Network Quality Research Articles

Innovative Governance Dalam Penyelengggaraan Pemerintahan Desa Di Kabupaten Kuantan Singingi (Studi pada Penerapan Aplikasi dan Website Gigades.id)

This research is motivated by the gap in technology, information and communication between villages and cities which causes slow governance in villages. This condition is a challenge for villages to actively participate in the current era of digitalization. The aim of village innovation is to encourage village development of higher quality, effectiveness and efficiency through various activities in village government administration that are more innovative and sensitive to the needs of village communities. This effort can encourage productivity and economic growth in rural communities in a sustainable manner to improve the socio-economic welfare of the community and village independence. However, in the development of village innovation, it has not proceeded according to the plans that have been set. This is because the community's digital awareness is still low, as well as the culture and organizational arrangements of the village government which are not yet fully ready to implement digitalization in the administration of village government. This research aims to analyze and explain innovative governance in the implementation of village government in Kuantan Singingi Regency, as well as identifying obstacles to implementing innovation in the form of the Gigades.id application and website. This research uses the Innovative Governance theory of Sangkala Tahun (2014) which explains that there are 6 criteria for best practices in an innovation, namely impact, partnership, sustainability, leadership and community empowerment, gender equality and social exclusion, innovation in the local context and transferability. This research uses an explanatory qualitative research method with a case study approach that uses data collection techniques through interviews, observation and documentation. The results of this research show that the implementation of village government in Kuantan Singingi Regency has made a breakthrough in the form of innovative governance in the implementation of village government in the form of innovation in the form of the Gigades.id application and website, but it has not been successfully implemented properly by the village government. Findings in the field show that the implementation of partnerships is still formed between the village government and the private sector, the trilogy of good governance in building partnerships has not been implemented well, even though the community has a big role in realizing the implementation of village government. Then the obstacles experienced by this innovation are the lack of socialization carried out by the village government and the private sector to village communities, the low quality of knowledge and innovation skills of village government officials, the inadequate quality of the internet network, and a community culture that is difficult to change.

Investigation Performance Analysis and Evaluation of VANET Routing Protocol on Urban Scenario Simulation: A Case Study of Melaka

Vehicles on the road create a VANET network using IEEE 802.11P for wireless data exchange. However, VANET is challenging since the characteristics of VANET such as high mobility and frequent topology making it harder to design an effective routing protocol. The needs of an efficient performance routing protocol are crucial since it is to ensure a better network Quality of Service (QoS). In this paper, the evaluation of the IEEE 802.11P performance is simulated in real-world scenario using the Melaka City roadmap. In an urban setting, the impact of vehicle density on the performance of VANET routing protocols including OLSR, AODV, and DSDV are examined. Reviewing the effectiveness of the current VANET routing protocols is the goal of this research since it is crucial to know which routing has high performance under specific circumstances. Quantitative measurements including Packet Delivery Ratio (PDR), Packet Loss Ratio (PLR), and end-to-end delay are evaluated using the Network Simulator NS-3 and SUMO. Findings from the investigation show that while proactive routing protocols like OLSR and DSDV perform better in terms of end-to-end delay, AODV performs exceptionally well in terms of PDR and PLR.

Channel prediction method based on the data-driving for distribution automation main station

A data-driven channel prediction method for distribution automation master is proposed to address the poor quality of communication network and communication system transmission problems in distribution network communication. In this paper, an adaptive broad learning network (ABLN) consisting of a standard broad learning network and a hybrid learning network is introduced to predict the channel state information of the communication system. Among them, the hybrid learning network is used to solve the ill-conditioned solution problem when estimating the output weight matrix of the standard broad learning network. Therefore, the ABLN produces sparse output weight matrices and provides excellent prediction performance. In the simulation analysis, the outdoor and indoor scenes are considered based on OFDM system. The prediction performance of ABLN is subsequently evaluated in one step prediction and multistep prediction. The results show that for the prediction performance is concerned, the maximum improvement of ABLN is about 96.49% as compared to other evaluation models, indicating that the CSI is effectively predicted by the ABLN to support the adaptive transmission of the main station of the distribution automation and to satisfy the quality of the communication network of the distribution network.

The National Healthcare Safety Network's digital quality measures: CDC's automated measures for surveillance of patient safety.

This article presents the National Healthcare Safety Network (NHSN)'s approach to automation for public health surveillance using digital quality measures (dQMs) via an open-source tool (NHSNLink) and piloting of this approach using real-world data in a newly established collaborative program (NHSNCoLab). The approach leverages Health Level Seven Fast Healthcare Interoperability Resources (FHIR) application programming interfaces to improve data collection and reporting for public health and patient safety beginning with common, clinically significant, and preventable patient harms, such as medication-related hypoglycemia, healthcare facility-onset Clostridioides difficile infection, and healthcare-associated venous thromboembolism. The NHSN's FHIR dQMs hold the promise of minimizing the burden of reporting, improving accuracy, quality, and validity of data collected by NHSN, and increasing speed and efficiency of public health surveillance.

Assessing the acceptance of mobile phone technology in Tanzanian SMEs

Purpose This study investigates the acceptance of mobile phone technology in Tanzanian small- and medium-sized enterprises (SMEs) using the Technology Acceptance Model (TAM) with a special focus on service quality.Design/methodology/approach The conceptual framework was designed by extending the TAM with an additional construct, service quality, before testing a model in a survey of 155 respondents and analysing using Smart PLS 4.Findings Service quality was found to be among the significant factors in the acceptance of mobile phone technology among SME employees.Research limitations/implications This implies that the higher the quality of service offered, the more employees accept and use mobile phone technology in their duties and improve the productivity of SMEs.Practical implications The aspects of quality of mobile phone technology usage such as call dropouts, network quality, speed, etc., must be improved significantly.Social implications The Mobile Network Operators and Regulators must understand that employees are offered the most accurate and reliable mobile phone services for its usefulness to be realised.Originality/value The originality is a modified version of a TAM that accommodates service quality that has been tested in the Tanzanian context.

Experience real-time, health and biological outcoMes of personal recovery in PeOple With mEntal disorders in Residential facilities (EMPOWER): a cohort study

Introduction Deinstitutionalization has resulted in diverse mental health care models, influenced by local resources, funding, and cultural factors. In Italy, 127 Department of Mental Health (DMHs) provide care for individuals with mental disorders. People with severe mental disorders (SMD) live independently or in residential facilities (RFs). Approximately half of the Italian DMH budget is allocated to RFs, serving around 3.6% of people with SMD. Italian RFs prioritize personal recovery, empowering individuals with SMD to live fulfilling lives despite symptoms and psychosocial challenges. While personal recovery is known to improve well-being and cost-effectiveness, its implementation in Italian RFs remains incomplete. There is insufficient evidence regarding its impact on various outcomes for residents, including health, psychosocial, and biological factors.Objectives The EMPOWER Study aims to assess whether adding personal recovery to Treatment As Usual (TAU) in Italian RFs could improve functioning (primary outcome), health, biological status, productivity and interpersonal relationships (secondary outcomes) among patients receiving the personal recovery-oriented treatment, compared with TAU. Additionally, data will be collected from informal caregivers, mental health professionals, and concerning the recovery orientation of RFs.MethodsThis study employs a longitudinal cohort design, gathering data at baseline and six-month follow-up in Italian RFs. A cohort of residents over 18 y.o. who receive a personal recovery-oriented treatment, the Mental Health Recovery Star (N=20), is compared to a matched group of residents receiving the TAU (N=20). International standardized assessments collect patients’ data on functioning, psychopathology, need for care, quality of life (QoL), positivity, social network, service satisfaction, and patient stigma. Informal caregivers’ data includes burden, QoL, positivity, and service satisfaction. Mental health professionals’ data encompasses burnout, stress, stigma, positivity, and work satisfaction. The working alliance between professionals and patients is assessed. Clinical and biological exams (blood and saliva samples) are collected, along with actigraphy data on patients’ circadian rhythm and physical activities. Digital data through a mobile app captures psychopathology, productive activities, social network, using the Experience Sampling Method with questions defined with patients. Focus groups with patients, professionals, and informal caregivers are facilitated by an expert by experience. Recovery orientation of RFs is assessed.ResultsNot yet available.ConclusionsThis study aims to generate novel insight that could improve our treatment approaches for patients in residential facilities.Disclosure of InterestNone Declared

Penerapan Metode Quality of Service (QoS) dalam Analisis Kualitas Jaringan Internet Burjo Pantry Semarang

The rapid progression of technology enables humans to exchange data and communicate remotely, eliminating the need for face-to-face interactions. The internet network, a product of this technological advancement, undergoes evaluation through the Quality of Service (QoS) method, which measures network service quality. This research focuses on assessing the internet network quality at Burjo Pantry in Semarang, utilizing a quantitative approach with a Quality of Service analysis. The throughput results reveal 1682Kbps in the terrace area and 7266Kbps indoors at Burjo, both categorized as 'very good.' Likewise, the delay, with 128,75ms in the terrace and 145ms indoors, falls into the 'very good' category. Both areas exhibit excellent jitter: 1,77ms for the terrace and 26,46ms indoors. Packet loss is minimal, with 1,73% in the terrace area and 0,68% indoors, both considered 'very good.' Overall, the study indicates the commendable quality of the internet network at Burjo Pantry in Semarang.

ANALISIS KUALITAS JARINGAN PADA LAYANAN INDIHOME UNTUK GAME ONLINE

The use and utilization of the Internet network is not only limited to its use for internet needs for social media but also for entertainment such as playing games such as the online game Valorant. The need for good network quality is very necessary to be able to play Valorant well. The purpose of this research is to determine the network quality of internet service provided by Indihome as one of the internet service providers (ISP) in Indonesia when playing the online game Valorant. With measurements using LAN cables and wireless at a speed of 50 Mbps using 2 laptop devices with the Indihome network. Measuring only the Delay and Packet Loss parameters using the Wireshark application, as well as measuring the Throughput parameters for the bandwidth requirements of the Valorant online game using the Netlimiter application for 4 weeks on Mondays and Wednesdays on weekdays and also weekends. The results of this test are the highest values of delay and packet loss for cable use, namely 6.81 ms and 0.285% and the highest values of delay and packet loss for wireless use, namely 6.15 ms and 0.548%. Where in testing the Quality of Service (QoS) value of the Indihome network when using cable and wireless, namely delay and packet loss, it shows good values compared to the TIPHON standard.

Automatic Cell Planning Method for Radio Network Optimization

As the first step in building a wireless communication network, wireless network optimization is crucial since it determines how the network will be built scientifically. Numerous challenges remain in the way of the Radio Network's deployment in Indonesia, not the least of which is the still-uneven coverage region. The Kiaracondong region in Bandung is one of the numerous areas in Indonesia that are still considered to be "bad spot areas" as a result. Based on the findings of the driving test conducted in the Kiaracondong sub-district, the KPI target was not fulfilled for the RSRP, SINR, and Throughput parameters. Therefore, this study primarily focuses on the physical tuning optimization using the Automatic Cell Planning (ACP) method for the LTE wireless network optimization. To assess the quality of the LTE network before and after optimization, the results of the ACP optimization simulation will be compared with the results of the existing or non-ACP site simulation and the results of the operator's ACP implementation. As a result, Area 1 has an average RSRP of -72.79 dBm, area 2 -73.17 dBm, and area 3 -68.22 dBm. Additionally, the average SINR in areas 1,2 and 3 is 8 dB, 6.58 dB, and 8.17 dB, respectively. The average downlink throughput in area 1 is 42652.66 Kbps, area 2 is 34420.88 Kbps, and area 3 is 43882.92 Kbps. Finally, the average throughput uplink for areas 1 to 3 is 51651.24 Kbps, 47895.99 Kbps, and 49648.84 Kbps, respectively.

English

English

Analisis Perangkat Pembelajaran Daring Berdasarkan Survei Siswa Akibat Pandemi Covid-19

The Covid-19 pandemic situation in 2021 resulted in various changes in various sectors, including education. Various methods were used to maintain learning activities by reducing physical contact to prevent the spread of the virus. The shift from face-to-face learning to online quickly led to new problems that reduced the effectiveness of student learning. These issues are caused by suboptimal internet network quality, difficulty in adapting to online learning methods, and differences in understanding material through video conferencing applications. This research aims to provide a comprehensive explanation of the effectiveness of online learning in the short and long term using non-parametric statistics and categorical data analysis through Chi-Square tests. The research sample consists of 150 students from universities in Jakarta and Bandung

A Model for Supervision Management to Improve the Education by Using the Area as Base in Digital Era under Primary Educational Service Area in the Northeastern Region

Educational reform in the modern era which the school administrators and all personnel in the school Must improve and develop themselves to keep up with changes in the era of globalization. By using the supervisory management model process to develop educational quality, these research objectives are to: 1) Study the problems and elements of supervision. Target group: 15 people 2) Create a supervisory model. By conducting in-depth interviews with 15 people involved. 3) Experiment with the supervision model with a sample group of 3 schools 4) Evaluate the use of the supervision model. By organizing a seminar with 15 experts and asking for opinions about its usefulness. Feasibility, appropriateness, and correctness of the format from 291 study supervisors. The instrument used was a questionnaire. Statistics were used to find the mean and standard deviation. It can be summarized as follows: 1) Problems in supervision include an insufficient number of supervisors. Study supervisors lack knowledge Lack of good supervision skills and no systematic planning. There are 5 important elements as follows: (1) objectives, (2) planning, (3) supervision, (4) monitoring and reflection, and (5) development and application. 2) Creating a model for supervision, including (1) objectives,(2) content of supervision, (3) process, (4) method, (5) supervisor and supervisor, (6) duration, (7) planning, (8) execution, (9) Evaluation (10) teamwork (11) network building (12) knowledge management (13) learning and quality development (14) building morale and (15) improving development. 3) The results of the trial use of the model had a reliability value of .80. Average comparison results in Knowledge before training and after training, tested with a t-test, and were found to be different. Statistically significant is at the .01 level. They were satisfied with the model. Overall, it is at the highest level (x̅ = 4.90, S.D. = 0.53) and the results of the overall evaluation of the use of the format are at the highest level (x̅ = 4.89) and overall satisfaction with the use of the format is at the highest level (x̅ = 4.63) 4) Model evaluation results are useful feasibility, suitability, and correctness. Overall, it is at the highest level (x̅ = 4.63, S.D. = 0.12).

Difficulties Experienced By Students In Learning From Mathematics During The Covid-19 Pandemic

This study aims to identify the obstacles faced by students learning from during the Covid-19 pandemic. The method used was descriptive qualitative approach, conducted at SMA 5 Palembang City involving 26 students as participants. This study used a questionnaire as a data collection tool, which was distributed to students online via WhatsApp using Google Form. The results showed that the main obstacles faced by students were related to the availability of facilities and inadequate internet connection. Some students do not have adequate access to support online learning, coupled with poor internet network quality, hindering their participation in online learning that requires a stable internet connection. In addition, in dealing with online learning, more creativity is needed from the teacher to prevent boredom and lack of motivation in students. Another obstacle is the limited communication between students and teachers. Which results in difficulties in understanding the learning materials.

Brain network entropy, depression, and quality of life in people with traumatic brain injury and seizure disorders.

Traumatic brain injury (TBI) often precedes the onset of epileptic (ES) or psychogenic nonepileptic seizures (PNES) with depression being a common comorbidity. The relationship between depression severity and quality of life (QOL) may be related to resting-state network complexity. We investigated these relationships in adults with TBI-only, TBI + ES, or TBI + PNES using Sample Entropy (SampEn), a measure of physiologic signals complexity. Adults with TBI-only (n = 60), TBI + ES (n = 21), or TBI + PNES (n = 56) completed the Beck Depression Inventory-II (BDI-II; depression symptom severity) and QOL in Epilepsy (QOLIE-31) assessments and underwent resting-state functional magnetic resonance imaging (rs-fMRI). SampEn values derived from six resting state functional networks were calculated per participant. Effects of group, network, and group-by-network-interactions for SampEn were investigated with a mixed-effects model. We examined relationships between BDI-II, QOL, and SampEn of each of the networks. Groups did not differ in age, but there was a higher proportion of women with TBI + PNES (p = 0.040). TBI + ES and TBI-only groups did not differ in BDI-II or QOLIE-31 scores, while the TBI + PNES group scored worse on both measures. The fixed effects of the model revealed significant differences in SampEn values across networks (lower SampEn for the frontoparietal network compared to other networks). The likelihood ratio test for group-by-network-interactions was significant (p = 0.033). BDI-II was significantly negatively associated with Overall QOL scale scores in all groups, and significantly negatively associated with network SampEn values only in the TBI + PNES group. Only TBI + PNES had significant relationships between depression symptom severity and network SampEn values indicating that the resting state network complexity is related to depression severity in this group but not in TBI + ES or TBI-only. The brain has a complex network of internal connections. How well these connections work may be affected by TBI and seizures and may underlie mental health symptoms including depression; the worse the depression, the worse the quality of life. Our study compared brain organization in people with TBI, people with epilepsy after TBI, and people with nonepileptic seizures after TBI. Only people with nonepileptic seizures after TBI showed a relationship between how organized their brain connections were and how bad was their depression. We need to better understand these relationships to develop more impactful, effective treatments.

Optical communication enhanced IDMBOC for maximizing backhaul-effect & maintaining optimum cell sizes

Abstract The increasing need for high data rates and low latency in optical communication networks necessitates innovative solution for system efficiency enhancements. With the persistent increase in data demand and the emergence of diverse applications in 5G networks, minimizing the backhaul-effect while maintaining optimal cell sizes has become a formidable obstacle. Existing methods are incapable of achieving a comprehensive optimization of network parameters, resulting in degraded performance metrics. To address these constraints, our proposed approach integrates optical communication infrastructure into IDMBOC systems which maximizes backhaul-effect and preserves optimal cell sizes. This work is primarily motivated by the need to improve the efficiency and quality of 5G networks in the face of rising data traffic. Existing methods frequently struggle to optimize concurrently multiple 5G network aspects, such as carrier aggregation, dynamic spectrum sharing, packet prioritization, network function virtualization, frequency planning, HetNets deployments, and network slicing process. As a result, these methods are incapable of delivering robust and scalable solutions. To solve these issues, we present an Iterative dual metaheuristic method that combines ant lion optimization (ALO) and grey wolf optimization (GWO) in a synergistic manner for 5G deployments. The proposed method is functionally superior to existing models. By capitalizing on the strengths of both ALO and GWO, our approach achieves superior performance metrics in comparison to recently proposed methods for maximizing backhaul-effect and maintaining optimal cell sizes. The preliminary results reveal a remarkable 8.3 % reduction in bit error rate (BER), 4.9 % reduction in energy consumption, 8.5 % increase in throughput, and 4.5 % reduction in communication delay. The achieved results demonstrate the revolutionary potential of our 5G network optimization approach and pave the way for future research and advancements in the field for different scenarios. These enhancements will revolutionize optical communication networks in order to accommodate the requirements of 5G, IoT, and other contemporary applications.

Enhancing user experience in home networks with machine learning-based classification

With the rapid development of mobile Internet, home broadband has been integrated into people's daily lives, and the market has become increasingly saturated. User experience and broadband quality have become the key factors determining market competitiveness, and consequently, most operators currently are increasing attention to network quality issues and how to improve user experience. This paper proposes an efficient machine learning model to accurately evaluate home user network experiences. The dataset used encompasses network indicator data from 500 anonymized users, and presents a set of formidable challenges including a non-standard sampling rate and time range, an uneven distribution of observations, multiple recorded observations for identical timestamps, a constrained sample size, a subjective definition of Internet experience, and a lack of essential information regarding the data collection setup. Our novel time series characteristic-based method extracts thousands of descriptive statistics from the time series sequences which reveal that, even in the face of the dataset's inherent complexities, our proposed method excels, achieving an impressive 67% validation accuracy. This represents a substantial 3% enhancement over the performance of conventional models on this dataset. Furthermore, we explore the potential of a Recurrent Neural Network (RNN) model, which also yields promising results with a validation accuracy of 58%. It is important to underscore that the performance of the RNN model could be substantially enhanced with a larger dataset. [...]

Enhanced Deep Neural Networks for Traffic Speed Forecasting Regarding Sustainable Traffic Management Using Probe Data from Registered Transport Vehicles on Multilane Roads

Early forecasting of vehicle flow speeds is crucial for sustainable traffic development and establishing Traffic Speed Forecasting (TSF) systems for each country. While online mapping services offer significant benefits, dependence on them hampers the development of domestic alternative platforms, impeding sustainable traffic management and posing security risks. There is an urgent need for research to explore sustainable solutions, such as leveraging Global Positioning System (GPS) probe data, to support transportation management in urban areas effectively. Despite their vast potential, GPS probe data often present challenges, particularly in urban areas, including interference signals and missing data. This paper addresses these challenges by proposing a process for handling anomalous and missing GPS signals from probe vehicles on parallel multilane roads in Vietnam. Additionally, the paper investigates the effectiveness of techniques such as Particle Swarm Optimization Long Short-Term Memory (PSO-LSTM) and Genetic Algorithm Long Short-Term Memory (GA-LSTM) in enhancing LSTM networks for TSF using GPS data. Through empirical analysis, this paper demonstrates the efficacy of PSO-LSTM and GA-LSTM compared to existing methods and the state-of-the-art LSTM approach. Performance metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Median Absolute Error (MDAE) validate the proposed models, providing insights into their forecasting accuracy. The paper also offers a comprehensive process for handling GPS outlier data and applying GA and PSO algorithms to enhance LSTM network quality in TSF, enabling researchers to streamline calculations and improve supposed model efficiency in similar contexts.

Analyzing the Impact of Sodium Discharge Lamps Inrush Currents on the Street Lighting System and Electric Network Quality

Analyzing the Impact of Sodium Discharge Lamps Inrush Currents on the Street Lighting System and Electric Network Quality

DDoS Protection System for SDN Network Based on Multi Controller and Load Balancer

DDoS attacks on SDN networks can create a single point of failure that has the potential to disrupt the overall network performance. In a single controller scheme, there is a potential risk of experiencing buffer overload, leading to traffic congestion as switches must wait for responses from the controller before forwarding network packets. To address this challenge, this research implements security measures using a multi-controller and load balancer approach, aiming to enhance SDN network resilience against DDoS attacks. The system operates by distributing the workload from the main controller to a backup controller through a load balancer when indications of a DDoS attack are detected. These attack indications are determined based on the miss rate value of unique forwarding requests exceeding a specific threshold. The results of this approach have proven effective in improving the reliability, responsiveness, and quality of SDN network traffic during DDoS attacks. The testing parameters involved in this research include controller response time and network traffic quality, comprising latency, bandwidth, throughput, and jitter. Based on the test results, the multi-controller and load balancer-based approach successfully enhanced network quality and controller responsiveness by 66.51% compared to the longer single controller scenario, specifically 202.49% during DDoS attacks. In terms of controller responsiveness, there is a very slight increase of around 0.01% in latency between the two. While Multi Controller demonstrated a remarkable 43.21% increase in throughput compared to Single Controller, this improvement in throughput is accompanied by a significant 204% increase in jitter.

Social networks of men who have sex with men engaging in chemsex in Germany: differences in social resources and sexual health

Meyer’s minority stress model posits that sexual minority communities can act as protective factors for individuals within the sexual minority. Given that existing evidence on this proposition is inconclusive, a social network approach was employed to capture diversity in the social environment of individuals involved in chemsex that might account for variations in social resources and sexual health. This study examined the social networks of men who have sex with men (MSM) involved in sexualised drug use, using data from a cross-sectional online survey. Utilising cluster analysis, four distinct social network types were identified based on network composition: MSM-diverse, partner-focused, family-diverse, and chemsex-restricted. In terms of social resources, the four network types did not exhibit significant differences in social support. However, individuals with a chemsex-restricted social network reported stronger social influence related to chemsex and less social engagement outside of chemsex. Contrary to initial expectations, the four network types did not differ in chemsex-related consequences or sexual satisfaction. MSM engaged in chemsex for over 5 years reported more chemsex-related consequences and lower sexual satisfaction, particularly those with a family-diverse social network. Additionally, indicators of network quality, such as perceived emotional closeness, reciprocity with network members, and overall satisfaction with the network, were more influential in predicting sexual health outcomes than social resources. The findings of the study suggest that the social environment of MSM engaged in chemsex plays a role in shaping their experiences. Insufficient inclusion in a sexual minority community is potentially associated with an elevated risk of poor sexual health. These findings underscore the importance of tailoring interventions to address the diverse needs of individuals exposed to different social environments.