Hasil untuk "Information technology"

Jue Ning, Xu Chen, Tao Wang et al.

Abstract The modulation of anticyclonic subsurface‐intensified mode‐water eddies (MWEs) on the oceanic physical and biological responses to tropical cyclones (TCs) is investigated using satellite measurements, in situ observations and numerical model outputs. Extreme cooling of the surface (4.2°C) and mixed‐layer (2.3°C) is observed in a MWE, which can be remarkably stronger than those in adjacent cyclonic eddy and non‐eddy environments. The special thermodynamic structure above the lens of MWEs, which would favor the TC‐induced entrainment more efficiently, facilitates the elevation of substantial subsurface cold water. It also leads to increased mixed‐layer salinity and deepening of the mixed‐layer. Additionally, variations in nitrate and chlorophyll‐a concentrations appear to be depressed and exhibit intricate multi‐layer patterns due to TC‐induced and MWE‐influenced vertical processes. This study provides novel insights into the interactions between TCs and subsurface‐intensified eddies.

Eric Lyimo, Neema B. Kulaya, Lembris Njotto et al.

Abstract Background Malaria, which affects over half of the world’s population, is controlled through clinical interventions and vector control strategies. However, these efforts are threatened by resistance to anti-malarial drugs and insecticides, as well as affected by environmental, ecological, and climatic changes. This study examined changes in malaria prevalence and related factors based on data from 18 cross-sectional surveys conducted in two villages in northeastern Tanzania. Methods From 2003 to 2021, annual cross-sectional malariometric surveys were conducted in two study villages, Mkokola (lowland) and Kwamasimba (highland), samples collected to determine Plasmodium falciparum infection and human exposure to malaria vector Anopheles. Pearson's chi-squared test was used for comparing proportions, logistic and linear regressions test were used analyse associations. Generalized Estimating Equations (GEE) was used to analyse the relationship between malaria prevalence and climatic variables. Results Malaria prevalence in Kwamasimba and Mkokola dropped from ~ 25% and ~ 80% to 0% and 1%, respectively, between 2003 and 2011, reaching 0% in both villages by 2014. This decline was associated with increased bed net use and reduced exposure to Anopheles bites. However, between 2018 and 2021, prevalence resurged, with Kwamasimba reaching 2003–2004 levels despite high bed net use. Between 2003 and 2021 there was an increasing trend in average monthly maximum temperatures (R2 = 0.1253 and 0.2005), and precipitation (R2 = 0.125 and 0.110) as well as minimum relative humidity (R2 = 0.141 and 0.1162) in Kwamasimba and Mkokola villages, respectively, while maximum relative humidity slightly decreased. Furthermore, during 2003–2011, malaria prevalence was positively associated with temperature, maximum temperature, and relative humidity, while precipitation showed a negative association (Estimate:− 0.0005, p < 0.001). Between 2012–2021, all climatic factors, including temperature (Estimate: 0.0256, p < 0.001), maximum temperature (Estimate: 0.0121, p < 0.001), relative humidity (Estimate: 0.00829, p < 0.001), and precipitation (Estimate: 0.000105, p < 0.001), showed positive associations. Conclusion From 2003 to 2014, malaria prevalence declined in two Tanzanian villages but resurged after 2018, particularly in highland Kwamasimba. Most likely, vector dynamics affected by changing climatic conditions drove this resurgence, emphasizing the need for adaptive, climate-informed malaria control strategies.

Atta Ur Rahman, Yousef Alsenani, Adeel Zafar et al.

Abstract Cardiovascular diseases (CVDs) continue to be the leading cause of more than 17 million mortalities worldwide. The early detection of heart failure with high accuracy is crucial for clinical trials and therapy. Patients will be categorized into various types of heart disease based on characteristics like blood pressure, cholesterol levels, heart rate, and other characteristics. With the use of an automatic system, we can provide early diagnoses for those who are prone to heart failure by analyzing their characteristics. In this work, we deploy a novel self-attention-based transformer model, that combines self-attention mechanisms and transformer networks to predict CVD risk. The self-attention layers capture contextual information and generate representations that effectively model complex patterns in the data. Self-attention mechanisms provide interpretability by giving each component of the input sequence a certain amount of attention weight. This includes adjusting the input and output layers, incorporating more layers, and modifying the attention processes to collect relevant information. This also makes it possible for physicians to comprehend which features of the data contributed to the model's predictions. The proposed model is tested on the Cleveland dataset, a benchmark dataset of the University of California Irvine (UCI) machine learning (ML) repository. Comparing the proposed model to several baseline approaches, we achieved the highest accuracy of 96.51%. Furthermore, the outcomes of our experiments demonstrate that the prediction rate of our model is higher than that of other cutting-edge approaches used for heart disease prediction.

S. Gaßner, S. Gaßner, S. Essing et al.

<p>The measurement of air quality, particularly the concentration of carbon dioxide (CO<span class="inline-formula">₂</span>), has gained significant interest due to increased public health awareness. Elevated concentrations of CO<span class="inline-formula">₂</span> in the air have been linked to negative effects on cognitive functions and directly correlate with the quality of indoor air. This work presents the prototype of a miniaturized sensor module designed for sensing CO<span class="inline-formula">₂</span> concentrations in the air. The sensor module utilizes the two-chamber photoacoustic concept and features a compact design combining an absorption cell with a wafer-bonded detector based on silicon MEMS (micro-electro-mechanical systems) microphone technology. The CO<span class="inline-formula">₂</span>-filled detector chip uses the photoacoustic effect and is able to detect pressure oscillations within an enclosed volume generated by the absorption of modulated infrared (IR) light by CO<span class="inline-formula">₂</span> molecules. The complete sensor module measures only <span class="inline-formula"><math xmlns="http://www.w3.org/1998/Math/MathML" id="M8" display="inline" overflow="scroll" dspmath="mathml"><mrow><mn mathvariant="normal">9</mn><mo>×</mo><mn mathvariant="normal">13</mn><mo>×</mo><mn mathvariant="normal">7.8</mn></mrow></math><span><svg:svg xmlns:svg="http://www.w3.org/2000/svg" width="58pt" height="10pt" class="svg-formula" dspmath="mathimg" md5hash="4ef0f2c465de24f9712df844104d42f9"><svg:image xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="jsss-13-219-2024-ie00001.svg" width="58pt" height="10pt" src="jsss-13-219-2024-ie00001.png"/></svg:svg></span></span> mm<span class="inline-formula">³</span> and the used detector chip is the smallest detector for two-chamber photoacoustic sensors reported to date. Experimental characterization showed that the prototype achieves a detection limit of 81 ppm CO<span class="inline-formula">₂</span> and exhibits a response time <span class="inline-formula"><i>τ</i>₆₃</span> of 53 s. The compact size and performance characteristics make the proposed sensor module suitable for applications in indoor air quality monitoring.</p>

Alzubaidi Laith H., Thakur Gaurav, G Vijayalakshmi et al.

This review explores Peer-to-Peer (P2P) Energy Trading Platforms in Local Energy Markets, drawing insights from three key studies. These markets, using P2P trading, efficiently distribute electricity within communities. Research assesses P2P trading’s impact in a Norwegian neighbourhood, comparing it to scenarios without local markets. It also examines integrating PV systems, batteries, and electric vehicles on grid operations. Findings reveal minimal grid impacts with PVs alone, but adding batteries increases voltage fluctuations and losses. However, P2P trading benefits end-users with cost savings and supports Distribution System Operator operations. The paper surveys global P2P energy trading projects, emphasising communication and control networks within local Microgrids. It discusses the transition from passive consumers to prosumers in power networks and introduces the concept of a federated power plant, combining virtual power plants and P2P transactions among prosumers to address challenges and unlock additional value. This review fills research gaps, shedding light on P2P energy trading’s multifaceted aspects in local markets and its transformative potential for the energy sector.

Teti Ratnawulan, Ricky Yoseptry, Iis Kusmiati et al.

The background of this research is based on the need to understand the influence and implications of utilizing Information and Communication Technology (ICT) in the learning processes of 10th-grade students at SMAN 1 Banjaran. The implementation of technology in the educational context has become an integral part of enhancing learning quality and influencing students' motivation to learn. A qualitative method was employed. Data were gathered in the field through in-depth, structured interviews, and from literature sources. Findings from the literature review and field study are presented as research outcomes. The presented data are then abstracted with the objective of showcasing facts. In the subsequent stage, this data is interpreted to produce information or knowledge. The study concludes that the use of ICT at SMAN 1 Banjaran, especially by 10th-grade students, has a significant impact on the learning context. Although the majority of students actively use the internet for learning, challenges such as unstable connections and inadequate devices remain barriers. The majority of students show good learning motivation, but there is a small group that is less motivated, emphasizing the importance of a more inclusive learning approach. Nonetheless, the use of technology contributes positively to student engagement. Despite challenges such as access difficulties and technological limitations, more effective utilization of ICT is expected to enhance the overall learning motivation of students at SMAN 1 Banjaran

Jisung Jo, Jayson L. Lusk

Although previous research has identified that consumers are willing to pay for traceability, it remains unknown which types of traceability information might have the highest value, and whether consumers have an intrinsic value for blockchain technology above and beyond the instrumental value of providing traceability. A choice experiment was conducted with over 1500 consumers in Hong Kong, South Korea, and the U.S. In all three countries, consumers were willing to pay premiums for beef with traceability related to all parts of the supply chain, country of origin, and temperature history; however, the preference ordering of beef from different countries varied across Hong Kong, South Korea, and the U.S. The intrinsic value of using blockchain to deliver traceability information differed by country and by attribute, and consumers in the U.S. were most sensitive to the information describing blockchain technology. Even when traceability conveys negative information, such as temperature rising above safe levels for a short period, we find that consumers prefer knowing to not knowing, suggesting uncertainty and ambiguity aversion.

Guojie Xie, Lijuan Huang, Hou Bin et al.

The digital divide between urban and rural communities has substantially narrowed as information and communication technology has evolved, enabling increasingly more interactions between urban and rural areas. Rural areas now have the foundation and conditions to take advantage of e-commerce opportunities, which is no longer exclusively a city-centric economic mode. Taking advantage of the Internet’s vast resources, many villagers jumped at the opportunity to launch rural e-commerce businesses. Rural inhabitants, however, face several challenges when it comes to starting their own e-commerce enterprises. Meanwhile, local governments and rural e-commerce platform providers, find it difficult to provide accurate help to practitioners and entrepreneurs. To this end, a system of indicators based on a model of entrepreneurial events was developed to identify e-commerce entrepreneurs. And the main objective of this paper is to explore the factors influencing the abilities and expectations of rural residents to set up their own e-commerce businesses in order to provide them with tailored support. Survey data from 162 rural e-commerce practitioners were analyzed using a deep neural network in R. The results reveal that the index system developed in this paper has a good level of reliability and validity, and the prediction approach has a high degree of precision (over 90%), indicating that it can successfully identify rural e-commerce entrepreneurs. Based on the findings of this study, we recommend that local governments and e-commerce businesses work together to address the practical issues of perceived feasibility and desirability for rural e-commerce practitioners. Residents in rural areas who want to start their own businesses can take advantage of the development opportunities provided by the information and communication technology, while local governments should keep up with the speed of digitization and informatization to better manage rural economic growth.

Sonja Klingberg, Molebogeng Motlhatlhedi, Gugulethu Mabena et al.

Participatory and digital health approaches have the potential to create solutions to health issues and related inequalities. A project called Co-Designing Community-based ICTs Interventions for Maternal and Child Health in South Africa (CoMaCH) is exploring such solutions in four different sites across South Africa. The present study captures initial qualitative research that was carried out in one of the urban research sites in Soweto. The aim was twofold: 1) to develop a situation analysis of existing services and the practices and preferences of intended end-users, and 2) to explore barriers and facilitators to utilising digital health for community-based solutions to maternal and child health from multiple perspectives. Semi-structured interviews were conducted with 28 participants, including mothers, other caregivers and community health workers. Four themes were developed using a framework method approach to thematic analysis: coping as a parent is a priority; existing services and initiatives lack consistency, coverage and effective communication; the promise of technology is limited by cost, accessibility and crime; and, information is key but difficult to navigate. Solutions proposed by participants included various digital-based and non-digital channels for accessing reliable health information or education; community engagement events and social support; and, community organisations and initiatives such as saving schemes or community gardens. This initial qualitative study informs later co-design phases, and raises ethical and practical questions about participatory intervention development, including the flexibility of researcher-driven endeavours to accommodate community views, and the limits of digital health solutions vis-à-vis material needs and structural barriers to health and wellbeing.

Kui-Ching Hsu, Mu-Rong Yi, Mu-Rong Yi et al.

Sequences of the complete mitochondrial cytochrome oxidase subunit I gene were used to identify Trichiurus species and examine their population genetic structure and demographic history along the coast of China. Three Trichiurus species were found. Trichiurus japonicus lives in colder waters along the continental shelves in the China Seas, while Trichiurus nanhaiensis lives warmer waters along continental slopes in the South China Sea, and Trichiurus brevis lives in shallow and warmer waters in the South China Sea. The migrations of these species were mainly associated with feeding and spawning preferences. Two major wintering and spawning grounds in the East China Sea and South China Sea were found. All species showed a lack of population genetic structure resulting from their oceanodromous life cycle (the degree of population substructure index NST = 0.000–0.149), but the results of approximate Bayesian computational approaches suggested population declines or stabilization and differentiation. The results of the TMRCA (time to the most recent common ancestor) showed that during glaciations, the Yellow Sea and the East China Sea were completely exposed, and the South China Sea acted as a refugium. Thus, the populations of these three species experienced differentiation during glaciations. This study also examined the limitations of Bayesian skyline plot analysis.

Ming Yan, Jianxi Yang, Cen Chen et al.

Abstract Deep neural networks have achieved great success in both computer vision and natural language processing tasks. How to improve the gradient flows is crucial in training very deep neural networks. To address this challenge, a gradient enhancement approach is proposed through constructing the short circuit neural connections. The proposed short circuit is a unidirectional neural connection that back propagates the sensitivities rather than gradients in neural networks from the deep layers to the shallow layers. Moreover, the short circuit is further formulated as a gradient truncation operation in its connecting layers, which can be plugged into the backbone models without introducing extra training parameters. Extensive experiments demonstrate that the deep neural networks, with the help of short circuit connection, gain a large margin of improvement over the baselines on both computer vision and natural language processing tasks. The work provides the promising solution to the low‐resource scenarios, such as, intelligence transport systems of computer vision, question answering of natural language processing.

Lorenzo Patera, Andrea Garbugli, Armir Bujari et al.

We are still in the midst of Industry 4.0 (I4.0), with more manufacturing lines being labeled as smart thanks to the integration of advanced ICT in Cyber–Physical Systems (CPS). While I4.0 aims to provision cognitive CPS systems, the nascent Industry 5.0 (I5.0) era goes a step beyond, aiming to build cross-border, sustainable, and circular value chains benefiting society as a whole. An enabler of this vision is the integration of data and AI in the industrial decision-making process, which does not exhibit yet a coordination between the Operation and Information Technology domains (OT/IT). This work proposes an architectural approach and an accompanying software prototype addressing the OT/IT convergence problem. The approach is based on a two-layered middleware solution, where each layer aims to better serve the specific differentiated requirements of the OT and IT layers. The proposal is validated in a real testbed, employing actual machine data, showing the capacity of the components to gracefully scale and serve increasing data volumes.

Sai Zhang, Zicheng Li, Hou‐Neng Wang et al.

Abstract A fractional order sliding mode control (FOSMC) based on single parameter adaptive law for nano‐positioning of Piezoelectric Actuators (PEAs) is proposed. First, the Bouc–Wen (B–W) model is used to describe the hysteresis of the nano‐position platform based on PEAs, which provides a mathematical model for the subsequent controller design. Then, theoretical support is provided to design the FOSMC based on adaptive law of different parameters, which are proposed for the displacement tracking problem of PEAs, and the position error convergence is also proved. Moreover, the core parameters of FOSMC based on single parameter adaptive law are identified by hybrid differential evolution (HDE) and adaptive differential evolution (ADE), which require considering the relationship between the scaling factor and the cross‐probability factor. Finally, experiments have been conducted with the displacement signals mixed with multiple frequencies and multiple amplitudes and the results obtained from them show that the proposed control scheme can produce a faster response and smaller tracking errors in PEAs system as compared to traditional control algorithms.

Sharaf Alhomdy, Fursan Thabit, Fua'ad Hasan Abdulrazzak et al.

The contagion of the Coronavirus (COVID-19) led to a global lockdown that put governments in emergency mode. With the total number of positive cases worldwide exceeding the 97.46 million mark, social distancing appears to be the only effective strategy to contain the virus at the moment. As a result, companies face obstacles and find it difficult to respond to this current challenge of remote working. The impact of the novel COVID-19 has created many new challenges, and many of us have had to adopt new ways of working. With the need for accessing to critical applications and the scalability of the infrastructure, cloud computing is emerging as an underlying technology. The cloud technology had a major role in fighting the epidemic; it becomes a salvation for governments and organizations in numerous fields of life, education, health, industry, communication, remote surveillance, and more information. Therefore, this study presents the benefits, characteristics and applications of cloud computing and explains how the cloud contributes to improving life in all regions of the world during COVID-19. It shows that the cloud computing helps countries in combating COVID 19, in education and health sectors, also in the economic and commercial aspects. It investigates the current state by distributing an online questionnaire to various people of academic and non-academic backgrounds in different places over the world in the ICT and education sectors. The results showed that there is an effective role for cloud computing during the epidemic.

Wijanarto Wijanarto, Seviana Pungki Brilianti

Penggunaan mobile banking meningkat seiring dengan kemajuan teknologi. Hampir setiap bank di Indonesia memiliki layanan mobile banking, termasuk BNI. Menurut survei dari Top Brand Award, BNI Mobile Banking menurun menjadi nomor 4 pada tahun 2016 dan 2017. Artinya terdapat relasi yang kuat antara ulasan pemakai aplikasi terhadap kinerja aplikasi. Dengan demikian membawa akibat pada pentingnya mempertahankan kualitas layanan serta kemampuan untuk bersaing dengan bank lain. Beberapa penelitian analisis sentimen sebelumnya belum melihat ketersediaan apakah dataset sudah dieksplorasi keseimbangannya atau tidak untuk meningkatkan performa model yang dipilih. Oleh karena itu, dalam artikel ini mencoba melakukan analisis sentimen pada ulasan pengguna aplikasi BNI Mobile Banking di Google Play sebanyak 6954 data terpilih dengan label positif dan negatif dan menggunakan 7 metode dasar sebagai baseline untuk dipilih satu yang mempunyai performa terbaik yitu Support Vector Classifier, setelah dilakukan resampling dataset dengan Repeated Edited Nearest Neighbours dan hyperparameter model C=1, degree=2 kernel poly didapatkan akurasi sebesar 98.54% pada data training dan akurasi 100% pada data uji. Selanjutnya dari 26 data mentah baru dilakukan eksperimen dan menghasilkan prediksi benar sebesar 19 sementara 7 salah dengan error rate sebesar 27%.

Takahira S., Sogabe T., Usuda T.S.

In this paper,we present the bidiagonalization of n-by-n (k, k+1)-tridiagonal matriceswhen n < 2k. Moreover,we show that the determinant of an n-by-n (k, k+1)-tridiagonal matrix is the product of the diagonal elements and the eigenvalues of the matrix are the diagonal elements. This paper is related to the fast block diagonalization algorithm using the permutation matrix from [T. Sogabe and M. El-Mikkawy, Appl. Math. Comput., 218, (2011), 2740-2743] and [A. Ohashi, T. Sogabe, and T. S. Usuda, Int. J. Pure and App. Math., 106, (2016), 513-523].

Generosa Lukhayu Pritalia

Dalam sebuah perusahaan e-commerce, stok barang merupakan salah satu faktor penting yang harus diperhatikan oleh perusahaan. Jumlah barang masuk maupun keluar perlu diperhatikan, tujuannya untuk menjaga stok yang tersedia dalam gudang menjadi stabil. Stok stabil yang dimaksud dalam gudang adalah barang tidak kelebihan stok maupun barang tidak kehabisan stok. Permasalahan yang dihadapi pada penjualan barang adalah setiap barang memiliki minat beli yang berbeda-beda. Barang dengan minat beli yang tinggi akan cepat habis dibandingkan dengan barang yang memiliki minat beli rendah. Untuk itu, stok barang perlu ditambah pada waktu stok barang menipis. Algoritma C4.5 merupakan kelompok algoritma dengan menggunakan pohon keputusan. Pohon keputusan merupakan metode klasifikasi dan prediksi yang sangat kuat dan terkenal. Semakin kaya informasi atau pengetahuan yang dikandung oleh data training, maka akurasi akan semakin meningkat. Algoritma ini digunakan untuk menganalisis waktu pembelian stok barang yang sudah menipis dengan mengklasifikasi barang mana yang sudah waktunya di tambah stok maupun belum, sehingga ketersediaan barang tetap stabil dan terjaga. Hasil dari analisis menggunakan algoritma C4.5 adalah untuk menentukan waktu penentuan ketersediaan barang memiliki tingkat keakuratan sebesar 98.9%.

Xun Li, Zhengfan Zhao, Li Liu et al.

We proposed a signal control optimization model for urban main trunk line intersections. Four-phase intersection was analyzed and modeled based on the Cell Transmission Model (CTM). CTM and signal control model in our study had both been improved for multi-intersections by three-phase theory and information-exchanging. To achieve a real-time application, an improved genetic algorithm (GA) was proposed finally, the DISCO traffic simulation software was used for numerical simulation experiment, and comparisons with the standard GA and CTM were reported in this paper. Experimental results indicate that our searching time is less than that of SGA by 38%, and our method needs only 1/3 iteration time of SGA. According to our DISCO traffic simulation processing, compared with SGA, if the input traffic flow is changed from free phase to synchronized phase, for example, less than 900 vel/h, the delay time can reduce to 87.99% by our method, and the minimum delay time is 77.76% of existing method. Furthermore, if input traffic volume is increased to 1200 vel/h or more at the synchronized phase, the summary and minimum values of average delay time are reduced to 81.16% and 75.83%, respectively, and the average delay time is reduced to 17.72 seconds.

P. Alpar, Moshe Kim

M. Bensaou, N. Venkatraman