Connection Cost Research Articles

Load-Balanced Topology Rebuilding for Disconnected Wireless Sensor Networks With Delay Constraint

In inhospitable environments, connectivity recovery plays a significant role in enabling normal data transmission in wireless sensor networks (WSNs). However, existing approaches lack thorough load-balancing and delay-control functions. In this article, we present a load-balanced connectivity recovery (LBCR) strategy to address these problems. This strategy consists of two relay-segment selection approaches. The first one is the delay-controlled connectivity mechanism, in which mobile relays and static relays are employed to connect isolated segments, and the path length of the two kinds of relays is adjusted based on the requirement of data delivery delay. The second one is the load-balanced connectivity mechanism, in which both the intra-segment and the inter-segment traffic distribution are evaluated to balance the traffic load. For intra-segment load equilibrium, we use the A-Star algorithm to calculate the number of disjoint paths of a relay segment, which helps to evaluate the load sharing ability from a micro perspective. For inter-segment load equilibrium, we compare the traffic load of different paths, which helps to evaluate the load sharing ability from a macroscopic angle. Extensive simulations demonstrate the effectiveness and advantage of our strategy in terms of connectivity cost, data collection delay, and system lifespan.

STRATEGY FOR INCREASING FOREIGN EXCHANGE INCOME IN THE TOURISM SECTOR IN CENTRAL ACEH USING THE COMPETITIVE DESTINATION OF HALAL TOURISM MODEL DURING THE COVID-19 PANDEMIC

The impact of the Corona Virus (Covid-19) outbreak on the tourism industry, especially Indonesia, is certainly very influential. A number of cancellations of foreign and domestic tourist arrivals have occurred since the virus outbreak was announced. The plane seats are empty, as well as hotels, cruise operators, and other business potentials. Minister of Tourism and Creative Economy Sandiaga Uno assessed that the limited mobility of the community due to the Covid-19 pandemic and the closure of recreational and entertainment places had a considerable economic impact on the tourism sector. This study aims to formulate a strategy to improve the tourism sector in Indonesia which is declining amid the covid-19 pandemic with the incentive sales method in collaboration with airlines or foreign agents who bring foreign tourists to Indonesia with a specific purpose. will be given a subsidy depending on the number and duration of tourists visiting Indonesia. Through a strategy mechanism to reduce connectivity costs and a competitive destination model (CDM) to anticipate a decline in tourism performance. This scientific research also aims to provide recommendations for sustainable strategies for the Indonesian tourism sector, especially in the province of Aceh in running the tourism sector amid the Covid-19 pandemic. This type of research is a qualitative research using a mix method by conducting interviews with the target population, namely 100 business actors who play a role in driving the economy in the tourism object business in Aceh province and formulating a model for increasing the productivity of the tourism sector by introducing direct promotion methods and collaborating with the government in the process. development and improvement of the tourism sector. In this study, a focus group discussion will be held by inviting local officials from the Aceh provincial tourism office and academics to provide input in completing the model for developing a strategy for increasing tourism productivity by focusing on the incentive sales method. The output of this research is the publication of reputable international journals

A review of impacts of electricity tariff reform in Africa

African power sectors are plagued with financial unsustainability, low rates of grid connection, and high consumer prices relative to other regions in the Global South. Reforms to electricity tariffs are a tool for decision makers to reduce costly energy subsidies, expand grid access, improve service quality, and increase affordability. This review examines 82 papers in the academic literature on the impacts of electricity tariff reform in Africa. We organize our results according to three modalities of reform: bill payment method; tariff structure; and tariff rate. Evidence on the impacts of payment reform indicates that prepaid meters may encourage residential electricity conservation and limit arrears. Increasing block tariff structures are highly regressive and poorly target consumers, and there is limited evidence on the cost or grid access implications of volume differentiated tariffs or subsidies for connection costs. Lastly, we find that demand for electricity is price inelastic across all sectors, and that tariff increases should be accompanied by protections for low-income consumers. Our analysis facilitates comparison across countries and sectors, shedding light on the successes and shortcomings of various tariff reform efforts on the continent. The review concludes with recommendations for future research and lessons for policy makers.

An exact reduction technique for the k-Colour Shortest Path Problem

The k-Colour Shortest Path Problem is a variant of the classic Shortest Path Problem. This problem consists of finding a shortest path on a weighted edge-coloured graph, where the maximum number of different colours used in a feasible solution is fixed to be k. The k-CSPP has several real-world applications, particularly in network reliability. It addresses the problem of reducing the connection cost while improving the reliability of the network. In this work, we propose a heuristic approach, namely Colour-Constrained Dijkstra Algorithm (CCDA), which is able to produce effective solutions. We propose a graph reduction technique, namely the Graph Reduction Algorithm (GRA), which removes more than 90% of the nodes and edges from the input graph. Finally, using a Mixed-Integer Linear Programming (MILP) model, we present an exact approach, namely Reduced Integer Linear Programming Algorithm (RILP), that takes advantage of the heuristic CCDA and the GRA. Several tests were performed to verify the effectiveness of the proposed approaches. The computational results indicate that the produced approaches perform well, in terms of both the solution’s quality and computation times.

GSS-VF: A Game-Theoretic Approach for Service Discovery in Fog Network of Vehicles

Vehicular Fog Computing exploits the computing, caching and communication resources at vehicles to facilitate different location-based applications in a smart urban environment. Today, consumer vehicles can discover and consume available services from nearby vehicles, acting as provider vehicles in a fog network. However, it is challenging for the consumers to first identify, and then select the most appropriate service provider, given, high mobility, intermittent connectivity, and heterogeneous costs associated with provider vehicles, that dedicate their resources in facilitating the respective service to consumers. In this paper, we deal with the issue of selecting the best provider vehicles in an urban environment, considering both costs and Quality of Service (QoS) requirements for both the provider vehicles in the fog as well as the consumer vehicles. Hence, we design a new game theory-based distributed scheme, namely GSS-VF, to manage the service provisioning in a vehicular fog. It allows the consumers to select the most suitable Fog nodes based on their probability of interactions. GSS-VF addresses two questions: (i) What are the optimal conditions under which the consumers may request the Fog nodes for services? and (ii) How to select the most suitable service with respect to the consumers’ preferences? To evaluate GSS-VF, extensive simulations are performed using urban mobility model on 1,500 vehicles, results show that the designed scheme efficiently identifies and selects the most adequate service providers for consumers in the fog.

Performance Assessment for Increasing Connection Rates of Private Water Supply Operators in Cambodia

Private water supply operators (PWSOs) play an important role in extending piped water services in small cities in Cambodia. However, the connection rates to PWSOs are highly varied. Therefore, this study aimed to find the reasons for the low connection rates of PWSOs and to propose ways to increase the connection rates. The three PWSOs selected for this study supply water continuously, with sufficiently high pressure and good water quality except for the low concentration of residual chlorine, while the per capita supply volume varies significantly. Households with alternative water sources, namely rainwater and well water, consume less piped water than those without alternative water sources. Scattered service areas far away from water treatment plants had coverage rates that were lower than in compact service areas. The present connection costs and water tariffs are higher than those that non-connected households are willing to pay, though they pay high costs for bottled water. Due to the high variation in household income, connection fees and water tariffs are a financial burden for low-income households. Because the operating rates of the PWSOs are 21–47%, it is advised that PWSOs reduce their connection fees and water tariffs to obtain more connected households in their service areas.

Redox flow battery time‐varying parameter estimation based on high‐order sliding mode differentiators

A new insight into vanadium redox flow batteries (VRFB) parameter estimation is presented. Driven by the electric vehicles proliferation, a hybrid fast-charging station with grid and a renewable energy connection is particularly considered. In this stationary application, the VRFB is operating as buffering module. This hybrid topology could contribute to reduce the grid connection cost of the charging station. However, to make VRFB a viable technology, improvements are needed. Among these, some of the most important are in the field of the estimation of the battery's State of Charge, State of Health, and internal parameters. The proposed estimation method is based on a recursive least square (RLS) estimation algorithm with forgetting factor, combined with a sliding mode finite-time convergent differentiation algorithm. The latter provides robust exact derivatives of both VRFB's current and voltage with a high degree of noise rejection, required by the RLS algorithm to perform a precise estimation. The proposed sliding mode-based estimation setup is completed with a systematic methodology to guarantee the validity of the on-line estimated values, depending on the persistence of excitation of the measured current and voltage. Finally, the methodology is thoroughly analysed and validated by computer simulation.

Minimizing Probability Graph Connectivity Cost for Discontinuous Filamentary Structures Tracing in Neuron Image.

Neuron tracing from optical image is critical in understanding brain function in diseases. A key problem is to trace discontinuous filamentary structures from noisy background, which is commonly encountered in neuronal and some medical images. Broken traces lead to cumulative topological errors, and current methods were hard to assemble various fragmentary traces for correct connection. In this paper, we propose a graph connectivity theoretical method for precise filamentary structure tracing in neuron image. First, we build the initial subgraphs of signals via a region-to-region based tracing method on CNN predicted probability. CNN technique removes noise interference, whereas its prediction for some elongated fragments is still incomplete. Second, we reformulate the global connection problem of individual or fragmented subgraphs under heuristic graph restrictions as a dynamic linear programming function via minimizing graph connectivity cost, where the connected cost of breakpoints are calculated using their probability strength via minimum cost path. Experimental results on challenging neuronal images proved that the proposed method outperformed existing methods and achieved similar results of manual tracing, even in some complex discontinuous issues. Performances on vessel images indicate the potential of the method for some other tubular objects tracing.

Analisis Implementasi Konektivitas Indihome Untuk Pengguna Smart Meter PLN

Smart meters are an integration of ICT in energy meters. The smart meter has a two-way communication feature that allows the operator to read energy data remotely and in real-time. Carrying out remote and real-time monitoring raises several problems including connection costs, coverage area, and the quality of the connection. Based on this background, the formulation of the problem in this study is how to choose effective and efficient smart meter connectivity for customers and how the performance of IndiHome services in the implementation of PLN's smart meters. The purpose of this study is to provide a recommendation system for the selection of an effective connection and propose a new architecture for PLN smart meter customers. This is one of the Internet of things (IoT) implementations to save cost in the use of smart meters. The method used is a literature review, survey, data collection, develop a new architecture, as well as analysis and evaluation of the results. The results of this study indicate that the proposed new IndiHome architecture can send monitoring data from the PLN smart meter device remotely and in real-time and does not incur costs that burden customers.

Blended Learning, The International Chinese Learning Trend In Post-Pandemic Era

In the early days of the Covid-19 pandemic, Chinese online learning faced many challenges, including (1) poor internet connection and high internet costs; (2) low computational literacy of teachers; (3) limited interaction between teachers and students; (4) inappropriate teaching materials and methods; and (5) the lack of student discipline and the difficulty of providing assessments. However, these challenges have turned into opportunities for the rapid development of online Chinese learning over time. Academics in China predict that online Chinese learning will be maintained in the post-pandemic era, the blended learning will become a learning trend that is applied globally. This research is descriptive qualitative research with data collection techniques through literature study method and Forum Group Discussion (FGD). The result of this study is a description of the solution to the challenges of Chinese online learning globally during the pandemic, blended learning, and its implementation strategy in the post-pandemic era based on the “Chinese Proficiency Grading Standards for International Chinese Language Education” issued in 2021.

Hydro-conditioning: Advanced approaches for cost-effective water quality management in agricultural watersheds

Accurate simulation of landscape hydrological connectivity is pivotal for planning practices required for treating agricultural farm pollution. This study assesses the role of an advanced geospatial approach, namely, ‘hydro-conditioning’ employed for modifying Digital Elevation Models, termed hDEMs to replicate landscape hydrology by simulating continuous downslope flow through drainage structures such as bridges and culverts. The capabilities of manual and automated hDEMs in delineating optimal locations and water treatment potential of Best Management Practices (BMPs) in a typical agricultural watershed were evaluated. Parallel processing of both hDEMs revealed that ‘ground truthing’ plays a critical role in the accurate placement of breach lines for allowing water movement through digitally elevated surfaces. Outcomes guide the practitioners in selecting appropriate hDEM (manual or automated) depending on the complexity of modeled hydrological pathways, which is essential for planning BMPs in a cost-effective manner at different spatial scales. Modeling results show that hDEMs greatly influence hydrological connectivity, catchment boundaries, BMP locations, treatment capacities, and related costs. The accuracy of hDEMs was verified using a robust sub-basin scale validation approach. The study recommends a hybrid approach for utilizing the strengths of both, automated and manual hDEMs for efficient agricultural farm pollution in an economical manner.

The Connected Critical Node Problem

The Critical Node Problem is a well-known optimisation problem that aims to find the subset of nodes in a graph whose removal impacts the graph connectivity as much as possible according to a specific connectivity measure. In this work, we study a new version of the Critical Node Problem, which we call the Connected Critical Node Problem, where the set of the removed nodes has to form a connected subgraph. We consider three connectivity measures and provide complexity results and solution approaches for general graphs and specific classes of graphs such as graphs with bounded treewidth, trees and series-parallel graphs. We consider the Connected Critical Node Problem where the pairwise connectivity (related to the number of pairs of vertices still connected in the graph) is minimised. We prove that this problem is strongly NP-hard and inapproximable on general graphs and is polynomial-time solvable on graphs with bounded treewidth and with unit connection costs. Further, we prove the NP-hardness of the problem with arbitrary connection costs over trees and series-parallel graphs and derive dynamic programming algorithms. We extend our results to the problem variants that consider the minimisation of the largest connected component and the maximisation of the number of connected components (also called K-way Vertex Cut Problem). As side results, we provide new complexity results for the classic Critical Node Problem on series-parallel graphs.

Hardware Implementation of IoT based Smart Power Protection Unit for Power Distribution System

Power protection devices are deployed to protect assets while also providing a steady supply of electricity. The importance of a power protection unit is that it maintains the security of electrical consumers connected to the electrical supply grid by interrupting the power supply in the case of a variety of problems, including overvoltage, overcurrent, leakage current, and electrical arc. Power protection systems with Arduino uno board leads to attain decreased efficiency, increased cost of internal connectivity and poor network reliability. IoT based power protection devices can overcome these difficulties in a better way. This research provides a power-system protection device that can be integrated into smart environments and is based on Internet-of-Things technology. The proposed system improves safety by rapidly disabling the power supply in the event of a disaster such as a leakage current, an electrical arc, a power surge, or an overcharge, and it is designed to be incorporated into intelligent devices such as smart buildings or green infrastructure to protect electrical equipment.

Analysis of the actual electrical loads of public premises embedded in residential buildings

THE PURPOSE. With the help of data from smart electricity meters, an analysis of the profiles of electrical loads of commercial organizations that are part of apartment buildings was carried out. The results obtained are compared with their current standard values. New values of specific electrical loads for public premises are considered: pharmacies, grocery and manufactured goods stores, catering establishments, office premises.METHODS. Half-hour load profiles were obtained from intelligent electricity metering devices installed directly at the objects under study, data transmission was carried out by an automated electricity metering system. The observation intervals were several tens of days. To process the experimentally obtained data, statistical methods for the analysis of electrical loads were used.RESULTS. The article describes the relevance of the topic, presents the profiles of electrical loads of public premises with the highlighting of characteristic features separately for each group of electricity consumers. New specific design electrical loads are considered, including an analysis in comparison with existing standards.CONCLUSION. The calculated values of electrical power in order to ensure technological connection for public premises, including social and cultural facilities, must be updated, since today there is a significant difference between the actual and calculated according to regulatory documents electrical loads. Updating the specific design electrical loads of public premises will reduce the locked capacity of these facilities, at the same time reduce the cost of technological connection, thereby increasing the rating of the investment climate in the region.

Investigation of new layout design concepts of an array-on-device WaveSub device

Wave Energy Converters (WECs) have not yet proven their competitiveness in the mainstream energy market. Research and development of this technology are necessary to find optimal solutions in terms both of energy produced and reduced cost. A WEC farm is expected to have reduced Levelized Cost of Energy (LCoE) compared to individual devices due to shared installation and grid connection costs. Studies show that energy yield of a WEC array is highly dependent on spacing and layout of the WECs. A method for selecting an optimal array layout is desirable.Here we show a comparison between 4 different design layouts of a WaveSub device with six floats. A six float configuration has been chosen because the LCoE reduces with increasing floats per device as shown in previous research. An optimal configuration in terms of LCoE and rated power is found for linear, rectangle, triangle and circular multi-float configurations. Parameters optimised are float spacing and Power Take Off (PTO) stiffness, damping and rated power. The optimisation algorithm uses a genetic algorithm combined with a Kriging surrogate model. Numerical simulations are solved in the time-domain in WEC-Sim while the hydrodynamic coefficients are calculated in Nemoh using a linear potential flow theory.For all geometric configurations, the smallest float spacing was the most promising because of the lower cost of the structure. In fact, the influence of the float spacing on the power produced by the device is shown to be less significant than the influence of float spacing on the capital cost. Overall, the circular configuration outperformed the other configurations. This study shows that layout configurations can be investigated with optimisation and this could be applied to other configurations and other WEC concepts in future.

Joint exploitation potential of offshore wind and wave energy along the south and southeast coasts of China

There is an increasing interest in co-exploiting marine energies of various types, as it can reduce grid connection and maintenance costs and enhance electricity production. A threefold objective of this work is as follows: i) investigate offshore wind and wave energy potential, complementarity & synergy, and correlation between the two resources in southern China's coastal region using long-term data; ii) analyze the benefits of wind-wave joint exploitation considering specific offshore wind turbine (OWT) and wave energy converter (WEC); and iii) propose a new index to determine the suitability for co-developing wind-wave projects. The results show that the Beibu Gulf and Taiwan Strait experience the highest correlation between the two resources, in contrast to the Zhejiang coast that exhibits the lowest one. On the other hand, the east waters of Taiwan and Zhejiang coast have the highest synergy. Moreover, quantitative and qualitative analysis shows that the combined device generates less variable power output and zero production in the areas with low correlation and high synergy than the OWT/WEC operating alone. The suggested best sites for future joint exploitation are along the Zhejiang coast, with the potential of generating nearly 40 GWh/year per combined device of SWT-6.0-154 and 6 MW Wave Dargon.

Political connections, related party transactions and firm performance: evidence from Tunisian context

PurposeThe purpose of this paper is to examine the effect of the presence of political connections on firm performance through related party transactions in Tunisia, a country where that is characterized by the Jasmin revolution in 2011.Design/methodology/approachThe study uses a sample of nonfinancial firms between 2008 and 2014 listed on the Tunis Stock Exchange and uses generalized least squares on panel data.FindingsFirst, the political connection and related parties' transaction enhances firm's market performance. Second, the study reveals that political connection moderates the relationship between the related party transactions and firm performance only in the period after revolution. Indeed, politicians seem to have used related party transactions to expropriate firms in a period of political instability. Finally, we show that politicians are more attracted by firms with higher market performance and with higher number of related parties' transactions.Practical implicationsThe empirical findings contribute to the current debate on the benefits and costs of political connections in emerging economies. It shows that political connections enhance market valuation of firms. However, political connection costs appear during political instability period.Originality/valueThis study addresses the interaction between related party transactions, political connections and firm performance. It is the first study to test if the related party transactions are used as a tool by politicians to expropriate firms.

Online Teaching and Learning at Primary School During COVID-19 Pandemic

This study intends to explore Indonesian primary school teachers' and parents' perceptions of online learning and teaching in the COVID-19 pandemic situations. Particularly, this study intends to identify the significant challenges encountered by the Indonesian teachers and students' parents during the sudden shift of teaching and learning. Semi-structured interviews with a series of open-ended questions were used to collect information. Eleven teachers and students' parents from public high schools in Gorontalo province participated in this study. The results indicate that lack of technological devices and the cost of internet data connections are among the problems faced by teachers and parents. Ultimately, several recommendations were suggested for better action and successful implementation of online learning, particularly in underdeveloped areas in the eastern part of Indonesia.

Drone Charging Stations Deployment in Rural Areas for Better Wireless Coverage: Challenges and Solutions

While fifth-generation (5G) cellular is meant to deliver gigabit peak data speeds, low latency, and connection to billions of devices, and 6G is already on the way, half of the world population living in rural areas are still facing challenges connecting to the internet. Compared to urban areas, users in rural areas are greatly impacted by low income, high cost of backhaul connectivity, limited resources, extreme weather, and natural geographical limitations. Therefore, how to connect the rural areas and the difficulties of providing connectivity draw great attention. This article first provides a brief discussion about existing technologies and strategies for enhancing the network coverage in rural areas, and their advantages, limitations, and cost. Next, we mainly focus on the UAV-assisted network in resource-limited regions. Considering the limitation of the onboard battery of UAVs and the electricity supply scarcity in some rural regions, we investigate the possibility and performance enhancement of the deployment of renewable energy (RE) charging stations. We outline three practical scenarios, and use simulation results to demonstrate that RE charging stations can be a possible solution to address the limited onboard battery of UAVs in rural areas, especially when they can harvest and store enough energy. Finally, future works and challenges are discussed.

An Albatross On the Neck: Social Media Use and Its Effects on Students’ Academic Performance in Ghana: A Comparative Study

This study aimed to examine social media usage and its effects on students' academic performance. The study adopted a survey design approach. The population for this study consisted of undergraduate students from two universities, thus, one private university (Valley View University – VVU) in Techiman in the Bono Region and one public university (Ghana Communications Technology University) in Takoradi, in the Western Region. The study used 5% of the population to arrive at a sample size of 381. The stratified and simple random sampling techniques were applied to select the students. A well–structured questionnaire was used as a data collection instrument. The study established that social media had negatively affected their English writing skills, which is detrimental to their academic performance. The results showed that most students visited social media platforms daily and spent more time on these platforms. The study identified challenges like; lack of personal security and privacy, poor internet services, unreliable power, the cost of internet connectivity, and many others. The study made recommendations to the management of both universities to organise workshops and seminars and educate students on the dangers of excessive use of social media platforms.