Search results for: cloud radio access network

Authors: Adedoyin Opeyemi Osokoya

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The study assesses the influence of social media on perceived learning outcome of agricultural science students in tertiary institutions in Oyo state, Nigeria. The four-stage sampling procedure was used to select participants. All students in the seven tertiary institutions that offer agriculture science as a course of study in Oyo State was the population. A university, a college of agriculture and a college of education were sampled, and a department from each was randomly selected. Twenty percent of the students’ population in the respective selected department gave a sample size of 165. Questionnaire was used to collect information on respondents’ personal characteristics and information related to access to social media. Data were analysed using descriptive statistics, chi-square, correlation, and multiple regression at the 0.05 confidence level. Age and household size were 21.13 ± 2.64 years and 6 ± 2.1 persons respectively. All respondents had access to social media, majority (86.1%) owned Android phone, 57.6% and 52.7% use social media for course work and entertainment respectively, while the commonly visited sites were WhatsApp, Facebook, Google, Opera mini. Over half (53.9%) had an unfavourable attitude towards the use of social media for learning; benefits of the use of social media for learning was high (56.4%). Removal of information barrier created by distance (x̄=1.58) was the most derived benefit, while inadequate power supply (x̄=2.36), was the most severe constraints. Age (β=0.23), sex (β=0.37), ownership of Android phone (β=-1.29), attitude (β=0.37), constraints (β =-0.26) and use of social media (β=0.23) were significant predictors of influence on perceived learning outcomes.

Keywords: use of social media, agricultural science students, undergraduates of tertiary institutions, Oyo State of Nigeria

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Authors: Sanjeev Kumar Sharma, Arnab Mondal, Ranjit Kumar Upadhyay

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Excitable cells often produce different oscillatory activities that help us to understand the transmitting and processing of signals in the neural system. We consider a FitzHugh-Rinzel (FH-R) model and studied the different dynamics of the model by considering the parameter c as the predominant parameter. The model exhibits different types of neuronal responses such as regular spiking, mixed-mode bursting oscillations (MMBOs), elliptic bursting, etc. Based on the bifurcation diagram, we consider the three regimes (MMBOs, elliptic bursting, and quiescent state). An analytical treatment for the occurrence of the supercritical Hopf bifurcation is studied. Further, we extend our study to a network of a hundred neurons by considering the bi-directional synaptic coupling between them. In this article, we investigate the alternation of spiking propagation and bursting phenomena of an uncoupled and coupled FH-R neurons. We explore that the complete graph of heterogenous desynchronized neurons can exhibit different types of bursting oscillations for certain coupling strength. For higher coupling strength, all the neurons in the network show complete synchronization.

Keywords: excitable neuron model, spiking-bursting, stability and bifurcation, synchronization networks

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Authors: Dong-Hyun Ha, Young-Min Ko, Chang-Bin Ha, Hyoung-Kyu Song

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In Heterogeneous network (HetNet) can provide high quality of a service in a wireless communication system by composition of small cell networks. The composition of small cell networks improves cell coverage and capacity to the mobile users.Recently, various techniques using small cell networks have been researched in the wireless communication system. In this paper, the cooperative scheme obtaining high reliability is proposed in the small cell networks. The proposed scheme suggests a cooperative small cell system and the new signal transmission technique in the proposed system model. The new signal transmission technique applies a cyclic delay diversity (CDD) scheme based on the multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) system to obtain improved performance. The improved performance of the proposed scheme is confirmed by the simulation results.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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Authors: I. Grigoratos, R. Monteiro

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Regions with a significant percentage of non-seismically designed buildings and reduced urban planning are particularly vulnerable to natural hazards. In this context, the project ‘Improved Tools for Disaster Risk Mitigation in Algeria’ (ITERATE) aims at seismic risk mitigation in Algeria. Past earthquakes in North Algeria caused extensive damages, e.g. the El Asnam 1980 moment magnitude (Mw) 7.1 and Boumerdes 2003 Mw 6.8 earthquakes. This paper will address a number of proposed developments and considerations made towards a further improvement of the component of seismic hazard. In specific, an updated earthquake catalog (until year 2018) is compiled, and new conversion equations to moment magnitude are introduced. Furthermore, a network-based method for the estimation of the spatial and temporal distribution of the minimum magnitude of completeness is applied. We found relatively large values for M_c, due to the sparse network, and a nonlinear trend between M_w and body wave (m_b) or local magnitude (M_L), which are the most common scales reported in the region. Lastly, the resulting b-value of the Gutenberg-Richter distribution is sensitive to the declustering method.

Keywords: conversion equation, magnitude of completeness, seismic events, seismic hazard

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Authors: Khalid Al-Snaie

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In this paper, the design and the testing of a symmetrical radiofrequency prototype coil with high B₁ magnetic field homogeneity are presented. The developed coil comprises four tuned coaxial circular loops that can produce a relatively homogeneous radiofrequency field. In comparison with a standard Helmholtz pair that provides 2nd-order homogeneity, it aims to provide fourth-order homogeneity of the B₁ field while preserving the simplicity of implementation. Electrical modeling of the probe, including all couplings, is used to ensure these requirements. Results of comparison tests, in free space and in a spectro-imager, between a standard Helmholtz pair and the presented prototype coil are introduced. In terms of field homogeneity, an improvement of 30% is observed. Moreover, the proposed prototype coil possesses a better quality factor (+25% on average) and a noticeable improvement in sensitivity (+20%). Overall, this work, which includes both theoretical and experimental aspects, aims to contribute to the study and understanding of four-element radio frequency (RF) systems derived from Helmholtz coils for Magnetic Resonance Imaging

Keywords: B₁ homogeneity, MRI, NMR, radiofrequency, RF coil, free element systems

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Authors: Michael Nthabiseng Moeti, Makhulu Relebogile Langa, Joey Jansen van Vuuren

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This paper examines the utilization of personal electronic devices like laptops, tablets, and smartphones for professional duties within a financial organization. This phenomenon is known as bring your own device (BYOD). BYOD accords employees the freedom to use their personal devices to access corporate resources from anywhere in the world with Internet access. BYOD arrangements introduce significant security risks for both organizations and users. These setups change the threat landscape for enterprises and demand unique security strategies, as conventional tools tailored for safeguarding managed devices fall short in adequately protecting enterprise assets without active user cooperation. This paper applies protection motivation theory (PMT) to highlight behavioral risks from BYOD users that may impact the security of financial institutions. Thematic analysis was applied to gain a comprehensive understanding of how users perceive this phenomenon. These findings demonstrates that the existence of a security policy does not ensure that all employees will take measures to protect their personal devices. Active promotion of BYOD security policies is crucial for financial institution employees and management. This paper developed a BYOD security model which is useful for understanding compliant behaviors. Given that BYOD security is becoming a major concern across financial sector, it is important. The paper recommends that future research could expand the number of universities from which data is collected.

Keywords: BYOD, information security, protection motivation theory, security risks, thematic analysis

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Authors: Hafida Ferfera-Harrar, Nacera Aiouaz, Nassima Dairi

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Super absorbents polymers received much attention and are used in many fields because of their superior characters to traditional absorbents, e.g., sponge and cotton. So, it is very important but challenging to prepare highly and fast-swelling super absorbents. A reliable, efficient and low-cost technique for removing heavy metal ions from waste water is the adsorption using bio-adsorbents obtained from biological materials, such as polysaccharides-based hydrogels super absorbents. In this study, novel multi-functional super absorbent composites type semi-interpenetrating polymer networks (Semi-IPNs) were prepared via graft polymerization of acrylamide onto chitosan backbone in presence of gelatin, CTS-g-PAAm/Ge, using potassium persulfate and N,N’ -methylenebisacrylamide as initiator and cross linker, respectively. These hydrogels were also partially hydrolyzed to achieve superabsorbents with ampholytic properties and uppermost swelling capacity. The formation of the grafted network was evidenced by Fourier Transform Infrared Spectroscopy (ATR-FTIR) and thermo gravimetric Analysis (TGA). The porous structures were observed by Scanning Electron Microscope (SEM). From TGA analysis, it was concluded that the incorporation of the Ge in the CTS-g-PAAm network has marginally affected its thermal stability. The effect of gelatin content on the swelling capacities of these super absorbent composites was examined in various media (distilled water, saline and pH-solutions).The water absorbency was enhanced by adding Ge in the network, where the optimum value was reached at 2 wt. % of Ge. Their hydrolysis has not only greatly optimized their absorption capacity but also improved the swelling kinetic. These materials have also showed reswelling ability. We believe that these super-absorbing materials would be very effective for the adsorption of harmful metal ions from waste water.

Keywords: chitosan, gelatin, superabsorbent, water absorbency

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Authors: Yosi Maria Wijaya, Florisma Arista Riti Tegu

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Background: Hypertension in pregnancy can be prevented by controlling the lifestyle. However, the majority of research on this topic has been conducted on lifestyle in women with normal pregnancy. Few studies of lifestyle have focused on Indonesian pregnant women with hypertension. Aim: The purpose of this study is to determine the association of demographic characteristics and the lifestyle of pregnant women who have hypertension. Methods: In this cross-sectional study, 76 women with hypertension during pregnancy were recruited from primary health care, West Java, Indonesia. Inclusion criteria were gestational age ≥ 28 weeks with the blood pressure systole ≥ 140 mmHg and diastole ≥ 90 mmHg. Data were collected using two instruments: demographic data and Health Promoting Life Style Profile (HPLP II). Data were analyzed with descriptive statistic and linear regression analysis. Results: The majority of participants were married, mean age was 27.96 years old (SD=6.77) with the mean of gestational age 33.21 (SD=3.49), most of them unemployed (94.7%) and more than a half participants have an education less than twelve years (59.2%). The total score of lifestyle was 2.44 (SD=0.34), more than a half participants experience unhealthy lifestyle (59.2%). Lifestyle was predicted by income, education years, occupation, and access to health care services, accounting for 20.8% of the total variance. Conclusion: Pregnant women with hypertension with low income, low level of education, non-occupational and hard to access health care services were related to unhealthy lifestyle. Understanding the lifestyle and associated factors contributes to health care providers ability to design effective interventions intended to improve healthy lifestyle among pregnant women with hypertension.

Keywords: demographic characteristics, hypertension, lifestyle, pregnancy

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Abdulah Fajar

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Electronic Procurement System has been implemented at government institution in Indonesia. This system has been developed centrally at Institution of National Procurement Policy (LKPP) and implemented autonomously at either local or national government institution. The lack of competency at many institution on Information Technology Management arise several major problems. The main concern of LKPP to local administrator is assured that the system is running normally and always be able to serve the needs of its users. Monitoring system has been identified as the one of solution to prevent the problems appeared. Monitoring system is developed using Simple Network Management Protocol (SNMP) and implemented at LKPP. There are two modules; Main Dashboard and Local Agent. Main Dashboard is intended for LKPP and Local Agent is intended to implement at local autonomous e-procurement system (LPSE). There are several resources that must be monitored such as computation, memory and network traffic. Agile paradigm is applied to this project to assure user and system requirement is met. The length of project is the one of reason why agile paradigm has been chosen. The system has been successfully delivered to LKPP.

Keywords: procurement system, SNMP, LKPP, LPSE

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Authors: M. Boudjerda, B. Touaibia, M. K. Mihoubi

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In Algeria agricultural irrigation is the primary water consuming sector followed by the domestic and industrial sectors. Economic development in the last decade has weighed heavily on water resources which are relatively limited and gradually decreasing to the detriment of agriculture. The research presented in this paper focuses on the optimization of irrigation water demand. Dynamic Programming-Neural Network (DPNN) method is applied to investigate reservoir optimization. The optimal operation rule is formulated to minimize the gap between water release and water irrigation demand. As a case study, Foum El-Gherza dam’s reservoir system in south of Algeria has been selected to examine our proposed optimization model. The application of DPNN method allowed increasing the satisfaction rate (SR) from 12.32% to 55%. In addition, the operation rule generated showed more reliable and resilience operation for the examined case study.

Keywords: water management, agricultural demand, dam and reservoir operation, Foum el-Gherza dam, dynamic programming, artificial neural network

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Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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Carefully scheduling the operations of pumps can be resulted to significant energy savings. Schedules can be defined either implicit, in terms of other elements of the network such as tank levels, or explicit by specifying the time during which each pump is on/off. In this study, two new explicit representations based on time-controlled triggers were analyzed, where the maximum number of pump switches was established beforehand, and the schedule may contain fewer switches than the maximum. The optimal operation of pumping stations was determined using a Jumping Particle Swarm Optimization (JPSO) algorithm to achieve the minimum energy cost. The model integrates JPSO optimizer and EPANET hydraulic network solver. The optimal pump operation schedule of VanZyl water distribution system was determined using the proposed model and compared with those from Genetic and Ant Colony algorithms. The results indicate that the proposed model utilizing the JPSP algorithm outperformed the others and is a versatile management model for the operation of real-world water distribution system.

Keywords: JPSO, operation, optimization, water distribution system

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Authors: Sofia Dokuka, Liz Lockhart, Alex Furman

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Organizational hierarchy, traditionally composed of individual contributors, middle management, and executives, is enhanced by the understanding of informal social roles. These roles, identified with organizational network analysis (ONA), might have an important effect on organizational functioning. In this paper, we identify three social roles – influencers, bridges, and soloists, and provide empirical analysis based on real-world organizational networks. Influencers are employees with broad networks and whose contacts also have rich networks. Influence is calculated using PageRank, initially proposed for measuring website importance, but now applied in various network settings, including social networks. Influencers, having high PageRank, become key players in shaping opinions and behaviors within an organization. Bridges serve as links between loosely connected groups within the organization. Bridges are identified using betweenness and Burt’s constraint. Betweenness quantifies a node's control over information flows by evaluating its role in the control over the shortest paths within the network. Burt's constraint measures the extent of interconnection among an individual's contacts. A high constraint value suggests fewer structural holes and lesser control over information flows, whereas a low value suggests the contrary. Soloists are individuals with fewer than 5 stable social contacts, potentially facing challenges due to reduced social interaction and hypothetical lack of feedback and communication. We considered social roles in the analysis of real-world organizations (N=1,060). Based on data from digital traces (Slack, corporate email and calendar) we reconstructed an organizational communication network and identified influencers, bridges and soloists. We also collected employee engagement data through an online survey. Among the top-5% of influencers, 10% are members of the Executive Team. 56% of the Executive Team members are part of the top influencers group. The same proportion of top influencers (10%) is individual contributors, accounting for just 0.6% of all individual contributors in the company. The majority of influencers (80%) are at the middle management level. Out of all middle managers, 19% hold the role of influencers. However, individual contributors represent a small proportion of influencers, and having information about these individuals who hold influential roles can be crucial for management in identifying high-potential talents. Among the bridges, 4% are members of the Executive Team, 16% are individual contributors, and 80% are middle management. Predominantly middle management acts as a bridge. Bridge positions of some members of the executive team might indicate potential micromanagement on the leader's part. Recognizing the individuals serving as bridges in an organization uncovers potential communication problems. The majority of soloists are individual contributors (96%), and 4% of soloists are from middle management. These managers might face communication difficulties. We found an association between being an influencer and attitude toward a company's direction. There is a statistically significant 20% higher perception that the company is headed in the right direction among influencers compared to non-influencers (p < 0.05, Mann-Whitney test). Taken together, we demonstrate that considering social roles in the company might indicate both positive and negative aspects of organizational functioning that should be considered in data-driven decision-making.

Keywords: organizational network analysis, social roles, influencer, bridge, soloist

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Authors: Lyamine Guezouli, Kamel Barka, Zineb Seghir

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Wireless sensor and actor networks (WSANs) present a research challenge for different practice areas. Researchers are trying to optimize the use of such networks through their research work. This optimization is done on certain criteria, such as improving energy efficiency, exploiting node heterogeneity, self-adaptability and self-configuration. In this article, we present our proposal for BIFSA (Biologically-Inspired Framework for Wireless Sensor and Actor networks). Indeed, BIFSA is a middleware that addresses the key issues of wireless sensor and actor networks. BIFSA consists of two types of agents: sensor agents (SA) that operate at the sensor level to collect and transport data to actors and actor agents (AA) that operate at the actor level to transport data to base stations. Once the sensor agent arrives at the actor, it becomes an actor agent, which can exploit the resources of the actors and vice versa. BIFSA allows agents to evolve their genetic structures and adapt to the current network conditions. The simulation results show that BIFSA allows the agents to make better use of all the resources available in each type of node, which improves the performance of the network.

Keywords: wireless sensor and actor networks, self-management, genetic algorithm, agent.

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Authors: Long Cheng, Tong He, Iraj Mantegh, Wen-Fang Xie

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Path planning is essential for UAVs (Unmanned Aerial Vehicle) with autonomous navigation in unknown environments. In this paper, an adaptive probabilistic sampling algorithm is proposed for the GPS-denied environment, which can be utilized for autonomous navigation system of multiple UAVs in a dynamically-changing structured environment. This method can be used for Unmanned Aircraft Systems Traffic Management (UTM) solutions and in autonomous urban aerial mobility, where a number of platforms are expected to share the airspace. A path network is initially built off line based on available environment map, and on-board sensors systems on the flying UAVs are used for continuous situational awareness and to inform the changes in the path network. Simulation results based on MATLAB and Gazebo in different scenarios and algorithms performance measurement show the high efficiency and accuracy of the proposed technique in unknown environments.

Keywords: path planning, adaptive probabilistic sampling, obstacle avoidance, multiple unmanned aerial vehicles, unknown environments

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Authors: Oduntan Oluwakemi, Obisesan Adekemi Adebisola, Ayo-Bello Taofeeq Ayodeji

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The study examined the factors influencing the adoption of climate-smart agricultural practices among maize farmers in Ondo State, Nigeria. A Multi-stage sampling procedure was used to randomly select one hundred respondents for the study. Primary data were collected from the respondents with the aid of a structured questionnaire and analysed using descriptive statistics and a probit regression model. The results of this study showed that crop diversification was the most adopted climate-smart agricultural practice by the respondents, and adoption of Climate Smart Agricultural practices is still very low among the respondents. Results of probit regression revealed that marital status, access to extension services, farming experience, membership of farmers’ association, and access to credit had a positive influence on the adoption of climate-smart agricultural practices, while age, farm size, and total income had a negative influence. Based on the findings of the study, it was recommended that government should develop suitable policies that will encourage farmers, especially rural farmers, to adopt and utilize Climate Smart Agricultural Practices (CSAP). Equally, the study also recommended government should be geared towards supporting improved extension services, providing on-farm demonstration training, disseminating information about climate-smart agricultural practices, and providing credit facilities through the Agricultural Credit Guarantee Scheme Fund and bank credit to farmers in order to enhance the adoption.

Keywords: adoption, agriculture, climate-smart, farmers, maize, Nigeria

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Authors: Deepika Christopher, Garima Anand

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To determine the best model for churn prediction in the telecom industry, this paper compares 11 machine learning algorithms, namely Logistic Regression, Support Vector Machine, Random Forest, Decision Tree, XGBoost, LightGBM, Cat Boost, AdaBoost, Extra Trees, Deep Neural Network, and Hybrid Model (MLPClassifier). It also aims to pinpoint the top three factors that lead to customer churn and conducts customer segmentation to identify vulnerable groups. According to the data, the Logistic Regression model performs the best, with an F1 score of 0.6215, 81.76% accuracy, 68.95% precision, and 56.57% recall. The top three attributes that cause churn are found to be tenure, Internet Service Fiber optic, and Internet Service DSL; conversely, the top three models in this article that perform the best are Logistic Regression, Deep Neural Network, and AdaBoost. The K means algorithm is applied to establish and analyze four different customer clusters. This study has effectively identified customers that are at risk of churn and may be utilized to develop and execute strategies that lower customer attrition.

Keywords: attrition, retention, predictive modeling, customer segmentation, telecommunications

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Authors: Kidist Mesfin Nguse

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Ethiopia is the second most densely populated nation in Africa, and about 121 million people as the 2022 Ethiopia population live report recorded. In recent years, the Ethiopian government (GOE) has been gradually growing its road network. With 138,127 kilometers (85,825 miles) of all-weather roads as of the end of 2018–19, Ethiopia possessed just 39% of the nation's necessary road network and lacked a well-organized system. The Ethiopian urban population report recorded that about 21% of the population lives in urban areas, and the high population, coupled with growth in various infrastructures, has led to the migration of the workforce from rural areas to cities across the country. In main roads, the heterogeneous traffic flow with various operational features makes it more unfavorable, causing frequent congestion in the stretch of road. The Level of Service (LOS), a qualitative measure of traffic, is categorized based on the operating conditions in the traffic stream. Determining the capacity and LOS for this city is very crucial as this affects the planning and design of traffic systems and their operation, and the allocation of route selection for infrastructure building projects to provide for a considerably good level of service.

Keywords: capacity, level of service, traffic volume, free flow speed

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Authors: Victor Emery David Jr., Jiang Wenchao, Daniel Mmereki, Yasinta John

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The fundamentals of public health are access to safe and clean drinking water. The presence of arsenic and other contaminants in drinking water leads to the potential risk to public health and the environment particularly in most developing countries where there’s inadequate access to safe and clean water and adequate sanitation. Liberia has taken steps to improve its drinking water status so as to achieve the Sustainable Development Goals (SDGs) target of ensuring clean water and effective sanitation but there is still a lot to be done. The Sustainable Development Goals are a United Nation initiative also known as transforming our world: The 2030 agenda for sustainable development. It contains seventeen goals with 169 targets to be met by respective countries. Liberia is situated within in the gold belt region where there exist the presence of arsenic and other contaminants in the underground water due to mining and other related activities. While there are limited or no epidemiological studies conducted in Liberia to confirm illness or death as a result of arsenic contamination in Liberia, it remains a public health concern. This paper assesses the drinking water quality, the presence of arsenic in groundwater/drinking water in Liberia, and proposes strategies for mitigating contaminants in drinking water and suggests options for improvement with regards to achieving the Sustainable Development Goals of ensuring clean water and effective sanitation in Liberia by 2030.

Keywords: arsenic, action plan, contaminants, environment, groundwater, sustainable development goals (SDGs), Monrovia, Liberia, public health, drinking water

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Authors: L. J. de Bessa Neto, M. R. B. Guerra Vale, F. K. O. M. Varella Guerra

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In recent years, solar energy has established itself as one of the main sources of renewable energy, gaining a large space in electricity generation around the world. However, due to the low performance of photovoltaic panels, technologies need to be sought to maximize the production of electricity. In this regard, the present study aims to develop a prototype of solar tracker for didactics applications, controlled with the Arduino® platform, that enables the movement of photovoltaic plates in relation to the sun positions throughout the day through an electromechanical system, optimizing, thus, the efficiency of solar photovoltaic generation and improvements for the photovoltaic effect. The solar tracking technology developed in this work was presented of the shape oral and practical in two middle schools in the municipality of Mossoró/RN, being one of the public network and other of the private network, always keeping the average age of the students, in the case, around 16 years, contemplating an average of 60 students in each of the visits. Thus, it is concluded that the present study contributed substantially to the dissemination of knowledge concerning the photovoltaic solar generation, as well as the study of solar trackers, thus arousing the interest and curiosity of the students regarding the thematic approached.

Keywords: alternative energy, solar tracker, energy efficiency, photovoltaic panels

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Authors: Navneet Kaur, Amarpreet Singh

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In Vehicular Adhoc Networks, Data Dissemination is a challenging task. There are number of techniques, types and protocols available for disseminating the data but in order to preserve limited bandwidth and to disseminate maximum data over networks makes it more challenging. There are broadcasting, multicasting and geocasting based protocols. Multicasting based protocols are found to be best for conserving the bandwidth. One such protocol named BEAM exists that improves the performance of Vehicular Adhoc Networks by reducing the number of in-network message transactions and thereby efficiently utilizing the bandwidth during an emergency situation. But this protocol may result in multicar chain collision as there was no V2V communication. So, this paper proposes a new protocol named Enhanced Bandwidth Efficient Cluster Based Multicasting Protocol (EBECM) that will overcome the limitations of existing BEAM protocol. And Simulation results will show the improved performance of EBECM in terms of Routing overhead, throughput and PDR when compared with BEAM protocol.

Keywords: BEAM, data dissemination, emergency situation, vehicular adhoc network

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Authors: Hasan Farahneh

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Smart asset management along roadsides and in deserted areas is a topic of deprived attention. We find most of the work in emergency reporting services in intelligent transportation systems (ITS) and rural areas but not much in asset reporting. Currently, available asset management mechanisms are based on scheduled maintenance and do not effectively report any emergency situation in a timely manner. This paper is the continuation of our previous work, in which we proposed the usage of Foglets and VLC link between smart vehicles and road side assets. In this paper, we propose a hybrid communication system for asset management and emergency reporting architecture for smart transportation. We incorporate Foglets along with visible light communication (VLC) and radio frequency (RF) communication. We present the channel model and parameters of a hybrid model to support an intelligent transportation system (ITS) system. Simulations show high improvement in the system performance in terms of communication range and received data. We present a comparative analysis of a hybrid ITS system.

Keywords: Internet of Things, Foglets, VLC, RF, smart vehicle, roadside asset management

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Authors: H. Scholz, P. Kuehne, G. Heckenberger

Abstract:

Dietary Anion-Cation Balance (DCAB) in grazing systems under German conditions has a tendency to decrease from May until September and often are measured DCAB lower than 100 meq per kg dry matter. Lower DCAB in grass feeding system can change the metabolic status of suckler cows and often are results in acidotic metabolism. Measurement of acid-base excretion in dairy cows has been proved to a method to evaluate the acid-base status. The hypothesis was that metabolic imbalances could be identified by urine measurement in suckler cows. The farm study was conducted during the grazing seasons 2017 and 2018 and involved 7 suckler cow farms in Germany. Suckler cows were grazing during the whole time of the investigation and had no access to other feeding components. Cows had free access to water and salt block and free access to minerals (loose). The dry matter of the grass was determined at 60 °C and were then analysed for energy and nutrient content and for the Dietary Cation-Anion Balance (DCAB). Urine was collected in 50 ml-glasses and analysed for net acid-base excretion (NSBA) and the concentration of creatinine and urea in the laboratory. Statistical analysis took place with ANOVA with fixed effects of farms (1-7), month (May until September), and number of lactations (1, 2, and ≥ 3 lactations) using SPSS Version 25.0 for windows. An alpha of 0.05 was used for all statistical tests. During the grazing periods of years 2017 and 2018, an average DCAB was observed in the grass of 167 meq per kg DM. A very high mean variation could be determined from -42 meq/kg to +439 meq/kg. Reference values in relation to DCAB were described between 150 meq and 400 meq per kg DM. It was found the high chlorine content with reduced potassium level led to this reduction in DCAB at the end of the grazing period. Between the DCAB of the grass and the NSBA in urine of suckler cows was a correlation according to PEARSON of r = 0.478 (p ≤ 0.001) or after SPEARMAN of r = 0.601 (p ≤ 0.001) observed. For the control of urine values of grazing suckler cows, the wide spread of the values poses a challenge of the interpretation, especially since the DCAB is unknown. The influence of several feeding components such as chlorine, sulfur, potassium, and sodium (ions for the DCAB) and dry matter feed intake during the grazing period of suckler cows should be taken into account in further research. The results obtained show that up a decrease in the DCAB is related to a decrease in NSBA in urine of suckler cows. Monitoring of metabolic disturbances should include analysis of urine, blood, milk, and ruminal fluid.

Keywords: dietary anion-cation balance, DCAB, net acid-base excretion, NSBA, suckler cow, grazing period

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Authors: Tamás Hartványi, Ferenc Tóth

Abstract:

European telecommunication distribution center performance is measured by service lead time and quality. Operation model is CTO (customized to order) namely, a high mix customization of telecommunication network equipment and parts. CTO operation contains material receiving, warehousing, network and server assembly to order and configure based on customer specifications. Variety of the product and orders does not support mass production structure. One of the success factors to satisfy customer is to have a proper aggregated planning method for the operation in order to have optimized human resources and highly efficient asset utilization. Research will investigate several methods and find proper way to have an order book simulation where practical optimization problem may contain thousands of variables and the simulation running times of developed algorithms were taken into account with high importance. There are two operation research models that were developed, customer demand is given in orders, no change over time, customer demands are given for product types, and changeover time is constant.

Keywords: CTO, aggregated planning, demand simulation, changeover time

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Authors: Huinan Zhang, Wenjie Jiang

Abstract:

Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Lisa Mockli, Chelsea Sambells

Abstract:

By combining the methodologies of history and translation studies, this study will explore the interplay between humanitarian action, politics, and translation within the advertising for a lesser-known Swiss child evacuation project of some 60.000 Belgium and French children to Switzerland for three month periods from 1940 to 1945. Inspired by Descriptive-Explanatory Translation Studies, this project compares Swiss speeches published between May and September 1942 (the termination of the evacuations). Radio broadcasts, leaflets and newspapers will triangulate the data. First, linguistic and content-related differences will be identified and described. Second, based on findings from the Swiss Federal Archives, the evidence from the comparative textual analysis will then be evaluated in order to explore how the speeches were modified, for what purpose, and which key issues were raised during their modification. By exploring these questions, this paper provides new insights into (I) Switzerland’s understanding of Swiss neutrality and humanitarianism during the Second World War, (II) the role of children in war and (III) the role of translation in shaping political discourse and humanitarian action. Moreover, this interdisciplinary approach also demonstrates how scholarly collaboration may help to make some elements of humanitarian action more self-reflexive and effective.

Keywords: children, history, humanitarianism, politics, translation

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Authors: Hong Su, Qiuju Yan, Wei Du, En Hu, Zhaoyu Yang, Wei Zhang, Yusheng Li, Tao Tang, Wang yang, Shushan Zhao

Abstract:

Osteoarthritis (OA) is a severe chronic inflammatory disease. As the main active component of Astragalus mongholicus Bunge, a classic traditional ethnic herb, calycosin exhibits anti-inflammatory action and its mechanism of exact targets for OA have yet to be determined. In this study, we established an anterior cruciate ligament transection (ACLT) mouse model. Mice were randomized to sham, OA, and calycosin groups. Cartilage synthesis markers type II collagen (Col-2) and SRY-Box Transcription Factor 9 (Sox-9) increased significantly after calycosin gavage. While cartilage matrix degradation index cyclooxygenase-2 (COX-2), phosphor-epidermal growth factor receptor (p-EGFR), and matrix metalloproteinase-9 (MMP9) expression were decreased. With the help of network pharmacology and molecular docking, these results were confirmed in chondrocyte ATDC5 cells. Our results indicated that the calycosin treatment significantly improved cartilage damage, this was probably attributed to reversing the imbalance between chondrocyte synthesis and catabolism.

Keywords: calycosin, osteoarthritis, network pharmacology, molecular docking, inflammatory, cyclooxygenase 2

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Authors: Bassem Boshra Thabet, Mohammed Ibrahim Elsabagh, Mohammad Adly Talaat

Abstract:

The number of cellular mobile phone users has increased enormously worldwide over the last two decades. Consequently, the monitoring of the performance of the Mobile Network Operators (MNOs) in terms of network coverage and broadband signal strength has become vital for both of the MNOs and regulators. This monitoring helps telecommunications operators and regulators keeping the market playing fair and most beneficial for users. However, the adopted methodologies to facilitate this continuous monitoring process are still problematic regarding cost, effort, and reliability. This paper introduces My Operator Coverage (MOC) system that is using Internet of Things (IoT) concepts and tools to monitor the MNOs performance using a crowd-sourced real-time methodology. MOC produces robust and reliable geographical maps for the user-perceived quality of the MNOs performance. MOC is also meant to enrich the telecommunications regulators with concrete, and up-to-date information that allows for adequate mobile market management strategies as well as appropriate decision making.

Keywords: mobile performance monitoring, crowd-sourced applications, mobile broadband performance, cellular networks monitoring

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Authors: Tulsi Ram Bhusal

Abstract:

Global climate change is known to have a huge impact on agriculture due to changing in rainfall pattern and elevated air temperature that lead to drought and/or flooding. This systematic study has focused on agriculture in Nepal. The study has shown that the trend of current climatic change is affecting rice production, while the farmers with technological access have tried to adapt to the changing conditions at their level. There is insufficient intervention from the government side in terms of policies and schemes. The lack of sufficient funds is one of the significant reasons in terms of governance. The climatic trends and the way it is affecting the annual riceyieldinNepal has been discussed in this study thoroughly. This study has reviewed published studies and ferred important points regarding the Nepal’s status on rice production. Mainly due to the increasing graph of average temperature and other physical conditions needed for the proper cultivation of ricearechanging due to which there is significant dropofannual rice production. Although from corners of the country, many farmers have attempted to adapt the methods of cultivation to the changing climatic conditions, lack of access to technologies, and fund allocation from the governmental level, it is difficult for the mtobringchanges in rice production by the crown without any institutional help. This systematic study effectively presents the magnitude of the impact on rice cultivation due to climatic changes inrecenttimesinNepal. This review aims to bring the current scenarioofNepal’sricefarming, and it impacts due to changing climate, which can subsequently contribute in devising plans for proper governance, formulating policies, and allocation of funds for the betterment.

Keywords: rice, climate change, rice production, nepal, agriculture

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