experimental demonstrations showcase the well-executed application of the proposed method to artificial phase samples, paramecium cells, fishtail cross-cut tissue, and diatom cells. Notably, our imaging system allows switching between four imaging modes—brightfield, optical spatial differential, differential interference contrast, and QPM. At a high level, this work may drive the advancement of single-shot and multi-mode integrated phase microscopy for biomedical imaging and diagnostics.

Lingyi Chen, Shitong Wu, Sicheng Xu et al.

The information bottleneck (IB) method is a technique designed to extract meaningful information related to one random variable from another random variable, and has found extensive applications in machine learning problems. In this paper, neural network based estimation of the IB problem solution is studied, through the lens of a novel formulation of the IB problem. Via exploiting the inherent structure of the IB functional and leveraging the mapping approach, the proposed formulation of the IB problem involves only a single variable to be optimized, and subsequently is readily amenable to data-driven estimators based on neural networks. A theoretical analysis is conducted to guarantee that the neural estimator asymptotically solves the IB problem, and the numerical experiments on both synthetic and MNIST datasets demonstrate the effectiveness of the neural estimator.

Usman Zafar, Kazuharu Bamba, Tabinda Rasheed et al.

We explore a Reissner-Nordström Anti-de Sitter (RN-AdS) black hole with a cloud of string and quintessence to study thermodynamics and thermodynamic topology in the presence of Barrow entropy, which is currently being used widely as the horizon of a black hole may not be a smooth surface as described in classical general relativity but instead could have a more intricate fractal-like structure. Here, we study the impact of the fractal correction parameter of Barrow entropy on the thermodynamics of such BHs. We compute the first law of black hole thermodynamics and the Smarr relation for RN-AdS black hole with a cloud of string and quintessence in terms of Barrow entropy by employing the generalized formula for spherically symmetric spacetime which is directly derived from the Einstein field equation. The significance of Barrow entropy has been verified from thermodynamic topology as well. We also found that the non-zero topological charge indicates the presence of the critical point.

Ismaila Ouedraogo, Borlli Michel J Some, Roland Benedikter et al.

Abstract BackgroundDiabetes is a significant health concern in sub-Saharan Africa, emphasizing the importance of assessing the health literacy and eHealth skills of hospitalized patients with diabetes. This study evaluated the health literacy and eHealth literacy of patients with diabetes at Donka Hospital in Guinea and Sanou Sourou Hospital in Burkina Faso, providing insights for targeted interventions and mobile health (mHealth) solutions to improve self-management and treatment outcomes. ObjectiveThe aim of this study is to evaluate the levels of health literacy and eHealth literacy among patients at Sanou Sourou Hospital in Burkina Faso and Donka Hospital in Guinea. MethodsThe study included 45 participants from Donka Hospital and 47 from Sanou Sourou Hospital. Data collection took place in May 2022, focusing on variables such as gender, age, education, income, and technology access. Health literacy and eHealth literacy were measured using the Brief Health Literacy Screen (BHLS) and the eHealth Literacy Scale (eHEALS), respectively. Statistical analysis was performed using SPSS 28. ResultsThe results indicated that 64% (64/99) of participants at Donka Hospital and 57% (57/99) at Sanou Sourou Hospital were female. The majority of participants (48/98, 49% in both hospitals) fell within the age range of 25-50 years. High rates of illiteracy were observed (62/100, 62% in Donka Hospital and 59/100, 59% in Sanou Sourou Hospital). Smartphone ownership was prevalent (62/99, 62% at Donka Hospital and 64/100, 64% at Sanou Sourou Hospital). Participants reported occasional use of technology for basic purposes and frequent internet usage for accessing health information. However, a significant proportion of participants demonstrated low health literacy (73/99, 73% at Donka Hospital; 79/101, 78% at Sanou Sourou Hospital) and inadequate eHealth literacy (57/100, 57% at Donka Hospital; 62/100, 62% at Sanou Sourou Hospital). Education was observed to positively correlate with health literacy, while age displayed a moderate negative correlation. Weak correlations were observed between gender, income, and health literacy, but these were not statistically significant. No significant correlation was found between the scores of the BHLS and the eHEALS in either hospital. ConclusionsThis study highlights the importance of targeted educational interventions and mHealth solutions aimed at enhancing health and eHealth literacy among hospitalized patients with diabetes. Addressing both health literacy and eHealth literacy is paramount for improving diabetes management and treatment outcomes in Guinea and Burkina Faso. Targeted interventions and mHealth solutions have the potential to empower patients, enabling their active involvement in health care decisions and ultimately improving overall health outcomes.

M. Iqbal Rachmad Anwar, Diah Priyawati

Judging from daily activities, human beings heavily rely on the internet for communication purposes. and exchange information using either social media applications or browsers, vonsistently fast internet speeds are incredibly beneficial for performing tasks and activities, particularly for students and professionals. A sluggish internet connection can be frustrating and may lead to interruptions in online activities and tasks if it persists. Hence, this study examines a comparative evaluation of two approaches, Per Connection Classifier (PCC) and Equal Cost Multi-Path (ECMP) in Load Balancing through GNS3 simulation. Load balancing, as a method for evenly distributing traffic loads, and failover, as a backup mechanism when the main connection experiences problems. GNS3 is a graphical network simulator program that can transmit more complex network topologies compared to other simulators, for example Cisco Packet Tracer. The primary aim of this study is to comprehend how efficiently both techniques distribute traffic loads, maintaining smooth internet access, and increasing reliability. The PCC method produces better throughput, delay and jitter compared to the ECMP method, even though it has slightly different values for each QoS parameter. In testing traffic distribution, the PCC method outperforms the ECMP method. The PCC method can distribute traffic evenly across both ISP lines when downloading and uploading data packets. Meanwhile, the ECMP method can only carry out download and upload activities on one traffic path.

Zamam Hassan, Fawad Z.A. Khan, Adel S. Aldosary et al.

The process of urban growth often results in the conversion of agricultural spaces, including orchards. In Pakistan, Multan - widely known as the city of Mangoes - has seen exponential urban growth in the past couple of decades, resulting in a huge loss of Mango orchards to urban settlements. This research focuses on investigating local farmers’ motivations for selling Mango orchards to urban colonies and their perceived implications of transforming mango orchards into residential areas in Multan, Pakistan. By surveying 100 participants, the study captures insights into urban expansion trends, primary motivations behind selling agricultural land, and the social, economic and environmental consequences of such conversions. Descriptive statistics and correlation analysis (heatmap) are used to dissect the farmers perceptions on the drivers and implications of Mango orchards' conversion to housing settlements in Multan, Pakistan. Notably, 96% of respondents highlighted that orchards nearer to urban centers were predominantly targeted for conversion. Furthermore, 57% believed less productive orchards were more frequently turned into urban developments. Our correlation analysis provided clarity on the economic dimensions. Participants who felt their orchard was not a profitable venture tended to see greater economic advantages from selling their orchards. Interestingly, individuals motivated by a desire to 'improve quality of life' generally observed an improvement in their living conditions post-sale. On the environmental spectrum, concerns such as potential future temperature rises were consistently associated with several selling motivations, indicating a broad awareness of environmental consequences. This comprehensive research highlight the interplay of economic, social, and environmental factors in orchard-to-housing conversions, presenting valuable knowledge for urban development strategists and decision-makers.

Minin Vladislav, Zakharov Anton, Murzaev Evgeniy

Crop Rotation Experiment was established on experimental facilities of the Institute for Engineering and Environmental Problems in Agricultural Production – branch of Agro-Engineering Centre VIM, Saint-Petersburg. The objective of the study was to consider the requirements for growing organic potatoes. In an experiment with potatoes (Solánum tuberosum) variety Udacha, the influence of 3 factors was studied: the effect of organic fertilizers; action of bio-fungicide; row spacing depth. The compost studied was produced in the Institute from chicken manure using an aerobic fermentation unit. Doses of composts corresponded to 0; 80; 110, 160 kg N/ha. Potato tubers were treated with a bio-fungicide using a sprayer installed on a potato planter, and the leaves were treated during the growing season. Organic technology for cultivating potatoes was developed at the institute and used in experiment. The experiment has been equipped with automated tools for collecting information. Weather conditions differed from each other during the experiment. In 2021, conditions were dry during the potato development period. Weather conditions in 2020 and 2022 were similar. Monitoring shows that deep cultivation of row spacing contributed to better absorption of precipitation. This created more convenient conditions for potato development. Compost helped to increase the content of mineral forms of nitrogen in the soil. Due to high soil fertility, the yield of standard potato tubers in the variant without compost and bio-fungicide reached the level of 20.3 – 20.5 t ha-1 in 2020 and 2022 and 13.4 tha-1 in 2021, a dry year. Compost provided a significant increase in potato yield from 4 to 9 tha-1, depending on the dose of compost and year. The array of experimental data was generated for 2017-2022. After mathematical processing, the dependence of potato yield on the hydro-temperature coefficient in May and the dose of compost used was obtained.

Songhua Li, Lingjie Duan

In location-based social networks (LBSNs), users sense urban point-of-interest (PoI) information in the vicinity and share such information with friends in online social networks. Given users' limited social connections and severe lags in disseminating fresh PoI to all, major LBSNs aim to enhance users' social PoI sharing by selecting $k$ out of $m$ users as hotspots and broadcasting their fresh PoI information to the entire user community. This motivates us to study a new combinatorial optimization problem that involves the interplay between an urban sensing network and an online social network. We prove that this problem is NP-hard and also renders existing approximation solutions not viable. Through analyzing the interplay effects between the two networks, we successfully transform the involved PoI-sharing process across two networks to matrix computations for deriving a closed-form objective to hold desirable properties (e.g., submodularity and monotonicity). This finding enables us to develop a polynomial-time algorithm that guarantees a ($1-\frac{m-2}{m}(\frac{k-1}{k})^k$) approximation of the optimum. Furthermore, we allow each selected user to move around and sense more PoI information to share and propose an augmentation-adaptive algorithm with decent performance guarantees. Finally, our theoretical results are corroborated by our simulation findings using both synthetic and real-world datasets.

Debadutta Dash, Rahul Thapa, Juan M. Banda et al.

Despite growing interest in using large language models (LLMs) in healthcare, current explorations do not assess the real-world utility and safety of LLMs in clinical settings. Our objective was to determine whether two LLMs can serve information needs submitted by physicians as questions to an informatics consultation service in a safe and concordant manner. Sixty six questions from an informatics consult service were submitted to GPT-3.5 and GPT-4 via simple prompts. 12 physicians assessed the LLM responses' possibility of patient harm and concordance with existing reports from an informatics consultation service. Physician assessments were summarized based on majority vote. For no questions did a majority of physicians deem either LLM response as harmful. For GPT-3.5, responses to 8 questions were concordant with the informatics consult report, 20 discordant, and 9 were unable to be assessed. There were 29 responses with no majority on "Agree", "Disagree", and "Unable to assess". For GPT-4, responses to 13 questions were concordant, 15 discordant, and 3 were unable to be assessed. There were 35 responses with no majority. Responses from both LLMs were largely devoid of overt harm, but less than 20% of the responses agreed with an answer from an informatics consultation service, responses contained hallucinated references, and physicians were divided on what constitutes harm. These results suggest that while general purpose LLMs are able to provide safe and credible responses, they often do not meet the specific information need of a given question. A definitive evaluation of the usefulness of LLMs in healthcare settings will likely require additional research on prompt engineering, calibration, and custom-tailoring of general purpose models.

Mohamed Baqar , Bader Awedat

Oil production from reservoirs undergo three stages. They are primary, secondary and tertiary stages. In the tertiary (EOR) stage, several methods and technologies are used to increase or uphold recovery from existing fields. These methods often involve the injection of fluid(s) and recently microbes into a reservoir. The variety in principle for EOR methods suggests the need for proper selection, design, and implementation technique. One of the most used method for quick screening is considering the successful previous experiences from the methods that have been applied in other fields. In this paper, an EOR screening tool, named "EOR Azzaytuna Analysis", has been designed using visual basic studio. The database of the tool is based on the updated screening criteria by Al Adasani and Bai which was published in 2010. The published data from some oil fields which have already applied the EOR methods, were acquired. The tool screened these fields and the obtained results were compared with the already given one to confirm the success of the development of "EOR Azzaytuna Analysis" as a screen tool.

Theshani Nuradha, Ziv Goldfeld

Pufferfish privacy (PP) is a generalization of differential privacy (DP), that offers flexibility in specifying sensitive information and integrates domain knowledge into the privacy definition. Inspired by the illuminating formulation of DP in terms of mutual information due to Cuff and Yu, this work explores PP through the lens of information theory. We provide an information-theoretic formulation of PP, termed mutual information PP (MI PP), in terms of the conditional mutual information between the mechanism and the secret, given the public information. We show that MI PP is implied by the regular PP and characterize conditions under which the reverse implication is also true, recovering the relationship between DP and its information-theoretic variant as a special case. We establish convexity, composability, and post-processing properties for MI PP mechanisms and derive noise levels for the Gaussian and Laplace mechanisms. The obtained mechanisms are applicable under relaxed assumptions and provide improved noise levels in some regimes. Lastly, applications to auditing privacy frameworks, statistical inference tasks, and algorithm stability are explored.

Ali Arya, Luciara Nardon, Md Riyadh

This paper addresses the role of Information and Communication Technology (ICT) in migration governance, support, and experience with particular attention to emerging technologies such as artificial intelligence, social media, and virtual reality. We propose a framework for technology use based on user groups and process types. We provide examples of using emerging technologies for migration-related tasks within the context of this framework. We then identify how such technologies can be applied to migration-related tasks, developed for customized use, and improved through research to add new features that can help different migration stakeholders. We suggest a series of possible directions for future research and development to take advantage of specific affordances of those emerging technologies more effectively.

Jiang Zhao, Han Liu, Jiaming Sun et al.

Uncertainty of target motion, limited perception ability of onboard cameras, and constrained control have brought new challenges to unmanned aerial vehicle (UAV) dynamic target tracking control. In virtue of the powerful fitting ability and learning ability of the neural network, this paper proposes a new deep reinforcement learning (DRL)-based end-to-end control method for UAV dynamic target tracking. Firstly, a DRL-based framework using onboard camera image is established, which simplifies the traditional modularization paradigm. Secondly, neural network architecture, reward functions, and soft actor-critic (SAC)-based speed command perception algorithm are designed to train the policy network. The output of the policy network is denormalized and directly used as speed control command, which realizes the UAV dynamic target tracking. Finally, the feasibility of the proposed end-to-end control method is demonstrated by numerical simulation. The results show that the proposed DRL-based framework is feasible to simplify the traditional modularization paradigm. The UAV can track the dynamic target with rapidly changing of speed and direction.

Keju Lu, Fahui Wu, Lin Xiao et al.

In this paper, an Unmanned Aerial Vehicle (UAV)-enabled two-way relay system with Physical-layer Network Coding (PNC) protocol is considered. A rotary-wing UAV is applied as a mobile relay to assist two ground terminals for information interaction. Our goal is to maximize the sum-rate of the two-way relay system subject to mobility constraints, propulsion power consumption constraints, and transmit power constraints. The formulated problem is not easy to solve directly because it is a mixed integer non-convex optimization problem. Therefore, we decompose it into three sub-problems, and use the mutation arithmetic of the Genetic Algorithm (GA) and Successive Convex Approximation (SCA) to dispose. Besides, a high-efficiency iterative algorithm is proposed to obtain a locally optimal solution by jointly optimizing the time slot pairing, the transmit power allocation, and the UAV trajectory design. Numerical results demonstrate that the proposed design achieves significant gains over the benchmark designs.

XiaoLi Jin, Yang Li, Yayang Yang et al.

Abstract Background Osteoclast cell increase is a major risk factor for osteoporosis and degenerative bone and joint diseases. At present, RANKL and M-CSF are commonly used to induce osteoclastogenesis. Thioacetamide (TAA) can lead to many types of liver and kidney damage, but less attention has been paid to the association of TAA with bone damage. In this work, we investigated the effects of TAA on the osteoclastogenesis and differentiation of bone marrow macrophages (BMMs). Methods BMMs of SD rat suckling mice were taken for primary culture. CCK-8 was used to detect the toxic effects of TAA on BMMs, and flow cytometry was used to detect the effects of TAA on the cell cycle, cell viability, apoptosis and intracytoplasmic Ca2+ concentration of BMMs. TRAP staining was used to detect the effect of RANKL and M-CSF and TAA on osteoclast differentiation of BMMs. Western Blot was used to detect the expression level of PI3K/AKT pathway and osteoclast-specific proteins (TRAP and cathepsin K). Results The results suggested that TAA inhibited the proliferation of BMMs, while enhancing osteoclastogenesis at 0.5 mg/mL and 1 mg/mL as assayed by TRAP staining. Exposed to TAA, BMMs could differentiate into osteoclast-like cells with overexpression of cathepsin K and TRAP proteins. Western blot results showed that TAA can activate the expression levels of P-PI3K, P-AKT, P-P38, and P-JNK, accompanied by apoptosis of BMMs and increase in intracellular Ca2+. Conclusion TAA may induce osteoclast formation in BMMs by activating the expression of PI3K/AKT pathway proteins, which is comparable to the classic osteoclast differentiation inducer RANKL and M-CSF. This suggests that we may find a cheap osteoclast inducer.

Svitlana Vakulenko, Evangelos Kanoulas, Maarten de Rijke

Conversational search is a relatively young area of research that aims at automating an information-seeking dialogue. In this paper we help to position it with respect to other research areas within conversational Artificial Intelligence (AI) by analysing the structural properties of an information-seeking dialogue. To this end, we perform a large-scale dialogue analysis of more than 150K transcripts from 16 publicly available dialogue datasets. These datasets were collected to inform different dialogue-based tasks including conversational search. We extract different patterns of mixed initiative from these dialogue transcripts and use them to compare dialogues of different types. Moreover, we contrast the patterns found in information-seeking dialogues that are being used for research purposes with the patterns found in virtual reference interviews that were conducted by professional librarians. The insights we provide (1) establish close relations between conversational search and other conversational AI tasks; and (2) uncover limitations of existing conversational datasets to inform future data collection tasks.

Ali Mobini-Dehkordi, Jahangir Yadolai-Farsi, Abolghasem Arabiun et al.

Introduction: Parallel with the growth of technologies, which affect the telemedicine, timely identification of telemedicine entrepreneurial opportunities seems to be necessary for the product development. This study aimed to identify applied aspects, medical fields, and technological trends in developing future entrepreneurial opportunities in telemedicine. Methods: A three-step framework for identifying future entrepreneurial opportunities was employed as a trend analysis method to identify telemedicine technological trends and the cross impact analysis to predict future strategic trends in the field. This was done by completing the 9*9 matrix in a panel of 5 experts in this field, and reviewing 109 articles in the Scopus database with keyword search (Telemedicine and Opportunity) to identify practical aspects and future of telemedicine opportunities. Results: In the first step, 9 technological trends affecting the future of telemedicine were identified. In the second step, the technological trends of artificial intelligence along with the Internet of Things were identified as effective trends; wearable technologies and cloud computing were identified as strategic trends. In the final step, it was revealed that practical aspects (i.e., prevention, diagnosis, treatment and healthy living), as well as psychology and psychiatry, education, information acquisition, nutrition, and cardiology, shape a great majority of opportunities for telemedicine in the next 5 years. Conclusion: To develop a successful new product in telemedicine, a three-dimensional framework (applied aspects, fields of medicine, and technology) should be considered; therefore, establishing cooperation between technology development companies and health companies seems to be necessary.

Qi Zhao, Qi Zhao, Qi Zhao et al.

The capture and storage of carbon dioxide (CO2) are urgent and crucial to achieve the goal of carbon neutrality. Hydrate-based CO2 capture technology is one of the promising technologies for capturing and storing CO2. This work studied the nucleation and growth of CO2 hydrate provoked by direct current–voltage accompanied by charge flow with the agitation of 450 rpm at an initial pressure of 3.5 MPa and a temperature of 274.15 K. The results show that the physical bubble behavior and electrochemistry mechanisms could influence CO2 hydrate formation process in the application of voltage. The induction time and semi-completion time of CO2 hydrate formation were decreased by 51% and 27.8% in the presence of 15 V, respectively. However, more product of electrolysis, Joule heat and ions, could inhibit the CO2 hydrate formation process in the application of a high voltage (60 V). In addition, a high voltage (60 V) could change the morphology characteristics of CO2 hydrate from gel-like to whisker-like. This study provides valuable information on the formation of CO2 hydrate under the action of charge flow.

Hong Jiang, WenJie Yang, QingFang Sun et al.

The adverse effects of hypercortisolism on the human brain have been highlighted in previous studies of Cushing’s disease (CD). However, the relative alterations in regional hypercortisolism in the brain remain unclear. Thus, we investigated regional volumetric alterations in CD patients. We also analyzed the associations between these volumetric changes and clinical characteristics. The study participants comprised of active CD (n = 60), short-term-remitted CD (n = 28), and long-term-remitted CD (n = 32) patients as well as healthy control subjects (n = 66). Gray matter volumes (GMVs) were measured via voxel-based morphometry. The GMVs of substructures were defined using the automated anatomical labeling (AAL) atlas. Trends toward normalization in GMV were found in most brain substructures of CD patients. Different trends, including enlarged, irreversible, and unaffected, were observed in the other subregions, such as the a mygdala, thalamus, and caudate. Morphological changes in GMVs after the resolution of hypercortisolism are a complex phenomenon; the characteristics of these changes signifi cantly differ within the brain substructures.