Unstable Network Research Articles

Digital Transformation in Higher Education System: Learning Technologies at Open University of Mataram

The proliferation of technology has significantly impacted learning development. This study aimed to investigate the effectiveness of learning technologies based on students’ perspectives and to discover the challenges encountered when using technologies. In conducting a qualitative case study, the researcher collected data using an open-ended questionnaire at the Open University of Mataram. The data from six informants were analyzed by using the thematic analysis technique. The analysis procedures were based on Kawulich's (2004), which encompassed narrative, coding, interpretation, confirmation, and presentation. The result showed that the students found technology in their learning was effective primarily in creating attractive, practical, and accessible learning experiences, promoting flexible learning and independent learners, and enriching and deepening understanding. Meanwhile, three main challenges were identified: an unstable network, social media, environmental distraction, and a lack of technological competence among students. This study recommends researching teachers’ perspectives on digital transformation for further studies

Project-based learning: Does it improve students’ ICT literacy skills and English learning autonomy?

This study aims to investigate and disclose the integration of project-based learning in promoting high school students' ICT literacy and English learning autonomy in Ruteng, Indonesia. This study surveyed 595 students from six senior high schools in Ruteng City. The questionnaire and interview served as the primary instruments for data collection, followed by quantitative and qualitative examination of the results using Jeffreys' Amazing Statistics Program. The results of the study indicate that the level of ICT literacy among the students falls in the medium category (3.5), and English learning autonomy was included in the medium category (3.32). Sixteen statements of ICT literacy competence indicated the category of ICT literacy competence, while ten items indicated English learning autonomy. In addition, five factors challenged the respondents' achievement of ICT literacy, namely, lack of enthusiasm and initiative of students regarding digital media literacy (61.59%), lack of cost of purchasing Internet data packages (71.20%), insufficient time allocated for using specific English learning software (59.48%), unstable Internet network connectivity (58.27%), and lack of available ICT infrastructure in schools (58.33%). Various issues hinder the level at which students could acquire ICT skills, and stakeholders are encouraged to address or overcome these obstacles.

Unpaired Image-to-Image Translation with Diffusion Adversarial Network

Unpaired image translation with feature-level constraints presents significant challenges, including unstable network training and low diversity in generated tasks. This limitation is typically attributed to the following situations: 1. The generated images are overly simplistic, which fails to stimulate the network’s capacity for generating diverse and imaginative outputs. 2. The images produced are distorted, a direct consequence of unstable training conditions. To address this limitation, the unpaired image-to-image translation with diffusion adversarial network (UNDAN) is proposed. Specifically, our model consists of two modules: (1) Feature fusion module: In this module, one-dimensional SVD features are transformed into two-dimensional SVD features using the convolutional two-dimensionalization method, enhancing the diversity of the images generated by the network. (2) Network convergence module: In this module, the generator transitions from the U-net model to a superior diffusion model. This shift leverages the stability of the diffusion model to mitigate the mode collapse issues commonly associated with adversarial network training. In summary, the CycleGAN framework is utilized to achieve unpaired image translation through the application of cycle-consistent loss. Finally, the proposed network was verified from both qualitative and quantitative aspects. The experiments show that the method proposed can generate more realistic converted images.

Feasibility of Employing mHealth in Delivering Preventive Nutrition Interventions Targeting the First 1000 Days of Life: Experiences from a Community-Based Cluster Randomised Trial in Rural Bangladesh.

An Android platform-based customised app and web-linked system was developed to aid in implementing selected nutrition interventions by community health workers (CHWs) in a community-based cluster randomised trial (c-RCT) in rural Bangladesh. Here, we describe the architecture of the intervention delivery system, and explore feasibility of employing mHealth as CHWs' job aid, employing a mixed-method study design covering 17 visits per mother-child dyad. We analysed CHWs' real-time visit information from monitoring and documentation data, and CHWs' qualitative interviews to explore the advantages and barriers of using mHealth as a job aid. Intervention coverage was high across the arms (>90%), except around the narrow perinatal period (51%) due to mothers' cultural practice of moving to their parents' homes and/or hospitals for childbirth. CHWs mentioned technical and functional advantages of the job aid including device portability, easy navigability of content, pictorial demonstration that improved communication, easy information entry, and automated daily scheduling of tasks. Technical challenges included charging tablets, especially in power cut-prone areas, deteriorated battery capacity over continuous device usage, unstable internet network in unsupportive weather conditions, and device safety. Nevertheless, onsite supervision and monitoring by expert supervisors remained important to ensure intervention quality. With appropriate training and supervision, CHWs utilised the tablet-based app proficiently, attaining high coverage of long-term visits. mHealth was thus useful for designing, planning, scheduling, and delivering nutrition interventions through CHWs, and for monitoring and supervision by supervisors. Therefore, this application and job aid can be adopted or replicated into the currently developing national health systems platform for improving coverage and quality of preventive maternal and child nutrition services. In addition, continuous supportive supervision by skilled supervisors must be accompanied to ensure CHWs' task quality. Finally, future studies should rigorously assess undesirable health and environmental effects of mHealth before and after mainstreaming, effective interventions addressing device-induced health hazards should be designed and scaled up, and effective e-waste management must be ensured.

Low-Contact Impedance Textile Electrode for Real-Time Detection of ECG Signals.

The quality of the electrocardiography (ECG) signals depends on the effectiveness of the electrode-skin connection. However, current electrocardiogram electrodes (ECGE) often face challenges such as high contact impedance and unstable conductive networks, which hinder accurate measurement during movement and long-term wearability. Herein, in this work, a bionic 3D pile textile as an ECGE with high electrical conductivity and flexibility is prepared by a facile, continuous, and high-efficiency electrostatic self-assembly process. Integrating pile textiles with conductive materials creates a full textile electrode for bioelectrical signal detection that can retain both the inherent characteristics of textiles and high conductivity. Moreover, the dense piles on the textile surface make full contact with the skin, mitigating motion artifacts caused by the sliding between the textile and the skin. The continuous conductive network formed by the interconnected piles allows the pile textile ECGE (PT-ECGE) to function effectively under both static and dynamic conditions. Leveraging the unique pile structure, the PT-ECGE achieves superior flexibility, improved conductivity, low contact impedance, and high adaptivity, washability, and durability. The textile electrode, as a promising candidate for wearable devices, offers enormous application possibilities for the unconscious and comfortable detection of physiological signals.

Managing a Resilient Multitier Architecture for Unstable IoT Networks in Location Based-Services

Managing a Resilient Multitier Architecture for Unstable IoT Networks in Location Based-Services

Efektivitas Konvergensi Program Intervensi Percepatan Penurunan Stunting di Tingkat Keluarga

This study aims to analyze the effectiveness of the convergence of intervention programs to accelerate the reduction of stunting at the family level in Serang District, Banten Province. Analytic quantitative design and interviews, with a sample of 150 respondents. Data collection technique with systematic random sampling. Data collection with secondary data, interviews and filling out questionnaires. There were 9 people (6 percent) inaccurate identification of families at risk of stunting (KRS) in the TPPS documents and verification by researchers. Inaccurate identification of families at risk of stunting who were included in the target of the intervention program between the TPPS documents and the researcher's verification was 8 people (5.3 percent). There were 5 people (3.3 percent) inaccurate identification of stunting-risk families who received intervention programs between TPPS documents and researcher verification. Recording and reporting of interventions is not optimal. There is a gap in the convergence of intervention programs due to several factors, namely inadequate quality of human resources, unstable internet network during data collection, limited time for orientation or training so that it is still conceptual, there are still residents who do not have a family card, lack of budget, non-compliant respondents take blood tablets. Not all of the effectiveness of the convergence of intervention programs has conformity in the documents at TPPS and researcher verification.

Improving 4G LTE network quality using the automatic cell planning

The growing demand for network services leads to an increase in traffic load on eNodeB, resulting in decreased network quality and performance, necessitating optimization. This research analyses the results of optimising 4G reference signal received power (RSRP), signal to interference noise ratio (SINR) and throughput parameters using the automatic cell planning (ACP) method. ACP has been shown to significantly improve the performance and quality of 4G LTE networks compared to traditional cell planning methods. Based on the standard parameter RSRP, increased after ACP optimisation which is dominant in the range ≥ -100 s.d ˃ -85 dBm and obtained an average value of -98.59 dBm with good category. The average SINR has increased by 18.23 dB with a good category. The dominant throughput is in the 14,000 Kbps range with an average value of 50,241.08 Kbps with the excellent category. The ACP method can enhance the performance of 4G LTE networks, potentially addressing operator issues of unstable network quality due to poor coverage. The ACP method significantly enhances 4G LTE network performance, coverage, and user experience, potentially addressing unstable network quality due to poor coverage. This research is crucial for both users and the telecoms industry.

Depth-dependent responses of soil bacterial communities to salinity in an arid region

Soil salinization adversely affects soil fertility and plant growth in arid region worldwide. However, as the drivers of nutrient cycling, the response of microbial communities to soil salinization is poorly understood. This study characterized bacterial communities in different soil layers along a natural salinity gradient in the Karayulgun River Basin, located northwest of the Taklimakan desert in China, using the 16S rRNA Miseq-sequencing technique. The results revealed a significant filtering effect of salinity on the bacterial community in the topsoil. Only the α-diversity (Shannon index) in the topsoil (0–10 cm) significantly decreased with increasing salinity levels, and community dissimilarity in the topsoil was enhanced with increasing salinity, while there was no significant relationship in the subsoil. BugBase predictions revealed that aerobic, facultatively anaerobic, gram-positive, and stress-tolerant bacterial phenotypes in the topsoil was negatively related to salinity. The average degree and number of modules of the bacterial co-occurrence network in the topsoil were lower under higher salinity levels, which contrasted with the trends in the subsoil, suggesting an unstable bacterial network in the topsoil caused by higher salinity. The average path length among bacterial species increased in both soil layers under high salinity conditions. Plant diversity and available nitrogen were the main drivers affecting community composition in the topsoil, while available potassium largely shaped community composition in the subsoil. This study provides solid evidence that bacterial communities adapt to salinity through the adjustment of microbial composition based on soil depth. This information will contribute to the sustainable management of drylands and improved predictions and responses to changes in ecosystems caused by climate change.

Evaluation of E-Government System Policies in Timor-Leste From 2017 To 2023

Information and communication technology is increasingly developing in the current era, the government is required to issue a policy to prepare and develop it in the government. In this case, the implementation of e-government system policies in Timor-Leste through the central agency of information and communication technology aims to digitize government activities and services towards a modern government and ensure a transparent, effective, and efficient government. In this study descriptive qualitative research methods. Data collection is carried out by interviews, observation, and documentation with the determination of informants determined by purposive techniques or methods. This study shows that the implementation of the e-government system policy in Timor-Leste is still not effective or optimal because there are still factors that become obstacles to its implementation. Furthermore, the central agency of Tic Timor. I.P. still lacks human resources in the field of IT or adequate technical personnel, lacks facilities, and slow or unstable internet networks. The conclusion in the research obtained from the results of this study is that the Timor-Leste government through the central agency Tic Timor. I.P. has tried to develop an e-government policy system but there are still many shortcomings such as human resources in the field of informatics and technology, and low internet networks. The input suggestion given by the researcher is that the government needs to increase the capacity of supervisors and human resources to develop and accelerate the implementation of e-government policies in various government agencies at the central and regional levels.

Gender differences in job satisfaction among gig workers in Bangladesh

The gig economy (temporary, contract, and freelance online jobs rather than permanent positions) is a component of the fourth industrial revolution and preview of future work. The rise of digital platforms has increased career opportunities and income potential, particularly for women. Yet, the sex-disaggregated evidence regarding platform usage, employment characteristics, and working motivations and satisfaction remains untapped. Using data from a quantitative survey of Bangladeshi gig workers (242 men and 201 women) conducted in 2022, this paper addresses these gaps between male and female workers. The gig economy appears to be gender-segregated across digital platform usages and working categories. Women tend to prioritize digital work options for managing multiple responsibilities, while men are often driven by the potential for higher income. This study conceptually utilized the two-factor theory and empirically ordered a probit model to identify gender differences in job satisfaction. Job satisfaction was significantly increased by work-life balance, monthly income, and social-media connection, while an increase in working hours, complexity in payment systems, and unstable networks all led to a decrease in job satisfaction. The findings have implications for the future growth of the gig economy, provide new insights into gender differences in job satisfaction, and underscore the need for gender-sensitive policies in the online labor market.

MURE: Multi-layer real-time livestock management architecture with unmanned aerial vehicles using deep reinforcement learning

In recent years, the combination of unmanned aerial vehicles (UAVs) and wireless sensor networks (WSNs) has gained popularity in livestock management (LM) due to energy constraints and network instability. Limited energy storage of sensor nodes (SNs) and the possibility of packet loss contribute to fast energy consumption and unstable networks, respectively. UAVs serve as relay nodes and data sinks, addressing these issues by temporarily storing data to reduce SN workload and establishing mobile nodes for network stability. We propose two innovations based on previous work: 1) We introduce a multi-layer wireless network architecture, categorizing UAVs into two layers based on their functions including data collection and data processing. This enhances task parallelization, bridging performance gaps among multiple UAVs; 2) We overcome the mobility limitation of SNs, considering their real-time movement in the network. Through deep reinforcement learning, UAVs learn to cooperatively locate moving SNs. This accounts for the inevitable mobility of livestock in the industry. Additionally, we simulate the environment and compare our approach to traditional methods, evaluating metrics such as collected data per timestep (DCPS), energy consumed per timestep (ECPS), and network stability (NS). Experimental results demonstrate that our method outperforms traditional approaches, achieving a data collecting gain of 4.84% and 8.20% compared to the methods without considering SN mobility or the multi-layer characteristics of WSNs, respectively. Under energy consumption limits, our method yields energy savings of 3.00% and 1.35% respectively. Furthermore, we extensively study and validate our method against other path planning algorithms, including genetic particle swarm optimization (GPSO), modified central force optimization (MCFO), and rapidly-exploring random trees (RRT). Our approach surpasses these methods in terms of data collecting efficiency and network stability.

IMPLEMENTASI PENGGUNAAN APLIKASI SIMANIS DALAM PENGELOLAAN ARSIP DI KANTOR DESA NGREJO KECAMATAN BAKUNG KABUPATEN BLITAR

Today, the application of information technology is an important requirement in a government organization, this is to facilitate archive management in bringing order to the document assets of an organization. One of them is the Ngrejo Village Government Office which has implemented the SIMANIS application in supporting the management of organizational records. The purpose of this study is to find out how the implementation of the SIMANIS application (Village Information and Administration Management System) at the Ngrejo Blitar Village Office is in archive management and what obstacles are faced by the manager. The research method is descriptive qualitative with data sources obtained through observation, interviews, and documentation. The informants in this study were the Head of Ngrejo Village, the head of planning as the officer responsible for managing the archives, and the administrative and general heads as officers who assisted in managing the archives. The data analysis technique uses data reduction, data presentation, and conclusion drawing. The results of this study indicate that archive management at the Ngrejo Village Office has implemented information technology, namely the SIMANIS application which aims to improve officer performance, improve services, and maintain archive security. The obstacles faced in implementing the SIMANIS application are unstable internet networks because SIMANIS is basically a web-based archive management application. For this reason, the Ngrejo Village government should improve the quality of the internet network so that when officers input archive data it can run smoothly.

Tuberculosis Information System: Evaluation Approach with HOT-FIT Framework

Background: The increase in the number of pulmonary TB cases increases the risk of illness and death, which indicates the need for TB prevention and control efforts through online recording and reporting of cases using the Tuberculosis Information System (SITB). However, there are several challenges in implementing the use of SITB, which results in delays in reporting TB cases and disrupts TB prevention and treatment efforts. Purpose: The purpose of this study was to describe the use of SITB with the HOT-FIT Framework in the UPT Puskesmas Lemo area, North Barito District, Central Kalimantan. Methods: This research applies qualitative research methods with a phenomenological approach. The study population consisted of five informants who were selected deliberately (purposive sampling), including the Head of Puskesmas, TB Program Manager, TB Program Management Assistant, General Practitioner, and Laboratory Officer. Results: The results highlight that the use of Tuberculosis Information System (SITB) applications faces a number of supporting and inhibiting factors, which eventually lead to delays in reporting. Although the availability of adequate human resources (HR) is one of the supporting factors for reporting tuberculosis (TB) cases through the SITB application, the unstable internet network and lack of facilities and infrastructure such as inadequate software are also inhibiting factors. Conclusion: Puskesmas Lemo has participated in the successful implementation of TB case recording and reporting activities using SITB, but there are several aspects that still need to be improved and followed up. Thus, the Lemo Health Center still needs regular guidance and monitoring by the Health Office in carrying out its functions.

Triggered saccadic oscillations: case series and review of the literature.

Saccadic oscillations (SOs) mostly occur spontaneously, but can be occasionally triggered by various stimuli. To determine clinical characteristics and underlying mechanisms of triggered SOs, we analyzed the clinical features and quantitative eye-movement recordings of six new patients and 10 patients in the literature who exhibited with triggered SOs. Eleven of the 16 patients (69%) had a lesion involving cerebellum and/or brainstem such as cerebellar degeneration, cerebellitis, or cerebellar infarction. The other causes were vestibular migraine (n = 2), multiple sclerosis (n = 1), Krabbe disease (n = 1), and idiopathic (n = 1). Vestibular stimulation was the most common trigger (n = 11, 69%), followed by removal of visual fixation (n = 4, 25%), hyperventilation (n = 1), light (n = 1), and blink (n = 1). The types of triggered SOs were varied which included ocular flutter (n = 13), opsoclonus (n = 3), vertical SOs (n = 2), and macrosaccadic oscillations (n = 1). Three patients exhibited downbeat nystagmus either before (n = 1) or after (n = 2) the onset of SOs. The frequency of triggered SOs ranged from 4 to 15Hz, and oscillations with smaller amplitudes had higher frequencies and smaller peak velocities. SOs can be triggered by the modulation of unstable saccadic neural networks through vestibular and visual inputs in lesions of the brainstem and cerebellum.

Pemanfaatan Media Pembelajaran Audio Visual Berbasis Channel Youtube dalam Pembentukan Karakter Anak di Taman Pendidikan Al-Qur’an

Character education should be implemented from an early age because early age really determines a child's ability to develop their potential. Problems found at Al-Ikhsan TPA include not respecting ustadz, rarely reciting the Koran, behaving impolitely, and there are still people who say dirty words at Al-Ikhsan TPA, Terbanggi Besar District. This research is field research with a qualitative descriptive nature, while the data analysis method uses a deductive method. Utilization of Audio Visual Learning Media Based on YouTube Channels in Forming Children's Character at Al-Ikhsan TPA, namely First, Introduction by preparing equipment including TV, Wifi and YouTube channels. Second, Exploration, namely students have diverse characters, activated through active, innovative, creative, effective and fun learning methods. Third, restructuring, namely the concept of learning by watching YouTube channels and continuing with the question and answer method. Fourth, implementation, namely a 60 minute learning process by broadcasting a YouTube channel about the stories of prophets and apostles. Fifth, Review or Evaluation, namely a question and answer session to evaluate children's understanding of the meaning contained in the YouTube channel. The use of audio visual media based on YouTube channels can shape the character of children at Al-Ikhsan TPA, especially children who have religious, honest, curious, hard working, social care and responsibility characters. Learning using the YouTube channel has several obstacles, including an unstable network and bad weather, resulting in changes to the learning schedule. Therefore, researchers provide recommendations in the form of adding a learning schedule by utilizing the YouTube channel 2-3 times a week, this is done so that children's character formation becomes more effective and optimal.

A Mobile AD Hoc Network Relay Method based on OLSR Protocol

Aiming at the reliability and performance problems of data transmission in the complex mobile AD hoc network environment, a relay method is designed and implemented in the unstable network environment with complex dynamics such as mobile, multi-hop and no center according to practical needs. By introducing a prior link-state routing protocol, OLSR is introduced. Using range value judgment, sliding window statistics and improved multi-point relay selection technology, it can effectively reduce the redundancy of relay node set, reduce the forwarding frequency of service data in the network, save the network overhead, and ensure the data transmission delay and quality in the large scale and dense mobile AD hoc network.

BONES: Near-Optimal Neural-Enhanced Video Streaming

Accessing high-quality video content can be challenging due to insufficient and unstable network bandwidth. Recent advances in neural enhancement have shown promising results in improving the quality of degraded videos through deep learning. Neural-Enhanced Streaming (NES) incorporates this new approach into video streaming, allowing users to download low-quality video segments and then enhance them to obtain high-quality content without violating the playback of the video stream. We introduce BONES, an NES control algorithm that jointly manages the network and computational resources to maximize the quality of experience (QoE) of the user. BONES formulates NES as a Lyapunov optimization problem and solves it in an online manner with near-optimal performance, making it the first NES algorithm to provide a theoretical performance guarantee. Comprehensive experimental results indicate that BONES increases QoE by 5% to 20% over state-of-the-art algorithms with minimal overhead. Our code is available at https://github.com/UMass-LIDS/bones.

IoT based sensor network clustering for intelligent transportation system using meta‐heuristic algorithm

SummaryInternet of Things (IoT) based sensor networks have been established as a pillar in intelligent communication systems for efficiently handling roadside congestion and accidents. These IoT networks sense, collect, and process data on a real‐time basis. However, IoT based sensor network clustering has various energy constraints such as inefficient routing due to long‐haul transmission, hot spot problem, network overhead, and unstable network whenever deployed along with the roadside that affect their architecture. In such networks, clustering techniques play a crucial role in extending the lifespan and optimizing the routes by integrating sensor devices through clusters. Therefore, a meta‐heuristic algorithm for clustering in IoT sensor networks for an intelligent transportation system is proposed. In this work, the seagull optimization algorithm is applied for clustering by considering residual and average energy, node spacing, and distance fitness parameters. Moreover, this work also considers the dynamic communication range of the cluster heads for increasing the stability period and lifetime of the proposed networks. The experiment results demonstrate that the proposed Seagull optimization algorithm for clustering in IoT networks (SOAC‐IoTNs) and Seagull optimization algorithm for clustering in IoT networks with dynamic communication range (SOAC‐IoTNs‐DR) achieve a significant increase in the stability period and network lifetime, with percentage increments of 55.68% and 71.47%, and 10.03% and 88.66% respectively, compared to the existing optimized genetic algorithm for cluster head selection with single static sink (OptiGACHS‐StSS).

A study on the effects of replacing fishmeal with soybean meal in the feed of Procambarus clarkii: Assessing growth performance, immunity, and gut microbiota

The unstable supply and high cost of fishmeal have led to increased interest in low fish meal feed. As such, the present study aimed to investigate the effects of replacing fishmeal in feeds with soybean meal (SM) on the growth, immunity, and gut microbiota of crayfish. A total of 750 crayfish (4.00 g) were randomly divided into five groups (SS0, SS25, SS50, SS75, and SS100) with three replicates, and were fed diets with different levels of soybean meal substituted for fishmeal for six weeks. The results revealed that crayfish subjected to high SM diets experienced a significant decrease in the final body weight, weight gain rate, and specific growth rate (p<0.05), together with enzyme activities related to nutrient digestion and absorption. Of note, the groups with 25–50 % SM replacement exhibited decreased final body weight without significance compared to that in the SS0 group (p>0.05). Moreover, increasing SM inclusion exhibited the potential to impair the intestine, characterized by the increase in hemolymph LD content, decrease in the levels of TC content, T-AOC, and AKP, along with the observed edema of the lamina propria, and up-regulated mRNA expression levels of nfkb, alf, and tlr. Furthermore, high SM diets resulted in the emergence of new species and a shift in Firmicutes, Bacteroidota, Proteobacteria, and Fusobacteriota. Specifically, the abundance of lower Firmicutes and higher Proteobacteria was observed in the SS100 group, which was closely correlated with genus-level Candidatus Bacilloplasma, and RsaHf231 abundance alterations. MENAs demonstrated that the high SM diets led to a more complex, yet fragile and unstable microbial network. The global network further indicated that the microbes contributing more to crayfish were in module eigen 4, in which 9 OTUs were identified as major biomarkers and mainly classified into Proteobacteria. Taken above, SM could replace 25 % of fishmeal in crayfish diets without negatively affecting growth performance, nutrient utilization, immunity, and antioxidant capacity. Excessive SM levels contributed to gut dysfunction and weakened the immune system of crayfish.