Search results for: global innovation network

Authors: John Segars

Abstract:

Built out of a real-world need to have better, more detailed, asset and infrastructure documentation, this project will lay out the case for using the database functionality of ArcGIS as a tool to track and maintain infrastructure location, status, maintenance and serviceability. Workflows and processes will be presented and detailed which may be applied to an organizations’ infrastructure needs that might allow them to make use of the robust tools which surround the ArcGIS platform. The end result is a value-added information system framework with a geographic component e.g., the spatial location of various I.T. assets, a detailed set of records which not only documents location but also captures the maintenance history for assets along with photographs and documentation of these various assets as attachments to the numerous feature class items. In addition to the asset location and documentation benefits, the staff will be able to log into the devices and pull SNMP (Simple Network Management Protocol) based query information from within the user interface. The entire collection of information may be displayed in ArcGIS, via a JavaScript based web application or via queries to the back-end database. The project is applicable to all organizations which maintain an IT infrastructure but specifically targets post-secondary educational institutions where access to ESRI resources is generally already available in house.

Keywords: ESRI, GIS, infrastructure, network documentation, PostgreSQL

Procedia PDF Downloads 168

Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

Procedia PDF Downloads 343

Authors: Rohit Dey, Sailendra Karra

Abstract:

This paper aims at solving the problem of multi-target searching in a Global Positioning System (GPS) denied environment using swarm robots with limited sensing and communication abilities. Typically, existing swarm-based search algorithms rely on the presence of a global coordinate system (vis-à-vis, GPS) that is shared by the entire swarm which, in turn, limits its application in a real-world scenario. This can be attributed to the fact that robots in a swarm need to share information among themselves regarding their location and signal from targets to decide their future course of action but this information is only meaningful when they all share the same coordinate frame. The paper addresses this very issue by eliminating any dependency of a search algorithm on the need of a predetermined global coordinate frame by the unification of the relative coordinate of individual robots when within the communication range, therefore, making the system more robust in real scenarios. Our algorithm assumes that all the robots in the swarm are equipped with range and bearing sensors and have limited sensing range and communication abilities. Initially, every robot maintains their relative coordinate frame and follow Levy walk random exploration until they come in range with other robots. When two or more robots are within communication range, they share sensor information and their location w.r.t. their coordinate frames based on which we unify their coordinate frames. Now they can share information about the areas that were already explored, information about the surroundings, and target signal from their location to make decisions about their future movement based on the search algorithm. During the process of exploration, there can be several small groups of robots having their own coordinate systems but eventually, it is expected for all the robots to be under one global coordinate frame where they can communicate information on the exploration area following swarm search techniques. Using the proposed method, swarm-based search algorithms can work in a real-world scenario without GPS and any initial information about the size and shape of the environment. Initial simulation results show that running our modified-Particle Swarm Optimization (PSO) without global information we can still achieve the desired results that are comparable to basic PSO working with GPS. In the full paper, we plan on doing the comparison study between different strategies to unify the coordinate system and to implement them on other bio-inspired algorithms, to work in GPS denied environment.

Keywords: bio-inspired search algorithms, decentralized control, GPS denied environment, swarm robotics, target searching, unifying coordinate systems

Procedia PDF Downloads 121

Authors: Muhammad Umar Khan, Mahesh Kumar, Faraz Neakakhtar

Abstract:

Although industrialization marks to the economy of a country yet it increases the pollution and temperature of the environment. The world is now shifting towards green energy because the utilization of fossil fuels is resulting in global warming. So we need to develop systems that can operate on renewable energy resources and have low heat losses. The combined solar and geothermal multigeneration system can solve this issue. Rather than making rankine cycle purely a solar-driven, heat from solar is used to drive vapour absorption cycle and reheated to generate power using geothermal reservoir. The results are displayed by using Engineering Equation Solver software, where inputs are varied to optimize the energy and exergy efficiencies of the system. The cooling effect is 348.2 KW, while the network output is 23.8 MW and reducing resultant emission of 105553 tons of CO₂ per year. This eco-friendly multigeneration system is capable of eliminating the use of fossil fuels and increasing the geothermal energy efficiency.

Keywords: cooling effect, eco-friendly, green energy, heat loses, multigeneration system, renewable energy, work output

Procedia PDF Downloads 248

Authors: Masoud Hassanzade Novin, Bahloul Salmani

Abstract:

The process of the translation is not merely the linguistic aspects. It is also considered in the cultural framework of both the source and target text cultures. The translation process and translated texts are confronted the new aspect in 20th century which is considered mostly in the patronage framework and ideological grillwork of the target language. To have these factors scrutinized in the process of the translation both micro-element factors and macro-element factors can be taken into consideration. For the purpose of this study through a qualitative type of research based on critical discourse analysis approach, the case study of the novel “1984” written by George Orwell was chosen as the corpus of the study to have the contrastive analysis by its Persian translated texts. Results of the study revealed some distortions embedded in the target texts which were overshadowed by ideological aspect and patronage network. The outcomes of the manipulated terms were different in various categories which revealed the manipulation aspects in the texts translated.

Keywords: critical discourse analysis, ideology, patronage network, translated texts

Procedia PDF Downloads 307

Authors: Anyia Nduka, Aslan Bin Amad Senin

Abstract:

Taking a behavioral perspective of Organization Culture, Strategic Leadership, and performance (OC, SLP). We examine the role of Strategic Leadership as key vicious mechanism linking OC,SLP to the organizational capacities. Given the increasing degree of dependence of modern businesses on the use and scientific discovery of relevant data, research efforts around the entire globe have been accelerated. In today's corporate world, Strategic Leadership is still the most sustainable option of performance and competitive advantage. This is why it is critical to gain a deep understanding of research area and to strengthen new collaborative networks in efforts to support research transition towards these integrative efforts. This bibliometric analysis is aimed to examine global trends in OC,SLP research based on publication output, author co-authorships, and co-occurrences of author keywords among authors and affiliated countries. 2829 journal articles were retrieved from the Scopus database Between 1974 and 2021. From the research findings, there is a significant increase in number of publications with strong global collaboration (e.g., USA & UK). We also discovered that while most countries/territories without affiliations were centered in developing countries, the outstanding performance of Asian countries and the volume of their collaborations should be emulated.

Keywords: organizational culture, strategic leadership, organizational resilience, performance

Procedia PDF Downloads 60

Authors: Simiao Ren, En Wei

Abstract:

Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

Procedia PDF Downloads 74

Authors: Shuaibu Umar Abdul

Abstract:

This paper examines Nigeria’s foreign policy in the age of global terrorism. It worth saying that the threat of ‘terrorism’ is not peculiar to Western and Middle Eastern countries alone, its tentacles are now spreading all over, Africa inclusive. The issue of domestic terrorism in Nigeria has become pervasive since the return of democratic rule in 1999. This development has never been a witness in any form throughout the year of statehood in Nigeria, the issues of banditry, armed robbery, ritual killing, and criminal activities like kidnapping and pipeline vandalization, the breakdown of law and order, poorly managed infrastructural facilities and corruption remain synonymous to Nigeria. These acts of terrorism no doubt have constituted a challenge that necessitates the paradigm shift in Nigeria’s foreign policy. The study employed the conceptual framework of analysis to lead interrogation; secondary sources were used to generate data while descriptive and content analysis were considered for data presentation and interpretation. In view of the interrogation and discussion on the subject matter, the paper revealed that Nigerian government underrated and underestimated the strength of terrorism within and outside her policy hence, it becomes difficult to address. As a response to the findings and conclusion of the study, the paper recommends among others that Nigeria’s foreign policy has to be rethought, reshaped and remodeled in cognizance to the rising global terrorism for peace, growth and development in the country.

Keywords: foreign policy, globe, Nigeria, rethinking, terrorism

Procedia PDF Downloads 349

Authors: Wann-Ming Wey

Abstract:

In today's popularity and progress of information technology, the big data set and its analysis are no longer a major conundrum. Now, we could not only use the relevant big data to analysis and emulate the possible status of urban development in the near future, but also provide more comprehensive and reasonable policy implementation basis for government units or decision-makers via the analysis and emulation results as mentioned above. In this research, we set Taipei City as the research scope, and use the relevant big data variables (e.g., population, facility utilization and related social policy ratings) and Analytic Network Process (ANP) approach to implement in-depth research and discussion for the possible reduction of land use in primary and secondary schools of Taipei City. In addition to enhance the prosperous urban activities for the urban public facility utilization, the final results of this research could help improve the efficiency of urban land use in the future. Furthermore, the assessment model and research framework established in this research also provide a good reference for schools or other public facilities land use and adaptive reuse strategies in the future.

Keywords: adaptive reuse, analytic network process, big data, land use strategy

Procedia PDF Downloads 191

Authors: Arenca Trashani

Abstract:

20 years after its first entrance in a General Assembly of the United Nation’s Resolution, human security has became a very important tool in a global debate affecting directly the whole main rules and regulations in international law and more closely in international human rights law. This paper will cover a very important issue of today at how the human security has its impact to the development of international human rights law, not as far as a challenge as it is seen up now but a tool of moving toward development and globalization. In order to analyze the impact of human security to the global agenda, we need to look to the main pillars of the international legal order which are affected by the human security in itself and its application in the policy making for this international legal order global and regional ones. This paper will focus, also, on human security, as a new and very important tool of measuring development, stability and the level of democratic consolidation and the respect for human rights especially in developing countries such as Albania. The states are no longer capable to monopolize the use of human security just within their boundaries and separated from the other principles of a functioning democracy. In this context, human security would be best guaranteed under the respect of the rule of law and democratization. During the last two decades the concept security has broadly developed, from a state-centric to a more human-centric approach: from state security to respect for human rights, to economic security, to environmental security as well. Last but not least we would see that human rights could be affected by human security not just at their promotion but also at their enforcement and mainly at the international institutions, which are entitled to promote and to protect human rights.

Keywords: human security, international human rights law, development, Albania, international law

Procedia PDF Downloads 743

Authors: N. R. Harris, J. Curry

Abstract:

This paper describes the construction and operation of an experimental LoRaWAN network surrounding the University of Southampton in the United Kingdom. Following successful installation, an experimental node design is built and characterised, with particular emphasis on radio range. Several configurations are investigated, including different data rates, and varying heights of node. It is concluded that although range can be great (over 8 km in this case), environmental topology is critical. However, shorter range implementations, up to about 2 km in an urban environment, are relatively insensitive although care is still needed. The example node and the relatively simple base station reported demonstrate that LoraWan can be a very low cost and practical solution to Internet of Things type applications for distributed monitoring systems with sensors spread over distances of several km.

Keywords: long-range, wireless, sensor, network

Procedia PDF Downloads 121

Authors: Bhuvanesh Baniya

Abstract:

Alzheimer disease is illnesses that are responsible for neuronal cell death and resulting in lifelong cognitive problems. Due to their unclear mechanism, there are no effective drugs available for the treatment. For a long time, herbal drugs have been used as a role model in the field of the drug discovery process. Holy basil in the Indian medicinal system (Ayurveda) is used for several neuronal disorders like insomnia and memory loss for decades. This study aims to identify active components of holy basil as potential inhibitors for the treatment of Alzheimer disease. To fulfill this objective, the Network pharmacology approach, gene ontology, pharmacokinetics analysis, molecular docking, and molecular dynamics simulation (MDS) studies were performed. A total of 7 active components in holy basil, 12 predicted neurodegenerative targets of holy basil, and 8063 Alzheimer-related targets were identified from different databases. The network analysis showed that the top ten targets APP, EGFR, MAPK1, ESR1, HSPA4, PRKCD, MAPK3, ABL1, JUN, and GSK3B were found as significant target related to Alzheimer disease. On the basis of gene ontology and topology analysis results, APP was found as a significant target related to Alzheimer’s disease pathways. Further, the molecular docking results to found that various compounds showed the best binding affinities. Further, MDS top results suggested could be used as potential inhibitors against APP protein and could be useful for the treatment of Alzheimer’s disease.

Keywords: holy basil, network pharmacology, neurodegeneration, active phytochemicals, molecular docking and simulation

Procedia PDF Downloads 88

Authors: Thomas Rockstuhl, Kok Yee Ng, Guido Gianasso, Soon Ang

Abstract:

Two meta-analyses show that intercultural experience is not related to intercultural adaptation or performance in international assignments. These findings have prompted calls for a deeper grounding of research on international experience in the phenomenon of global work. Two issues, in particular, may limit current understanding of the relationship between international experience and global work performance. First, intercultural experience is too broad a construct that may not sufficiently capture the essence of global work, which to a large part involves sensemaking and managing intercultural conflicts. Second, the psychological mechanisms through which intercultural experience affects performance remains under-explored, resulting in a poor understanding of how experience is translated into learning and performance outcomes. Drawing on recognition primed decision-making (RPD) research, the current study advances a cognitive processing model to highlight the importance of intercultural conflict familiarity. Compared to intercultural experience, intercultural conflict familiarity is a more targeted construct that captures individuals’ previous exposure to dealing with intercultural conflicts. Drawing on RPD theory, we argue that individuals’ intercultural conflict familiarity enhances their ability to make accurate judgments and generate effective responses when intercultural conflicts arise. In turn, the ability to make accurate situation judgements and effective situation responses is an important predictor of global work performance. A relocation program within a multinational enterprise provided the context to test these hypotheses using a time-lagged, multi-source field study. Participants were 165 employees (46% female; with an average of 5 years of global work experience) from 42 countries who relocated from country to regional offices as part a global restructuring program. Within the first two weeks of transfer to the regional office, employees completed measures of their familiarity with intercultural conflicts, cultural intelligence, cognitive ability, and demographic information. They also completed an intercultural situational judgment test (iSJT) to assess their situation judgment and situation response. The iSJT comprised four validated multimedia vignettes of challenging intercultural work conflicts and prompted employees to provide protocols of their situation judgment and situation response. Two research assistants, trained in intercultural management but blind to the study hypotheses, coded the quality of employee’s situation judgment and situation response. Three months later, supervisors rated employees’ global work performance. Results using multilevel modeling (vignettes nested within employees) support the hypotheses that greater familiarity with intercultural conflicts is positively associated with better situation judgment, and that situation judgment mediates the effect of intercultural familiarity on situation response quality. Also, aggregated situation judgment and situation response quality both predicted supervisor-rated global work performance. Theoretically, our findings highlight the important but under-explored role of familiarity with intercultural conflicts; a shift in attention from the general nature of international experience assessed in terms of number and length of overseas assignments. Also, our cognitive approach premised on RPD theory offers a new theoretical lens to understand the psychological mechanisms through which intercultural conflict familiarity affects global work performance. Third, and importantly, our study contributes to the global talent identification literature by demonstrating that the cognitive processes engaged in resolving intercultural conflicts predict actual performance in the global workplace.

Keywords: intercultural conflict familiarity, job performance, judgment and decision making, situational judgment test

Procedia PDF Downloads 165

Authors: Vanaja Rao

Abstract:

In the recent times, the need for the integration of Renewable Energy Sources (RES) in a Smart Grid is on the rise. As a result of this, associated energy storage systems are known to play important roles in sustaining the efficient operation of such RES like wind power and solar power. This paper investigates the importance of location selection of Energy Storage Systems (ESSs) in a Smart Grid. Three scenarios of ESS location is studied and analyzed in a Smart Grid, which are – 1. Near the generation/source, 2. In the middle of the Grid and, 3. Near the demand/consumption. This is explained with the aim of assisting any Distribution Network Operator (DNO) in deploying the ESSs in a power network, which will significantly help reduce the costs and time of planning and avoid any damages incurred as a result of installing them at an incorrect location of a Smart Grid. To do this, the outlined scenarios mentioned above are modelled and analyzed with the National Grid’s datasets of energy generation and consumption in the UK power network. As a result, the outcome of this analysis aims to provide a better overview for the location selection of the ESSs in a Smart Grid. This ensures power system stability and security along with the optimum usage of the ESSs.

Keywords: distribution networks, energy storage system, energy security, location planning, power stability, smart grid

Procedia PDF Downloads 283

Authors: Samuel Oye Bandele

Abstract:

A policy is a system of principles to guide activities and strategic decisions of an organisation in order to achieve stated objectives and meeting expected outcomes. A Computer Based Test (CBT) policy is therefore a statement of intent to drive the CBT programmes, and should be implemented as a procedure or protocol. Policies are hence generally adopted by an organization or a nation. The concern here, in this paper, is the consideration and analysis of issues that are significant to evolving the acceptable policy that will drive the new CBT innovation in Nigeria. Public examinations and internal examinations in higher educational institutions in Nigeria are gradually making a radical shift from Paper Based or Paper-Pencil to Computer-Based Testing. The need to make an objective and empirical analysis of Policy issues relating to CBT became expedient. The following are some of the issues on CBT evolution in Nigeria that were identified as requiring policy backing. Prominent among them are requirements for establishing CBT centres, purpose of CBT, types and acquisition of CBT equipment, qualifications of staff: professional, technical and regular, security plans and curbing of cheating during examinations, among others. The descriptive research design was employed based on a population consisting of Principal Officers (Policymakers), Staff (Teaching and non-Teaching-Policy implementors), and CBT staff ( Technical and Professional- Policy supports) and candidates (internal and external). A fifty-item researcher-constructed questionnaire on policy issues was employed to collect data from 600 subjects drawn from higher institutions in South West Nigeria, using the purposive and stratified random sampling techniques. Data collected were analysed using descriptive (frequency counts, means and standard deviation) and inferential (t-test, ANOVA, regression and Factor analysis) techniques. Findings from this study showed, among others, that the factor loadings had significantly weights on the organizational and National policy issues on CBT innovation in Nigeria.

Keywords: computer-based testing, examination, innovation, paper-based testing, paper pencil based testing, policy issues

Procedia PDF Downloads 231

Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard Jorswieck

Abstract:

The capacity of fifth-generation (5G) vehicle-to-everything (V2X) networks poses significant challenges. To ad- dress this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a heterogeneous vehicular network (HetNet). We propose a new framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles while guaranteeing the WiFi users' throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: vehicle-to-everything (V2X), resource allocation, BS assignment, new radio (NR), new radio unlicensed (NR-U), coexistence NR-U and WiFi, deep deterministic policy gradient (DDPG), deep Q-network (DQN), joint BS assignment and resource allocation (JBSRA), duty cycle mechanism

Procedia PDF Downloads 84

Authors: Fengjuan Wang, Azilawati Jamaludin

Abstract:

Developmental Dyscalculia (DD) is defined as a particular learning difficulty with continuous challenges in learning requisite math skills that cannot be explained by intellectual disability or educational deprivation. Recent studies have increasingly recognized that DD is a heterogeneous, instead of monolithic, learning disorder with not only cognitive and behavioral deficits but so too neural dysfunction. In recent years, neuroimaging studies employed group comparison to explore the neural underpinnings of DD, which contradicted the heterogenous nature of DD and may obfuscate critical individual differences. This research aimed to investigate the neural heterogeneity of DD using case studies with functional near-infrared spectroscopy (fNIRS). A total of 54 aged 6-7 years old of children participated in this study, comprising two comprehensive cognitive assessments, an 8-minute resting state, and an 8-minute one-digit addition task. Nine children met the criteria of DD and scored at or below 85 (i.e., the 16th percentile) on the Mathematics or Math Fluency subtest of the Wechsler Individual Achievement Test, Third Edition (WIAT-III) (both subtest scores were 90 and below). The remaining 45 children formed the typically developing (TD) group. Resting-state data and brain activation in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), and intraparietal sulcus (IPS) were collected for comparison between each case and the TD group. Graph theory was used to analyze the brain network under the resting state. This theory represents the brain network as a set of nodes--brain regions—and edges—pairwise interactions across areas to reveal the architectural organizations of the nervous network. Next, a single-case methodology developed by Crawford et al. in 2010 was used to compare each case’s brain network indicators and brain activation against 45 TD children’s average data. Results showed that three out of the nine DD children displayed significant deviation from TD children’s brain indicators. Case 1 had inefficient nodal network properties. Case 2 showed inefficient brain network properties and weaker activation in the IFG and IPS areas. Case 3 displayed inefficient brain network properties with no differences in activation patterns. As a rise above, the present study was able to distill differences in architectural organizations and brain activation of DD vis-à-vis TD children using fNIRS and single-case methodology. Although DD is regarded as a heterogeneous learning difficulty, it is noted that all three cases showed lower nodal efficiency in the brain network, which may be one of the neural sources of DD. Importantly, although the current “brain norm” established for the 45 children is tentative, the results from this study provide insights not only for future work in “developmental brain norm” with reliable brain indicators but so too the viability of single-case methodology, which could be used to detect differential brain indicators of DD children for early detection and interventions.

Keywords: brain activation, brain network, case study, developmental dyscalculia, functional near-infrared spectroscopy, graph theory, neural heterogeneity

Procedia PDF Downloads 41

Authors: Juliza Hidayati, Yesie M. Sinuhaji, Sawarni Hasibuan

Abstract:

A company producing drinking water through many incompatibility issues that affect supply chain performance. The study was conducted to determine the factors that affect the performance of the supply chain and improve it. To obtain the dominant factors affecting the performance of the supply chain used Analytic Network Process, while to improve performance is done by using Kaizen. Factors affecting the performance of the supply chain to be a reference to identify the cause of the non-conformance. Results weighting using ANP indicates that the dominant factor affecting the level of performance is the precision of the number of shipments (15%), the ability of the fulfillment of the booking amount (12%), and the number of rejected products when signing (12%). Incompatibility of the factors that affect the performance of the supply chain are identified, so that found the root cause of the problem is most dominant. Based on the weight of Risk Priority Number (RPN) gained the most dominant root cause of the problem, namely the poorly maintained engine, the engine worked for three shifts, machine parts that are not contained in the plant. Improvements then performed using the Kaizen method of systematic and sustainable.

Keywords: analytic network process, booking amount, risk priority number, supply chain performance

Procedia PDF Downloads 279

Authors: Tzu-Yang Lin, Chuan-Ching Sue

Abstract:

Sleep mechanisms are commonly used to ensure the energy efficiency of each optical network unit (ONU) that concerns a single class delay constraint in the Ethernet Passive Optical Network (EPON). How long the ONUs can sleep without violating the delay constraint has become a research problem. Particularly, we can derive an analytical model to determine the optimal sleep time of ONUs in every cycle without violating the maximum class delay constraint. The bandwidth allocation considering such optimal sleep time is called Green Bandwidth Allocation (GBA). Although the GBA mechanism guarantees that the different class delay constraints do not violate the maximum class delay constraint, packets with a more relaxed delay constraint will be treated as those with the most stringent delay constraint and may be sent early. This means that the ONU will waste energy in active mode to send packets in advance which did not need to be sent at the current time. Accordingly, we proposed a QoS-aware GBA using a novel intra-ONU scheduling to control the packets to be sent according to their respective delay constraints, thereby enhancing energy efficiency without deteriorating delay performance. If packets are not explicitly classified but with different packet delay constraints, we can modify the intra-ONU scheduling to classify packets according to their packet delay constraints rather than their classes. Moreover, we propose the switchable ONU architecture in which the ONU can switch the architecture according to the sleep time length, thus improving energy efficiency in the QoS-aware GBA. The simulation results show that the QoS-aware GBA ensures that packets in different classes or with different delay constraints do not violate their respective delay constraints and consume less power than the original GBA.

Keywords: Passive Optical Networks, PONs, Optical Network Unit, ONU, energy efficiency, delay constraint

Procedia PDF Downloads 268

Authors: Bin Li

Abstract:

In the era of the digital economy, digital transformation has gradually become a strategic choice for enterprise development, but there is a relative lack of systematic research from the perspective of enterprise growth. Based on the sample of Chinese A-share listed companies from 2011 to 2021, this paper constructs A digital transformation index system and an enterprise growth composite index to empirically test the impact of enterprise digital transformation on enterprise growth and its mechanism. The results show that digital transformation can significantly promote corporate growth. The mechanism analysis finds that reducing operating costs, optimizing human capital structure, promoting R&D output and improving digital innovation capability play an important intermediary role in the process of digital transformation promoting corporate growth. At the same time, the level of external digital infrastructure and the strength of organizational resilience play a positive moderating role in the process of corporate digital transformation promoting corporate growth. In addition, while further analyzing the heterogeneity of enterprises, this paper further deepens the analysis of the driving factors and digital technology support of digital transformation, as well as the three dimensions of enterprise growth, thus deepening the research depth of enterprise digital transformation.

Keywords: digital transformation, enterprise growth, digital technology, digital infrastructure, organization resilience, digital innovation

Procedia PDF Downloads 40

Authors: Mohammed Sale Abubakar, Kabir Omar, Mohammed Umar Abba

Abstract:

The effects of climate change continue to ravage globe upsetting or even overturning the entire communities in its wake. It is therefore on the front burner of most global issues affecting the world today. Hardly any field of endeavor has escaped the manifestation of its effects. The effects of climate change on agricultural productivity calls for intense study because of the nexus between agriculture, global food security and provision of employment for the teaming population in sub-saharan Africa. This paper examines current challenges of climate change on agricultural productivity in this region. This challenge indicated that both long and short-term change in climate bring unpleasant repercussion on agricultural productivity as they manifest in the vulnerability of industrial work force. The paper also focused on the impact of agriculture and bio-environmental engineering as a separate entity that will help to fight these major challenges facing humanity currently associated with negative effects of climate change such as scarcity of water, declining agricultural yields, desert encroachment, and damage of coastal structures. Finally, a suggestion was put forward as an effort that should be directed towards mitigating the negative effects of climate change on our environment.

Keywords: climate change mitigation, desert encroachment, environment, global food security, greenhouse gases (GHGs)

Procedia PDF Downloads 339

Authors: Ran An, Dang Wang

Abstract:

Background: Mechanical ventilation has been confirmed to increase the incidence of postoperative pulmonary complications (PPCs), and several studies have shown that low tidal volumes combined with positive end-expiratory pressure (PEEP) and recruitment manoeuvres (RM) reduce the incidence of PPCs. However, the optimal lung-protective ventilatory strategy remains unclear. Methods: Multiple databases were searched for randomized controlled trials (RCTs) published prior to October 2023. The association between individual PEEP (iPEEP) or other forms of lung-protective ventilation and the incidence of PPCs was evaluated by Bayesian network meta-analysis. Results: We included 58 studies (11610 patients) in this meta-analysis. The network meta-analysis showed that low ventilation (LVt) combined with iPEEP and RM was associated with significantly lower incidences of PPCs [HVt: OR=0.38 95CrI (0.19, 0.75), LVt: OR=0.33, 95% CrI (0.12, 0.82)], postoperative atelectasis, and pneumonia than was HVt or LVt. In abdominal surgery, LVT combined with iPEEP or medium-to-high PEEP and RM were associated with significantly lower incidences of PPCs, postoperative atelectasis, and pneumonia. LVt combined with iPEEP and RM was ranked the highest, which was based on SUCRA scores. Conclusion: LVt combined with iPEEP and RM decreased the incidences of PPCs, postoperative atelectasis, and pneumonia in noncardiac surgery patients. iPEEP-guided ventilation was the optimal lung protection ventilation strategy. The quality of evidence was moderate.

Keywords: protection ventilation strategies, postoperative pulmonary complications, network meta-analysis, noncardiac surgery

Procedia PDF Downloads 20

Authors: Luther Ollier, Sylvie Thiria, Anastase Charantonis, Carlos E. Mejia, Michel Crépon

Abstract:

Sea Surface Height Anomaly (SLA) is a signature of the sub-mesoscale dynamics of the upper ocean. Sea Surface Temperature (SST) is driven by these dynamics and can be used to improve the spatial interpolation of SLA fields. In this study, we focused on the temporal evolution of SLA fields. We explored the capacity of deep learning (DL) methods to predict short-term SLA fields using SST fields. We used simulated daily SLA and SST data from the Mercator Global Analysis and Forecasting System, with a resolution of (1/12)◦ in the North Atlantic Ocean (26.5-44.42◦N, -64.25–41.83◦E), covering the period from 1993 to 2019. Using a slightly modified image-to-image convolutional DL architecture, we demonstrated that SST is a relevant variable for controlling the SLA prediction. With a learning process inspired by the teaching-forcing method, we managed to improve the SLA forecast at five days by using the SST fields as additional information. We obtained predictions of a 12 cm (20 cm) error of SLA evolution for scales smaller than mesoscales and at time scales of 5 days (20 days), respectively. Moreover, the information provided by the SST allows us to limit the SLA error to 16 cm at 20 days when learning the trajectory.

Keywords: deep-learning, altimetry, sea surface temperature, forecast

Procedia PDF Downloads 73

Authors: N. Drir, L. Barazane, M. Loudini

Abstract:

It is well known that photovoltaic (PV) cells are an attractive source of energy. Abundant and ubiquitous, this source is one of the important renewable energy sources that have been increasing worldwide year by year. However, in the V-P characteristic curve of GPV, there is a maximum point called the maximum power point (MPP) which depends closely on the variation of atmospheric conditions and the rotation of the earth. In fact, such characteristics outputs are nonlinear and change with variations of temperature and irradiation, so we need a controller named maximum power point tracker MPPT to extract the maximum power at the terminals of photovoltaic generator. In this context, the authors propose here to study the modeling of a photovoltaic system and to find an appropriate method for optimizing the operation of the PV generator using two intelligent controllers respectively to track this point. The first one is based on artificial neural networks and the second on fuzzy logic. After the conception and the integration of each controller in the global process, the performances are examined and compared through a series of simulation. These two controller have prove by their results good tracking of the MPPT compare with the other method which are proposed up to now.

Keywords: maximum power point tracking, neural networks, photovoltaic, P&O

Procedia PDF Downloads 322

Authors: Mohamad Mahdi Namdari

Abstract:

In today's rapidly changing and evolving business competition, companies and organizations require advanced and efficient tools to manage their markets and sales networks. Big data analysis, quick response in competitive markets, process and operations optimization, and forecasting customer behavior are among the concerns of executive managers. Artificial intelligence, as one of the emerging technologies, has provided extensive capabilities in this regard. The use of artificial intelligence in market and sales network management can lead to improved efficiency, increased decision-making accuracy, and enhanced customer satisfaction. Specifically, AI algorithms can analyze vast amounts of data, identify complex patterns, and offer strategic suggestions to improve sales performance. However, many companies are still distant from effectively leveraging this technology, and those that do face challenges in fully exploiting AI's potential in market and sales network management. It appears that the general public's and even the managerial and academic communities' lack of knowledge of this technology has caused the managerial structure to lag behind the progress and development of artificial intelligence. Additionally, high costs, fear of change and employee resistance, lack of quality data production processes, the need for updating structures and processes, implementation issues, the need for specialized skills and technical equipment, and ethical and privacy concerns are among the factors preventing widespread use of this technology in organizations. Clarifying and explaining this technology, especially to the academic, managerial, and elite communities, can pave the way for a transformative beginning. The aim of this research is to elucidate the capacities of artificial intelligence in market and sales network management, identify its opportunities and benefits, and examine the existing challenges and obstacles. This research aims to leverage AI capabilities to provide a framework for enhancing market and sales network performance for managers. The results of this research can help managers and decision-makers adopt more effective strategies for business growth and development by better understanding the capabilities and limitations of artificial intelligence.

Keywords: artificial intelligence, market management, sales network, big data analysis, decision-making, digital marketing

Procedia PDF Downloads 11

Authors: Sinan Alsaadi, Mustafa Merdan

Abstract:

Communication and access systems can be made with many methods in today’s world. These systems are such standards as Wifi, Wimax, Bluetooth, GPS and GPRS. Devices which use these standards also use system resources excessively in direct proportion to their transmission speed. However, large-scale data communication is not always needed. In such cases, a technology which will use system resources as little as possible and support smart network topologies has been needed in order to enable the transmissions of such small packet data and provide the control for this kind of devices. IEEE issued 802.15.4 standard upon this necessity and enabled the production of Zigbee protocol which takes these standards as its basis and devices which support this protocol. In our project, this communication protocol was preferred. The aim of this study is to provide the immediate data transmission of our robot from the field within the scope of the project. In addition, making the communication with the robot through Zigbee Protocol has also been aimed. While sitting on the computer, obtaining the desired data from the region where the robot is located has been taken as the basis. Arduino Uno R3 microcontroller which provides the control mechanism, 1298 shield as the motor driver.

Keywords: ZigBee, wireless network, remote monitoring, smart home, agricultural industry

Procedia PDF Downloads 263

Authors: K. Parandhama Gowd

Abstract:

The aim of this research paper is to conceptualize, discuss, analyze and propose alternate design methodologies for futuristic Black Box for flight safety. The proposal also includes global networking concepts for real time surveillance and monitoring of flight performance parameters including GPS parameters. It is expected that this proposal will serve as a failsafe real time diagnostic tool for accident investigation and location of debris in real time. In this paper, an attempt is made to improve the existing methods of flight data recording techniques and improve upon design considerations for futuristic FDR to overcome the trauma of not able to locate the block box. Since modern day communications and information technologies with large bandwidth are available coupled with faster computer processing techniques, the attempt made in this paper to develop a failsafe recording technique is feasible. Further data fusion/data warehousing technologies are available for exploitation.

Keywords: flight data recorder (FDR), black box, diagnostic tool, global networking, cockpit voice and data recorder (CVDR), air traffic control (ATC), air traffic, telemetry, tracking and control centers ATTTCC)

Procedia PDF Downloads 557

Authors: Mathias Linden, André Schneider, Harald F. O. von Korflesch

Abstract:

The risk of train accidents is an ongoing concern for railway organizations, governments, insurance companies and other depended sectors. Safety technologies are installed to reduce and to prevent potential damages of train accidents. Since the budgetary for the safety of railway organizations is limited, it is necessary not only to achieve a high availability and high safety standard but also to be cost effective. Therefore, an economic assessment of safety technologies is fundamental to create an accurate risk analysis. In order to conduct an economical assessment of a railway safety technology and a quantification of the costs of the accident causes, the Global Railway Accident Database & Evaluation (GRADE) has been developed. The aim of this paper is to describe the structure of this accident database and to show how it can be used for risk analyses. A number of risk analysis methods, such as the probabilistic safety assessment method (PSA), was used to demonstrate this accident database’s different possibilities of risk analysis. In conclusion, it can be noted that these analyses would not be as accurate without GRADE. The information gathered in the accident database was not available in this way before. Our findings are relevant for railway operators, safety technology suppliers, assurances, governments and other concerned railway organizations.

Keywords: accident causes, accident costs, accident database, global railway accident database & evaluation, GRADE, probabilistic safety assessment, PSA, railway accidents, risk analysis

Procedia PDF Downloads 342

Authors: Morteza Khorrami

Abstract:

The idea of final triumph of peace and justice on evil force, conflict and global spread of the religious faith, the full deployment of human values, constitute a utopia and the ideal society is discussed by many of religions. Thus, mankind has always been waiting for a savior and has received good tidings for coming of Great Savior at the end of Time. Of course, various persons were introduced as the Promised Saviors by different religions, but all of the religions share in this fact that the future of humanity is very bright and promising and the future will belong to the righteous and justice. In this article which is written with a descriptive and analytic method, the author tries to show the vision of global justice at the end of time. The opinion of various religions such as Judaism, Christianity, Zoroastrianism, Islam and even idolatry about the great savior as well as the justice status in his era in the world will be discussed. Also the viewpoint of Muslims and specially Shiites, which is explained clearly in their scripts, will be depicted. Current human responsibility towards this golden era will be discussed, too. Based on paper findings, religious doctrine promises that a heaven person and sacred character will come as a reformer of the world. In his era, humanity will be saved from tyranny, oppression and inequality, and the earth will be filled with peace, security, justice, and equity. Moreover promoting justice, truth and spreading religion in the world, economic, scientific, political and moral development will be happened.

Keywords: future of humanity, global justice, islam, religions

Procedia PDF Downloads 356

Authors: Fahad Al Beyahi, Justin Thomas, Md Mamunur Rashid

Abstract:

Various definitions of digital well-being have emerged in recent years, most of which center on the impacts -beneficial and detrimental- of digital technology on health and well-being (psychological, social, and financial). Other definitions go further, emphasizing the attainment of balance, viewing digital well-being as wholly subjective, the individual’s perception of optimal balance between the benefits and ills associated with online connectivity. Based on this broad conceptualization of digital well-being, we undertook a global survey measuring various dimensions of this emerging construct. The survey was administered across 35 nations and 7 world regions, with 1000 participants within each territory (N= 35000). Along with attitudinal, behavioral, and sociodemographic variables, the survey included measures of depression, anxiety, problematic social media use, gaming disorder, and other relevant metrics. Coupled with nation-level policy audits, these data were used to create a multinational (global) digital well-being index. Nations are ranked based on various dimensions of digital well-being, and predictive models are used to identify resilience and risk factors for problem technology use. In this paper, we will discuss key findings from the survey and the index. This work can inform public policy and shape our responses to the emerging implications of lives increasingly lived online and interconnected with digital technology.

Keywords: technology, health, behavioral addiction, digital wellbeing

Procedia PDF Downloads 60